docsuwin sandu 2007 - OPUS at UTS - University of Technology Sydney
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suwin sandu 2007 - OPUS at UTS - University of Technology Sydney
ASSESSMENTOFCARBONTAXASAPOLICY OPTIONFORREDUCINGCARBONDIOXIDE EMISSIONSINAUSTRALIA SUWINSANDU FacultyofEngineering UniversityofTechnology,Sydney AdissertationsubmittedtotheUniversityofTechnology,Sydneyinfulfilmentofthe requirementsforthedegreeofDoctorofPhilosophy(EnergyPlanningandPolicy) 2007 i CERTIFICATEOFAUTHORSHIP/ORIGINALITY Icertifythattheworkinthisthesishasnotpreviouslybeensubmittedforadegree,nor has it been submitted as part of the requirements for a degree, except as fully acknowledgedwithinthetext. Ialsocertifythatthethesishasbeenwrittenbyme.AnyhelpthatIhavereceivedin my research work and the preparation of the thesis itself has been acknowledged. In addition,Icertifythatallinformationsourcesandliteratureusedareindicatedinthe thesis. SignatureofCandidate ____________________________ ii ACKNOWLEDGMENTS I am grateful to Associate Professor Deepak Sharma, my major supervisor, for his encouragement,guidanceandsupportincarryingoutthisresearch.Hiscriticismsand suggestions,throughoutthisresearch,arehighlyvaluable.Ialsobenefitedgreatlyfrom thediscussionwithhimonvariousissuesbeyondthescopeofthisresearch.Iamalso grateful to Emeritus Professor Rod Belcher, my cosupervisor, for his advice during thisresearch. Igratefullythankmyuncle,AssociateProfessorTrichakSandhu,whohasgivenmea good foundation that allows me to undertake this research. Having no parents, it would have been difficult for me to be where I am now. He is like my father and I knowthathewouldbeproudfrommyachievement. ThankstotheFacultyofEngineeringforprovidingtherighttypeofenvironmentand financial assistance for carrying out this research. Thanks are also due to the staff of UTSlibraryinassistingmeinacquiringvaluableinformationforthisdissertation.My particularappreciationalsogoestomyeditor,MsPatSkinner. I would like to especially thank my colleagues in the Energy Planning and Policy Program for their encouragement and cheerful assistance. Particular thanks go to Ms Supannika Wattana and Ms Srichattra Chaivongvilan for providing a consistent support,particularlyasamediumofcommunicationswithmymajorsupervisor,while IamworkinginCanberra.ThanksalsotoMrRonnakornVaiyavuthfordiscussionon variousaspects,includingthisresearch,overapegofsoju. Finally,IsaythankyoutomyfiancéNiradaManosornwhohasgivenmethestrength, particularly over the last two years of my research. I look forward to our future life together. iii ABSTRACT Thisresearchhasanalysedtheeconomywideimpactsofcarbontaxasapolicyoption toreducetherateofgrowthofcarbondioxideemissionsfromtheelectricitysectorin Australia. These impacts are analysed for energy and nonenergy sectors of the economy. An energyoriented Input–Output framework, with ‘flexible’ production functions, based on Translog and CobbDouglas formulations, is employed for the analysis of various impacts. Further, two alternative conceptions of carbon tax are consideredinthisresearch,namely,basedonPolluterPaysPrinciple(PPP)andShared ResponsibilityPrinciple(SRP). Inthefirstinstance,theimpactsareanalysed,fortheperiod2005–2020,fortaxlevelsof $10and$20pertonneofCO2,inasituationofnoapriorilimitonCO2emissions.The analysisshowsthatCO2emissionsfromtheelectricitysector,whencarbontaxisbased on PPP, would be 211 and 152 Mt, for tax levels of $10 and $20, respectively (as comparedto250MtintheBaseCasescenario,thatis,thebusinessasusualcase).The net economic costs, corresponding with these tax levels, expressed in present value terms, would be $27 and $49 billion, respectively, over the period 2005–2020. These economic costs are equivalent to 0.43 and 0.78 per cent of the estimated GDP of Australia. Further, most of the economic burden, in this instance, would fall on the electricity sector, particularly coalfired electricity generators – large consumers of direct fossil fuel. On the other hand, in the case of a carbon tax based on SRP, CO2 emissions would be 172 and 116 Mt, for tax levels of $10 and $20, respectively. The corresponding net economic costs would be $47 (0.74 per cent of GDP) and $84 (1.34 per cent of GDP) billion, respectively, with significant burden felt by the commercial sector – large consumers of indirect energy and materials whose production would contributetoCO2emissions. Next,theimpactsareanalysedbyplacinganapriorilimitonCO2emissionsfromthe electricitysector–equivalentto108percentofthe1990level(thatis,138Mt),bythe year2020.Twocasesareanalysed,namely,earlyaction(carbontaxintroducedin2005) and deferred action (carbon tax introduced in 2010). In the case of early action, the analysis suggests, carbon tax of $25 and $15, based on PPP and SRP, respectively, iv wouldberequiredtoachievetheabovenotedemissionstarget.Thecorrespondingtax levels in the case of deferred action are $51 and $26, respectively. This research also showsthattheneteconomiccosts,inthecaseofearlyaction,wouldbe$32billion(for PPP) and $18 billion (for SRP) higher than those in the case of deferred action. However, this research has demonstrated, that this inference is largely due to the selection of particular indicator (that is, present value) and the relatively short time frame(thatis,2005–2020)foranalysis.Byextendingthetimeframeoftheanalysisto theyear2040,thecaseforanearlyintroductionofcarbontaxstrengthens. Overall,theanalysisinthisresearchsuggeststhatanimmediateintroductionofcarbon tax,basedonSRP,isthemostattractiveapproachtoreducetherateofgrowthofCO2 emissionsfromthe electricitysectorandto simultaneously meeteconomic andsocial objectives.Ifthedecisiontointroducesuchataxisdeferred,itwouldberatherdifficult to achieve not only environmental objectives but economic and social objectives as well. v TABLEOFCONTENTS CertificateofAuthorship/Originality……………………………………………..i Acknowledgments…………………………………………………………………..ii Abstract………………………………………………………………………………iii TableofContents…………………………………………………………………....v ListofTables………………………………………………………………………viii ListofFigures……………………………………………………………………..... ix Abbreviations…………………………………………………………………………x CHAPTER1 INTRODUCTION............................................................................................1 1.1 Background..............................................................................................1 1.2 ResearchObjectives ................................................................................9 1.3 ResearchMethodology.........................................................................10 1.3.1 HistoricalReview ...................................................................................... 12 1.3.2 ModellingPerspective............................................................................... 13 1.3.3 PolicyAnalysis.......................................................................................... 14 CHAPTER2 1.4 ScopeofthisResearchandDataConsiderations .............................14 1.5 SignificanceofthisResearch ...............................................................18 1.6 OrganisationoftheThesis ...................................................................19 EVOLUTIONOFTHECOAL–ELECTRICITYCOMPACT...................20 2.1 HistoricalReviewoftheAustralianElectricityIndustry ................21 2.1.1 2.1.2 2.1.3 2.1.4 2.1.5 2.2 OriginsoftheElectricityIndustry(1880s–1900) ................................... 21 GenesisofCoal–ElectricityCompact(1901–1950s) ................................ 22 ConsolidationoftheCompact(1950s–1980s).......................................... 24 FurtherStrengtheningoftheCompact(1980s–1990s) ........................... 27 FurtherEntrenchmentoftheCompact(1990s–present) ....................... 29 FutureDirectionoftheAustralianElectricityIndustry ..................32 2.2.1 TechnicalConsiderations .......................................................................... 33 2.2.2 EconomicConsiderations.......................................................................... 35 2.2.3 PoliticalConsiderations ............................................................................ 37 2.3 CHAPTER3 SummaryandConclusions..................................................................40 AUSTRALIANGREENHOUSEPOLICYDEVELOPMENT .................42 3.1 ElectricityIndustryandCarbondioxideEmissions ........................42 3.1.1 TotalCarbondioxideEmissions ............................................................... 42 3.1.2 CarbondioxideEmissionsfromElectricityGeneration .......................... 44 3.2 DevelopmentofAustralia’sGreenhousePolicy...............................46 vi 3.2.1 3.2.2 3.2.3 3.2.4 3.2.5 3.3 ACarbonTaxPolicyforAustralia .....................................................56 3.3.1 3.3.2 3.3.3 3.3.4 3.4 CHAPTER4 ThePacesetter............................................................................................ 46 TheChangingStance ................................................................................ 48 ReaffirmationoftheStance ....................................................................... 50 TheLaggardNation .................................................................................. 51 EntrenchmentoftheStance ...................................................................... 53 EnvironmentalPolicyOptions ................................................................. 56 ConventionalCarbonTaxApproach ........................................................ 58 AModifiedCarbonTaxApproach ........................................................... 63 SectoralResponsibilitiesofAustralianEmissions ................................... 66 SummaryandConclusions..................................................................69 AREVIEWOFMATERIALSBALANCEFRAMEWORK .....................72 4.1 BackgroundofMaterialsbalanceFramework..................................72 4.2 CriteriaforExaminingMethodologicalApproaches.......................75 4.3 PhysicalFlowMethods ........................................................................76 4.3.1 4.3.2 4.3.3 4.3.4 4.4 MaterialFlowAnalysis............................................................................. 79 LifecycleAnalysis .................................................................................... 80 ReferenceEnergy–materialSystemAnalysis........................................... 82 PhysicalFlowMethods:ASummaryofObservations ............................ 84 EmbodiedEnergyMethods.................................................................86 4.4.1 ProcessAnalysis........................................................................................ 86 4.4.2 Input–outputAnalysis.............................................................................. 91 4.4.3 EmbodiedEnergyMethods:ASummaryofObservations ...................... 94 4.5 CHAPTER5 SummaryandConclusions..................................................................95 METHODOLOGICALFRAMEWORKFORTHISRESEARCH..........98 5.1 OverallMethodologicalFramework ..................................................98 5.2 AllocationofCarbondioxideEmissions .........................................100 5.2.1 EmissionsAllocation:PolluterPaysPrinciple ...................................... 101 5.2.2 EmissionsAllocation:SharedResponsibilityPrinciple ......................... 102 5.3 DeterminationofCarbonTax............................................................105 5.4 AssessmentofPriceImpactofCarbonTax.....................................106 5.5 ExaminationofFactorSubstitutionduetoCarbonTax ................108 5.5.1 5.5.2 5.5.3 5.5.4 ModificationofInput–outputCoefficients ............................................. 108 ModellingofElectricityGenerationMix ............................................... 111 ModellingofFinalDemand.................................................................... 113 EconometricSpecificationandParameterEstimation........................... 114 5.6 EconomywideImpactModule ........................................................123 5.7 DataSourcesandPreparation...........................................................126 5.7.1 DataPreparationforInput–outputModel............................................. 126 5.7.2 DataPreparationforProductionFunctionModel................................. 132 vii 5.8 CHAPTER6 SummaryandConclusions................................................................134 ASSESSMENTOFTHEIMPACTSOFCARBONTAX .......................136 6.1 FrameworkforAssessingImpactsofCarbonTax .........................136 6.2 AlternativeCarbonTaxRegimes......................................................138 6.3 AnalysisoftheImpactsofAlternativeCarbonTaxRegimes.......140 6.3.1 EnergyandEnvironmentalImpacts ...................................................... 140 6.3.2 EconomicandSocialImpacts.................................................................. 156 6.4 CarbonTaxtoAchieveAnAprioriEmissionTarget.....................175 6.4.1 6.4.2 6.4.3 6.4.4 CHAPTER7 EarlyIntroductionofCarbonTax .......................................................... 179 DeferredIntroductionofCarbonTax ..................................................... 182 EarlyActionvsDeferredAction:SomeEarlyResults .......................... 184 EarlyActionvsDeferredAction:SomeFurtherAnalysis .................... 185 6.5 ComparisonwithOtherStudies .......................................................189 6.6 PolicyImplicationsofCarbonTax:Someadditionaldiscussion .192 6.7 SummaryandConclusions................................................................195 CONCLUSIONSANDRECOMMENDATIONSFORFURTHER RESEARCH ...................................................................................................200 7.1 Conclusions..........................................................................................200 7.2 SomeRecommendationsforFurtherResearch...............................209 APPENDICES AppendixA ExampleofEmissionsAllocation:PPPvs.SRP………………………….212 AppendixB DescriptionofInput–outputandProductionFunctionModels……....216 AppendixC DatasetsRequiredforThisResearch…………………………………….233 AppendixD CO2EmissionsCalculatedforPPPandSRP……………………………..270 AppendixE ComputerProgram(Eviews)OutputforProductionFunctionModel.275 AppendixF ResultsfromEconomywideImpactofCarbonTax…………………….287 BIBLIOGRAPHY…………………………………………………………………………..356 viii LISTOFTABLES Table11 Dataconsiderationsforeachspecificobjective................................................17 Table21 Installedcapacity,electricitygenerationandfuelconsumptioninESI........29 Table22 Marginalcostsandemissionratesofelectricitygeneration...........................36 Table31 Australia’sgreenhousegasemissions...............................................................43 Table32 SummaryofselectedcarbontaxstudiesbasedonPPPforAustralia...........61 Table33 AustralianCO2emissions:PPPvs.SRP ............................................................68 Table41 Studiesadoptingphysicalflowmethod ...........................................................77 Table42 PhysicalFlowMethods:KeyFeatures...............................................................85 Table43 Modellingstudiesadoptingembodiedenergymethod .................................87 Table44 EmbodiedEnergyMethods:KeyFeatures .......................................................94 Table51 Parameterestimatesforelectricitysector:energysubmodel .....................119 Table52 Parameterestimatesforelectricitysector:interfactormodel .....................120 Table53 Parameterestimatesforfinaldemand:energysubmodel...........................121 Table54 Parameterestimatesforfinaldemand:interfactormodel...........................122 Table55 Summaryofsectoralclassification...................................................................127 Table56 Economicandtechnicalcharacteristicsofpowerplants ..............................129 Table61 Technologymixforelectricitygeneration......................................................142 Table62 Electricitysupplycosts ......................................................................................145 Table63 Primaryenergyconsumptionandenergydiversity .....................................151 Table64 Percentagechangesincarbondioxideemissions..........................................154 Table65 Impactsofcarbontaxoneconomicoutput:2005–2020.................................157 Table66 Increaseinsectoralprices:2005–2020..............................................................167 Table67 Fiscalrevenuefromcarbontax:2005–2020.....................................................170 Table68 Neteconomicimpactsofcarbontax:2005–2020............................................172 Table69 Impactsofcarbontaxtoachieveanaprioriemissiontarget........................177 Table610 Comparisonofeconomiccosts:PresentandFuturevalues .........................187 Table611Comparisonofeconomiccosts:Shortterm(2020)andLongterm(2040)..188 Table612 ComparisonsofresearchresultsfromcarbontaxstudiesforAustralia ....190 Table613 Summaryofenvironmentaleconomicsocialtradeoffs ................................194 ix LISTOFFIGURES Figure11 AnnualgrowthinenergyconsumptionandrealGDPinAustralia .............. 3 Figure12 Energybalance ...................................................................................................... 7 Figure13 Materialsbalance................................................................................................... 8 Figure14 Overallresearchframework ...............................................................................11 Figure15 Sectoralcoverageforthisresearch.....................................................................15 Figure21 Primaryenergyconsumptionforelectricitygeneration.................................31 Figure22 Domesticmarketshareofblackcoal .................................................................32 Figure31 Carbondioxideemissionsfromelectricitygeneration ...................................45 Figure41 Aclassificationofmaterialsbalanceapproaches ............................................74 Figure51 Schematicdiagramoftheoverallmethodologicalframework......................99 Figure52 Representationofdirectandindirectenergyconsumption.........................104 Figure53 Substitutioneffectinneoclassicaleconomictheory ......................................109 Figure54 Inputstructureoftheelectricityindustry.......................................................112 Figure55 Consumptionpatternforfinaldemand ..........................................................114 Figure61 Attributesforassessingimpactsofcarbontax...............................................137 Figure62 Primaryenergyconsumptionforelectricityproduction ..............................148 Figure63 Carbondioxideemissionsfromfossilfuelcombustion ...............................153 Figure64 Annualpercentagechangesineconomicparameters...................................158 Figure65Sectoraloutputs..................................................................................................161 Figure66Sectoraldemandforinvestment ......................................................................161 Figure67Sectoraloutputsforfinalconsumption...........................................................162 Figure68Sectoraloutputsforintermediateconsumption ............................................162 Figure69Sectoraloutputsforexports..............................................................................163 Figure610Sectoralsupplyofinvestmentgoods ............................................................163 Figure611 Increasesininflationrates.................................................................................168 Figure612 Percentagechangesintotalemployment .......................................................173 Figure613 Changesinsectoralemployment .....................................................................173 Figure614 EmissionspathwayofachievingaprioriCO2limit .......................................176 Figure615 Economicimpactsofachievingemissionstargetfromelectricitysector ...178 x ABBREVIATIONS/GLOSSARY AAEC ABARE ABRCC ABS ACA ACARP AGO ASFF BCA BCSE CCS CES CISS COAG COP CSIRO DITR ECNSW ERAA ESAA ESD ESI ETSA GCP GDP GHG IEA IHA IPCC LCA LETAG LETDF MARKAL MATTER MESSAGE MFA MIMES MRET Mt NEM AustralianAtomicEnergyCommission AustralianBureauofAgriculturalandResourceEconomics AustralianBusinessRoundtableonClimateChange AustralianBureauofStatistics AustralianCoalAssociation AustralianCoalAssociationResearchProgram AustralianGreenhouseOffice AustralianStocksandFlowsFramework BusinessCouncilofAustralia BusinessCouncilforSustainableEnergy CarbonCaptureandSequestration ConstantElasticityofSubstitution CoalinaSustainableSociety CouncilofAustralianGovernment ConferenceoftheParties CommonwealthScientificandIndustrialResearchOrganisation DepartmentofIndustry,TourismandResources ElectricityCommissionofNewSouthWales EnergyRetailersAssociationofAustralia ElectricitySupplyAssociationofAustralia EcologicallySustainableDevelopment ElectricitySupplyIndustry ElectricityTrustofSouthAustralia GreenhouseChallengeProgram GrossDomesticProduct Greenhousegas InternationalEnergyAgency InternationalHydroAssociation IntergovernmentalPanelonClimateChange LifecycleAnalysis LowerEmissionsTechnologyAdvisoryGroup LowEmissionsTechnologyDemonstrationFund MARKetALlocation MATerials Technologies for greenhousegas Emission Reduction Model for Energy Supply Strategy Alternatives and their GeneralEnvironmentalimpacts MaterialFlowAnalysis Model for description and optimisation of Integrated Material flowsandEnergySystems MandatoryRenewableEnergyTarget Milliontonnes NationalElectricityMarket NGAP NGGIC NGRS NGS NGSC NIEIR OECD PJ ppmv PPP RBA RES RMS RRI SECV SMHES SRP TIC Translog UNFCCC xi NationalGreenhouseAdvisoryPanel NationalGreenhouseGasInventoryCommittee NationalGreenhouseResponseStrategy NationalGreenhouseStrategy NationalGreenhouseSteeringCommittee NationalInstituteofEconomicandIndustryResearch OrganisationforEconomicCooperationandDevelopment Petajoules Partspermillionbyvolume PolluterPaysPrinciple ReserveBankofAustralia ReferenceEnergySystem ReferenceMaterialSystem ResourceResearchInstitute StateElectricityCommissionofVictoria SnowyMountainsHydroElectricScheme SharedResponsibilityPrinciple TechnoInstitutionalComplex TranscendentalLogarithmic UnitedNationsFrameworkConventiononClimateChange 1 CHAPTER1 1 INTRODUCTION 1.1 Background Climatechangeisoneofthemostpressingproblemsfacinghumanity.1Itisaresultof increaseinglobaltemperature(globalwarming)causedbythereleaseofgreenhouse gases into the atmosphere. The emission of greenhousegases is partly a result of natural environmental processes and partly due to human activity. The naturally occurring greenhousegases help balance the incoming and outgoing solar radiation, thusmaintainingtheearth’stemperatureatanaverageofabout15°C(2001).Without this natural phenomenon, the earth’s average temperature would be 15–20°C below zero, which would make it difficult for living beings to survive. However, it is the humaninduced activity that has been the major cause of global warming. Since the beginningoftheIndustrialRevolution–lateeighteenthandearlynineteenthcenturies – the concentrations of greenhousegases in the atmosphere have increased dramatically. Atmospheric concentrations of CO2 – a major greenhousegas – has increasedbymorethan30percent,from280ppmvduringpreindustrialrevolution, to 368 ppmv in the year 2000 (Houghton et al. 2001). The increase in anthropogenic greenhousegas concentration in the atmosphere tends to destabilise the naturally occurringradiativeforcing2betweentheearthandsolarsystem.Thishasresultedinan increase in the global average temperature by 0.6 ± 0.2°C since the late nineteenth century(Houghtonetal.2001).InAustralia,theaveragetemperaturehasincreasedby 0.7°Coverthelastcentury(Pittock2003).Intheabsenceofanypolicyactiontoreduce There is of course some scepticism about the enormity of this problem (see, for example, Lomborg(2001).Thisresearchhowevertakesthemorewidelyheldview–alsoendorsedby theIPCC–onclimatechange,namely,thatclimatechangeisindeedapressingissue. 2Radiativeforcing,according to Houghtonet al.(2001), isameasure oftheinfluenceafactor has in altering the balance of incoming and outgoing solar radiation to the earth, and is an indexoftheimportanceofthefactorasapotentialclimatechangemechanism. 1 2 greenhousegasemissions,theworldemissionsareprojectedtoincreasesubstantially. Thiscouldleadtoanannualaveragewarmingof0.4°Cto2°CovermostofAustralia by2030and1°Cto6°Cby2070,ascomparedto1990temperaturelevels(CSIRO2001). It is now widely accepted that even a slight increase in temperature would have a significantly detrimental impact on economic, social, and natural ecosystems. As evidenced in 2002, Australia experienced its worst drought since at least 1950 which was the first drought when the impact of humaninduced global warming could be clearlyobserved.Thisdroughtnotonlyledtothedisruptionofecologicalsystem,but alsodecreasedagriculturalproductivity,whichreducedtherateofeconomicgrowthin Australia during 200203 by 0.75 per cent (Karoly, Risbey & Reynolds 2003). Further, the recent drought of 2006 is also expected to have a similar impact. ABARE (2006b) estimatesthatthisdroughtcouldreduceeconomicgrowthinAustraliafor200607by around 0.7 per cent. According to Pittock (2003), the impact of climate change in Australiainclude:“50percentdecreaseinwatersupplyinPerthsince1970s…nearrecord low water levels in reservoirs in the southeast Australia in 200203 due to low rainfall and hightemperature…increasingtheseverityofdrought…severeandwidespreadbleachingon theGreatBarrierReef“.Attheinternationallevel,theimpactofclimatechangehasbeen significantaswell.SelectedexcerptsfromStern(2006)shouldsubstantiatethis,“China experiencedlossesin1.2percentofGDPin2004duetocombinationofdroughtandflood… the2000flood in West Bengaldestroyedsignificant transportinfrastructures …theLaNiña drought in Kenya in 199899 and 19992000 caused damage amounting to 16% of GDP for each year … the drought in Ethiopia between 19982000 caused poverty level to increase by 25% … Hurricane Katrina in New Orleans in 2005 costs 1.2% of US GDP … European heatwave in 2003 (2.3°C hotter than average) caused deaths of around 35,000 people across Europe”.Inaddition,thefutureimpactofclimatechangeisexpectedtobelargerthan in the past, mainly due to frequency of extreme weather variations and coastal flooding(ibid). Emissions of greenhousegases come from a variety of sources and locations. The combustion of fossil fuels is the single most important source of anthropogenic CO2 emissions, contributing about threequarters of global emissions (Houghton et al. 3 2001).InAustralia,theproductionanduseofenergyisthesinglelargestsourceofCO2 emissions. For example, in 2004, it accounted for over 85 per cent of total CO2 emissions and 63 per cent of total greenhousegases emissions (AGO 2006). The Australianenergysectorisdominatedbyfossilfuels,whichaccountedforaround95 percentofprimaryenergyconsumedin2005(ABARE2006a).Also,itiswidelyagreed thatenergyisanessentialingredientforeconomicprosperity.Thelinkbetweenenergy consumption and economic growth in Australia is shown in Figure 11. This figure shows the annualgrowthratesof energyconsumption andreal GDPsince 1975.Itis noticedthatenergyconsumptiongrewataratethatcloselymatchestherateofgrowth in GDP. A rapideconomicgrowth will clearly resultin largeincrease inthedemand forenergy.Butthisgrowthwillbesustainableonlyifthereisareliable,uninterrupted supply of energy in a form that does not threaten the environment. In Australia, the primary energy consumption is expected to increase by 46 per cent by 202930 to support an economicgrowthof 2.6 per cent peryear(CuevasCubria &Riwoe 2006). Nearly94percentofthisincreaseislikelytocomefromfossilfuels(ibid). Figure11 AnnualgrowthinenergyconsumptionandrealGDPinAustralia 8 6 4 percent 2 0 1975 1980 1985 1990 1995 2000 2005 2 4 realGDP energyc onsumption Source: ABARE(2006a),ABS(2006a) 4 Electricity industry is a major contributor to environmental problems. According to Diesendorf (2003, p. 2), “About 97 per cent of the electricity industry’s greenhousegas emissions comes from twentyfour coalfired power stations … an amount of greenhouse pollutionequivalenttotheannualemissionsfromabout40millioncars”.Theseemissionsare equivalent to about half of total Australia’s CO2 emissions. The Australian electricity sector is the largest consumer of fossil energy and historically has been one of the fastest growing sectors (Dickson & Warr 2000). Electricity generation in Australia is dominated by coalfired power generation. In 2005, about 84 per cent of Australia’s electricitywasgeneratedfromcoal(ESAA2006),comparedto26percentinEuropean Union and 50 per cent in the United States (IEA 2006). Furthermore, it is anticipated that the amount of future investments needed to finance the world’s burgeoning energysupplywillbesignificantlyhigherthanhasoccurredinthepast.Morethan$16 trillionneedstobeinvestedinenergysupplyinfrastructureworldwideoverthenext three decades, out of which $10 trillion would be needed for the development of electricity sector alone (OECD/IEA 2003). Thus, if emissions are to be reduced substantially, the electricity industry will have to undergo profound changes in the technologies that generate electricity. However, unless there is a decisive way to address environmental problem, within a few years, growth in electricity sector emissionswillstarttodriveAustralia’sgreenhousegasemissionsinexorablyupward. The urgency of reducing CO2 emissions has begun to influence policy agendas worldwideonlyinthelastdecade.Thiswasduetotheincreasingawarenessaboutthe impending dangers from climate change as mentioned earlier. Over the last several years,therehavebeenincreasingnationalandinternationalpressuresforcountriesto showresponsibilitybylimitingCO2emissions.Thefirststepstowardsconfrontingthe climatechangewerediscussedinTorontoconferencein1988.Inthisconference,there was a “call for action” to reduce global CO2 emissions. This was followed by the establishment of international environment bodies (such as IPCC and UNFCCC), which later on lead to the formulation of environmental protocol in 1997 (i.e., Kyoto 5 Protocol). The Kyoto Protocol requires each of the Annex I countries3 to reduce its greenhousegas emissions to at least 5 per cent below 1990 levels in the commitment period 20082012. As of February 2007, 84 countries (including Australia) had signed the Kyoto Protocol, and 170 countries had ratified it. Australia has, however, not yet ratifiedtheProtocol. Arangeofpolicyoptionsarebeingconsideredbyvariouscountriesaroundtheworld to mitigate greenhousegas emissions. These policy measures are based either on command and control (or regulatory) standards, voluntary action, marketbased mechanisms, or a combination of these approaches. Regulatory standards require polluterstomeetaspecificlevelofemissionstarget,regardlessoftherelativecostsof meeting this target. This approach, together with voluntary action, have been mainly adopted in Australia, as it can be manipulated to serves commercial interest and achievethepoliticalgoal(seeSection3.2fordiscussiononthisissue).Assuggestedby ERAA (2004, p. 2), “the existing policy environment in Australia, which is mainly characterised by regulatory approach, are a fragmented array of shortterm State and Federal Government greenhousegas abatement measures that tend to be poorly targeted, overly complex and highly inefficient as mechanisms for reducing emissions”. Also, emission reductionfromelectricitysectorareunlikelytohappenfromvoluntaryaction(MMA 2002). In contrast, marketbased approaches alters market price signals to provide an incentive for consumers to conserve energy and for producers to invest in cleaner energy technologies. This approach is favoured by most economists and some environmentalists because it treats the environmental cost of energy in a transparent manner. Environmental factors are normally “external” to the market system, that is, they are not taken into account in the conventional economics oriented decision Annex I comprises of 36 countries, including Australia, Austria, Belgium, Bulgaria, Canada, Croatia, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Latvia, Lithuania, Luxembourg, Netherlands, New Zealand, Norway,Poland,Portugal,Romania,RussianFederation,Slovakia,Slovenia,Spain,Sweden, Switzerland,Ukraine,UnitedKingdom,andtheUnitedStates. 3 6 making. A marketbased environmentalpolicy approach instead ensures that these externalities are internalised (in the economic costs); it allows market mechanism to sendpricesignalsthatcanachieveanappropriatebalancebetweeneconomicbenefits ofenergyuseanditsenvironmentalcosts. Emissionstradingandcarbontaxaretwomainmarketbasedinstrumentsthatapolicy makercanchoosetoreduceCO2emissions.4However,theseapproaches,carbontaxin particular, have not received unqualified support in the past. This is because of the perceived adverse economic impacts of these approaches – carbon tax, in particular. Thisoppositiontothecarbontaxoption,thisresearchcontends,isbasedonlessthan completeunderstandingoftheeconomicsandbroaderdynamicsofthisoption.Much ofthediscussiononcarbontax,forexample,focusesontheformulationofcarbontax on the basis of Polluter Pays Principle (PPP). Based on this principle, the polluter (emitter) is defined as a consumer of primary energy (called direct energy) where combustion takes place. CO2 emission is, therefore, considered as the sole responsibility of this emitter. The magnitudes of (direct) energy consumption and associatedCO2emissions,basedonPPP,aretraditionallydeterminedfromanenergy balance approach. A schematic of this approach is shown in Figure 12. It shows the unidirectionalrelationshipbetweenenergy,economy,andtheenvironment.Here,the flow of energy is relatively straightforward, beginning with the primary energy extractionfromthe environment, toenergy conversion, andending with itsenduses such as by households and industry. In this approach, the electricity sector is considered as the consumer of primary energy; this energy is used for electricity production. Further, renewable resource based technology is considered as a zero emissions technology because it consumes only nonfossil energy. This implies that carbontaxbasedonPPPtendstopenalisebigpolluterssuchasfossilfuelindustries, particularly coalbased electricity industry. Based on this principle, electricity Carbontax,infact,involvesamixtureofregulatoryandmarketbasedapproaches.Itrequires government intervention in regulating the tax components to ensure the internalisation of externalities and, at the same time, requires free market principles to send price signals in ordertoachieveemissionreduction. 4 7 generatedfromrenewableenergyresourceswouldnotbepenalisedatall.Inaddition, the endusers, such as households and industries, are only responsible for a small amount of direct fossil energy consumption, although they are large consumers of electricity producedfrom fossilfuels.Theapplication of carbontax,basedonPPP,is considered inequitable by some because it holds fossil fuel consumers as solely responsibleforcreatingemissions. Figure12 Energybalance An alternative approach to the formulation of carbon tax is based on Shared Responsibility Principle (SRP). This approach assigns the responsibility for CO2 emissions not only to the polluters of emissions, but also the consumers of products and services whose production would have caused CO2 emissions. In this approach, for example, renewable technology (which would have been considered as a zero emission technology in terms of the PPP approach) would be considered responsible forCO2 emissionsto the extent of energyand hence CO2 emissionsembedded inthe materials that are used to build and operate this technology, over its lifetime. By a similarreasoning,industrieswouldbeliableforCO2emissionsnotonlytotheextent of their CO2emitting direct fuel consumption, but also to the indirect energy embeddedinothermaterialinputstheyconsumeintheproductionprocess.Similarly, households are responsible for consuming CO2emission embedded consumption goodsandservices. 8 The task of determining indirect energy (and associated CO2 emissions) for each economic activity in a society is, however, complex. Reasonably robust policyuseful estimationscould,however,bedevelopedbyadoptingamaterialsbalanceapproach.5 AschematicofmaterialsbalanceisshowninFigure13. Figure13 Materialsbalance The energyeconomyenvironmental interactions shown in materialsbalance are relativelymorecomplex.Takerenewabletechnologyasanexample.Itwasconsidered as a zero emission technology under the PPP (or the energybalance approach). However,underthematerialsbalanceapproach,someemissionsarealsoattributedto thistechnology,inproportiontotheconsumptionofmaterials.Theincreaseindemand for renewable electricity will resulted in increase demands for these materials. The production of these materials would require additional energy, which inturn would produce CO2 emissions. In contrast to the energybalance, here the renewable electricity is also responsible for creating CO2 emissions. Using the materialsbalance The materialsbalance approach discussed here is adapted from the materialsbalance approachdevelopedbyKneese,Ayersandd’Arge(1970).SeeSection3.3.3andSection4.1for morediscussion. 5 9 approach,theenvironmentalimpactfromtheconsumptionofenergy(andemissions) embodied in materials can also be captured. Hence, the responsibility for CO2 emissions could be appropriately assigned, based on both direct as well as indirect (thatis,embeddedinthematerials)energyconsumption. The application of carbon tax based on materialsbalance (rather than the energy balance) provides a fuller understanding of energyeconomyenvironmental interactions. Furthermore, this approach provides a foundation for allocating emissions to each economic activity in the economy in a manner that truly reflects environmental impacts of that activity. Despite this advantage, there is a lack of analysis and discussion about various facets of this approach. This is the subject of investigationinthisresearch. 1.2 ResearchObjectives Against the above background, the main objective of this research is to examine the appropriatenessofcarbontax(designedonthebasisofenergybalanceandmaterials balance approaches) as a policy option to reduce carbondioxide emissions from the electricitysectorinAustralia.Inordertoachievethisobjective,fourspecificobjectives havebeenset.Theseareasfollows. I. Review the evolution of the Australian electricity industry with a view to develop a wider perspective on the role of coal in the Australian electricity complex. II. ProvideanoverviewofthedevelopmentofgreenhousepolicyinAustraliawith aviewtoexaminetheforcesthathaveshapedthispolicyand,inparticular,the rolethatcoal–electricitycompacthasplayedinshapingthispolicy. III. Reviewalternativemethodologiesavailablefordesigningacarbontaxandfor determining the impact of carbon tax on the wider economy – and identify a methodologicalframeworktobeappliedinthisresearch. 10 IV. Apply the framework identified in III above to assess the economywide impacts of carbon tax and analyse the appropriateness of alternative conceptionsofcarbontaxaspolicymeasurestoreduceCO2emissionsfromthe electricitysectorintheAustraliancontext. 1.3 ResearchMethodology TheoverallmethodologicalframeworkusedinthisresearchisshowninFigure14.A combination of methodologies are applied in this research. These methodologies are dividedintothreeparts–historicalreview,energyandenvironmentalmodelling,and policyanalysis.Asummarisedoverviewofthesalientfeaturesofthesemethodologies isprovidedinthissection.Adetaileddescriptionforeachmethodologyisprovidedin relevantchaptersofthisthesis. Figure14 Overallresearchframework 11 12 1.3.1 HistoricalReview Thehistoricalreviewinthisresearchinvolvesareviewoftwoaspects–theevolution ofelectricityindustryandthedevelopmentofenvironmentalpolicyinAustralia. For the first objective, the evolution of the electricity industry is reviewed. Several studies have reviewed the history of the Australian electricity industry, for example, ESAA (1973), McColl (1976), Rosenthal and Russ (1988), Johnson and Rix (1991), Kellow (1996), Sharma and Bartels (1998), Booth (2003), Sharma (2003), and Fathollazadeh(2006).Thesestudiesdescribedchangesintheelectricityindustry over time. However, the historical review in this research focuses specifically on the circumstances during the evolution of the electricity industry that lead to the intensification of coal–electricity compact. The review of the Australian electricity industryinthisresearchisdividedintofivetimeperiods–theoriginsoftheindustry (1880s1900),thegenesisofthecoal–electricitycompact(1900s1950),theconsolidation of the compact (1950s1980), further strengthening of the compact (1980s1990s), and theentrenchmentofthecompact(1990spresent).Further,areviewofrecentliterature ontechnical,economic,andpoliticalaspectsoftheelectricityindustryisundertakenin order to indicate how the coal–electricity compact would influence the future developmentoftheelectricityindustry. For the second objective, the historical development of the Australian greenhouse policiesisreviewed.Severalstudieshavereviewedtheevolutionofgreenhousepolicy developmentinAustralia,forexample,Taplin(1994),Bulkeley(2001),Hamilton(2001), Hunt (2004), Christoff (2005), and Riedy (2005). The historical review undertaken in this research focuses on understanding the process of how greenhouse policy development has progressed in Australia. Greenhouse policy development in Australia is still in its infancy (as compared with the development of the electricity industry);itonlystartedtoexertsomepolicyinfluenceinthe1990s.Consequently,the review in this research particularly emphasises the changing stance of the Australian Government towards the greenhouse policy in the recent past. Further, a review of studiesfocusingontheapplicationofcarbontaxintheAustraliancontextisperformed 13 in detail. This review focuses on developing an understanding of the basis (that is, energybalanceapproach)onwhichcarbontaxdebatewasfoundedinthepast.Itthen proposesanalternativebasis(thatis,materialsbalance)forthedesignofcarbontax. 1.3.2 ModellingPerspective Thisresearchadoptsamaterialsbalanceapproachforanalysingtheimpactsofcarbon tax.Inthisapproach,thedescriptionofenergyeconomyenvironmentalinteractionsis underpinnedbyadetailrepresentationofenergyandmaterialflowsintheeconomy. The formulation of a framework required for such representation is obviously a challengingtask.Thischallengeisaddressedinthisresearchinthefollowingmanner. First,theconceptualfoundationsofvariousmethods,thatcanincorporatematerialand energyflowsarereviewed.Thesemethodsareclassified intotwo –methodsthat are based on physical material flows and those based on embodied energy flows. The purpose of this review is to determine the strengths and weaknesses of different methods,sothattheappropriatemethodforthisresearchcanbeselected.Thisreview wasconductedinthecontextofthefollowingcriteria;theabilitytoperformanalysisat sufficient level of sectoral detail (spatial scope), ability to provide analysis over long timeframe (temporal scope), ability to capture changes in technology and capital investment (dynamics), ability to analyse price impacts of carbon tax (price considerations),andtheflexibilityintermsofdatarequirements. Based on this review, input–output method, with modified production function, is selected for application in this research. The framework based on this method comprisesoffiveinterlinkedmodules.Inthefirstmodule,CO2emissionsareallocated across different economic sectors based on energy as well as materialsbalance approaches. Based on these allocations, CO2 intensities are estimated. In the second module,acarbontaxisassignedbasedonenergyintensities.Inthethirdmodule,the relative changes in energy and material prices, in response to a carbon tax, are estimated.Thesectoralpriceeffectsareestimatedusinginput–outputpricemodel.In the fourth module, the substitution effects, in response to changes in energy and materialprices,areanalysed.Thedesignoftheproductionfunction,fortheanalysisof 14 these substitution effects, is based on multistage estimation procedure developed by Fuss (1977). The substitution possibilities between aggregate factor inputs (capital, labour, electricity, energy, and materials) and energy inputs (coal, oil, and gas) are estimatedusingTranslogcostfunction;whereasthesubstitutionpossibilitiesbetween material inputs are estimated using CobbDouglas cost function. In the final module, theeconomywideimpactsofcarbontaxareanalysed.Theseimpactsinclude–energy, environmental, economic, and social. These impacts are analysed using energy environmentorientedinput–outputmodel,proposedbyProopsetal.(1993). 1.3.3 PolicyAnalysis The policy implications of carbon tax (based on both energy and materialsbalance approaches)areanalysedwithreferencetoCO2emissions. A basecase scenario is created in this research so that the impacts arising from the applicationofcarbontaxbasedonenergyandmaterialsbalanceapproachescouldbe compared and policy inferences drawn. In the first instance, the economywide impactsofcarbontaxareassessedwithoutimposinganyaprioriemissionslimits.Two levels of carbon tax are considered, namely, $10 per tonne and $20 per tonne of CO2 emissions.Anassessmentoftheimpactsofcarbontaxisalsoundertakeninasituation where there is an apriori restriction on CO2 emissions from the electricity sector. A comparison is also made between the policy implication of early and delayed introductionofcarbontax. 1.4 ScopeofthisResearchandDataConsiderations ThisresearchfocusesonAustralia.Thespatial,temporal,andsectoralscopeofanalysis has been dictated by the consideration of data availability. The scope of sectoral coverageisshowninFigure15. 15 Figure15 Sectoralcoverageforthisresearch TheAustralianeconomy,inthisresearch,hasbeenorganisedintermsofeightenergy sectors (suppliers of primary and secondary energy) and twenty economic sectors (suppliers of nonenergy materials). This sectoral organisation is based on national input–output tables published by the Australian Bureau of Statistics (ABS). The 28 energyandeconomicsectors(asnotedabove)areanaggregatedversionofanumber ofsectors–rangingbetween106and113–representedintheAustralianinput–output tables.Thefourenergysupplyandconversionsectorsareadopteddirectlyfrominput– output tables. The electricity sector has been disaggregated into five generation technologies – namely – conventional coalfired, internal combustion, gas turbine, combinedcycle, and renewable. Such disaggregation allows for a representation of different characteristic of major electricity generation technologies used in Australia which account for more than 97 per cent of electricity production capacity. This disaggregationisalsoaccordwiththeannualdatapublishedbytheElectricitySupply 16 Association of Australia (ESAA). The renewable electricity technology sector in this researchincludeshydro,wind,solarthermal,photovoltaic,etc.Thesetechnologiesdo not consume fossil energy directly for electricity production but are highly materials intensiveascomparedtofossilfuelbasedpowerstation. Theaggregationoftwentyeconomicsectorsisbasedonenergyintensivenessofeach sector. More energy intensive sectors are kept separate while less energy intensive sectorsareaggregatedintoonesector.Forexample;ironandsteelandnonferrousmetal sectorsarekeptseparate,whilethesubsectorsinagriculture,food,textileandcommercial sectors are combined (see Table 55 for the summary of sectoral classification). As a consequence,somesectorscompriseasinglesector,whileothers–several.Thesectoral classificationofthisresearch,ascomparedtosectoralclassificationofnationalinput– outputtables,isgiveninTableC1(AppendixC,pp.234237). ToavoiddoublecountingofCO2emissionsduetoenergyconsumption,thisresearch has constructed primary energy consumption tables in correspondence with sectoral classification of the input–output tables (as outlined in Figure 15). The primary energies considered in this research are – black coal, brown coal, natural gas, and petroleum.Theconstructionofthistableisbasedonprimaryenergyconsumptiondata for28sectors,whicharepublishedannuallybytheAustralianBureauofAgricultural andResourceEconomics(ABARE2006a).Further,theCO2emissionsareestimatedon the basis of emission factors for each type of primary energy. These emission factors aretakenfromNGGIC(1996). The time period for analysis in this research is 1980 to 2020. The most recent input– outputtableusedinthisresearchisfortheyear2002–publishedbyABSinJuly2006. Asmentionedabove,thisresearchrequiresawiderangeoftimeseriesdataonenergy, economy, and environment. These data are collected from a variety of published sources,andsupplementedbypersonalcorrespondencewithprofessionalsworkingin these sectors of the economy. The overview of data considerations for each specific objective is shown in Table 11. Further details of data sources and preparation (for modellingpurposes)forthisresearcharediscussedinSection5.7. 4 3 No (a)CapitalIOcoefficients Yes Yes No (a)GDPgrowthrateforfuture (a)Labourproductivityforfuture (b)Energyefficiencyimprovement Yes Yes Yes Yes Incomplete Incomplete Yes (a)TechnicalIOcoefficients (b)Primaryenergyconsumption (c)CO2emissionfactor (d)Electricitycapacitybytechnology (d)Electricitygenerationbytechnology (e)FactorcostsharesforESI (f)FactorPricesforESI Yes gap (e)ABS(input–outputtables) (f)ABS(labourandmaterialsprices) (f)ABARE(nonelectricenergyprice) (f)ESAA(electricityprice) (f)RBA(capitalprice) (a)CommonwealthofAustralia (b)ABARE (c)AGO (d)ESAA (a)ABS No Yes No No No No Yes Yes No No No No Yes No Assumption Datainterpolation Datainterpolation Secondarydata# overcomedatagap Data Strategiesto Books,journalarticles,reports,legislation, Partial andpolicypapers Dataconsiderationsforeachspecificobjective Data DataSources Availability Informationforelectricitysectorand environmentalpolicyinthepastand expectedfuture Table11 17 ABAREAustralianBureauofAgriculturalandResourceEconomics;ABSAustralianBureauofStatistics;AGOAustralianGreenhouseOffice;ESAAElectricity SupplyAssociationofAustralia;RBAReserveBankofAustralia. # Datatodevelopcapitalinput–outputtableisnotdirectlyavailable.Thisisestimatedfromsecondarydata(thatis,fromvariousotherABSpublications). 1&2 Objectives Datarequirements Note: 18 1.5 SignificanceofthisResearch This research has made a significant contribution to the analysis of one of the most criticalissuecurrentlydominatingpolicydebateinAustralia,namely,climatechange. In particular this research has provided valuable insights into assessing the appropriateness of carbon tax as a policy measure to reduce climatechanging CO2 emissions. Traditionally,carbontaxisformulatedbasedonthePolluterPaysPrinciple.According tothisprinciple,emissionsresponsibilityisallocatedtovarioussectorsintheeconomy by using an energybalance approach. This approach considers the energyeconomy environmentalinteractionsasarisingfromtheflowofdirectenergyonlyandignores energy embodied in the use of materials. The application of this approach for policy formulation could lead to an incorrect estimation of energyeconomyenvironmental interactions and hence result in erroneous policy choices. This research proposed an alternative concept for designing carbon tax, namely, based on Shared Responsibility Principle. Under this principle, emissions responsibility is reallocated across the economyonthebasisofamaterialsbalanceapproach.Thisconceptionofcarbontax– this research has demonstrated – has significantly different (that is, different from those based on Polluter Pays Principle) ramifications on the economy. This demonstration is provided in this research through the development and application ofacomprehensiveresearchframeworkthatallowsforthecapturingofthecomplexity of the energyeconomyenvironmental interactions in a detailed manner, at national, sectoralandsubsectorallevels. TheresultsofthisresearchmightbeofinteresttotheAustralianenvironmentalpolicy makers,policyanalystsandprofessionalsengagedindevelopingAustralia’sresponse to the climate change issue. This research should also be useful for other researchers who might wish to employ this framework to analyse other energyenvironmental issues. 19 1.6 OrganisationoftheThesis Thisthesisconsistsofsevenchapters. Chapter 2 describes the evolution of the coal–electricity compact in the Australian context. This description includes a brief historical overview of Australian electricity industryfromitsinceptionthroughtothepresenttimeanditslikelyfutureevolution. Chapter3providesanoverviewofthedevelopmentofgreenhousepolicyinAustralia. The purpose of this review is to demonstrate the government’s attitudes towards environmentalpolicy(carbontaxinparticular).Therationaleandstrategyfortheuse of carbon tax (based on materialsbalance approach) as a future policy option is also discussed. Chapter 4 reviews methods for applying the materialsbalance concept, for determining the direct and indirect contribution made by various economic activities to CO2 emissions. The purpose of this review is to understand the relative strengths and weaknesses of each method in order to select an appropriate method for this research. The methodological framework, for assessing the impacts of carbon tax, is thendescribedindetailinChapter5. In Chapter 6, the economywide impacts of carbon tax are analysed. This analysis is carried out separately, based on energy and materialsbalance approaches. Also discussed in this chapter are some of the policy implications of carbon tax in the Australian context. Chapter 7 presents the main conclusions of this research, and providessomerecommendationsforfutureresearch. 20 CHAPTER2 2 EVOLUTIONOFTHECOAL–ELECTRICITYCOMPACT The electricity industry is one of the most important industries in the Australian economy. In the year 2005, it contributed approximately 1.6 per cent to the gross domesticproduct,waswortharound$100billion(nominalprices)inassets,employed nearly 40,000 persons, incurred a capital expenditure of over $6 billion (nominal prices), and yielded a sales revenue of over $34 billion (nominal prices) (ABS 2006b). The industry provided over 22 per cent of the total final energy for domestic consumption in 2004, which increased from 14 per cent in 1980 (ABARE 2006a). The electricity industry also has a significant impact on climate change. It contributed nearly35percentoftotalAustraliangreenhousegasemissionsin2004(nearly50per centoftotalCO2emissions)(AGO2006).Thisisbecausecoalisthedominantfuelfor electricity production in Australia, contributing about 84 per cent of the electricity produced in 2004 (ESAA 2006). It is expected that the domination by coal is likely to continue in the years to come. For example, it is estimated that coal will represent about70percentofelectricityproductionin2030(CuevasCubria&Riwoe2006).The environmentalconsequences(inparticular,CO2emissions)ofsuchdominationshould beobvious.Bythisreasoning,the“role”ofcoalinthewiderelectricitycontextwould beamajorconsiderationinanyenvironmentalpolicyinitiativetakenbythecountryto containCO2emissions.Adeeperunderstandingofthisroleisthereforeaprerequisite for developing an insightful perspective on the efficacy of various environmental initiatives for containing CO2 emissions, including carbon tax – the focus of this research.Thischapterisdevotedtowardsthatend. Thischapterisorganisedasfollows.Section2.1providesabriefhistoricaloverviewof the Australian electricity industry from its inception to the present. This review is intendedtodemonstratewhytheelectricitysysteminAustraliabecamedominatedby coal. This is followed by a discussion on the likely future direction of the electricity industry(Section2.2),andwhycoalislikelytocontinuetoplayadominantroleinthe 21 future.Finally,asummaryofthemajorfindingsofthischapterisprovidedinSection 2.3. 2.1 HistoricalReviewoftheAustralianElectricityIndustry Thefocusofthereviewinthissectionistodemonstratethecircumstancesduringthe historicalevolutionoftheelectricitysupplyindustrythathaveledtotheintensification ofthecoal–electricitycompact.Thereisanextensiveliteraturethatreviewsthehistory of the evolution of the Australian electricity industry, for example, ESAA (1973), McColl (1976), Rosenthal andRuss (1988), Johnson and Rix (1991), Kellow (1996), Sharma and Bartels (1998), Booth (2003), Sharma (2003) and Fathollazadeh (2006). Somebroadinferencescanbedrawnfromthesereviewsaboutthenatureofthecoal– electricity compact. In this chapter, these inferences are supplemented by additional information in order to develop a more complete picture of this compact. For this purpose, the historical review in this section is divided into five time periods – the origins of the electricity industry (1880s–1900), the genesis of the coal–electricity compact (1901–1950s), the consolidation of the compact (1950s–1980s), further strengtheningofthecompact(1980s–1990s),anditsentrenchment(1990s–present). 2.1.1 OriginsoftheElectricityIndustry(1880s–1900) Australia is a federation of six states and two territories. The Australian electricity industrystartedinthelatenineteenthcentury,aroundstatecapitalsandruraltowns. Atthat time, electricitywasrelativelymoreexpensive than other energysources and wasconsideredasaluxury.Thetechnologiesthatwereusedforgeneratingelectricity in those day were typically distributed, with separate plant supplying electricity to each town and community (Sharma & Bartels 1998). The industry ownership was largelyprivate. The availability of indigenous coal was an important determinant of the early development of the electricity industry in Australia. Australia possessed abundant reservesofcoal,andthecoalminingindustrywasalreadywellestablishedpriortothe inceptionoftheelectricityindustry.Forexample, NewSouthWalesiswell endowed 22 with large reserves of highquality black coal. In fact, the first coal field in Australia was discovered in New South Wales in the Hunter and Illawarra regions in 1791 (Hargraves1993).Victoriahassignificantreservesofbrowncoalandhasminedthem, since 1890, in the Latrobe Valley. However, qualitatively this coal is inferior to black coal. This posed many problems in mining and combustion. Victoria has therefore been forced to rely on black coal from New South Wales for electricity generation. Queensland, like New South Wales, has abundant supplies of black coal. South Australia,however,doesnothaveanyappreciablecoalreservescomparedwithother states. The only accessible source of coal is available in Leigh Creek. However, it is expensive to mine and transport, difficult to burn, and has ash and salt problems (Booth2003).SouthAustraliahasthereforereliedonimportedblackcoalfromBritain andNewSouthWalesforelectricitygeneration.TasmaniaistheonlyAustralianstate thathasnotreliedoncoalasafuelforelectricitygeneration.Tasmaniahaslargehydro reserves,whichweretheleastcostlyandmostflexibleformofpowergenerationatthat time.Tasmaniawasalsothefirststatetoestablishanauthorityexclusivelyresponsible for electricity supply, when the first power station became operational in 1895 (Rosenthal & Russ 1988). In summary, coal was the most important primary energy fuelforelectricitygenerationinmostpartsofAustraliainthevery earlyyearsofthe development of the electricity industry. Separate, small power stations based on coal thereforebecamethenorminthoseyears. 2.1.2 GenesisofCoal–ElectricityCompact(1901–1950s) FollowingtheformationoftheAustraliafederationin1901,energybecameoneofthe residual powers retained by the states (AATSE 1988). The Australian state governments began to realise the development potential and political appeal of electricity (Sharma 2003). Further, it was widely argued that the industry was under increasing return to scale6 and natural monopoly (Fathollazadeh 2006). Accordingly, AccordingtoEatwell,MilgateandNewman(1998),thismeansthat“totalcostsofproductionare lowerwhenasinglefirmproducestheentireindustryoutputthanwhenanycollectionoftwoormore firmsdividedthetotalamongthemselves”. 6 23 stategovernmentsbegantodevelopandcontroltheirelectricitysystems.However,it was not until the 1920s that steps were taken towards government ownership and controloftheindustry,throughtheenactmentofavarietyofstatelegislations. During this period, the emergence of the coal–electricity compact in many states becameclearlyvisible.ThefirstsignificantstepwastakeninVictoria.Majorindustrial problems on the New South Wales coalfields in 1917 left Victoria with supply shortagesofblackcoal.Todealwiththissituation,theStateElectricityCommissionof Victoria (SECV) was formed in 1921, following the establishment of the Victorian BrownCoalAdvisoryCommittee.TheSECVwasestablishedwithaveryclearpurpose – to develop brown coal resource at Yallourn (the only known coal resource of any significanceinVictoriaatthattime),inordertoremoveVictoria’srelianceonimported New South Wales coal. Despite the difficulty in using brown coal for electricity generation,thegovernmentgavesupportforthisdevelopment,whichwouldnothave occurred had matters been left to the market (Kellow 1996). This led to a rapid developmentofbrowncoalminingatYallourn,whereoutputrosefrom79thousand tons in 1921, to 4.8 million tons in 1944 (Shaw & Bruns 1947). A similar situation occurred in South Australia. Following the Second World War, the supply of coal became critically low and there was a fear of black coal supply disruptions to South Australia.Inordertopreventsuchasituation,theSouthAustralianGovernmenttook over all power generation and transmission facilities in 1946, and established the Electricity Trust of South Australia (ETSA). Although it was costly to change the existingelectricitysysteminordertoconsumestatecoal,thegovernmentannounced proposalsfortheconstructionoftwopowerstations.Likewise,theNewSouthWales government had established the Electricity Commission of New South Wales (ECNSW)in1950,andassigneditthetaskofbuildingasupplysystembasedprimarily onpowerstationslocatedonthecoalfieldsandtransmittingpowertothemetropolitan areas(Booth2003). By the late 1940s, the electricity industry was predominantly owned by the state governments(Sharma2003).Itwasalsoduringthisperiodthatdemandforelectricity increased dramatically, from 172 GWh in 1910 to 13,622 GWh in 1954 (Boehm 1955). 24 The increase in electricity production capacity was associated with economic growth andindustrialisationinthatperiod.Thepoliticalsupportforindigenous(state,inthis context) fuel sources (that is, coal) and the increasing reliance of the Australian economyonelectricityduringthisperiodresultedinthecreationofelectricitysupply systems that were dominated by coalfired power plants. This created a system of “lockin” by coalbased technology (or in other words, a coalbased technological complex),whichwastoprovedifficulttooverturninthelateryears. 2.1.3 ConsolidationoftheCompact(1950s–1980s) Fromthe1950sto 1980s,the roleofstategovernmentsin guiding electricity industry development increased substantially. The strong economic growth after the Second WorldWar,combinedwithtechnologicaldevelopmentsinlargeelectricitygeneration capacities, propelledtheAustralian electricityindustryinto the “golden age”(Johnson & Rix 1991). The continuous trends in increasing electricity demand and a series of power shortages during 1949–1953 firmly established the grounds for centralised electricitysupply.Thisledtoaverticalintegrationoftheelectricitysupplyindustries in all states, controlled by the state statutory authorities. These authorities were responsible for all decisions such as dispatching, pricing, and investment planning. The power plants were dispatched centrally, in terms of their economic merit. Environmentalimpactsfromelectricitygenerationdidnotinfluencedecisionsrelating to the scheduling of existing capacity and/or investments in newcapacity (Sharma & Sproule1998).Thegovernmentdecisionmakingatthattimegenerallydisregardedthe pollution damage from environmentally inferior technologies, that is, the environmentalexternalitiesassociatedwiththeuseofpollutingelectricitytechnologies wereimplicitlyvaluedatzerodollars(Kline2001).Further,undercentralisedcontrol, the number of power stations increased significantly, including large hydro (for example, the Snowy Mountains Hydro Electric Scheme)7 and many steamthermal TheconstructionoftheSMHESstartedin1949andwascompletedin1974.Thisschemeisthe first interstate coordination scheme which was jointly financed and operated by the AustralianCapitalTerritory,NewSouthWalesandVictoria. 7 25 power stations. The generating capacity of SMHES is approximately 3,756 MW, producing electricity on average of 4,500 GWh per year. This project consists of 16 large dams and 7 power stations. Many of these investment decisions, especially SMHES,werefoundtobenoneconomicaland,assuggestedbyJohnsonandRix(1991, p.19),“theprivatesectorwouldnotbeinterestedinconstructingsuchscheme,asitproduceda negativenet present value”.However,the policy behind suchdecisions wasto provide adequate and reliable energy supply, in order to support economic growth and prosperity. Further,in1979,theAustraliangovernmentencouragedthestateelectricityauthorities toinvestheavilyinexpandinggenerationcapacityinanticipationofthe“mineralboom” (Saddler1996).Atthesametimethepossibilityofusingnuclearenergyforelectricity generation drewtheattentionoftheAustralianelectricityauthorities.Thisisbecause the practicality of nuclear power generation had been well established in many countries, and Australia possessed significant reserves of uranium. The Australian AtomicEnergyCommission(AAEC)tooktheroleofpromotingtheconstructionofa nuclearreactorinNewSouthWales.Althoughinitiallythegovernmentcommittedto building the reactor, the project was abandoned, as it was considered as being ill conceived and uneconomic (TEC 1984). Once again, abundant supplies of coal had renderednuclearenergyasuneconomicandhenceunfeasibleinAustralia.Asaresult, aseriesofcoalfiredpowerstationswereestablishedinordertomeetelectricityneeds for an expected “mineral boom”. These electricity infrastructure projects, as selectively extractedfromBooth(2003),include: … in Victoria … the Loy Yang project … eight 500 MW units fed by new opencut browncoalmine…improvetheperformanceofHazelwoodandmuchmoneywasspent on successive modification program … developed the Yallourn power station, initially withtwo350MWunits,andlaterextendeditbytwo375MWunits;…inNewSouth Wales…theECNSWdecidedtotaketheBayswaterproject(4×660MW)tocompletion …proposedaninnovativeschemetofinancenewfour660MWunitsatEraringonLake Macquarie…tocomplete2×660MWprojectatMtPiper;…inQueensland…began thedevelopmentofGladstonepowerstationprojectwithinstalledcapacityof1,680MW 26 …newgenerationofpowerstationsbasedonten350MWunitsizeinstalledatTarong (4units),CallideB(2units)andStanwell(4units);…inSouthAustralia…additional to 1,280 MW natural gasfired Torrens Island power plants, the 500 MW Northern power station was developed to make more efficient use of the Leigh Creek coal; … in Western Australia … a series of four 200 MW units … two at an extension to Muja powerstationoperatingonColliecoal…twoweretobeinstalledatKwinanaandfired byoil…whichlaterconvertedtocoalfiringasaresponsetooilshocks. Thestrategyofmovingsuccessiveconstructionprojectsfromcoalfieldtocoalfieldwas adoptedsoastomakeuseofcoalfromstateownedcoalminesandprivatelyowned companies (ibid). Further, these coalfired power plants benefited from a massive amount of government investment. The accelerated power station construction programplacedasignificantburdenonstatefinancialresources.Inseveralcasesstate authorities borrowed money from overseas, which led to the worsening of the country’scurrentaccountdeficit,toaround4.5percentofGDP(Kelly1992,p.198).As previouslymentioned,therationalebehindthedevelopmentoftheelectricityindustry was to provide a cheap and reliable electricity supply; the construction of these coal firedpowerplantswasthereforeheavilysubsidised.Thesesubsidieswereintheform of governmentguaranteed borrowings which gave electricity authorities access to lowercost debt finance, exemption from paying taxes (such as income tax and other taxes and charges) and other nontaxation financial imposts, in return for those electricity authorities performing community service obligations and allowing differing degrees of control by the minister in each state (Booth 2003). Therefore, the developmentoftheelectricityindustryduringthisperiodcreatedasystemofmutually beneficial symbiosis between the political, cultural, social, economical and technical interests;whichwasusedbythepoliticalpartiesinAustraliatopromotetheirpolitical agendasandhencetoimprovetheirelectoralprospects(Sharma2003).Inresponseto thedevelopmentmentionedabove,theenvironmentalcriticsoftheelectricityindustry had very quickly recognised that many of the new investments during this period wouldnotbeneededandwere,therefore,wastefulofpublicfundsandunnecessarily detrimentaltotheenvironment(Saddler1981). 27 Thisperiodclearlyconsolidatedthecoal–electricitycompactbynotonlyexpandingits coalbasedtechnology,butalsotheassociatedinstitutionsgoverningtheindustry.8In otherwords,thisperiodhasfirmlyestablishedthecoalbasedtechnologicallockinand started the creation of the institutional lockin of the coal–electricity compact in Australia. 2.1.4 FurtherStrengtheningoftheCompact(1980s–1990s) Bytheearly1980s,thestructureoftheelectricityindustry,whichwascharacterisedas a “natural monopoly”, was challenged. As a result of the overexpansion of electricity capacity in the 1970s and early 1980s, the electricity industry was criticised as being inefficient.Thisinefficiency,accordingtotheIndustryCommission(1991b),wasdueto poor investment decisions that led to overcapacity, overstaffing and pricing inefficiencies. This criticism initiated a process of internal reform of the electricity industrywithaviewtoimprovingtheindustry’sperformance.Itisimportanttonote here that although state governments appeared to be a driving force in the development of the electricity industry in past decades, it was electricity authorities that,withthetechnicalknowledgeandexpertiseintheelectricityindustry,hadahigh level of control of the industry. Therefore, following the criticism by the Industry Commission,thestategovernmentstookthisopportunitytointerveneintheelectricity utilities and at the same time improve their own credentials as responsible economic managers, by adopting legislative and nonlegislative measures focusing on better management and control of the industry (Sharma 2003). Such an attempt was first initiated in 1982 by the new government in Victoria to make the SECV more accountabletothegovernment(Johnson&Rix1991).Thisprocesswasthenfollowed byotherstategovernments,especiallyNewSouthWalesandTasmania.Inresponseto thegovernment’sapproach,theelectricityauthoritiesundertookstrategicinitiativesto improvetheirimageandtoensuretheirlongertermsurvivalbyadoptinganumberof The process of technological and institutional lockin in the energy system is discussed in Unruh(2000;2002)throughthenotionof“TechnoInstitutionalComplex”(TIC). 8 28 reform measures.9 This shows that the role of the governments in shaping the electricityindustrywasfurtherstrengthened.ThisiswellobservedbySharma(2003): A review of the history of electricity in Australia also reveals that reform measures actually adopted by the respective state governments (from among those recommended/dictated by various inquiries/economic analyses) were well circumscribed by the political exigencies of the time. Selected excerpts from Kellow (1996) should substantiate this observation: ‘… in Victoria … the recommendations to ensure public consultationinenergypolicywerenotimplementedastheydidnotfindfavourwiththe government…thegovernmentdidnottakeinitialstepstoimplementrecommendations arisingfromintegratedleastcostplanningstudy…(and)foundtheelectoralattraction of power station construction irresistible … the energy policy document was carefully crafted to woo swinging voters … addressed concerns about employment and environmentalprotection…decisiontoproceedwitha(particular)projectwasnotbased oncarefuleconomicanalysisbutonthefactthatitwouldprovidecontinuedemployment ...government’sflipfloppingbeforeandaftertheelection.’Theverypoliticalforceswhich contributed to the development of an inefficient electricity industry in Australia also contributedtotheimprovementsinitsefficiency. Although this period witnessed a slow growth in electricity demand and changes in industry structure to address the problem of overcapacity, many projects that were under construction in the preceding period were commissioned. This increased the share of coal in electricity generation, at the expense of oilfired and hydroelectric power plants (see Table 21). This shows that even in the era when the industry was faced with a changing course (that is, internal reform), the coal–electricity compact further strengthened its status under the combined influence of technological lockin andinstitutionallockin. DetailsofthesereformmeasurescanbefoundinJohnsonandRix(1991)andKellow(1996). 9 29 Table21 Installedcapacity,electricitygenerationandfuelconsumptioninESI InstalledCapacity Total CF IC GT CC RE Total CF (MW) (GWh) 1955 ElectricityGeneration (PerCent) 3,526 79 5.1 8,455 73 1.8 IC GT CC RE Total BlCBrC NG Oil RE (PerCent) 16 25 13,853 83 2.6 33,461 74 0.8 1975 19,594 69 1.3 1.6 29 1985 32,450 73 1.1 4.2 1965 Fuelconsumption (PJ) (PerCent) 14 6.1 14 25 237 51 464 37 29 34 3.7 25 66,840 76 0.8 0.1 23 820 41 29 4.0 3.1 23 21 111,348 85 0.7 1.0 13 1,245 49 25 8.1 1.8 16 1995 38,115 73 0.9 5.8 0.3 20 160,114 88 0.3 1.2 0.4 10 1,623 55 26 8.7 0.4 10 2005 44,889 70 0.3 8.3 4.5 17 216,647 87 0.1 1.4 4.3 2,288 53 31 8.4 0.3 Sources: Note: 2.1.5 7 7 ESAA(various). CF–Coalfired;ICInternalcombustion;GT–Gasturbine;CC–Combinedcycle;RE– Renewableelectricity;BlCBlackcoal;BrCBrowncoal;NGNaturalGas. FurtherEntrenchmentoftheCompact(1990s–present) In the 1990s, the Australian state governments agreed to initiate a broader economic reformprogram(alsoknownasmicroeconomicreformorsimplymarketreform).This reformprogramwasbasedonthebeliefinthesupremacyof“freemarketprinciples”in enhancing economic efficiency10 (Sharma 2003). In Australia, the case for electricity industryreformwasbuiltonthegroundsthatitwouldleadtosubstantialcostsavings, lowerelectricityprices,andothereconomicbenefits(Hilmer,Raynor&Taperell1993; Industry Commission 1991b, 1995). Further, taking note of the increasing concerns aboutenvironmentalissuesinthe1970sand1980s,proponentsofreformarguedthat reformwouldalsobebeneficialfortheenvironment.Forexample,“acompetitivemarket willprovidetherightpricesignalwhichwillensurethatefficiencymeasures,renewableenergy options and demand side measures are adopted where they are more cost effective” (AGPS 1994).Althoughtherewassomequestioning11ofsuchclaims,itwas,however,unable todentthepoliticalopinionsinfavourofchange(Sharma2003). Accordingly, in 1991, the state governments agreed on a reform package for the electricity industry, which included the creation of the National Electricity Market Economic efficiency is often used interchangeably with community welfare and public interest. 11Fordetails,seeJohnsonandRix(1991)andESAA(1996). 10 30 (NEM)12. The NEM was expected to create an environment in which free and fair competition can be achieved. In the NEM, public and privately owned generators greaterthan30MWcompetebylodgingbidstosupply electricitytoa common pool on a halfhourly basis. Bids are then ranked and dispatched on the basis of a purely economiccriterion,namely,thelowesttothehighestbidprices(Sharma2003).Thebid price,therefore,isessentiallyitsshortrunmarginalcostwhichdependsprimarilyon the type of fuel used and the nature of fuel procurement contracts between various marketplayers(Sharma&Sproule1998).Suchbiddinganddispatchingcriteriaclearly discourageanyotherconsiderations,suchastechnical,socialorenvironmental,which will invariably result in higher costs (Sharma 2003). As brown coal is the cheapest energysourceforelectricityproduction,itsshareoftotalprimaryenergyconsumption, inrecentyears,hasincreasedtothesamelevelasinthe1960s.Havingreached300PJ in1982,consumptionofbrowncoaldidnotexceed400PJforsixyears(until1988),and itdidnotexceed500PJforanothereightyears(until1996).However,withinthetwo years to 1998, the use of brown coal for electricity generation jumped to over 600 PJ (seeFigure21). The NEM was established across all states except Tasmania (which subsequently joined in 2005),WesternAustralia,andNorthernTerritory. 12 31 Figure21 Primaryenergyconsumptionforelectricitygeneration (PJ) 2,500 2,000 1,500 1,000 500 0 1955 1960 1965 Blackcoal 1970 1975 Browncoal 1980 1985 Naturalgas 1990 1995 Oil 2000 2005 Renewable Sources: ESAA(various). Recent market arrangements also support the development of coalbased electricity generation, which further entrenched the coal–electricity compact. For example, the privatisedbrowncoalfiredHazelwoodpowerstationintheLatrobeValleyhadbeen refurbished in the late 1990s, which extended its life by another 30 years (Hamilton 2001, p. 28). According to Hamilton (2001), it is likely that a similar strategy – of refurbishing existing browncoalfired power stations – would be adopted to meet future electricity demand under current market arrangements. In addition to the refurbishmentstrategy,newcoalfiredpowerstationswerealsocontinuingtodevelop despitethepressingenvironmentalconcernsduringthatperiod,particularlyfromthe impacts of climate change from combustion of coal. For example, in 1994, the construction of a new 135 MW coalfired power station in the Hunter Valley was approved, even though there was a massive overcapacity of electricity generation in NewSouthWales(ibid,p.35). ThedevelopmentoftheNEMisalsothemostimportantdevelopmentforthedomestic thermal coal market (Productivity Commission 1998). In addition to the increase in electricityproductionfrombrowncoal(asdiscussedearlier),theuseofblackcoalfor electricitygenerationalsoincreasedsignificantly.Theshareofblackcoalforelectricity generationincreasedfrom49percentin1985to53percentin2005(seeTable21).This 32 has led the domestic market share of black coal for electricity generation to increase from66percentin1980to85percentin2005,asshowninFigure22. Figure22 Domesticmarketshareofblackcoal Ce me nt Othe rs7.4% Othe rs6.6% Ce me nt Industry2.4% Industry1.3% Iron&Ste e l Industry7.6% Iron&Ste e l Industry 24.0% Electricity Industry 66.2% Ele ctricity Industry 84.5% 1980 2005 Sources: ABARE(various). The discussion above clearly shows that the recent market arrangements favour the use of black and browncoalfired technology for electricity generation. Such development further solidifies the coal–electricity compact by way of further entrenchingtheinstitutionallockinfortheuseofcoalintheelectricityindustry. 2.2 FutureDirectionoftheAustralianElectricityIndustry BasedonthehistoricalreviewoftheAustralianelectricityindustryinSection2.1,itis clear that coal has traditionally been the dominant energy source for electricity generationin Australia.TheelectricityindustryinAustraliaislocked intocoalbased technology through continuous development of physical structures using this technology. As the coalbased technological system expanded, institutions (through extensive linkages between the coal industry, electricity utilities, and governments) alsoemergedinacoevolutionarymannertosustainthewellestablishedtechnological system.Thistechnologicalandinstitutionallockinofthecoal–electricitycompacthas the ability to withstand external pressures (such as the current environmental 33 pressures) and make the transition to alternative technologies difficult. According to Unruh(2000,p.818): TechnoInstitutional Complex (TIC) developed through a pathdependent, co evolutionary process involving positive feedbacks among technological infrastructures andtheorganizationsandinstitutionsthatcreate,diffuseandemploythem.Oncelocked in, TIC are difficult to displace and can lockout alternative technologies for extended periods,evenwhenthealternativesdemonstrateimprovementsuponestablishedTIC. ThissectiondiscussesthelikelyfuturedirectionoftheAustralianelectricityindustry. Future electricity directions are analysed within three arenas – technical, economic, and political – to show why coal is likely to continue to be a dominant electricity resourceinthefuture. 2.2.1 TechnicalConsiderations Australia has abundant supplies of coal resources, with around 800 years of brown coal and 290 years of black coal deposits (OECD/IEA 2001). In addition to these abundant coal reserves, Australia is also well endowed with renewable resources, especiallysolarandwind.Highandconsistentwindsarecommonalongthesouthern coastline and in Tasmania where wind speed exceeds 8 m/s, while average solar radiationexceeds4.5kWh/m2/dayinmanyareasofNewSouthWales,SouthAustralia, Western Australia, and the Northern Territory (Blakers & Diesendorf 1996). With currentelectricitydemand(ofaround220millionMWhperannum),thelandareaof about900km2(0.01percentofthetotallandsurface)wouldberequiredforgenerating electricityfromsolarenergy.13Thisshowsthattheopportunityforthedevelopmentof renewable electricity is not limited by the availability of natural resources. Questions are however raised by some regarding the intermittency of renewable resources, especially solar and wind. It is argued that they can only reliably generate electricity whenthesunisshiningorthewindisblowing.Theexampleofopencyclegasturbine, The required land area is estimated using assumptions of average solar radiation of 4.5 kWh/m2/daywith15percentconversionefficiency(Blakers&Diesendorf1996). 13 34 whichisaninefficienttechnologyforgeneratingelectricity,asabackupforrenewable electricity, is often cited to support the argument. Others however hold a different opinion and argue that renewables, much like coal, are reliable sources of electricity generation. Some Australian scientists have shown that a system of largescale and geographicallydispersedwindpowercangenerateelectricitysmoothlyandasreliable as a conventional baseload coalfired power plants (Diesendorf 2007; Saddler, Diesendorf & Denniss 2004). With sophisticated grid management technologies and improved wind forecasting models, such a system could play a valuable role in an optimalmixofbase,intermediate,andpeakloadelectricity. ExistinghydroelectricpowerinAustraliarepresentsonly49percentofthetechnically feasible hydro resources that have been developed in the country (IHA 2003). However, there are public concerns about the considerable environmental impacts of large dams. It is unlikely that any further largescale dams with incorporated hydroelectric plants would be built in Australia. Nevertheless, there is potential for increasing hydroelectric generation, through maintaining and refurbishing existing assets.Saddler,DiesendorfandDenniss(2004)estimatedthattheefficiencyofexisting plantscouldbeincreasedby6percentonaverageandcapacitiesbyupto30percent. Carbondioxide Capture and Sequestration (CCS) is another option for reducing greenhousegas emissions from power stations. CO2 can be collected from fossilfuel fired power stations, compressed and transported in highpressure pipelines to the longertermstoragelocations,eitherundergroundorintheocean.However,thereare significant technological, economic, environmental and political risks associated with this technology (Baer 2003). These include: the limited potential for sufficient CO2 storage sites, for example, the largest storage potential is in Western Australia while the biggest pointsource emitters are in eastern Australia (Diesendorf 2003, p. 9); the cost of capturing CO2 from existing power stations is uncertain, ranging from $36 to $157 per tonne of CO2 avoided (Saddler, Riedy & Passey 2004, p. 29); and the environmental risk is also uncertain concerning the leakage of CO2 from either pipelines or reservoirs, due to little knowledge about the geology of the sites, particularly the deep saline aquifers in which geosequestration is proposed for 35 Australia(Saddler,Riedy&Passey2004,p.33).Thesuddenleakageofalargevolume ofCO2couldresultinadisruptionintheecologicalenvironmentandpeoplebecoming asphyxiated(Diesendorf2003). Electricity generated from nuclear power, like renewable energy, does not emit greenhousegasemissionsduringitsoperation.Nuclearfissionisaproventechnology andhasalreadybeenusedasbaseloadcapacityinmanycountries,contributingnearly 16 per cent to the total world electricity generation in the year 2003 (IEA 2005). Australia has a significant potential for nuclear power, as it has vast reserves of uranium. However, nuclear energy has significant waste disposal problems and has beenlinkedtonuclear weapons proliferation(Fiore2005). Nuclearfusion hasalong termpotentialforelectricitygeneration.Suchtechnologycanprovidecheapelectricity, no greenhousegas emissions, negligible radioactive wastes and an infinite supply of energy (Fiore 2005). The first fusion power is expected to start operating in southern Francein2016. 2.2.2 EconomicConsiderations Table 22 summarises the marginal costs and emission rates for different electricity generationtechnologies.Thetableshowsthatcurrently,conventionalcoalfiredpower stationsproduceelectricityatthelowestcost,withintherangeof3to4centsperkWh. Also, the recent expansions in interstate gas pipeline networks, particularly the development of the Eastern Gas Pipeline, have led to a reduction in real natural gas prices. As a result, the cost of electricity from natural gasfired power stations has fallen to about 4 to 6.7 cents per kWh. However, it remains at a price disadvantage comparedwithcoal,especiallyinVictoriaandNSW,owingtostrongcompetitionfrom lowcost coal. Renewable electricity in Australia is currently more expensive than traditional electricity supply. Currently, the most competitive renewable energy is wind power, with an estimated cost of 7 to 12 cents per kWh. Over time, the advancementinrenewabletechnologiesisexpectedtoreducethiscost. 36 Table22 Marginalcostsandemissionratesofelectricitygeneration MarginalCost EmissionRate Electricitygenerationtechnology (tonsCO (¢/kWh) 2e/GWh) Conventionalcoal 3.50–4.00 941–1175 Naturalgascombinedcycle(NGCC) 4.13–6.67 491–655 Advancedcoal(IntegratedgasificationCC) 5.47–8.13 750–857 Wind 7.30–11.9 13–40 Nuclear(Fission) 7.50–10.5 10–130 Hydro 7.80–15.1 11–44 SolarThermal 19.9–26.0 n.a. Wave 20.0–25.0 n.a. SolarPhotovoltaic 44.8–54.9 53–217 Sources:CommonwealthofAustralia(2006),MMA(2006a;2006b). Notes: †EmissionrateshowninthisTableincludelifecycleemissionsfromelectricitygeneration n.a.denotesnotavailable. Thedifferencesofelectricitysupplycostsforvariouselectricitysupplyoptionsdonot reflect the true economic value of energy resources. These cost differentials are, as suggestedbyRiedy(2005),embeddedthroughhistoricalpathdependentprocessesin the electricity system. Such processes, for example, include subsidy, government investment for a particular technology, and the neglect of the environmental costs associated with technologies (ibid). This historical development provides economic advantagetocoalbasedelectricitytechnologyoverothertechnologies. Over the years, the government has provided a variety of subsidies for fossilfuel development.Forexample,sincetheendofWorldWar2,thefossilfuelindustryasa wholehasreceivedover$3billionindirectsubsidies,andconsumersoffossilfuelhave received about $37 billion of subsidies (Sonneborn 2004). Although it can be argued that renewable technologies have also received significant subsidies, as estimated by Riedy (2005), the extent of these subsidies was less than 15 per cent of the total subsidiesreceivedbythefossilfuelindustry.Forinstance,in1994,outof$180million ofgovernmentsupportforenergysectorresearch anddevelopment,only$27million wasprovidedforthedevelopmentofrenewableenergy(NIEIR1996).Whilemanyof thesesubsidieshavebeendiscontinued,theywereimportantinthedevelopmentofthe fossilfuelindustry. 37 Also,asdemonstratedinSection2.1,coalbasedelectricitygenerationtechnologyhasa long production history under the ownership of stateowned utilities and, therefore, benefited from significant government investment. These massive government investmentshelpedreducedtheircostsmanyfold.Itisdifficultforothertechnologies tobecostcompetitivewithanestablishedtechnologythathasreceivedfarmorepublic fundingovertime(Riedy2005). Further, the electricity costs shown in Table 22 do not take into account any environmentalexternalities.Themainenvironmentalexternalityofburningfossilfuel inelectricitygenerationplantsisthecostofclimatechange.Ifsuchcostsareincluded, itislikelythatrenewableenergysourceswouldbecompetitivewithfossilfuels. 2.2.3 PoliticalConsiderations Coal and electricity industries have traditionally enjoyed significant political power. Thishascreatedaninstitutionalbarrierforthedevelopmentofothertechnologies.The electricity industry also has extensive linkages with the coal industry, either through ownershiporequityinterestinmines(ProductivityCommission1998).Theselinkages (and also those discussed earlier in Section 2.1), along with the institutional barriers noted above, inhibit the ability of other contenders to coal to compete with coal. For example, nuclear power, with its technical potential, would be a viable option as a baseloadplanttoprovideelectricity;thisis,however,hinderedbyexistinglegislation. The Nuclear Activities (Prohibitions) Act 1983 in Victoria and the Uranium Mining and Nuclear Facilities (Prohibitions) Act1986in New South Walesprohibittheconstruction oroperationofanynuclearreactor(UIC2005). State governments have an incentive to prefer coalfired over gasfired power generationbecausecoalcreatesmoreemploymentandusuallyattractsastateexciseor royalty14, whereas offshore gas is subject to the Commonwealth Petroleum Resource Rent Tax (PRRT) arrangements (OECD/IEA 2005). One of the recent cases was the Forexample,theexploitationofbrowncoaldepositsinVictoriawaslargelytaxfree(ACG& MMA1999,p.80). 14 38 decisiontobuildtheColliecoalfiredpowerstationinWesternAustraliain1999.The state government supported the construction of the Collie power station, although it acknowledged that a gasfired power station would have been more economic. The total additional cost is estimated to be $170 million and, if the government were to attempt to meet the target of CO2 stabilisation, the additional cost would double, to $330million(OECD1997). Therenewableelectricityindustryisinitsinfancy,confinedtosmallandfragmented marketslocated in remoteareas.Theyrequire support (as coalbased technology had received)inordertohelpdevelopintoamatureindustry.TheAustraliangovernment has established a Mandatory Renewable Energy Target (MRET) for electricity generation,tolimitthegrowthinemissionsandtopromoterenewableenergyindustry development. The original aim of the MRET was to increase the proportion of renewable energy in electricity generation by two per cent by 2010, which later was changedtoanincreaseinrenewablegenerationof9,500GWhperyearuntil2010.Since its commencement in 2001, the MRET has contributed significantly in attracting the electricity generation from renewable sources. According to the MRET Review Panel (2003,pp.12,14): 190powerstationshadbecomeaccreditedundertheMRETmeasure,acrossawiderange ofeligiblerenewableenergysources…duringthefirsttwoyearsofMRET’soperation, nearlytwiceasmanyRenewableEnergyCertificates(RECs)havebeencreatedthanare initiallyrequiredbytheinterimtargets. With this success, the MRET Review Panel has recommended that the target be extendedto 2020,with an increase in renewable electricity generation of20,000 GWh per year (ibid). Such a policy would allow greater penetration of renewable technologiesintothefutureelectricitymarket.However,thegovernmenthasdecided notto extendthetarget.Thisdecisionshowsthecontinuingpolitical influence of the coal–electricitycompact.AccordingtoRiedy(2005,p.211): ThedecisionnottoextendtheMRETisparticularlyinterestingforwhatitrevealsabout theinnerworkingofFederalCabinet.Mediareports(e.g.ABC2004a)andstatementsby 39 the Federal Environment Minister (ABC 2004b) strongly suggest that the Minister argued in Cabinet for an increase to the MRET, but was defeated by other Ministers concerned about the continued subsidisation of the renewable energy industry and the economicimpactsofthemeasure. Withoutsuchpolicysupport,therewillbealackofinvestmentinthedevelopmentof renewable energy. Further, the government also ceased the funding for the CooperativeResearchCentredevotedtorenewable energy –theonlyresearch centre that focused on the development of renewable energy (Diesendorf 2003; Riedy 2005). This action left the country without a renewable energy research and development funding agency, for the first time since the oil shocks of the 1970s (Sonneborn 2004). Support for research and development is critical to the development of renewable industryinsuchawaythatitcancompetewithtraditionaltechnologies.Thishasbeen expressedbyrenewableindustryrepresentativesinACGandMMA(1999,p.62), The sustainable energy industry sees R&D support as critical to its development. It is important to develop longer term R&D funding arrangements for sustainable energy technologies,toensurethatappropriateR&Dinfrastructurecanbebuiltupin astable policycontext. Despite increasing environmental concerns, the government’s longterm strategies favour the established coal–electricity compact. As stated by DITR (2004, p. 3), “It is recognisedthatgivenAustralia’shighleveloffossilfuelresources,wecanbeexpectedtoremain substantiallyreliantonfossilfuelsforenergyneedsfortheforeseeablefuture”.Itisclearthat the CCS option seems to be favoured by the Australian government. As stated by Diesendorf(2003,p.8): ThefederalgovernmentisfundingthreeCooperativeResearchCentres(CRCs)devotedto fossilfuelindustries,andhasjustannouncedthatoneofthesehasbeenrenamedtheCRC forgreenhousegastechnologies,whichfocusedentirelyonCCS,andrenewedforseven yearsfrom1July2003withanadditional$21millionofgovernmentfunding. The continuing increase in coalmining activities reflects the government’s policy preferences.Forexample,in2005,fournewmajorcoalprojectsinNSWandQLD,with 40 acapitalexpenditureofover$1billion,werecompleted.Thesewilladdover10million tonnesofcoalproductioncapacity(ACA2005).Suchprojectswillcontinuetosupply lowcost coal to the electricity market, which will help maintain the coal–electricity compactforextendedperiods. 2.3 SummaryandConclusions This chapter has investigated the nature of the relationship between the Australian electricityandcoalindustries.Thisinvestigationsuggeststhat: x Coalhastraditionallyplayedacriticalroleinthedevelopmentoftheelectricity industry in Australia. The abundance of indigenous coal resources provided initial incentive for the establishment of the coal–electricity compact. Consequently, small power stations based on coal became the norm in most partsofAustraliaduringitsearlydevelopment. x Overtime,thiscompactwasstrengthenedbyeconomicandpoliticalinterests. By the mid1900s, the electricity industry was predominantly owned by the state governments, with the intention of developing power stations based on coalfields located within the state rather than importing energy from other states. This marked the beginning of the technological lockin of coalbased electricityinfrastructures.Inthesecondhalfofthetwentiethcentury,aseriesof large coalfired power stations were built with government subsidies, in anticipationofamineralsboom.Thisconsolidatedthetechnologicallockinof coalbasedtechnology. x Theeconomicandpoliticalinterestssoontransformedthetechnologicallockin into aninstitutionallockin. The useofsignificant publicfundsin the form of subsidies in the development of power stations in the earlier period has allowedthedirectinvolvementofpoliticalinterestsintotheelectricityindustry. The influence of these interests became evident in the investment strategies, includingtheselectionoffuel(coal)forelectricitygeneration.Evenintherecent development of the electricity industry, rules which govern the national electricity market (particularly dispatching criteria) also favour coalbased 41 electricity generation. This demonstrates the institutional lockin of the coal– electricitycompactinAustralia. Thischapterhasalso,basedonanhistoricalreview,attemptedtoinvestigatethelikely futureoftheelectricityindustry.Thisinvestigationsuggeststhat: x Thecoal–electricitycompactislikelytoremaindominantintheyearstocome. Although there is technical potential for the use of alternative fuels for electricity generation in Australia (for example, solar, wind, hydro, and nuclear), the uptake of this potential would be restricted by its economic and politicaldisadvantages. x Theeconomicadvantageofthecoal–electricitycompactoverothertechnologies has been developed through historical pathdependent processes in the electricity system. These processes include government investment and subsidiesforcoalbasedelectricitytechnologythatartificiallyloweredtheircost forelectricityproduction.Theexclusionofnegativeenvironmentalexternalities associated with coalbased electricity generation technology also enhances its economicadvantage. x The political connections of the coal–electricity compact has further deepened the economic and political advantages of this compact. It has created an institution barrier (through legislation and financial support) against the development of alternative electricity technologies. The longterm policy directions and political support, particularly for the development of carbon capture and sequestration – are evidence of the continuing sway of the coal– electricitycompact. 42 CHAPTER3 3 AUSTRALIANGREENHOUSEPOLICYDEVELOPMENT Chapter2providedanhistoricalreviewoftheevolutionofthecoal–electricitycompact inAustralia.Itwasnoticedinthisreviewthatthecoalindustryhasplayedamajorrole inthedevelopmentoftheelectricityindustry.Itwasalsoarguedthatthiscompactis likely to remain strong in the foreseeable future. Australia’s coal–electricity compact clearlyhassignificantenvironmentalimpacts.Byimplication,italsohasthepotential to significantly influence the Australian government’s stance on policies to reduce greenhousegasemissions. Againsttheabovebackground,theobjectiveofthischapteristoprovideanoverview ofthedevelopmentofgreenhousepolicyinAustraliaandtodevelopaperspectiveon carbon tax as a policy option to reduce Australia’s carbondioxide emissions. This chapter is organised as follows. Section 3.1 describes the nexus between electricity production and CO2 emissions. Section 3.2 describes the development of Australia’s greenhouse policy aimed at combating CO2 emissions. The rationale and strategy for the use of carbon tax as a future policy option is discussed in Section 3.3. Finally, a summaryofmajorfindingsofthischapterisprovidedinSection3.4. 3.1 3.1.1 ElectricityIndustryandCarbondioxideEmissions TotalCarbondioxideEmissions Globalwarming and climatechangearecurrentlythemostsignificant environmental challenges facing humanity. Emissions of greenhousegases from the combustion of fossil fuels is the dominant anthropogenic emission contributing to climate change. Greenhousegasemissionscomefromavarietyofsources.InAustralia,theproduction and use of energy provides the single largest source of greenhousegas emissions. In 2004,Australia’stotalgreenhousegasemissionscomprised565milliontonnesofCO2 43 equivalent (Mt CO2e), out of which 63 per cent (356 Mt CO2e) represented the contributionfromfuelcombustionalone(AGO2006). CO2isthelargestcomponentofgreenhousegasemissions,withashare,in2004,of73 per cent (415 Mt CO2e), followed by CH4 with 22 per cent, and others (that is, N2O, HFCs, PFCs and SF6)15, 5 per cent (AGO 2006). Therefore, CO2 is the single largest contributor to climate change. Fossilfuel combustion is the major source of CO2; it accountedforover85percent(352Mt)ofCO2emissionsin2004.Outofthis,electricity generationaloneaccountedfor55percent(194Mt).TheremainingCO2fromthedirect combustion of fossil fuels was contributed by transport (21 per cent), manufacturing andconstruction(12percent),andotherenergycombustionactivities(12percent),as showninTable31. Table31 Australia’sgreenhousegasemissions CO2e emissions(Mtonnes) 1990 2004 CO2 GHG CO2 Fuelcombustion 254 257 352 Electricityindustry 129 129 194 Transport 61 62 74 Manufacturingandconstruction 37 38 42 Others 28 29 41 Fugitivefuels 6 29 6 Industrialprocesses 18 25 24 Agriculture 91 Landusechangeandforestry 125 129 33 Waste 0 19 0 TotalGHGEmissions 402 551 415 Sources: GHG 356 195 76 42 42 31 30 93 35 19 565 AGO(2005;2006). During the period 1990–2004, the nationwide CO2 emissions increased by only 3 per cent, from 402 Mt in 1990, to 415 Mt in 2004. This was due to significant emission reductions(73percent)inlandclearingandforestry.However,emissionsfromfossil fuel combustion increased by 39 per cent (AGO 2005). More importantly, over this period, CO2 emissions from electricity generation increased by 51 per cent, from 129 CH4:methane,N2O:nitrousoxide,HFCs:hydrofluorocarbons,PFCs:perfluorocarbons,SF6: sulphurhexafluoride. 15 44 Mt, to 194 Mt. Thus, the future growth in CO2 emissions from electricity generation, together with the fully utilised reduction potential from landclearing, will put great pressureonAustralia’scommitmenttoreducetotalCO2emissions. 3.1.2 CarbondioxideEmissionsfromElectricityGeneration Theelectricityindustryhasaverysignificanteffectontheenvironment.Burningfossil fuel produces CO2 emissions. The quantity of emissions depends on the carbon and hydrogencontentofvariousfuels.Forexample,inAustralia,burningeachGJofbrown coal,blackcoal,petroleumandnaturalgasproduces,onaverage16,95.7,90.4,69.3,and 51.3 kg of CO2, respectively (NGGIC 1996). Brown coal is the most carbonintensive fuelforgeneratingelectricityinAustralia.Renewableenergy(forexample,wind,solar, hydro, etc.) does not generate any CO2 emissions during electricity production, although it may be responsible for significant emissions during the manufacture and constructionofrenewableenergytechnologiesandsystemsforelectricitygeneration. Electricity generation accounts for a large proportion of Australia’s greenhousegas emissions. Its share of total CO2 emissions has increased dramatically over the last decade–fromabout30percentoftotalCO2emissionsin1990toalmost50percentin 2004, as shown in Figure 31. This is due to the dominance of coalfired power generation. As Diesendorf (2003, p. 1) states, “Twentyfour coal power stations are the largest source of greenhouse gas emissions in Australia, pumping out 170 million tonnes of carbondioxideeveryyear”.AsdiscussedinSection2.1.5,coalaccountedfornearly85per centofprimaryenergyfuelusedforelectricitygenerationin2004. These emission factors are the averages over thelastdecade.Emission factorsforeachyear canbefoundinthecitedpublication. 16 45 Figure31 Carbondioxideemissionsfromelectricitygeneration 50 175 40 150 125 30 100 20 75 50 10 25 0 0 1990 Source: 1992 1994 1996 1998 2000 2002 ShareoftotalCO 2 emissions(percent) CO2 emissionsfromESI(Mtonnes) 200 2004 AGO(2005). In Australia, there are no legal requirements on coalfired power generators to limit their greenhousegas emissions (Diesendorf 2003). Further, the introduction of the competitive electricity market in several states has also boosted emissions. CO2 emissionsfromelectricitygenerationhavebeenrisinggraduallysince1990.However, in a single year after the implementation of the NEM Phase 1 (May 1997)17, the emissionincreasedsharplyby10percent,from152Mtin1997,to167Mtin1998(see Figure31).FollowingtheintroductionoftheNEMinDecember1998,CO2emissions continued to grow steadily at an average rate of 3 per cent per annum. The implementationoftheNEMhasenabledcoalfiredelectricitygenerationtoincreaseits shareinelectricitygeneration,duetoitsfuelpriceadvantage(AGO2005).Theshareof browncoalhasincreasedfrom29percentto34percent(orfrom497PJto680PJ)over the single year after the implementation of the competitive electricity market (see Figure21).Theincreasingdependenceonbrowncoalisbecausetheoperationofthe NEM causes companies to seek the cheapest sources of electricity, with no Anationalelectricitygenerationpoolbeganoperationon5May1997,whenVictoriaandNew SouthWalesbegananinterstatewholesaleelectricitytradingmarket.Thefulloperationofthe NEMstartedinDecember1998. 17 46 consideration for environmental impacts (Beder 2003). Brown coal is cheap but has relativelylowenergycontentperunitofvolume;itthereforeproducesrelativelyhigh amount of CO2 emissions per unit of energy produced. Old brown coal plants that have paid off their loans can therefore produce electricity at low marginal costs but producehigherlevelofCO2emissions(ibid).Browncoalfiredelectricitygenerationin Victoria displaced blackcoalfired generation in New South Wales and gasfired generation in South Australia. This is a consequence of the market criterion for plant ranking and dispatching in the NEM, which could bring further adverse environmental impacts from the electricity industry. As noted by AGO (2005, p. 15), “TheintroductionoftheNationalElectricityMarketin1998enabledbrowncoalpowerstations to increase their share of the electricity market in the eastern States due to their fuel price advantage”. It is further clear that the electricity industry reforms proved to hinder, ratherthanhelptoachieveemissionreduction,aswasclaimedbythegovernment(see Section2.1.5). 3.2 DevelopmentofAustralia’sGreenhousePolicy This section provides an overview of the development of greenhousegas policies in Australia.Itisimportanttounderstandhowgreenhousepolicyhasbeendevelopedin a country where the coal–electricity compact has been strong. Such a review could provide a basis for designing an appropriate greenhouse policy – that takes into accountallactorsinvolvedinAustraliangreenhousegasdiscourse.Thereviewinthis section draws on a number of previous studies, for example, Taplin (1994), Bulkeley (2001),Hamilton(2001),Hunt(2004),Christoff(2005),andRiedy(2005).Thisreviewis divided into five subsections – the pacesetter, the changing stance, reaffirmation of stance,thelaggardnation,andentrenchmentofthestance–accordingtothechanging positiontakenbytheAustraliangovernmenttowardsgreenhousepolicy. 3.2.1 ThePacesetter The concerns about the environmental impacts of coalbased electricity production (especially in view of the entrenched nature of the coal–electricity compact, as 47 discussed in Chapter 2) provided the initial spur for developing policy response to mitigate such impacts. The global impact of climate change was first discussed in a conference in Austria in 1985 (Kay 1997). A concern was expressed at the conference thatincreasingratesoftheuseoffossilfuelswouldincreasethelevelofCO2emissions, which could worsen the condition of the climate. In 1988, the first steps towards confrontingclimatechangewerediscussedinToronto.Atthisconference,therewasa “callforaction”toreduceglobalCO2emissionsby20percentfromthe1988levelsby theyear2005(Torontotarget).Later,inthesameyear,theIntergovernmentalPanelon ClimateChange(IPCC)wasestablishedtoinvestigatetheimpactsofglobalwarming and to suggest strategies to overcome such problems. Australia’s initial response to these developments was highly cooperative and, according to Christoff (2005, p. 39), was “shaped by an altruistic public discourse focused on global responsibility and with little sense of economic reality”. Consequently, in 1990, the Australian government adopted the “interim planning target” to stabilise emissions of greenhousegases at the 1988 levelsbytheyear2000andthenreducetotheagreedlevelof20percentby2005.The governmentconsideredtheestablishmentofdomesticgreenhousepolicybasedonthe assessment of such targets through the advice of the Ecologically Sustainable Development (ESD) working groups (consisting of representatives from government, industry, and environment groups) and the Industry Commission. In the meantime, influenced by the findings of the IPCC, the United Nations (1992) adopted the FrameworkConventiononClimateChange(FCCC)withtheobjectiveof: …stabilizationofgreenhousegasconcentrationsintheatmosphereatalevelthatwould prevent dangerous anthropogenic interference with the climate system. Such a level shouldbeachievedwithinatimeframesufficienttoallowecosystemstoadaptnaturally to climate change, to ensure that food production is not threatened and to enable economicdevelopmenttoproceedinasustainablemanner. Until this stage, Australia took a progressive position during the negotiations of the conventionandwasoneoftheeightpacesettercountriestoratifya“callforaction”. 48 3.2.2 TheChangingStance Such global leadership in combating climate change was soon undermined by the outcome of the interim target assessment. The Industry Commission (1991a, p. 4) estimated that achieving the Toronto target would lead to a 2.1 per cent decline in Australia’snationalproductswiththegreatestimpactfallingonthecoalindustry.The impactonthecoalindustrywouldbedueto thereallocationofresourcesawayfrom carbonproducingandusingindustriestootherindustries(ibid,p.110).Ascarbontax wasconsideredasoneofthemainpolicyinstrumentsdiscussedinthereport,itsoon becamethesubjectofascarecampaignbythemedia.Thismarkedthebeginningofthe debateoncarbontaxinAustralia.AccordingtoHamilton(2001,p.33): Thefossilfuelindustryreactedwithoutrageandthecarbontaxbecamethebogeymanfor industry in the debate, with both Labor and Coalition governments shunning the measure(i.e.carbontax)favouredbymosteconomists. Incontrast,recognisingthepotentialfromenergysystemsinreducinggreenhousegas emissions, the ESD working groups concluded that “there was a large range of actions which would be costeffective on energy grounds alone, so that the additional benefit in greenhouse gas reductions would be free” (Wilkenfeld, Hamilton & Saddler 1995, p. 9). Becausetheworkinggroupconsistedofrepresentativeswithdifferentviewpoints,the outcomewasseenasthereconciliationofenvironmentalandeconomicobjectiveswith precautionary measures – particularly noregrets measures18 – to respond to climate change. It was also made clear by the ESD working groups that although noregrets measures would have a negative impact on some industries, this would be compensatedbythegrowthinotherindustries,suchasenergyefficiencyorrenewable energy(Bulkeley2001,p.161). This“noregrets”measureisinterpretedasameasurewhichhaseconomicbenefits,oratleast no economic losses, as well as achieving a reduction in greenhousegas emissions (National GreenhouseSteeringCommittee1992). 18 49 In 1992, the Council of Australian Government (COAG) released the National Greenhouse Response Strategy (NGRS), which was a comprehensive national approach to reduce greenhousegas emissions. Although the NGRS adopted the no regrets measure, the term noregrets was interpreted differently from the interpretation of the ESD working groups. As stated by the National Greenhouse SteeringCommittee(1992,p.12): Equity consideration should be addressed by ensuring that response measures meet the broad needs of the whole community and that any undue burden of adjustment potentiallybornebyaparticularsectororregionisrecognisedandaccountedfor. ThisstatementwasinfluencedbytheIndustryCommissionfindings,whichrecognised the supremacy of economic over environmental objectives in the development of climatechangepolicy.Itimpliedthatanyindustrysector,includingemissionintensive industries, should not be economically worse off. Despite this stance by the government, the NGRS included sufficient measures – particularly on energy supply side–toreducegreenhousegasemissions.This,accordingtotheNationalGreenhouse SteeringCommittee(1992,p.16),included: … limit greenhouse gas emissions arising from energy production and distribution wherevereconomicallyefficientbyminimisinggreenhousegasemissionsperunitofeach typeofenergysuppliedto endusers, and by promotingalternative energy sources that havethepotentialtolowergreenhousegasemissionsperunitofenergysupplied. This declaration was similar to the claim made by the government that the market reform program, which was implemented at the same time, would benefit both economic and environmental objectives (see Section 2.1.5). However, the government failed to implement NGRS and responses were left to adhoc government processes andcommercialdecisions,whichwerecountertothestatementgivenintheNGRS,as notedabove.ThefollowingcitationfromHamilton(2001,p.35)substantiatesthis: Nearlyeverymajorenergysupplydecisiontakenbystateandterritoriesgovernmentsin the years subsequent to adoption of the NGRS favoured the options with the higher greenhouse gasemissions,includingnewcoalfired power stationsand extensionofthe 50 electricity grid into areas previously served by remote area power system (RAPS) and where renewable energy sources would have been cheaper. The electricity industry, throughitsorganisationtheElectricitySupplyAssociationofAustralia(ESAA),hasat alltimesresistedanyseriousmeasurestoattempttolimitemissionsfromcoalburning. This, together with the existence of the coal–electricity compact (as discussed in Chapter2),suggeststhatthegovernmentgaveeconomicpriorityprecedenceoverthe environmentalconcernsendorsedintheUNFCCC. 3.2.3 ReaffirmationoftheStance By1994,itwasevidentthattheNGRSwasfailingtomeetitstarget.Acomprehensive reviewoftheNGRSbyWilkenfeldetal.(1995,p.1)suggestedthatthestrategy: … has failed to make any impact on Australia’s greenhouse gas emissions. After two years of its operation, there is no evidence that even one tonne of carbon emissions has beensavedasaresultoftheNGRS.Moreover,Australia’sexcessofemissionsoverthe targetoftheFrameworkConventiononClimateChange–toreturnto1990levelsbythe year 2000 – is likely to be far greater than has been admitted by the Commonwealth Government. With the increased international pressure19 arising in response to the failure of the NGRS, the government opted to use an alternative strategy. A package of additional measures, called Greenhouse 21 C, was proposed in March 1995. As a part of these measures,asmallcarbontax–intheformofgreenhouselevy–wasalsoproposed.A tax rate of $1.25 per tonne of CO2 would have been imposed on the domestic consumptionoffossilfuels,withtheaimofusingpartoftherevenuefromthetaxin establishinganAustralianSustainableEnergyAuthoritytopromoteenergyefficiency andrenewableenergy(Hoerner&Muller1996).However,giventheirdomination,in the media and policy circles, the fossilfuelbased industries overcame attempts to ThisinternationalpressurewasexpectedtoariseinthefirstConferenceoftheParties(COP1) attheUNFCCCinBerlinin1995. 19 51 establish even a small level of carbon tax (Christoff 2005). As noted by Diesendorf (1996,p.39): Pricesforelectricityandfossilfuelsdonotincludethe‘external’environment,healthand social costs of their use. Although electricity industry restructuring should in theory include the internalisation of these external costs, in practice there is strong resistance fromtheresourceindustries.Indeed,inearly1995,followingintenselobbyingandmedia campaigning by the resource industries, the Federal government rejected a proposal to introduceacarbontax/levyonfossilfuels. Asaresult,thegovernmentintroducedthenewGreenhouseChallengeProgram(GCP) in October 1995. The GCP is a program that, as an extension to the NGRS, relied on voluntaryimplementationofnoregretsmeasuresbyindustriesinreturnforpublicity for their green credentials. This program would not undertake those measures that would have an adverse economic impact on the industry. As a result, the GCP attracted considerable support from fossilfuelbased industries in return for their – governmentfunded–publicityinresponsetoconcernoverclimatechange.Thedebate overtheimplementationofcarbontax–thatmightimposecostsontheircommercial interests–wasagaindeflected(Bulkeley 2001).Inthesubsequentyears,theGCPhas dominated Australia’s greenhouse policy development. Also, it was consistently referred to as a program that demonstrated the government’s commitment to reduce GHGemissionsthroughgovernmentandindustries’partnership(Hamilton2001). 3.2.4 TheLaggardNation Attheinternationallevel,itwasapparentthatvoluntarymeasureswerenotsufficient toreducegreenhousegasemissions.ThiswasreflectedattheCOP1meetinginBerlin in1995,whichwasleadingtowardslegallybindingnegotiationstoreducegreenhouse gasemissions.Thesenegotiationswere arguingforlegally bindingtargetagreements foreachcountryatCOP3inKyotoin1997,whichwouldbecometheKyotoProtocol. DuringtherunuptoKyoto,theAustraliangovernmentassumedanaggressivestance ininternationalnegotiationsoveruniformemissionreductionsof15percentbelowthe 1990 level by 2010 (Christoff 2005). The government made a considerable effort to 52 negotiateforalenienttarget.Suchnegotiationclearlyreflectedtheinfluenceoffossil fuelbased industries (also the coal–electricity compact) in guiding greenhouse policy inAustralia.AccordingtoHamilton(2001,p.54): …thegovernmentarguedthatduetoAustralia’sheavyrelianceonfossilfuels,uniform emissionreductionrequirementswouldimposeanunfaireconomicburdenonAustralia. Itadvocatedacomplicatedformulafor‘differentiated’targets,whichwouldawardamore lenienttasktoAustraliathanothercountries. This strong claim by the government was supported by a single modelling study performedbyABARE.Thestudyfoundthattomeetuniformemissionreduction,there would be decline in almost all sectoral outputs in the Australian economy, which would lead to an increase in unemployment levels and reduction in wage rates (ABARE1997).Thisstudy,particularlytheuseoftheMEGABAREmodel,waswidely criticised,particularlybysomeeconomists,greengroups,andsomeofthosewithinthe ranks of the party in power (see also, Bulkeley 2001; Hamilton 2001; Hamilton & Quiggin1997;Tarlo1996).Itwasarguedbythesecriticsthatthisstudyexaggeratedthe cost of emissionreduction measures and has compromised its neutrality due to fundingbyfossilfuelbasedindustries(Bulkeley2001;Hamilton2001). Togetherwiththenegotiationsfor“differentiated”targetsattheinternationallevel,the government assigned the National Greenhouse Advisory Panel (NGAP) the task of reviewing the NGRS. Again, the focus was given to noregrets measures at an individual level (that is, any industry should not be economically worse off). Just beforeKyoto,thegovernmentreleasedapackageofmeasures–SafeguardingtheFuture – that constituted the National Greenhouse Strategy (NGS) (Commonwealth of Australia1998).TheNGSwasformalisedwiththeobjectiveoflegitimisingAustralia’s responsibility towards greenhouse issue at the COP3 in Kyoto (Christoff 2005). Despite its ineffectiveness in reducing emissions (as with NGRS), there is one policy statedintheNGSspecificallyidentified asgoing beyond noregrets–theMandatory RenewableEnergyTarget(MRET). 53 The strong position taken by the government before and during the Kyoto negotiations,particularlythethreattowithdrawfromthenegotiations,attractedwide condemnation (Hamilton 2001, p. 97). However, as a political bargain, Australia was allowedalenienttargetofemissionlevels–108percentabovethe1990level,bythe period 2008–2012, together with the inclusion of emissions from landclearing in greenhouse accounting. Emissions from landclearing in Australia had declined sharplysince1990;inclusionoftheminthebaseyearwouldallowfossilfuelemissions toincreasetoatleast120percentof1990levelsbytheyear2010(Hamilton2001,p.88). This agreement clearly provided Australia with room – under the Kyoto target – for substantial growth in emissions and, hence, there was little incentive to address the greenhouseissue. 3.2.5 EntrenchmentoftheStance SinceKyoto,therehasbeennosignificantinternationalpressureforAustraliatofocus on developing an environmental policy. However, domestically, the opinion, particularly among the supporter of the government’s voluntary approach to greenhousepolicy,begantofragment.AsstatedbyChristoff(2005,p.40): Late in 2000, ruptures occurred within the Business Council of Australia (BCA), a leading public supporter of government climate policy, when BHP – then Australia’s largestcompany–alsodecidedtosupportadomesticemissionstradingsystem. At that time, the BCA appears to have been thoroughly captured by big mining and fossil industry interests that consistently opposed any government initiative for implementingAustralia’sKyotoobligations(Hamilton2001,p.134).Tomoderatethe situation,severalothermeasureswereincorporatedintheexistingNGSatthenational level.ThesemeasuresincludetheMRET,energyefficiencythroughminimumenergy performance standards (for fossilfuel electricity generation, equipment and appliances,andtheBuildingCodeofAustralia),andfurtherengagingindustryinthe voluntary Greenhouse Challenge (Commonwealth of Australia 2000). In contrast, at the state level, the moves towards greenhouse policy were more progressive. These includemeasuressuchastheGreenhousegasAbatementSchemeinNSWandthe13 54 percentGasSchemeinQueensland.Althoughthesemeasuresweredirectedtoreduce greenhousegasemissionsbylargeramounts,comparedwiththoseundertakenatthe nationallevel,theywereconsideredaspoorly targetedinthesensethattheydidnot allow the market to identify the costeffective options to reduce emissions (ERAA 2004). In2004,RussiaratifiedtheKyotoProtocol,andthisProtocolwasbackontheagenda. TheAustraliangovernment,however,reiterateditslongstandingrefusaltoratifythe Protocol.Thisclearlywasmeanttoprotectthecompetitiveadvantageenjoyedbythe fossilfuel industry and to hinder (even though by implication) the uptake of renewable energy technologies (Christoff 2005). This was also reflected in the new energyandgreenhousepolicystatement“SecuringAustralia’sEnergyFuture”,released earlier that year20 (Commonwealth of Australia 2004). The Australian government’s entrenchedgreenhousepolicypositionwasfirmlyarticulatedinthisWhitePaper.The government has clearly disadvantaged the renewable industry by its decision not to extend the MRET (also discussed in Section 2.2.3). Further, subsidies were made available to the fossilfuel industries through a Low Emissions Technology Demonstration Fund (LETDF). According to the White Paper, the LETDF “support industryled projects for largescale demonstration of low emissions technologies that could reduce the cost of technologies with significant longterm abatement potential” (Commonwealth of Australia 2004, p. 182). Although the LETDF is equally available forallindustries,duetothedecisionnottoextendtheMRET,ithasdemonstratedits support for wellestablished fossilfuel industries in the development of CCS (BCSE 2004).AccordingtoRiedy(2005,p.212): Itishardlysurprisingthatthe White Paperfavoursestablished industrysectors,given the extent of their involvement in the development of the policy. The … confidential meeting of the Lower Emissions Technology Advisory Group (LETAG)21 … with the ThispolicystatementiscommonlyreferredtoastheEnergyWhitePaper. TheLETAGisagroupcomprisinglargecompaniesintheenergyandresourcesectors. 20 21 55 Prime Minister and Industry Minister … reveal that the LETDF was specifically developedtoaccelerateinvestmentinnewtechnologiesbyestablishedindustries. TheWhitePaperwas lateronrevealedasacompleteendorsementofthe“greenhouse mafia’s”22agenda(Pearse 2005,p. 355),whosecommercialinterestswouldbeaffected byanymovetoreducegreenhousegasemissions. More recently (January 2006), the Australian government came up with a new initiative – the Asia–Pacific Partnership on Clean Development and Climate (also knownasAP6).23TheAP6aimstoachieveemissionsreductionthroughcollaboration on the development of existing and emerging clean energy technologies (PM 2006). AlthoughtheAP6doesnotexplicitlysupportanyparticulartechnology,CCSisoneof themajortechnologiesthe“partnership”ishighlightingandfostering.Despitebeingan unproven technology in the context of electricity generation, compared to commerciallyviablerenewabletechnologies(suchaswind,solarandbiomass),mostof the recent funding under the “$500 million LETDF” program has been made for the development of CCS in Australia. Of the total $410 million of funds that have been allocatedtodate,$335millionhavebeenallocatedforthedevelopmentofCCS(AGO 2007). This shows that such a partnership supports the development of select fossil basedtechnologies,forexample,CCS. The government decisions in relation to the development of greenhouse policy, as discussedinthissection,wereoverwhelminglyinfluencedbythestrengthofthecoal– electricity compact. Such influences are likely to prevent the development of greenhouse policy that balances the longterm interests of various segments of the economy. It is also clear from this discussion that without the political will, the opportunitiestoimplementeffectivegreenhousepolicywillsimplyneverhappen. This term, according to Pearse (2005, p. 341), is a selfdescriptor used by some industry lobbyistsinreferencetotheAustralianIndustryGreenhouseNetwork(AIGN). 23TheAP6countriesareAustralia,China,India,Japan,SouthKorea,andtheUSA. 22 56 3.3 ACarbonTaxPolicyforAustralia AreviewofthehistoricaldevelopmentofAustralia’sgreenhousepolicy(aspresented intheprevioussection)suggeststhattheAustraliangovernmenthasoptedtofollowa “waitandsee”24approachtothedevelopmentofthispolicy.Itswingsintoactiononly when there is some external (for example, international and/or public) pressure. Further, such policy development has been strongly influenced by the undue power wieldedbythefossilfuelindustries.Theseissueshaveinhibitedtheformulationofan effective greenhouse policy (Johnson & Rix 1991, p. 43). Based on the government’s current approach to the greenhouse issue, together with the influence of the coal– electricity compact, it is very likely that any future greenhouse targets for Australia willbemoredifficulttoachieve.Itisnowcommonlyacceptedthatinordertoreduce greenhousegas emissions by any significant amount, the fuel mix for electricity generationmustchangesubstantially(Gerlagh&vanderZwaan2006;Grubb,Carraro & Schellnhuber 2006). This would be possible only – given the focus of the current economic reform emphasising freemarket principles – if electricity generation technologiesreceiveappropriatepricesignalsthatcanachieveanappropriatebalance betweeneconomicbenefitsandenvironmentalcosts. This section first discusses various environmental policy options. Then carbon tax policy,asconventionallyadopted,isdiscussedtogetherwithitslimitations.Finally,an alternativeperspectiveoncarbontaxisdevelopedandputforwardasapolicyoption toreducecarbondioxideemissionsinAustralia. 3.3.1 EnvironmentalPolicyOptions A range of policy options are being considered by various countries to mitigate greenhousegas emissions. These policy options are based either on a commandand control (or regulatory) approach or a marketbased approach. A regulatory approach generally specifies standards and, through regulation, ensures that polluters meet ThistermisgivenbyJohnsonandRix(1991,p.41). 24 57 these standards, regardless of the relative costs of control. Direct regulation involves the imposition of technical or emission standards through licensing and monitoring. Thisapproach(togetherwithvoluntaryaction)hasbeenthetraditionalmainstayofthe Australian approach to redressing environmental issues. Its attractiveness to the Australian policymakers arises from the fact that it can be manipulated to serve the commercialinterestsofthecoal–electricitycompactwhileachievingthepoliticalgoals (see Section 3.2). This approach, however, argue its critics, lacks flexibility and motivation,anddoesnotprovidemarketsignalsthatwouldencouragetheuptakeof leastcostoptionsformeetingemissionstandards(Armstrong1997;Owen1992;Pearce 1991).AsimilardisadvantageintheAustraliancontextwasalsopointedoutbyERAA (2004,p.2): ... the existing policy environment in Australia, which is mainly characterised by regulatoryapproach,areafragmentedarrayofshorttermStateandFederalGovernment greenhousegasabatementmeasuresthattendtobepoorlytargeted,overlycomplexand highlyinefficientasmechanismsforreducingemissions. Further, emission reductions from the electricity sector are unlikely to happen under the most favourable approach adopted by the Australian government, namely, voluntaryaction(MMA2002).Incontrast,themarketbasedapproach,arguethecritics of regulatory approach, alters market price signals with the objective of providing incentives for consumers to conserve energy and for producers to invest in cleaner energy technologies. This approach is favoured by most economists and some environmentalists because it treats the environmental cost of energy in a transparent manner(thatis, itinternalisesthe negativeexternality associated with environmental impacts) and allows market mechanisms to send a price signal that can achieve an appropriate balance between the economic benefits of energy use and its environmentalcosts.Emissionstradingandcarbontaxareoftenconsideredasthetwo main marketbased environmental policy options to achieve reductions in CO2 emissions (Common & Hamilton 1996; Cornwell & Creedy 1995; Missfeldt & Hauff 2004; Price Waterhouse 1991). A hybrid marketbased approach that combines elementsofbothemissionstradingandcarbontax,calledapermitandfeesystem,was 58 alsorecentlyconsidered(McKibbin&Wilcoxen2006).Infact,the“carbontax”option involvesamixtureofregulatoryandmarketbasedapproaches.Itrequiresgovernment intervention in regulating the tax components to ensure the internalisation of externalitiesand,atthesametime,requiresfreemarketprinciplestosendpricesignals thatwouldencourageemissionreduction. In order to achieve reductions in CO2 emission, both regulatory and marketbased approaches have often been recommended to be used in combination (Topham & Hennessy 1996). However, as suggested by Price Waterhouse (1991), before combinations of measures can be efficiently adopted, each measure needs to be understoodinisolation. The discussion in Section 3.2 revealed that the carbon tax approach has not received much support in Australia in the past, due to concerns about its likely adverse economicimpacts.Thisresearch,however,arguesthatthisoppositiontocarbontaxis based on a less than complete understanding of the various facets of this approach, including alternative principles for the design of appropriate levels of carbon tax, its economywide impacts, etc. It is also argued in this research that if these facets of carbontaxareappropriatelyunderstood,muchoftheoppositiontoitwouldweaken andthatitcouldinfactbetechnically,economicallyandpoliticallyanattractiveoption toreduceCO2emissions.Oneofthekeyattractivenessofthisapproachisthatitcould enable a correct pricing of negative environmental externalities and, hence, allow cleaner electricity production technologies to compete with the traditional technologies. Moreover, a carbon tax policy is deemed by some as being the easiest environmentalpolicytobeimplementedandmonitored(Owen1992).Accordingly,in the subsequent subsections, the rationale and strategy for the implementation of a carbontaxpolicyforreducingAustralia’sgreenhousegasemissionsisassessed. 3.3.2 ConventionalCarbonTaxApproach A carbon tax is a tax imposed on the total quantity of greenhousegas emission. Its main objective is to encourage the use of fuels with lower carbon content. This is 59 achieved by taxing the use of fossil fuels. The level of tax is typically related to the carboncontentofthefuel. Carbontaxistraditionallyformulatedbasedonstandardneoclassicaleconomictheory ofexternalities,includingPigouviantax25andCoaseantheorem.26Theleveloftaxisbased ontheformer,whiletheallocationofemissions,isbasedonthelatter.Thesetheories, in essence, define the core of what is known as the Polluter Pays Principle (PPP). Following the adoption of this principle by the OECD in 1972 and European Community in 1975, it occupies a prominent place as a background principle for developingenvironmentalpolicymeasuresaroundtheworld(Steenge1999). AccordingtothePPP,thepolluterisdefinedastheagentwhoisprimarilyresponsible for taking measures to maintain desired environmental quality levels (OECD 1994). The polluters are treated as consumers of primary energy (called direct energy).27 Emissionsare,therefore,allocatedasthesoleresponsibilityofthesepollutersand,asa result,requirethesepolluterstoberesponsibleforthecostsofcontrollingpollution,by taxingthemaccordingtotheirlevelsofemissions.Clearly,carbontax–basedonPPP– tends to penalise big polluters such as fossilfuel industries. The impact on these industries would be directly proportional to the carbon content of each fossil fuel consumed.Thismeansthatacoalfiredpowerstationwouldbepenalisedmorethana gasfired powerstation.Electricitygeneratedfromrenewableenergyisassignedzero emissions, as it does not consume any fossil fuel and, hence, will not be penalised at all. Acarbontaxpolicy,basedonthePPP,hasbeenwidelydebatedinAustraliasincethe early 1990s. Such debate was particularly intense during the times of international APigouviantaxreferstoalaxleviedoneachunitofapolluter’soutput,inanamountjust equal to the marginal damage it inflicts upon society at the efficient level of output (Pigou 1978). 26The Coaseantheoremreferstotheallocationofpropertyrightsand, through the process of bargaining among parties concerned, the market would solve the environmental problem (Coase1960). 27 The flow of direct energy can be represented in terms of the energy balance, as shown in Figure12(Chapter1). 25 60 debateon waysofcombatingclimate change,for example,theTorontoconference in 1988,theCOP1inBerlinin1995,andtheCOP3inKyotoin1997. A number of studies were conducted during this period to assess the suitability of carbon tax as a measure to achieve emissions reduction. These studies assessed the economicimpactofdifferentlevelsofcarbontax.Thisimpactwasassessedintermsof changesinthegrossdomesticproductsaswellaschangesinthelevelofoutputsfrom differenteconomicsectors. Table32presentsasummaryofkeyresultsofthesestudies.Thetableshowsthatthe introductionofcarbontaxwouldsignificantlyimpactontheAustralianeconomyand the energy industries. For example, according to the Industry Commission (1991a), a taxof$21.75pertonneofCO2wouldberequiredtomeettheTorontotargetandthis leveloftaxwouldresultina2.1percentlossinAustralianeconomicgrowthoverthe period1991–2005.AccordingtoMcDougal(1993),acarbontaxof$19pertonneofCO2 would result in a GDP loss of 0.9 per cent over the period 1993–2005. Similarly, according to NIEIR (1995), a tax of $14 per tonne of CO2 would result in economic lossesequivalentto$179billionovertheperiod1995–2005. 19c 21.75b 2.10% 26.2 Emissiontax($/tonne CO2) ChangeinGDP Blackcoal 3.1 Construction 1.8 +0.2 2.1to+0.2 6.5 1.3 4.8 0.5 4.4 20.8 11.2 100 67 20percentof 1990by2005, stabiliseby2010 +0.1 +0.3 0.3 0.1 1.1 0.62%to0.01%g $179bnf 7 Common& Hamilton(1996) 14d Toronto targeta NIEIR (1995) reduceGHGemissionsto20percentbelow1988levelbytheyear2005; 1988prices; 1987prices; consideredcarbontaxincombinationwithotherpolicymeasures; $1.25/tonnein1995andincreasesgraduallyuntilitreaches$13.8/tonnein2005,thenmaintainedatthisrateto2010; presentvaluewith8percentdiscountrate; reductionofGDPby0.62percentin2004,0.13percentin2014,andincreaseinGDPby0.01percentin2024. Services a: b: c: d: e: f: g: 2.2 Manufacturing 7.6 Electricity 9.5 Oil Ironandsteel 19.3 Gas Nonferrousmetal 62.3 Browncoal 0.90% Toronto targeta Torontotargeta CO2emissions reductiontarget Thorpeetal. (1994) ABARE(1997) 61 1.1%pa 4.3%pa $61bnf 1.2513.8e +3 +6 32 60 8 24 1990levelby 1990levelby2010 2005 &10percentbelow 1990by2020 McKibbin& Pearce(1996) SummaryofselectedcarbontaxstudiesbasedonPPPforAustralia McDougal (1993) Table32 Industry Commission (1991a) Notes: Sectoralimpact(percent) 62 Further, these studies have shown that the introduction of carbon tax would particularly adversely affect fossilfuel industries. For example, Thorpe et al. (1994) estimatedthat,in order toachievetheToronto target andthen stabiliseemissions by 2010,thebrowncoalsectorwouldbecompletelyphasedoutby2010,whiletheblack coalsectorwoulddeclinebyalmost70percentofitstotalproduction.Notonlywould fossilfuelsectorsbeheavilyaffected,fossilfuelconsumptionsectors,suchasenergy intensivemetalprocessingandelectricityindustries,wouldalsobeaffectedbycarbon tax.Forexample,McDougall(1993)estimatedthat,inresponsetoacarbontaxof$19 per tonne of CO2, while coal production would decline by about 20 per cent, the outputsoftheelectricityindustryandnonferrousmetalindustrywouldalsodecline by5and7percent,respectively.Asimilarpatternofresultsisalsosuggestedbythe Industry Commission (1991a). These studies marked the beginning of the debate on carbontaxinAustralia.Theoutcomeofthesestudiesinvitedastrongreactionfromthe fossilfuel industries. In response to this reaction, the government released the alternativegreenhousepolicystatementthatwasbasedonthevoluntarymeasures(as discussedinSection3.2.2). Inthemid1990s,beforetheincreasedinternationalpressureattheCOP1,carbontax was again being considered by the Australian policymakers as a policy option to reduceGHGemissions.Thistimeasmallamountoftax($1.25pertonneofCO2)was considered as a part of a larger policy package, titled Greenhouse 21 C (see Section 3.2.3).McKibbinandPearce(1996)arguedthateventhissmalltaxwouldreduceGDP by$61bn,andtheimpactonfossilfuelindustrieswouldbesevere.Theseassessments of the negative impacts of carbon tax on fossilfuel industries, together with their dominationwithinthepolicycircles,ensuredthatcarbontaxwouldnotbetakenupas apolicyoptiontoreduceCO2emissions(seeSection3.2.3).Similaradverseimpactsof carbontaxonfossilfuelindustrieswerealsohighlightedearlierbyABAREintherun up to Kyoto (ABARE 1997). However, the study by ABARE showed that the impact would not be confined to fossilfuel industries; other industries, for example, some exportoriented industries, such as nonferrous metal and iron and steel, would be adversely impacted upon as well. Consequently, carbon tax policy was continually 63 rejected by the Australian government, on the grounds that it would endanger the survivalofthefossilfuelindustriesandimpedeeconomicgrowth. Given the unrivalled political influence of the coal–electricity compact, the politics of climate change has been very intense in Australia. A key element of this policy has beenoppositiontotheimpositionofcarbontax.Theadoptionofsuchpolicywould,as mentionedinTheAustraliannewspaper,“penalisethebigcarbondioxideproducerssuchas fossilfuelindustryandcouldcause additionalpoliticalbarrier”(Murphy 2005).Thisisthe reasonwhythecarbontaxpolicyhasnotbeenreceivedwellinAustralia. However,thisresearcharguesthattheestimatesabouttheadverseeconomicimpacts ofcarbontaxbasedonPPP(asdiscussedabove)areflawed.Inthisapproach(thatis, PPP),nonfossilfuelconsumingsectorsarenotconsideredas“polluters”,eventhough theyusetechnologieswhosemanufacturemightproduceCO2emissions.Inaddition, they consume electricity produced from fossil fuels. The contribution to CO2 of these sectors is not captured in the PPP. This contribution can, however, be captured if carbon tax is designed on the basis of a modified approach called Shared ResponsibilityPrinciple(SRP).Thisapproachisdiscussedinthenextsection. 3.3.3 AModifiedCarbonTaxApproach Although the PPP has been widely adopted as the background principle for developingarangeofenvironmentalpolicies,includingcarbontaxpolicy,itmaynot be the most appropriate and effective principle for this purpose. There are two main shortcomingsofthisprinciple. First,theformulationofPPPisbasedonpurelyeconomictheoriesanddoesnotreflect the real physical world in term of a complete materials balance (see, for example, Ayers1978;Ayers1999;Ayers&Kneese1969;Boulding1966;Fritsch,Schmidheiny& Seifritz 1994; GeorgescuRoegen 1971; Kneese, Ayers & dArge 1970). Essentially, the materialsbalance approach holds that all materials (that is, energy and nonenergy) extractedfromtheenvironmentandusedintheeconomyareaccountedforbyeither remaining in the economy as durable goods or disposed of in the environment as 64 emissions(Cordato2004;Pearce&Turner1990;Perrings1987;Pethig2003;Ruth1993). This approach therefore implies that environmental problems are a part of economic processes and all goods and services produced in an economy are (directly and indirectly) associated with energy use. In other words, energy is consumed in any economicactivityintwoways–directlyintheformofprimaryenergy,andindirectly intheformofenergyembodiedinmaterials(calledindirectenergy).Thisindirectuse ofenergy,accordingtoSpreng(1988,p.138),includes: …(1)energyembodiedinmaterialsconsumedduringoperationoftheprocess;(2)energy embodiedinthecapitalfacilitiesofthesystem(includingtheenergyembodiedinallthe manufacturedcomponentsaswellastheenergydirectlyconsumedduringconstruction of these components); (3) energy embodied in the capital facilities that produce the materials and components and in the equipment used during construction; and (4) energyrequiredtoproducethefuelsandelectricityconsumeddirectly. The indirect energy thus comprises a chain of direct energy requirements leading upstreamtorawmaterialsintheground.Therefore,inordertocompletethematerials flowandhenceaccuratelyrepresentenergy–environment–economicinteractions,both directandindirectenergyhavetobeaccountedfor.Thishasalsobeenemphasisedby Owen(2004,p.131)inthat,withinthecontextofenvironmentalimpactofenergyuse: …alifecycleapproachmustbeadoptedinordertoidentifyandquantifyenvironmental addersassociated withtheprovision ofenergyservices. This approach providesdetailed and comprehensive evaluation of energy supply options (based upon both conventional andrenewablesources). In the case of renewable technologies, while PPP considers them as zero emission technologies,theymayinfactconsumesignificantamountsofenergythroughtheuse ofmaterialsovertheirentireoperatinglife.Thisincludes,forexample,theconstruction of power plants requiring steel (from the iron and steel industry), copper (from the nonferrous metal industry), cement (from the construction industry). Moreover, the operationofthesetechnologiesmayrequireelectronics(fromtheelectronicsindustry), plastics (from the chemical industry), and so on (Proops et al. 1996, p. 230). The 65 productionofthesematerialsrequirestheburningofvarioustypesoffossilfuels,and hencethereleaseofCO2emissions. FromthediscussioninSection3.3.2,itisclearthatcarbontaxbasedonPPPdoesnot consider the environmental consequences arising from this indirect energy. If this indirect energy is considered, there could be, this research contends, different economywideimplicationsofcarbontaxpolicyfromtheonethatisbasedonPPP. Thesecondshortcoming(relatedtotheabovenotedshortcoming)ofdesigningcarbon tax based on PPP is the issue of equity. Because PPP does not consider indirect emissions, the responsibility of controlling pollution rests solely upon fossilfuel consumers.Inthisapproach,renewableindustry,usingnonfossilfuelinputs,remains sheltered from environmental responsibility. Accordingly, this could pose an unfair burdenonfossilfuelindustries.Themessagehereisthattheclimatechangeproblem should not be considered as the responsibility of only the fossil fuel consumers (or pollutersastheyaredefinedbyPPP);itshouldbetheconcernofthewholeeconomy. In light of these shortcomings, a number of principles have been developed as alternatives to PPP. These include usershouldpay (UP), polluterandusershouldpay (PUPP),andvictimpay(VP)(Steenge1999).However,likethePPP,alltheseprinciples alsohavesomeshortcomings.Forexample,inthecomplicatednetworksofindustrial complexes,itisdifficulttoidentifywhoshouldbeconsideredasthepolluter,user,or victim(Steenge1999,p.165).Iftheliabilityofmaintainingenvironmentalstandardsis setastheresponsibilityofanysingleparty,itwouldinevitablyposeanunfairburden onthatparticularparty. Inadditiontotheabove,thereisanotherprinciplethathasrecentlybeenmentionedin theEuropeanUnionFifthActionProgram.Thisprincipleisderivedfromtheconcept of shared responsibility and, therefore, is called the Shared Responsibility Principle (SRP) in the context of this research. This principle seeks to alter production and consumption patterns in the economy. Such alteration is driven by environmental considerations (for example, CO2 emissions) of various production and consumption patterns (Steenge 1999). In other words, this principle assigns responsibility for CO2 66 emissions to both fossilfuel consumers and consumers of other products whose production may have consumed CO2emitting fossil fuels. Under this principle, both direct fossil fuel consumers and consumers of indirectfuel that is embodied in materials would be proportionally responsible for CO2 emissions. By taking into accounttheinterconnectionswithintheeconomy,onlypartoftheproducedpollution from fossilfuel consumption is imputed to the sector that actually consumes those fossil fuels, with the remaining parts being imputed to the consumers of their products.Thisway,environmentalemissionswouldberelatingmoredirectlytoboth productionandconsumptionactivitiesintheeconomy. This research proposes the use of this principle as a basis for developing carbon tax basedenvironmentalpolicy.Inthisalternativeprinciple,theflowofdirectandindirect energy in the economy can be examined.28 These flows reflect the true interactions between an economic activity and its impactontheenvironment. The environmental impactsfromnonfossilfuelconsumerscanalsobecaptured.Ifcarbontaxisimposed basedonSRP,theseindirectenergyconsumerswillalsobeconsideredasthepolluters andhencewouldalsobeliableforenvironmentalresponsibilities. 3.3.4 SectoralResponsibilitiesofAustralianEmissions In Section 3.3.2 and 3.3.3, two principles that can be used for designing carbon tax policy were discussed. These are the Polluter Pays Principle (PPP) and the Shared Responsibility Principle (SRP). The main difference between these two principles (as was also noted in these sections) is in terms of the procedures for allocating CO2 emissionresponsibilitiesacrossdifferentsectorsintheeconomy(anumericalexample is also given in Appendix A to provide further clarification on this aspect). Once emissions are allocated, however, carbon tax is imposed on the same basis in both casesandthepricemechanisminfluencesthebehaviouroftheeconomicagentsinthe samemanner. Theflowofdirectandindirectenergycanberepresentedintermsofthematerialsbalance,as showninFigure13(Chapter1). 28 67 Table33showssectoralCO2emissionsfortheAustralian economyin2002.TheCO2 emissions are allocated based on both PPP and SRP (using a method discussed in Chapter5).Thesectoralclassificationshowninthistableisthesameasthatshownin Figure1.4. Thetableshowsthat,underPPP,theelectricitysectoristhelargestemitterofCO2in theAustralianeconomy.ItwasresponsibleforsixtypercentofthetotalCO2emissions in2002.Thecommercialsector,accountingfornearlyhalfofthecountry’sproduction, ranked thirteenth, responsible for just over one per cent of total CO2 emissions. The tablealsosuggeststhat,basedonPPP,thebigfossilfuelconsumers(forexample,the electricitysector,roadandairtransport,ironandsteelindustry,andnonferrousmetal industry)areresponsibleformostoftheemissionsintheeconomy.Ontheotherhand, when allocation of CO2 emissions is based on SRP, the electricity sector contributes only 21 per cent of total CO2 emissions. In this case, the commercial sector is ranked first.Itisresponsiblefor33percentoftotalCO2emissions.Althoughthecommercial sector does not consume fossil energy directly, it consumes significant amount of electricity, as well as other materials. These materials and electricity, in turn, are producedfromCO2emittingfossilfuels. 68 Table33 AustralianCO2emissions:PPPvs.SRP Rank PolluterPaysPrinciple(PPP) Sector SharedResponsibilityPrinciple(SRP) Mt % Sector Mt % 1 Electricitysector 187.04 60.47 Commercialsector 102.07 33.00 2 Roadtransport 20.52 6.64 Electricitysector 65.12 21.05 3 Ironandsteelindustry 14.89 4.81 Foodindustry 21.58 6.98 4 Nonferrousmetalindustry 14.41 4.66 Nonferrousmetalindustry 20.75 6.71 5 Airtransport 11.96 3.87 Miningsector 11.02 3.56 6 Coalsector 9.17 2.97 Airtransport 10.26 3.32 7 Chemicalindustry 8.90 2.88 Roadtransport 10.25 3.31 8 Petroleumsector 7.96 2.57 Coalsector 10.00 3.23 9 Nonmetalindustry 6.18 2.00 Agriculturesector 7.55 2.44 10 Agriculturesector 5.47 1.77 Othertransport 6.72 2.17 11 Miningsector 4.64 1.50 Machineryandequipmentindustry 6.71 2.17 12 Watertransport 3.78 1.22 Petroleumsector 6.65 2.15 13 Commercialsector 3.75 1.21 Chemicalindustry 6.56 2.12 14 Foodindustry 2.46 0.79 Ironandsteelindustry 4.00 1.29 15 Constructionsector 1.90 0.62 Woodandpaperindustry 3.88 1.26 16 Woodandpaperindustry 1.83 0.59 Watertransport 3.55 1.15 17 Railwaytransport 1.55 0.50 Railwaytransport 3.47 1.12 18 Othertransport 1.02 0.33 Textileindustry 3.06 0.99 19 Gassector 0.93 0.30 Waterindustry 2.14 0.69 20 Textileindustry 0.41 0.13 Constructionsector 1.06 0.34 21 Machineryandequipmentindustry 0.32 0.10 Nonmetalindustry 1.02 0.33 22 Fabricatedmetalindustry 0.13 0.04 Fabricatedmetalindustry 0.79 0.26 23 Waterindustry 0.08 0.03 Gassector 0.67 0.22 24 Othermanufacturingindustry 0.02 0.01 Othermanufacturingindustry 0.44 0.14 TotalCO2Emissions Notes: Year2002 309.32 100 TotalCO2Emissions 309.32 Thistablepresentstheresultsobtainedfromtheapplicationofequation53forPPPand equation56forSRP,asdetailedinChapter5,Section5.2.Fordetailedresults–seeTableD1 toD4,AppendixD,pp.271274. CO2emissionsfromroadtransportdonotincludefuelusedinprivatevehicles.Although privateroadtransportisamajorsourceofemissions,thefocusofthisresearchisonthe productionsideoftheeconomy. ItisalsoclearfromTable33thatcarbontaxpolicybasedonSRPwouldhavecertain advantagesoverthatbasedonPPP.Theprincipleofreallocationofemissionsbasedon SRPisinlinewiththematerialsbalanceapproach.Itinvolvesintegratingtheenergy andnonenergyrelatedemissionsandassigningthemtoaparticulareconomicactivity (GWA & ES 2002).Inother words,itnotonly considers emissionsfromdirectuse of energy, but also indirect emissions from the use of energy embodied in materials for 100 69 eachgoodproduced.Thisway,acomprehensiveevaluationofenergysupplyoptions– fossilsandrenewable–couldbecarriedout.Also,basedonSRP,theresponsibilityfor CO2emissionscanbefairlyattributedacrossallsectorsintheeconomy(seeTable33). Despite these advantages of SRP over PPP, there is a lack of discussion and further investigation of its policy implications in Australia and indeed worldwide. This investigationconstitutesacoreaspectofthisresearch. 3.4 SummaryandConclusions Themainobjectiveofthischapterwastoprovideanoverviewofthedevelopmentof greenhousepolicyinAustraliaandtodevelopaperspectiveoncarbontaxasapolicy optiontoreduceAustralia’scarbondioxideemissions.Themajorconclusionsfromthis chapteraresummarisedasfollows. x Carbondioxide emissions from electricity generation in Australia are substantial and increasing. Its share of total CO2 emissions increased from 32 percent(129Mt)in1990,to47percent(194Mt)in2004–anincreaseof51per centascomparedwithanincreaseof3percent(from402Mtto415Mt)oftotal CO2 emissions. Specifically, the introduction of the national electricity market has contributed to a considerable increase in emissions. For example, these emissions increased from 152 Mt in 1997 to 167 Mt in 1998. This is due to an increaseintheshareofbrowncoal(from29percentin1997to34percentin 1998)–thecheapestanddirtiestfuel–forelectricitygeneration.Intheabsence ofanydecisiveenvironmentalpolicy,thefuturegrowthinCO2emissionsfrom electricity generation will place significant pressure on Australia’s total CO2 emissions. x The climate change policy development in Australia has, in the initial years, been guided by genuine concerns about global warming. In these years, Australia indeed acted as a global leader in proposing strategies to combat climate change. Australia was among the first countries to ratify with the internationalpartyandconductedthedomestic“interimplanningtarget”based mainlyontheadoptionofcarbontaxtoreduceCO2emissions.Later,however, 70 as the economic impacts of such policies became clearer, especially on fossil fuel industries, Australia drastically changed its environmental stance. The release of key policy papers thereafter (for example, National Greenhouse Response Strategy, Greenhouse Challenge Program, and Energy White Paper) firmly established a stance that favours economic objectives over environmentalobjectives. x Thecoal–electricitycompacthasexertedastronginfluenceontheevolutionof Australia’sgreenhousegasreductionpolicies.Suchpolicieshavereliedmainly on voluntary initiatives for the reduction of greenhousegases. These policies were,however,characterisedbya fragmentedarrayofshorttermcommercial and economic interests and lacked consideration of longterm environmental sustainability. x The use of marketbased instruments, particularly carbon tax, has been continually rejected by the Australian federal political parties, on the grounds that it would impede economic growth. Its expected impact on Australian industries has created “carbon tax phobia” among coalelectricity interests, which has significantly influenced the government’s greenhouse policy development. x Carbontax,astraditionallyexamined,isbasedonanarrowlydefinedprinciple –thePolluterPaysPrinciple.Emissionsbasedonthisprincipleareconsidered as the sole responsibility of the consumer of direct energy. This approach, therefore,tendstopenalisebigfossilfuelindustries. x There are two main shortcomings of carbon tax that are based on PPP. It ignoresindirectenergy embodied inmaterials,and is inequitableinassigning environmentalresponsibility. x TheSharedResponsibilityPrinciple(SRP)couldovercometheseshortcomings andhencecouldbeusedasanalternativemethodforthedesignofacarbontax policy.Thisprincipleconsidersemissionsarisingfrombothdirectandindirect energyconsumption.Hence,it providesacomprehensiveandrealisticpicture of the real impact of carbon tax on various segments of society. This method 71 also promotesfairness(intermsof emissionsaccreditation)between all actors involvedintheAustraliangreenhousegasdiscourse. x Despite these advantages of SRP, there is a lack of analysis about the applicationofcarbontaxbasedonthisprinciple.Thisresearchdevotesspecific attentiontothisissue. 72 CHAPTER4 4 AREVIEWOFMATERIALSBALANCEFRAMEWORK InChapter3,acasewasmadeforconsideringacarbontaxpolicybasedontheShared ResponsibilityPrinciple(SRP)asameanstoreduceCO2emissions.Suchconsideration would require the representation of various economic activities (for example, electricity production) in terms of their energy and material input requirements, or materialsbalance (as also shown in Figure A2 in Appendix A). There are several methods for developing materialsbalances. Each of these methods poses some challenges. Theobjective ofthischapter is toreviewmethodsthatincorporatematerialsbalance, tounderstandtheirrelativestrengthsandweaknesses,andtousethisunderstanding to select an appropriate method for this research. Section 4.1 introduces the background of the materialsbalance framework and describes the broad contours of two materialsbalance frameworks. Before a review of these two materialsbalance frameworksisconducted,asetofcriteriaisoutlinedinSection4.2.Themethodthat will be selected from this review must satisfy these criteria. This is followed by a review of studies adopting the materialsbalance framework. These studies are grouped into two materialsbalance frameworks discussed in Sections 4.3 and 4.4. A summaryofthemajorfindingsofthischapterarepresentedinSection4.5. 4.1 BackgroundofMaterialsbalanceFramework Since the seminal work by Kneese, Ayers and d’Arge (1970), the need to include all inputs–energyaswellasnonenergy(materials)–intheproductionsystemhasbeen extensivelydiscussedinthecontextofenvironmentalpolicyanalysis(seeforexample, Ayers1978,1999;Ayers&Kneese1969;Boulding1966;Fritsch,Schmidheiny&Seifritz 1994; GeorgescuRoegen 1971; Kneese, Ayers & dArge 1970; Pearce & Turner 1990; Perrings 1987; Ruth 1993). This principle is called the materialsbalance in literature. 73 Thematerialsbalanceframeworkisfoundedonthephysicallawsofthermodynamics, particularly the law of mass conservation. The law of mass conservation states that energy and materials cannot be created or destroyed, but their characteristics change from one state to another. This law implies that all of the energy and materials are extracted from the environment, flow through the economic system in the form of productionandconsumptionofgoodsandservices,andaredisposedofbackintothe environment in the form of emissions and other waste products. This principle, in contrast with the traditional economic view29, regards environmental problems as a pervasiveandinevitablephenomenon.Itregardsenvironmentalproblemsasapartof economicprocessesthatcanonlybeadequatelyassessedifthecompletematerialflow intheeconomyisenvisioned(Pethig2003).Itfocusesonthecompleterepresentation of the relationship between the economy and the environment. Every input into an economic activity must be considered in order to understand the true environmental impactassociatedwiththateconomicactivity.Thematerialsbalanceframeworkisalso referred to, by Daly (2002), as the representation of materials throughput in the economy. Initsmostbasicform,thematerialsbalancecanberepresentedintheformofphysical flowsofenergyandmaterials,withflowsexpressedintheiroriginal(thatis,physical) units. The motivation for the physical flow approach is that the economy is underpinnedby a physical worldofstocks andflows of energy andmaterials.These stocks and flows are used to determine the economic choices and social behaviour (Poldy 1998). In order to be better informed about this dimension of the physical world,itisessentialtounderstandtheseflowsintheiroriginalforms.Thisapproachis favouredbyenvironmentalistsandecologists,asitrepresentsthephysicalindicatorsof sustainabledevelopment,whichcovera“broadersetofsocialvaluesandamenitiesanddo nothaveanintegrativepowerofmonetaryaggregatesgeneratedinenvironmentalaccounting systems” (Bartelmus & Vesper 2000). There are three methods that can be classified In the traditional economic view, an economic system – comprising production and consumptionactivities–isviewedincompleteisolationfromtheenvironmentalsystem.The environmentisregardedasexternaltotheeconomicsystem. 29 74 under the physical flow approach – material flow analysis, lifecycle analysis, and referenceenergy–materialsystemanalysis–asshowninFigure41. Figure41 Aclassificationofmaterialsbalanceapproaches Another approach to materialsbalance is to employ an embodied energy approach, ratherthanthephysicalflowofmaterials.Theembodiedenergymethodsstartedinthe late1970s,mainlyinanefforttoaddresstheproblemoffossilfuelsdepletionfollowing the1973energycrisis,whichwasthemainconcernatthattime.Anumberofstudies (for example, Bullard & Herendeen 1975; Chapman 1975; Chapman, Leach & Slesser 1974;Wright1974,1975)wereinitiatedatthattime;thesestudiesusedenergyflowsin the economy, rather than monetary flows, to analyse the energy used for the productionofenergyandmaterials.Theembodiedenergyapproachisdefinedas“the computation and measurement of energy flows in society, and, in particular, as the quantificationofthevolumeofenergyresourcessequestered,directlyandindirectly,invarious commodities” (IFIAS 1978). The total embodied energy comprises energy required directlyforthemainprocess(forexample,coalusedforelectricityproduction)andthe indirect energy embodied in the material inputs to the process (for example, energy used for readying coal needs for electricity production and energy used for the construction of power stations). The embodied energy approach can be used as a ctoral price effects are estimated using input–output price model. In the fourth module,thesubstitutioneffects,inresponsenthematerials.Thesentimentbehindthis argumentiscapturedinthefollowingstatementsbyFritsch,SchmidheinyandSeifritz (1994,p.186): 75 …Ifacertainresourceisdepleted,itsmaterialcomponentshavenotceasedtoexist(law ofconservation).Rather,thisresourceoritscomponentpartsarenotavailablewiththe concentration,intheproperplace,andatthepropertime.Thisconditioncanbefulfilled forpracticallyallelementsofthesystem.This,however,requiresenergy.Forthisreason, the resource or raw material problem can be reduced to the problem of energy – ‘the ultimateresource’. Process analysis and input–output analysis can be classified as embodied energy methods(seeFigure41). Anumberofstudieshavebeencarriedoutusingphysicalflowandembodiedenergy methodsfordevelopingmaterialsbalanceframeworks.Thesemethodsarereviewedin Sections4.3and4.4. 4.2 CriteriaforExaminingMethodologicalApproaches As shown in Figure 41, there are several methods that can be used to develop a materialsbalance.Anumberofstudieshaveincorporatedthesemethodsforanalysing different environmental issues, with the common single purpose of better understandingtherelationshipbetweentheeconomyandtheenvironment.However, before reviewing these studies, a set of criteria needs to be established in order to examineeachmethodagainstthesecriteria.Themethodthatwillbeselectedfromthis reviewmustsatisfythesecriteria.Thesecriteriaare: i. Goal: this research examines the economywide impacts of carbon tax as a policy option for reducing CO2 emissions. Therefore, the selected framework mustalsobe ableto analyse carbontax and assess its impactsonthenational economy. ii. Spatial scope: the impact of carbon tax would vary across sectors in the economy,dependingonthesectoralcontributiontoCO2emissions.Therefore, the selected framework must allow the analysis to be performed at disaggregatedlevels. iii. 76 Temporalscope:becauseofthelongtermnatureofenvironmentalissues,the frameworkmustallowtheanalysisoverthemediumtolongterm. iv. Dynamics: the dynamism of a model is an important characteristic in any modelling study. Two aspects of dynamism need to be captured in this research. First, the model must capture changing technological characteristics over time. This can be achieved through the substitution of factor inputs in responsetochangesinfactorpricesarisingasaresultoftheintroductionofa carbontax.Second,themodelmustbeflexibleinallowingcapitalinvestmentto be adjusted in response to the introduction of carbon tax. This would further improvetheabilityoftheselectedframeworkforlongtermanalysisbecauseit wouldallowthemodeltocapturechanginginvestmentpatterns(forexample, incleanertechnologies). v. Price consideration: the inclusion of carbon tax would increase the cost of production from an economic sector to the extent of its contribution to CO2 emissions,and henceraise the priceof outputfromthatsector.Therefore,the selectedframeworkmustbeabletocapturepriceimpactsacrossvarioussectors oftheeconomy. vi. Data requirement: the availability of data is always a challenge in any empirical study. This is especially the case in this research, because detailed data on material flows would be required. The framework selected for this researchmustbeopeninusingthepubliclyavailableinformation. 4.3 PhysicalFlowMethods As discussed in Section 4.1, the materialsbalance can be represented in terms of the physicalflow approach.Anumberofstudies havebeenconductedinthepast,using differentmethodsbasedonthephysicalflows.Theseare:MaterialFlowAnalysis,Life cycleAnalysis,andReferenceEnergy–MaterialSystemanalysis(seeFigure41).Table 41providesasummaryofthesestudies,whicharediscussedindetailinthefollowing subsections. Australia n.s. Australia USA USA Poland ACARP(2002) Gagnonetal.(2002) GWA&ES(2002) Meier(2002) Stiegel(2002) Góralczyk(2003) Renewable Electricity Electricity Energy Electricity Electricity Electricity Electricity Economy USA Mann&Spath(2000) Canada Macdonaldetal.(1997) EU Bringezu&Schütz(2001) Netherlands Economy Guinéeetal.(1999) 3sectors EU Spangenbergetal.(1998) Economy Sector 4countries Country Scope Adriaanseetal.(1997) Author(Year*) Table41 n.a. n.a. n.a. 1990&99 n.a. n.s. n.s. 1990 Focus Identifylifecycleenvironmentalimpacts LCAofgasfiredpowerplants LCAofnaturalgas&photovoltaic Allocatelifecycleemissionstoendusers Compareenvironmentalperformanceof electricitygenerations ExamineLCAofelectricitytechnologies Determiningelectricitysupplyoptionsin marketbasedeconomiesbasedonLCA Comparebiomass,coal,andNGelectricity LifeCycleAnalysis(LCA) Comparetotalwithdirectmaterialrequirement Analyseenvironmentalimpactsofmetalflows ComparematerialflowswithNational Accounts Developmaterialflows MaterialFlowAnalysis(MFA) 1987&95 1990 1990 n.s. Study period Studiesadoptingphysicalflowmethod Providedlifecycleemissionsofgasfired electricity Providedlifecycleemissionsofrenewable electricity ProvidedlifecycleemissionsofNG&PV Environmentalperformance– hydro>wind>nuclear>gas>coal Listoflifecycleemissionsatenduselevel Providedalonglistoflifecycleemissions LCAcanbeusedasanefficientmethodfor internalisingenvironmentalexternalities Environmentalperformance:Biomass>Coal Directmaterialrequirementsdeclined,while totalmaterialrequirementsincreased UseofNationalAccountsunderestimates environmentalimpacts Environmentalimpactsfrommaterialflows aresignificant Emissionsfromindirectmaterialflows>direct KeyFindings 77 Netherlands Manufacturing 1990–2040 Europe Europe Europe Belgium Europe Gielen(1995) Gielen&Kram(1998) Gielen(1999a) Gielen(1999b) Nemryetal.(2001) OECD(2001) Economy 3products Construction IronandSteel 1990–2050 1990–2010 1990–2030 1990–2030 Manufacturing 1990–2050 1989 1977 Sweden Papermill Focus Analysetwopolicyscope(Energyand Energy+Material)foremissionsreduction AnalyseCO2reductionfromenergy(E)and materials(M)systemimprovement AnalyseCO2reductionfromenergy(E)and materials(M)systemimprovement EvaluatelifecycleGHGemissions AnalyseCO2reductionfromenergy(E)and materials(M)systemimprovement GHGreductionpotentialfrommaterialsystem Maximiseprofitfrommaterialreduction Minimisematerialscostinpackagingsector ReferenceEnergyMaterialSystemAnalysis(REMS) Study period Sundberg&Wene(1994) Packaging Sector USA Country Scope Hoffman(1980) Author(Year*) Notes: n.a.=Notapplicable,n.s.=Notspecified. * Yearofpublications. Costreductionachievedfromchangingcostof otherinputs,ratherthanmaterialsubstitution Costreductionachievedfromrecycled material CO2reductioncostsfromE+Marelowerthan ifcomparedwithimprovementfromEalone Materialsystemcancontributeupto50%to totalemissionreduction CO2reductioncostsfromE+Marelowerthan ifcomparedwithimprovementfromEalone CO2reductioncostsfromE+Marelowerthan ifcomparedwithimprovementfromEalone Productsubstitutionsignificantlyreduceslife cycleemissions Includingmaterialoptionsimprove effectiveness&efficiencyofGHGmitigation policies KeyFindings 78 4.3.1 79 MaterialFlowAnalysis Material Flow Analysis (MFA) is similar to the approach favoured by industrial ecologists, for analysing how materials and energy flow within a system. This approach describes the flow of one type of material through different sectors in any giventimeperiod(Kandelaars1999).Inthisapproach,physicalquantitiesofdifferent materialsaretracedwithinanindustryorasectorintheeconomywiththeuseofinput andoutputratios(Boumanetal.2000).Becausethefocusinthisapproachisaspecific material, only sectors that are directly involved in the life cycle of that material are consideredintheanalysis.Also,thesystemboundaryofthisapproachrangesfroma singleindustrytothewholeeconomy. MFA has recently received a lot of attention. Adriaanse et al. (1997) adopted this methodtomeasurethetotalmaterialrequirementsforGermany,Japan,Netherlands, andtheUSA.Theyfoundthatabout55to70percentofmaterialflowsarenotshown inthenationalaccounts,whichunderestimatestheuseofnaturalresources andtheir environmental impacts. Spangenberg (1998) developed material flows for energy, transport, and construction sectors in the European Union in 1990. These studies showed that material flows in these sectors were significant and so were their environmental impacts. The author suggested some material recycling options as means to reduce environmental impacts. Guinée et al. (1999) analysed the flows of metalsintheNetherlandseconomy.Theyfoundthatwhileemissionsfromdirectuse of metals had declined, their use as inputs in other products have increased significantly, which led to a net increase in emissions. Bringezu and Schütz (2001) estimated the total material requirement for the European Union in 1985 and 1997. Theyfoundthatwhiledirectmaterialconsumptionappearedtobedeclining,thetotal materialconsumptionwasinfactincreasing. The discussion above shows that MFA is a useful approach for assessing specific technical options in terms of material substitution or recycling in reducing CO2 emissions from a particular sector. It can be used to identify areas where system improvements would result in increased materials efficiency or reduced waste, or 80 other materials management objectives (Tisdale 2002). However, it requires a high level of detail, incorporating all flows of materials in question. As a result, a large amountofdataisrequiredtotracematerialflows.Thedatarequiredforsuchanalysis isveryexpensiveand,inmanycases,difficulttoobtain.Furthermore,MFAisashort term, static approach used to describe a current material system, which inhibits its abilitytocapturethechangesineconomicsystem. 4.3.2 LifecycleAnalysis Lifecycle Analysis (LCA) is a method that can be employed to assess the environmentalconsequencesofaproductfromcradletograve(Boumanetal.2000).It is similar to MFA in that it takes a productfocused approach in studying how a particular product (or material) flows. However, LCA does not limit the flow of productwithinanyparticularregionortimeperiod,butfocusesonitswholelifecycle. This method was developed on the basis of process analysis (process analysis is discussed in Section 4.4.1). The process analysis method has been refined and expandedtoincludealltypesofenvironmentalimpacts.LCAcanbeusedforassessing theenvironmentalimpactsofeachstepinvolvedincreatingaproduct.Asdefinedin ISO1404030: Life cycle analysis is a technique for assessing the environmental aspects and potential impactsassociatedwithaproductbycompilinganinventoryofenvironmentallyrelevant inputs and outputs of a system, evaluating the potential environmental impacts associated with those inputs and outputs and interpreting the results of the inventory andimpactphasesinrelationtotheobjectivesofthestudy. LCAisamethodusedforidentifyingtheenvironmentalimpactsofvariousstagesofa life cycle. In other words, it attempts to measure the “cradletograve” environmental impacts of a product: from materials acquisition and production, through ISO 14040 belongs to the ISO 14000 families of standards concerning environmental management.Itprovidesaclearoverviewofthepractice,applicationsandlimitationsofLCA (ISO1997). 30 81 manufacturing, system use and maintenance, and finally through the end of the system’s life. In the electricitygeneration sector, for instance, such assessment would include processes associated with the extraction, processing and transportation of fuels,the buildingofpowerplants,productionofelectricityanddecommissioningof power plants (Gagnon, Bélanger & Uchiyama 2002). The analysis of life cycle is thereforebasedontheknowledgeofaccompanyingprocesses. LCA has been used since the late 1960s for estimating the requirements of natural resources for the production of various commodities. Its application in the electricity sectorhasonlyrecentlybegun.SomeexamplesofsuchapplicationsincludeBergerson andLave(2002),Gagnon,BélangerandUchiyama(2002),Góralczyk(2003),Mannand Spath(2000),Meier(2002),andStiegel(2002).ThesestudieshaveessentiallyusedLCA to assess a range of environmental impacts of different electricity generation technologies.Forexample,Macdonaldetal.(1997)analysedelectricitysupplyoptions inAlberta(inCanada)basedonLCAfortheyear1990andfoundthatthismethodis appropriateforuseasanefficientmethodininternalisingenvironmentalexternalities. Gagnonetal.(2002)adoptedLCAtocomparetheperformanceofdifferentelectricity generationtechnologiesintermsoftheirenvironmentalimpacts.Thestudyfoundthat, basedonlifecycleemissions,renewablepowerplantshaveanexcellentenvironmental performance compared with fossilfuel power plants. Mann and Spath (2000) also performed lifecycle assessments of biomass, coal, and gasfired power stations and found that biomass provides significant environmental benefits over conventional fossilbasedpowerstations. The LCA approach has also been applied in Australia to determine total emissions generated from the full fuelcycle of electricity generation. For example, Coal in a SustainableSociety(CISS)isamajorprojectforexaminingthecradletograve,orfull lifecycle, impacts of current and developing technologies for electricity generation (ACARP 2002). This study has developed lifecycle analysis for several electricity generationtechnologiesandfoundthatgasfiredelectricitygenerationhavesimilar(or even higher than, in some case) greenhouse emissions to coalbased electricity generation. The study by GWA and ES (2002) has also adopted a similar method, 82 calledthefuelcycleanalysisoftheenergysector,foreachoftheAustralianstates.This studyhasalsoincludednaturalgasandpetroleum,solidfuels,andelectricitysectors. Theprimaryobjectiveofthisstudywastocomputethefuelcycleoftheenergysector that would “relate greenhousegas emission moredirectly to productionactivities and tothe consumptionofgoodsandservices,sothattheimplicationsofemissionreductionstrategiescan bebetterplannedandunderstood”(ibid,p.8). Notwithstanding the usefulness of LCA, it suffers from several limitations, for example: itsinabilitytoperformtheanalysisforthewholeeconomy–thisisduetothe arbitrarinessassociatedwiththedrawingoftheboundariesofthesystemthat isbeinganalysed(Fiksel1996); its inability to capture the dynamics of changing markets and technologies (Fiksel1996); the unavailability or poor quality of data to perform the analysis (Lave et al. 1995);and itsexpensiveness(intermsofmoneyandtime)arisingfromtheneedtosource input data and environmental burdens that have to be either empirically gatheredorobtainedfromliterature(Hendriksonetal.1998). 4.3.3 ReferenceEnergy–materialSystemAnalysis The REMS is similar to the Reference Energy System (RES); RES is a method to representvariouselementsofanenergysystemfromprimaryenergyextractiontoend uses.Togetherwiththeflowofenergythroughvariousstages(forexample,extraction, conversion, transport, end use), REMS also includes the flow of materials from their extraction to product development to end use. The energy and material system represented in REMS can be analysed with the help of mathematical programming techniques. 83 Hoffman (1980) was the first to adopt the REMS approach and use a mathematical programming model to minimise material system cost for a hypothetical packaging sector. Although this method was developed in 1980, it received greater attention in themid1990sonly,withthedevelopmentoftwomodels–Modelfordescriptionand optimisation of Integrated Material flows and Energy Systems (MIMES) and MATerials Technologies for greenhousegas Emission Reduction (MATTER). MIMES, developed by Sundberg and Wene (1994), is a static nonlinear programming optimisation model used to estimate the optimal condition for the linked energy and material systems. The purpose of developing this model was to examine materials reduction strategy and waste management planning at the individual industry level. MATTER is a linear optimisation model of the energy–materials system for the WesternEuropeaneconomy(Gielen,Bos&Gerlagh1998).Thismodelistheextension of a traditional energy system analysis model – MARKAL (MARKet ALlocation). It considersmaterialflowsalongwithenergyflowsintheeconomy.Inaddition,another energy system optimisation model – MESSAGE (Model for Energy Supply Strategy AlternativesandtheirGeneralEnvironmentalimpacts)–isalsocapableofintegrating material flows. However, no attempt has been made to date in order to represent materialflowswiththeexistingenergyflow(Strubegger2003). Unlike the optimisation models mentioned above, the Australian Stocks and Flows Framework (ASFF) is a highly disaggregated simulation framework which can keep trackofallphysicalstocksandflows(suchasland,livestock,people,buildings,etc.)in the economy (Gault et al. 1987). This framework contains a simulation model and a database,withmodulesorcalculatorsrepresentingphysicalprocessesintheeconomy. Foran and Poldy (2002) applied this model to analyse the impact of longterm migrationpolicyontheAustralianeconomyandtheenvironmentalsystem.Although comprehensiveinitsrepresentationoftheeconomy,thismodel,however,ignoresthe influence of prices and, hence, does not provide signals for interfuel substitution to achievedesirableenvironmentaloutcomes. AlthoughtherearemanymodelsavailableforanalysingmaterialsflowinREMS,only MARKALMATTER is being used widely. Gielen (1995; 1999a; 1999b), Gielen and 84 Kram (1998), OECD (2001) and Nemry et al. (2001) used this model for analysing emissions reduction potential from energy and material system improvements. All these studies concluded that the inclusion of the material system (along with the energy system) would provide greater opportunities in GHG reduction with lower cost, compared with improvements from the energy system alone (see Table 41). Further,MARKALMATTERhasbeenusedmainlyforanalysingemissionsreduction potential from production processes in manufacturing industries (for example, iron and steel, paper mill, packaging, etc.). Also, due to its huge data requirements, only material chains with a significant potential to reduce GHG emissions are included in theREMS(thatis,itincludesonlyGHGintensivematerialssuchasironandsteel). The REMS approach is technologically detailed, representing all of the energy– materials relevant processes in each sector of the economy. The energy and material flowsbetweenindustriesarerepresentedintermsofinputsandoutputsspecifiedfor eachtechnology.Thismeansthateachtechnologyhasacorrespondingsetofdatathat details the incoming materials and outgoing products or materials. Because it incorporates a high resolution of material flows, it is often more suitable for the analysisofaparticularprocessorindustryratherthanpolicyanalysisforthenational economy. 4.3.4 PhysicalFlowMethods:ASummaryofObservations Areviewofthestudiesusingphysicalflowmethods(asdiscussedinSections4.3.1to 4.3.3)showsthateach methodhasitsownstrengthsandweaknesses.Theirstrengths or weaknesses are summarised in Table 42, in accordance with the methodological criteriaoutlinedinSection4.2. 85 Table42 PhysicalFlowMethods:KeyFeatures Methods MaterialFlowanalysis Features Goal Identifykeymaterials flowsandpotentialfor materialsubstitution Lifecycleanalysis Evaluatelifecycle environmentalimpacts ofaproduct ReferenceMaterial Systemanalysis Examineleastcost strategyforemission reduction 1product (x) 1product (x) Sectorspecific (x) Short (x) Short/Medium (x) Long (9) Dynamics No (x) No (x) Yes (9) Priceconsideration No (x) No (x) Yes (9) High (x) High (x) High (x) Spatialscope Temporalscope Datarequirement Notes: SymbolsinparenthesesrepresentthecompatibilitywithcriteriaoutlinedinSection4.2. ‘9’denotescompatiblewhile‘x’denotesincompatible. FromTable42,itisnoticedthat: Noneofthephysicalflowmethodsfullysatisfiestherequirementsoutlinedearlierin Section 4.2. Hence, they are not suitable for the analysis in this research. Some reasoninginsupportofthisobservationisprovidedbelow. In terms of a spatial scope, this research requires analysis for disaggregated sectors forthewhole economy. The physicalflowmethodsfocus on anarrow rangeofmaterialflows.MFAandLCAfocusontheflowofoneproduct,while REMSfocusesonmaterialsflowinanyspecificsector. Intermsoftemporalscope,thisresearchrequirestheanalysisforalongtime frame.Ofallthephysicalflowmethods,REMSistheonlymethodthatcanbe usedforthispurpose. In the physical flow approach, REMS is the only method that can capture economic dynamics. It is capable of capturing both changes in technology as wellasallowingforadjustmentofcapitalinvestmentendogenouslywithinthe model. For this research, price consideration is an important aspect that needs to be captured within the framework. MFA and LCA do not provide an economic rationalising behaviour (that is, they can not be use to analyse the price 86 responsiveness of an economic agent). REMS is a suitable method for this purpose. Lastly,datarequirementsposeamajorproblemforthephysicalflowmethods. All three methods discussed above require a high level of data for materials flows.Inmanycasesthesedataaredifficulttoobtain. 4.4 EmbodiedEnergyMethods AsdiscussedinSection4.1,embodiedenergymethodscanbeusedasanalternativeto physical flow methods for developing a materialsbalance framework. A number of studieshavebeenconductedusingembodiedenergymethods.Thesemethodscanbe classifiedintermsofthosethatemployprocessanalysisandthosethatemployinput– output analysis. Table 43 provides a summary of studies employing these methods. Detailsarediscussedinthefollowingsubsections. 4.4.1 ProcessAnalysis Process analysis is the traditional tool of an industrial engineer. It begins with the examination of a process employed to produce a particular product. It then lists all energyandnonenergyinputsrequiredtoproducethisproduct.Theenergyandnon energy inputs are further examined to determine the energy and nonenergy inputs requiredfortheirproduction.Thisprocesscontinues,tracingallenergyconsumptions totheirorigins. UK Netherlands Australia Proopsetal.(1996) Konijnetal.(1997) Lenzen(1998) 45sectors Metalindustry 1993 1990 1989 1968&88 UK/Germany Sectoral Proopsetal.(1993) Electricity 1974&80 Sectoral Australia Shariful&Morison(1992) 1987 Sectoral Common&Salma(1992) 1972 Sectoral New Zealand Australia Carter,Peet&Baines(1981) 1973 Scotland AlAli(1979) 42sectors UK Wright(1975) Examinenetenergyuseofrenewable electricity Examinelifecycleemissions Examinedirect&indirectenergy consumption Examineenergycostsofmaterials Examineappropriatenessofmaterial flowsusinginput–outputanalysis Examineenergyuseinfinal consumption&investment Examineenergyuseinfinal consumption&investment Examineenergyuseinfinal consumption Analysechangesindirectindirect energy AnalysefuturescenariosforCO2 reduction Examinelifecycleemissions Examineenergyuseinfinal consumption Investigatestructureofenergydemand Examinetotalenergyinfinal consumption Examineenergyrequiredinproducts Input–OutputAnalysis 1963&68 USA Bullard&Herendeen(1975) 1986 9commodities USA Wright(1974) Electricity n.s. 1967 USA SanMartin(1989) Electricity 357sectors Japan RRI(1983) Focus ProcessAnalysis 1963 UK Chapman(1975) Study period Energy 1968&72 industry Manufacturing 1968 Sector Scope Input–outputissuitableforcalculatingtotal materialorenergyintensities Mostenergyassociatedwithindirectuse Emissions:coal>gas>wind>solar>nuclear Outoftotalincreaseinenergyconsumption, 31%areassociatedwithindirectenergy DomesticCO2responsibility<CO2emission Mostenergyassociatedwithindirectuse Mostenergyassociatedwithindirectuse Demandforindirectenergy>direct Mostenergyassociatedwithindirectuse Productscontainedmoreofindirectenergy Mostenergyassociatedwithindirectuse Materialrecycling&useofrenewable energywouldreduceenergyconsumption Energy&materialconservationinproduct designwouldreduceitsenergycosts Totalenergyuse:hydro>geothermal>wind> tidal>wave Providedlifecycleemissions KeyFindings Modellingstudiesadoptingembodiedenergymethod 363sectors UK Country Chapmanetal.(1974) Author(Year*) Table43 87 USA USA n.s. Japan Australia USA Canada Australia Australia Kuwait Denmark Herendeen&Plant(1981) Uchiyama(1992) Nishimuraetal.(1996) Treloaretal.(2001) Berndt&Wood(1975) Fuss(1977) Turnovskyetal.(1982) Truong(1985) Burney&AlMatrouk(1996) Weir(2000) Country Bullardetal.(1978) Author(Year*) n.s. 1976 1967 1966–1990 1965–1990 Manufacturing 1969–1981 Manufacturing 1947–1975 Manufacturing 1961–1971 Electricity& Water Construction Analysetotalenergyrequirement Embodiedenergyinproduct Develophybridprocess+Inputoutput model Examinenetenergyuseofgeothermal electricity Examinelifecycleemissions Examinesubstitutionpossibility betweenfactorinputs Econometricestimatesofsubstitution betweenplastic,cement&steel Examinesubstitutionpossibility betweenfactorinputs Examinesubstitutionpossibility betweenfactorinputs Examinesubstitutionpossibility betweenfactorinputs Examinesubstitutionpossibility betweenfactorinputs ProductionFunctionStudies 1993 Manufacturing 1947–1971 Residential building Focus HybridProcess&Input–OutputAnalysis Study period Manufacturing 1985 Electricity Electricity Economy Sector Scope Notes: n.a.=Notapplicable,n.s.=Notspecified. * Yearofpublications. Materialwithcapital,labour&energy: strongsubstitution Materialwithcapital:strongsubstitution Materialwithlabour:weaksubstitution Materialwithenergy:complements Materialwithcapital,labour&energy: strongsubstitution Materialwithcapital:strongsubstitution Materialwithlabour&energy:weak substitution Strongownprice&weaksubstitution potentialwithcapital&energy Existenceofsubstitutionpossibilitybetween allmaterial;higherbetweencement&steel Emissions:coal>oil>gas>wave>tide> wind>geothermal>hydro Existenceofsubstitutabilitybetween materialusedinconsumergoods Hybridapproachisbetterthanindividual (ProcessorIO)approach Combinedmodelcanincreaseaccuracyof embodiedenergyanalysis Energyoutput/inputratiogreaterthanunity KeyFindings 88 89 Severalauthorshaveanalysedtherequirementsfornaturalresources,particularlythe energy needed for the production of various commodities, using this approach. For example, Chapman et al. (1974) analysed direct and indirect energy consumption by theenergysupplysector.Chapman(1975)analysedtotalenergycosts(includingdirect andindirectcostsformanufacturingindustries.Bothstudiesconcludedthatmaterials recyclingandincreasingrenewableenergysourceswouldreduceenergyconsumption andhenceitscosts.RRI(1983)andSanMartin(1989)adoptedthismethodtoexamine lifecycleenergyuseandCO2emissionsforvariouselectricitygenerationtechnologies. These studies show that renewable electricity generation also contributes to a significantamountofemissions.IAEA(1994)providesacomprehensivelistofstudies that have employed process analysis for determining net energy consumption for differentelectricitygenerationtechnologies. Processanalysis,likeMFAandLCA,isaverydetailedmethodforincludingmaterial flows. It tracks down all inputs that are required to produce a targeted product. Becauseofthelevelofdetailrequired,manyinputsareoftenexcludedfromtheflows. Someattemptshavebeenmadetoimprovetheaccuracyandcompletenessofprocess analysis(Bullard,Penner&Pilati1978).Severalstudieshaveadoptedacombinationof processanalysisandinput–outputanalysis(input–outputanalysisisdiscussedinthe nextsubsection)toanalyseanyparticularproductorprocess,forexample,Herendeen andPlant(1981),Uchiyama(1992),Nishimuraetal.(1996),andTreloaretal.(2001).All thesestudiesadoptedacombinationofbothmethodstoexaminetotalenergyuseand its associated emissions. They concluded that hybrid methods could provide a comprehensive representation of the materials chain and more accurately determine the total energy requirements and associated emissions associated with a particular process. 90 ProcessanalysishasalsobeenappliedinAustralia,intheformoftheOzECCOmodel. This model is an Australian adaptation of the ECCO31 model developed by the ResourceUseInstituteinEdinburg.Themodelintegratesthestructureofthenational economy and its energy accounts. The capital stocks are expressed in equivalent petajoulesofembodiedenergyratherthaninmonetaryterms(CSIRO1998).Activities withintheeconomyareexpressedasenergyflows(inpetajoulesperyear).Inthisway, alleconomicactivityisconvertedtophysicalactivity,expressedinenergyunits,which is consistent with the first and second laws of thermodynamics. All economic transactions are represented by their corresponding physical transformations. Foran andCrane(2000)usedthismodeltoinvestigatetheuseofbiofuelsintheAustralian energysector,particularlytheuseofethanolandmethanolintransportandtheuseof biomass in the electricity sector. The investigation focused on determining forest plantation areas and wood requirements to meet certain level of future biofuels demand for these sectors. The analysis found that in order to meet energy demand overthenext50years,croplandsof17–31millionhectareswouldberequired. The foregoing discussion shows that process analysis potentially can produce very accurate, reliable and specific results. However, it suffers from the following shortcomings: Since process analysis involves tracing the energy content of all energy and nonenergy inputs into production processes, the data required for such analysisareveryextensive.Thisdatainmanycasesmaybedifficulttoobtain. Theapplicationofthismethod,likeLCA,suffersfromtheissueoftheselection of appropriate boundaries for analysis. It invariably leads to the exclusion of several small inputs. It is very difficult to determine all of the upstream ECCO(originally:EvaluationofCarryingCapacityOptions;morerecently:Enhancementof CapitalCreationOptions)isanembodiedenergymodelfocusingonidentifyingfeasiblerates of change of economies under specified technological assumptions and resource and environmentalconstraints(Slesser1992). 31 91 processes required indirectly by a process, let alone to quantify their direct energyrequirements(Laveetal.1995). 4.4.2 Input–outputAnalysis Input–output analysis can also be used for carrying out embodied energy analysis. ThismethodwasfirstdevelopedbyWassilyLeontiefin1936asatooltorepresentthe structureofaneconomybyexplicitlyrepresentingtheinterdependenciesofeconomic sectorsandindustries(Duchin1998).Theinterindustryflowsofcommoditiesandraw materials are central to this technique. The input–output method traces the flow of commoditiesandrawmaterialsacrossvarioussectorsintheeconomy.Thisframework can be adapted to analyse embodied energy flows by converting the economic relationshipintoestimatesofassociateddirectandindirectenergyintensities(Bullard &Herendeen1975).Thisapplicationallowsforthecalculationofembodiedenergyfor anysectorintheeconomy. Input–outputanalysishasbeenappliedbymanyresearchersforempiricalanalysisof embodied energy. For example, Wright (1974; 1975), Bullard and Herendeen (1975), Proops (1977), AlAli (1979), Carter, Peet andBaines (1981) and Shariful Islam and Morison (1992) employed this method to examine direct and indirect energy requirements for various economic sectors. Many of these studies found that most of the energy flows are associated with indirect use, to produce goods and services requiredintheeconomy.Further,CommonandSalma(1992),GayandProops(1993), Proops et al. (1996) and Lenzen (1998) employed this method to examine direct and indirect emissions associated with energy use. While many of the above studies focused on the flows of direct–indirect energy to meet enduse demands for final consumption, only Carter, Peet and Baines (1981), Proops et al. (1996) and Lenzen (1998) have focused on these flows to also meet the demand required for capital investment. The input–output method has not only been used to account for direct– indirectenergyrequirementsandassociatedemissions,Proops,FaberandWagenhals (1993)andCruz(2002)appliedthismethodforfuturescenarioanalysistoreduceCO2 emissions. Some of the scenarios focused on analysing technological improvements 92 through changes in energy and material inputs. However, owing to the fact that the input–output method is characterised by fixed coefficients, both studies above have arbitrarilyadjustedinputcoefficientstoreflectthechangesininputstructure,without anyeconomicrationality. The underlying production function of the traditional input–output method is characterised by Leontief’s production function. This type of production function assumes “zero” elasticity of substitution, which does not allow one input to be substituted with another input. Due to this limitation, some question the appropriatenessofinput–outputmethodforanalysingtheimpactofcarbontaxonthe entireeconomy(whichisafocusofthisresearch)andinsteadsupporttheapplication of ageneralequilibriumframeworkfor this purpose.But onecanalsoarguethatthe general equilibrium framework is after all basically supported by input–output representation of the economy! As noted by Dixon et al. (1992, p. 19) that, “The prototype for modern applied general equilibrium models is Leontief’s input–output model”. Moreover, input–output coefficients can be endogenously determined rather than exogenouslygivenasfixedparameters(thatis,changesfromLeontief’stoothertypeof productionfunction).Suchmodificationshouldenabletheinput–outputframeworkto incorporateeconomicrationalityintermsofsubstitutioninresponsetopricechanges, as is the case in a general equilibrium framework. This issue will be discussed in greaterdetailinChapter5. To date, there exists no study that uses the input–output method, employing alternativeproductionfunctionspecifications,forembodiedenergyanalysis.However, some studies have adopted other types of production functions in incorporating the materialsbalance approach in another context. For example, Gross and Veendorp (1990) adopted the CobbDouglas production function that satisfies the materials balancetoshowthatsuchafunctionsetsalimittogrowthforthecaseofaneconomy thatobtainsitsmaterialinputsfromnonrenewableresources.Weir(2000)studiedthe useofplastic,cementandsteelintheDanishconstructionindustry,byemployingan econometric model to evaluate the substitution possibilities between different materials, in response to changes in material prices. Own and crossprice elasticities 93 wereusedtorepresent thepotentialforsubstitutionbetweendifferentmaterials.The study shows that there are substantial substitution possibilities in the construction sector, particularly between the use of concrete and metal. Other studies have used alternative production functions to estimate elasticities of substitution between aggregatevariables–material,energy,capitalandlabour(forexample,ErnstR.Berndt & Wood 1975; Burney & AlMatrouk 1996; Fuss 1977; Hudson & Jorgenson 1974; Truong 1985; and Turnovsky, Folie & Ulph 1982). These studies employed Translog typeofproductionfunctiontoestimatesubstitutionpossibilities.Itwasfoundthat,at an aggregate level, material inputs can be substituted with almost all other factor inputs. These results implied that assumed “zero” substitution possibilities for input coefficients in input–output analysis are inappropriate and other flexible types of productionfunctionsshouldbeemployed. An advantage of adopting approaches based on input–output analysis is that they could make use of readily available input–output tables; statistical offices in most countries periodically produce such tables. Although such tables may not contain information at the level of individual companies or processes (IAEA 1994), they can provide sufficient detail at disaggregate levels which could be adapted to the further level of detail required for analysis. The inclusion of embodied energy flows at such disaggregated levels ensures that all emissions are accounted for in the economy. Further, the input–output method is flexible in the sense that it allows longerterm analysis, by replacing Leontief’s type with other forms of production function. The replacementofproductionfunctiondoesnotcaptureonlychangesinthebehaviourof the agents in response to changes in prices; it can also capture changes in the input structures of technologies used for production. Also, the input–output model is capable of adjusting capitalrequirement withinthe model, whichmakes this method appropriate for longterm analysis (further discussion on these issues is provided in Section5.5.2). 94 4.4.3 EmbodiedEnergyMethods:ASummaryofObservations Thereviewofstudiesusingembodiedenergymethods(asdiscussedinSections4.4.1 and4.4.2)showsthatbothmethods–processandinput–output–havetheirstrengths and weaknesses. Their strengths or weaknesses are summarised in Table 44, in accordancewithcertaincriteriaoutlinedinSection4.2. Table44 Methods Features Goal Spatialscope Temporalscope EmbodiedEnergyMethods:KeyFeatures Processanalysis Identifylifecycle environmentalimpacts ofaproductorprocess Leontief’sInput–output analysis FlexibleInput–output analysisa Examineeconomywide Examineeconomywide impactofenergy impactofenergy environmentalpolicy environmentalpolicy 1product (x) Sectoral (9) Sectoral (9) Short (x) Short/Medium (x) Long (9) b (x) Yes (9) Dynamics No (x) Priceconsideration No (x) No (x) Yes (9) High (x) Low/Medium (9) Low/Medium (9) Datarequirement Partly Notes: SymbolsinparenthesesrepresentthecompatibilitywithcriteriaoutlinedinSection4.2. ‘9’denotescompatiblewhile‘x’denotesincompatible. a Theterm‘flexible’referstotheuseofothertypeofproductionfunction. b This‘partlydynamism’characteristicofLeontief’sinput–outputanalysisreflectonly treatmentofcapitalinvestmentandnottechnologicalchangeasapartofthemodel. FromTable44,itisnoticedthat: Amongsttheembodiedenergymethods,theinput–outputmethod,withmoreflexible type of production function, satisfies all the criteria outlined earlier in Section 4.2. Somepointsinsupportofthisselectionarenotedbelow. In terms of a spatial scope, this research requires analysis at disaggregated levelsoftheeconomy.Input–outputisanappropriatemethodforthispurpose. Although most of the published input–output tables do not provide much detail, the user can further disaggregate it to the level of detail required for analysis. Intermsofatemporalscope,thisresearchrequirestheanalysisforalongtime frame. A “flexible” input–output is the only method that is suitable for this purpose. A “traditional” input–output has limitations for longterm analysis 95 due to its assumption of fixed input–output coefficients. Replacing “flexible” forms of the production function with the “Leontief’s” production function wouldallowtheanalysistobeperformedoverthelongterm. A “flexible” input–output method can satisfactorily capture economic dynamics. It is capable of capturing changes in technology (in terms of a flexibleproductionfunction)andallowingforadjustmentofcapitalinvestment endogenously. Forthisresearch,particularlyinthecontextofanalysingtheimpactsofcarbon tax,priceconsiderationisanimportantaspectthatneedstobecapturedwithin theframework.A“flexible”input–outputsatisfiesthiscriterion.Thisisbecause thereplacementofLeontiefwithotherformsofproductionfunctionsallowsthe economicagentstomaketheirdecisionsbasedonchangesinprices. Finally, regarding data requirements, input–output has an advantage over othermethods.Allinformationrequiredfortheanalysiscanbeobtainedfrom thenationalstatisticaloffices. Therefore,theinput–outputmethod,withamoreflexibletypeofproductionfunction, isselectedasaframeworkusefortheanalysisinthisresearch. 4.5 SummaryandConclusions Thischapterhasreviewedvariousmethodologiesthathavebeenemployedtodevelop the materialsbalance framework. The purpose of this review was to analyse their strengthsandweaknessesandtousetheseinsightstoselectanappropriatemethodfor thisresearch.Themainfindingsofthischapterinclude: x The methodologies that can be used for developing materialsbalance frameworkcanbeclassifiedintotwo–physicalflowandembodiedenergy.The physical flow method represents the flow of energy and materials in their original units. The embodied energy method represents energy flows in the 96 same way as the physical flow method, but represents materials flows as the flowsofindirectenergy. x The physical flow approach can be classified into three categories – Material Flow Analysis (MFA), Lifecycle Analysis (LCA), and Reference Energy– materialSystemanalysis(REMS). - MFA is not a suitable method for this research. The spatial and temporal scopeofthismethodislimited,thatis,itfocusesontheflowofoneproduct over a short period of time. This method does not allow for technological changes and does not allow for capital adjustment in response to price changes (that is, for example, induced by the introduction of carbon tax). Also,datarequirementsforthismethodarehigh. - LCA is very similar to MFA and, therefore, not suitable for this research. Although the timeperiod considered in LCA is longer than in the MFA, it focusesontheflowofoneproductoveritsentirelife.Thismethodalsodoes not capture technological changes, neither does it allow for any capital adjustments.Thedatarequirementsforthismethodaswellarehigh. - Ofthephysicalflowmethods,REMSisthemostappropriatemethodforthis research. It can capture priceinduced effects, allows for autonomous technological change, and has a mechanism for capital adjustments and, therefore, is appropriate for longterm analysis. It, however, suffers from intense data requirements, which limits its use for an economywide analysis. x Theembodiedenergyapproachcanbeclassifiedintotwo:processanalysisand input–outputanalysis. - Processanalysisisnotasuitablemethodforthisresearch.Thesectoralscope of this method is limited, that is, it focuses on the flow of various types of energy and materials to produce one product. This method does not allow for technological changes and for capital adjustment. Also, data requirementsforthismethodarehigh. 97 - The traditional Leontief’s input–output method is appropriate for the analysisofdisaggregatedeconomicsectors,bymakinguseofinput–output tableswhicharepubliclyavailable.The“dynamic”versionofinput–output method also allows for capital adjustments in response to price changes induced by carbon tax. However, in order to capture other aspects of economic reality (for example, producer/consumer behaviour in relation to prices),theunderlyingLeontiefproductionfunctionmustbereplacedwith other flexible forms of production functions. Such replacement of production functions could allow input–output analysis to be used for analysingtheimpactsofapricedrivenpolicylikecarbontax. x Based on the review in this chapter, the input–output method with a flexible form of production function is selected as the methodological framework for thisresearch.Furtherdetailsofthismethodologicalframeworkareprovidedin thenextchapter. 98 CHAPTER5 5 METHODOLOGICALFRAMEWORKFORTHISRESEARCH In Chapter 4, various methodologies for developing a materialsbalance framework werereviewed.Basedonthisreview,itwasconcludedthattheinput–outputmethod, withamodifiedproductionfunction,wouldbethemethodforthisresearch–inorder toanalysetheeconomywideimpactsofacarbontax.Thismethodhasthepotentialto consider the indirect energy embodied in materials; perform the analysis at disaggregatedsectorallevels;analysethepriceimpactsofcarbontax;andprovidean analysisoveralongtimeframe.Moreover,itisrelativelylessburdensomeintermsof datarequirements. The objective of this chapter is therefore to provide details of this methodological framework. This chapter is divided into eight sections. Section 5.1 briefly introduces the overall methodological framework employed in this research. This framework comprises five modules, namely, emission allocation, tax imposition, price impact, input substitution, and economywide impacts. Sections 5.2 to 5.6 provide details of eachofthesefivemodules.Section5.7providesadescriptionofdatasourcesanddata preparationforthismethod.Finally,Section5.8summarisesthemainfindingsofthis chapter. 5.1 OverallMethodologicalFramework This section presents an overview of the proposed methodological framework for analysing the impacts of carbon tax in this research. This framework is developed based on the input–output model with a flexible form of production function, as suggestedinChapter4. Theframeworkcomprisesfiveinterlinkedfunctionalmodules(Figure51). 99 Figure51 Schematicdiagramoftheoverallmethodologicalframework A brief description of these modules, particularly the linkages of each module, is providedbelow(detailsareprovidedinSections5.2to5.6). Thefirstmoduleformsthecoreoftheanalysisinthisresearch.ItallocatesCO2 emissions to responsible sectors of the economy, based on both the Polluter Pays Principle (PPP), using an energybalance approach; and Shared Responsibility Principle (SRP), using an energy–materials balance approach (see Section 3.3 for a discussion on these principles). CO2 emissions are calculated from input–output tables for the base year (2004). CO2 emission intensities32arealsoestimatedbasedontheseemissions.Adetaileddiscussion andmathematicaldescriptionforthisstageispresentedinSection5.2. ThesecondmoduleassignsacarbontaxforvariousCO2emittingsectorsofthe economy, as identified in the previous module. For the PPP, carbon tax is applied on the basis of direct emission intensity, and, for SRP, carbon tax is appliedonthebasisoftotal(thatis,directandindirect)emissionintensity.The outcomeofthisstageisthespecificationofcarbontaxratesforPPPandSRPfor the base year. The mathematical specification for determining the appropriate levelofcarbontaxisprovidedinSection5.3. In the third module, the relative changes in energy and material prices in responsetothecarbontaxareestimated.Theoutcomeofthisstageisthenew CO2emissionintensityofeachsectorreferstotheamountofCO2emittedperdollarvalueof thatsectoroutput. 32 100 price levels (for 2005) obtained as a consequence of the introduction of the carbon tax. These sectoral price effects of carbon tax are estimated using the input–outputpricemodel.Themathematicalspecificationsofthepriceimpact modulearedetailedinSection5.4. Next, the substitution effect in response to changes in energy and material prices is analysed. The own and crossprice elasticities are employed for this purpose. These elasticities are estimated by assuming Translog and Cobb Douglas production functions to examine the relationship between factor inputs, such as fossil energy, electricity, nonenergy materials, capital, and labour. These elasticities are then used to modify the baseyear input–output technical coefficients in order to give a new economic structure. The mathematicalspecificationsofthesubstitutionmoduletogetherwithestimated parametersareprovidedinSection5.5. In the final module, the economywide impacts of carbon tax are analysed. These impacts include energy, environmental, economic, and social. The new economic structure (output of the previous module) would lead to different patterns of energy consumption and associated emissions. These impacts are analysed using an energyenvironmentoriented input–output model. The mathematical specifications of this module are presented in Section 5.6. The results from this module, that is, the economywide impacts due to the introductionofcarbontax,arepresentedanddiscussedinChapter6. 5.2 AllocationofCarbondioxideEmissions As mentioned in Section 5.1, this section provides a detailed discussion on the methodologyusedtocalculateCO2emissionsfromvarioussectorsoftheeconomyand to develop estimates of associated CO2 intensities, employing both Polluterpays and SharedResponsibilityPrinciples. 101 5.2.1 EmissionsAllocation:PolluterPaysPrinciple The allocation of CO2 emissions based on PPP is straightforward. As introduced in Section3.3.2,CO2emissionsarebasedonthequantitiesandtypesoffossilfuelsused directly at the point of combustion. Accordingly, CO2 intensities can be measured by theamountofCO2emittedperunitofoutput. Tobeginwith,letFfibethefossilfueloftypefconsumedbyproductionsectori.Also, the total output (Xi) of production sector i goes to satisfy intermediate and final demands(discussedinSectionB.1.2,AppendixB,p.217).Therefore,energyintensity ofsectori–denotedbycfi–canbeexpressedas: c fi Ffi Xi (51) Thisexpressioncanbewritteninamatrixnotationas: C F X 1 (52) where C: matrixofenergyintensities(PJper$); F: matrixoftotalfossilfueluse(PJ);and X: vectoroftotaloutput($). Equation52estimatesenergyintensitybasedonPPP,or“directenergyintensity”. CO2 emissions from a particular activity can be determined by multiplying energy consumptionbythatactivitywithfuelemissionfactors(thatis,E=eF),thatis, EPPP eCX where EPPP: vectorofCO2emissionsfromeachsectorbasedonPPP(Mt);and e: vectoroffixedCO2emissionfactorforeachtypeoffuel(MtperPJ). (53) 102 Similar to energy intensities, CO2 intensities (W) can be derived by dividing CO2 emissionsbysectoraloutputsX.Therefore,CO2intensitybasedondirectenergyinputs (WPPP)canbewrittenas: WPPP eC (54) Equations 53 and 54 are used to determine CO2 emissions and CO2 intensities, respectively,basedonPPP. 5.2.2 EmissionsAllocation:SharedResponsibilityPrinciple TheallocationofCO2emissionsbasedonSRPiscomparativelymorecomplicated.As introduced in Section 3.3.3, CO2 emissions, according to this principle, also take into accounttheindirectenergyusedbyasector,thatis,theenergyembodiedinthesupply of other materials and services. The framework adopted in this research for such allocation is based on the input–output model. The fundamental description of the input–outputmodelisprovidedinSectionB.1,AppendixB,p.216. The detailed manner in which the input–output model can be used for examining economic activities opens the way for studies that deal not only with industrial production,butincreasinglywithotheraspectsofhumanactivitiesaswell(Duchin& Steenge1999).Input–outputtablesprovideausefulframeworkfortracingenergyuse and environmental pollution for economic activities, through the extension of the Leontief input–output model (Miller & Blair 1985). Energy and environmental dimensions can be incorporated into the standard model in order to determine embodiedenergyandassociatedemissionsfromanysector. Energy and associated emission intensities can be calculated either by using the “hybridunit” approach or the “energycoefficient” approach. In the hybridunit approach, energy flows, which are expressed in the input–output table in monetary units,aresimplyreplacedbyflowsexpressedinphysicalunits(Bullard&Herendeen 1975). In order to relate monetary value in the input–output table to the physical quantityofenergy,priceassumptionsarerequired(Miller&Blair1985).TheLeontief’s inverseisthencalculatedfromthisupdatedinput–outputtable,wherebyenergyflows 103 areexpressedinphysicalunitsandnonenergyflowsareexpressedinmonetaryunits. However, Dietzenbacher and Stage (2006) have shown that this approach can sometimeproducearbitraryresults. Theenergycoefficientapproach,ontheotherhand,requiresasatelliteenergyaccount, corresponding with the sector outlined in the input–output table (Proops, Faber & Wagenhals 1993). This satellite energy account (called the energy dissipation table) allows the calculation of energy consumed in the economy through the intersectoral relationshipswithintheeconomy,withoutmakinganyadjustmenttotheinput–output table, thus avoiding the need for arbitrary price assumptions. Therefore, the energy coefficient approach is the preferred method in this research to determine CO2 emissionsandintensities. The mathematical specification of the energy coefficient approach is discussed as follows.Fromequation 52,theenergyrequirementforthe productionsectorscanbe representedas: F CX (55) Now, by substituting the identity of total output X ª I A B º Y (see Section ¬ ¼ 1 B.1.5, Appendix B, p. 223, for the derivation of this identity) into equation 55, the sectoralenergyrequirementcanbewrittenas: F C ª¬ I A B º¼ Y 1 (56) where A: matrixofinput–outputtechnicalcoefficients; B : matrixofweightedmeancapitalcoefficients;and Y*: vectoroffinaldemands(excludingdemandforcapitalinvestment). 1 Theterm C ª¬ I A B º¼ inequation56representssectoralenergyintensitiesbased onSRP.Thetotalenergyconsumptionpresentedinequation56canbedisaggregated intoenergyuseddirectlytoproduceasector’soutputandtheinfiniteseriesofindirect 104 energyembodiedintheuseofmaterials(seeequationsB7toB9,AppendixB,p.221, fortheprocedureofthisdecomposition). F CY C A B Y C A B Y ! C A B Y 2 f (57) Inequation57,CY*–theentityontherighthandsideoftheequationrepresentsdirect energy consumption, whereas the rest of the entities represent an infinite series of indirect energy consumption. In fact, all these indirect energy consumptions are derived from energy consumed for the production of materials at each downstream level,asshowninFigure52. Figure52 * [CY ] Representationofdirectandindirectenergyconsumption 1 * [C( B) Y ] Stage 1 Stage0 Note: 2 * [C( B) Y ] Stage 2 f * [C( B) Y ] Stage f AdaptedfromBousteadandHancock(1979),citedinTreloar(1998). Asmentionedabove,CO2emissionsassociatedwiththecombustionoffossilfuelscan beobtainedbymultiplying energyconsumptionby associated fuels’ emissionfactors (thatis,E=eF).Therefore,usingenergyconsumptionfromequation56,CO2emissions basedonSRPcanbewrittenas: ESRP e C ª¬ I A B º¼ Y 1 (58) Similar to direct–indirect energy consumption, equation 58 can be decomposed into directCO2emissionsandaninfiniteseriesofindirectCO2emissionsas: E eCY eC ( A B )Y eC ( A B ) 2 Y ! eC ( A B )f Y (59) In equation 59, ‘eCY*’ – the entity on the righthand side of the equation represents directCO2emissions,whereastherestoftheentitiesrepresentindirectCO2emissions. 105 1 Also, the term eC ª¬ I A B º¼ in equation 58 represents sectoral CO2 intensities thattakeintoaccountbothdirectenergyandenergyembodiedintheuseofmaterials. Therefore,CO2intensitiesbasedonSRP(WSRP)canbewrittenas: e C ª¬ I A B º¼ 1 WSRP (510) Equations58and510areusedinthisresearchtodetermineCO2emissionsandCO2 intensities,basedonSRP. 5.3 DeterminationofCarbonTax Carbontax,eitherbasedonPPPorSRP,isappliedinthisresearchonthesamebasis, namely,inproportiontosectoralCO2intensities(estimatedinthepreviousstep). Fordeterminingthelevelofcarbontax,thisresearchhasadoptedaproceduresimilar totheoneemployedbySymonsetal.(1994),CornwellandCreedy(1995;1996;1997), andCreedyandMartin(2000).Accordingly,itisassumedthatthecarbontaxisfully transferredthroughenergyandmaterialprices.33Asaresult,carbontaxincreasesthe priceoffactorinputsinproportiontotheirCO2emissions.Thesepricechangescanbe regarded as being equivalent to indirect taxes (Cornwell & Creedy 1995). The ad valorem tax rates (t), which is a percentage of the taxexclusive value of energy and materialsgoods,canbedeterminedfrom: tn tn P WPPP P WSRP o o (511) (512) where tn: advaloremtaxrateforindustryiinthecurrentyear; The assumption of full shifting requires competitive market and constant returns to scale. However,itisthestandardassumptionusedinpartialequilibriumanalysesofindirecttaxes (Creedy1997). 33 106 leveloftaxonCO2emissions(measuredindollarspertonneofCO2)34; : WPPPo : CO2intensitybasedonPPPinthepreviousyear,ascalculatedfromEquation5 4(measuredintonnesofCO2perdollarofsectoralproduction); WSRPo : CO2intensitybasedonSRPinthepreviousyear,ascalculatedfromEquation5 10(measuredintonnesofCO2perdollarofsectoralproduction). Thetermtncanbeconsideredasequivalenttoasetofindirecttaxesimposedoneach sectori,whichwillbeused(inpriceimpactmodule)todeterminetheimpactofcarbon taxonincreasesinenergyandmaterialprices. 5.4 AssessmentofPriceImpactofCarbonTax In this module, the increase in energy and material prices, as a result of the introductionofcarbontax,isestimated.Theintroductionofcarbontaxwouldhavea similar impact to other indirect taxes, that is, it would increase the sectoral value addedcosts.Thissectoralpriceeffectofcarbontaxisestimatedusingtheinput–output price model (see Section B.1.4, Appendix B, p. 221, for theoretical discussion of the input–outputpricemodel). Becausecarbontaxwouldincreasetheenergyandmaterialpricesthroughincreasesin sectoralvalueaddedcosts,thechangeinthesepricescanbedeterminedfromequation 513: P I Ac 1 V (513) Equation513isthestandardLeontief’sinput–outputpricemodel(seeequationB13, Appendix B, p. 223, for the derivation of this equation). This equation is appropriate for use in this research as it can be used to “assess the impact on prices throughout the economyofanincreaseinvalueaddedcostsinoneormoresectors’(Dixon&Rimmer2000; Kula1998;Melvin1979;Miller&Blair1985,p.356). Forexample,=0.01impliesataxof$10pertonneofcarbondioxide. 34 107 First, the baseyear price level needs to be calculated. When applying equation 513 with baseyear data (including baseyear input–output technical coefficients and sectoralvalueadded), oneobtains avectorof baseyear prices forallsectors equal to one. Next, the sectoral advalorem carbon tax rate (which is obtained from the tax imposition module, from equation 511 and 512) is imposed on the sectoral value added. The new energy and material prices can be endogenously determined by addingthe advaloremtax rate, obtained from the previous module,tothebaseyear valueadded,asshowninequation514. Pn I Aoc Vo tn 1 (514) where Pn: vectorofnewsectoralpricelevel; Ao: matrixofinput–outputtechnicalcoefficientsforbaseyear; Vo: matrixofsectoralvalueaddedbytotaloutputforbaseyear;and tn: vectorofnewsectoraladvaloremcarbontaxrate(calculatedfromEquations5 11and512). This would give the index of changes in prices of energy and materials compared to thebaseyear: P P Pn Po Po (515) Equation515canalsobeinterpretedaschangesinthepriceofthesectorthatsupplies energy and materials to the economy. It is also worthwhile to mention here that, according to Valadkhani and Mitchell (2002), the weightedmean of prices from all sectorswouldrepresentaseriesofconsumerpriceindices(inflation). 5.5 108 ExaminationofFactorSubstitutionduetoCarbonTax Whenenergyandmaterialinputspricesincrease,basedonmicroeconomictheory,the producerseekstosubstitutetheseinputswithoneanotherorwithotherfactorinputs suchascapitalandlabour.However,thissubstitutioneffectcannotbecapturedwithin thetraditionalLeontiefinput–outputmodel(seeSectionB.2.1,AppendixB,p.226,for comparison between Leontief and neoclassical production functions). The input– outputmodeldoesnot provideamechanismfor evaluatingtheimpactofchangesin technology(throughitstechnicalcoefficients).Thisisduetoitsunderlyingassumption about the fixed proportionality of input–output coefficients. In reality, these coefficients are likely to undergo continual changes, for example, due to new innovations, changes in consumer/producer preferences, and policyinduced changes (Rose1984).Thesechangeswouldhaveanimpactoninputpricesandhencechanges in technology through changes in factor inputs. Therefore, if one is to assess how carbon tax would influence technological change, one must make the input–output coefficients responsive to price changes. The method to modify these input–output technical coefficients is discussed in Section 5.5.1. Further, this research assumes that the substitution between factor inputs is limited only to the electricity industry (for modelling producers’ behaviour) and final demand category, including consumption and exports (for modelling consumer behaviour). The modelling of the electricity industryandfinaldemandisdiscussedinSections5.5.2and5.5.3,respectively.Finally, theeconometricspecificationandparameterestimationfortheelectricityindustryand finaldemandarediscussedinSection5.5.4. 5.5.1 ModificationofInput–outputCoefficients The underlying theory of Input–output analysis is represented in terms of perfect complements(shownasrightangledisoquantsinFigureB2(a)inAppendixB,p.227) which ignore the substitution effect. In reality, an increase in the price of one productioninputwillcausesubstitutionbetweenvariousinputsandhencewillaffect the overall input mix through substitution between various inputs. This economic realitycanbecapturedinneoclassicalproductionfunctionsthatallowforsubstitution 109 between various inputs. Such a production function is shown in Figure 53. For instance,whenthepriceofcommodity1increases,itsdemandwilldecreaseanditwill be substituted with commodity 2. The proportions of inputs 1 and 2 are shown as a movement from point A to B. This movement in the use of factor inputs can be econometrically estimated in terms of elasticities of substitution, which can then be used to modify input–output coefficients (Rose 1984). The process of such a modification of input–output technical coefficients, used in this research, is based on themethodproposedbyWuandChen(1990).Thisisoutlinedbelow. Figure53 Substitutioneffectinneoclassicaleconomictheory Supposethattheproductionfunctionfortheproductionofoutputj(Xj)frominputs1 and 2 is Xj = f(x1, x2). According to the cost minimisation theory of input use (Varian 1987),theconstantoutputtoproducejdependsonthepricesofitsinputs.Thiscanbe shownas: Xj g Pi , Pj (516) Bydifferentiatingequation516withregardtotime,gives: wX j wt X j § wX j wPi · § wX j wPj · ¸¸ ¨ ¸ ¨¨ © wPi wt ¹ © wPj wt ¹ Dividingbothsidesofequation517byXj,gives: (517) 110 X j § wX j Pi · Pi § wX j Pj ¨¨ ¸¸ ¨¨ © X j wPi ¹ Pi © X j wPj Xj · Pj ¸¸ ¹ Pj (518) Thetermsinbracketsrepresentcrosspriceandownpriceelasticities(),respectively. By substituting these terms with their respective elasticities, equation 518 can be writtenas: X j Kij Xj Pj Pi K jj Pi Pj (519) where X j : percentagechangeindemandforinputj; Xj Pi : Pi Pj Pj percentagechangeinpriceofiusedasinputtoproducej;and : percentagechangeinpriceofjusedasinputtoproducej. When incorporating such effects into the input–output model, according to Wu and Chen(1990),theinput–outputtechnicalcoefficientscanbemodifiedas: aijn § X j · aijo ¨1 ¨ X j ¸¸ © ¹ (520) where aijo : matrixofinput–outputtechnicalcoefficientsforthepreviousyear;and aijn : anupdatedmatrixofinput–outputtechnicalcoefficients. Equations 519 and 520 make it particularly clear that if own and crossprice elasticities of each input are available, the technical coefficients in the input–output modelcanbeadjustedinresponsetotherelativechangesinfactorcosts(thatis,their ownpricesandpricesofotherinputs)broughtaboutasaresultoftheintroductionof carbontax.Thepercentagechangesininputpricesarederivedinthisresearchinthe price impact module discussed earlier in Section 5.4. The own and crossprice 111 elasticities of substitution can be derived by assuming other types of production functionratherthantheLeontiefproductionfunction.Thisisthemainpurposeofthis module. Once the new sets of input–output technical coefficients are derived, these willbeusedinthenextmoduleforanalysingtheeconomywideimpactsofacarbon tax. 5.5.2 ModellingofElectricityGenerationMix Theinput–outputtechnicalcoefficientsmentionedaboveshould,ideally,bemodified for all sectors. That is to say that this method should be applied to all 28 sectors (including five electricity generation technologies), as listed in Figure 15. However, due to the excessive calculations involved, this research assumes that there is no substitutionbetweenvariousinputsforotherproductionsectors,exceptforelectricity generation (substitution between consumers’ goods and services is discussed in Section 5.5.3). This means that except for five electricity generation technologies, all other production sectors assumed zero elasticity of substitution based on the underlying Leontief production function. This assumption of zero elasticity of substitution for other sectors means that it will underestimate the CO2 reduction potential andoverestimate the economiccoststo the economy.35This is becausesuch anassumptiondoesnotallowotherproductionsectors(excepttheelectricitysector)to substitute their emissionsintensive expensive inputs (due to carbon tax) with low emissioncheaperinputs.Thehighpriceemissionintensiveinputsinthesesectorsare continuously used in the same (Leontief) proportion in which they were used before thecarbontaxisimposed. In this research, five types of electricity generating technologies – conventional coal fired (CF), internalcombustion (IC), gasturbine (GT), combinedcycle (CC), and Amodelwasalsorun,asatest,byassumingotherproductionsectorstobeperfectsubstitutes in the useoffactor inputsinresponsetochangesinprice duetothecarbontax.Theresults show that, for the carbon tax of $10 per tonne, the model developed for this research overestimates the total economic costs (GDP) by about 0.09 per cent ($5.6 billion in 1990 prices)andunderestimatestheCO2reductionpotentialbyabout15percent(58Mt). 35 112 renewable electricity (RE) – have been considered. These are the major current and likely technologies for electricity production in Australia. The factor input mix for variouselectricitytechnologiesconsideredinthisresearchisshowninFigure54. Figure54 Inputstructureoftheelectricityindustry These technologies differ from each other in terms of their use of inputs. Each technology is characterised by five factor inputs – capital, labour, electricity, fossil energy,andmaterials.Further,therearethreetypesoffossilfuels(thatis,coal,oil,and gas) and twenty types of materials used as inputs for electricity production. These materialsareprovidedbytwentynonenergysectors,asoutlinedearlierinFigure15. Because a large number of inputs are included, the application of the production function can be burdensome. Therefore, the use of all these inputs for any electricity 113 technology is constructed based on a nested structure, as suggested by Fuss (1977). Based on this input structure, the use of the production function limits the direct substitutionbetweenmajorfactor inputswithanyparticularenergyormaterials.For example,itdoesnotallowadirectsubstitutionbetweencapitalandcoalorlabourand steel.However,itallowsaninterfuelsubstitution(forexample,betweencoalandgas) andinterfactorsubstitution(forexample,betweencapitalandaggregateenergy).The application of the nested input structure and the selection of the appropriate productionfunctionarediscussedindetailinSection5.5.4. After accounting for substitution (or modification of input–output technical coefficients) for each electricity generation technology, the electricity industry then combines outputs from these five technologies to meet the electricity demand. The share of electricity produced from each technology in the total electricity supply is determinedonthebasisofshortrunmarginalcosts(SRMC).36TheaverageSRMCfor each technology for the base year is predetermined from information provided in Table22.TheseSRMCsforST,CC,GT,IC,andREforthebaseyearare3.6,5.8,6.8,12 and15¢/kWh,respectively.Thenewsetsofinput–outputtechnicalcoefficientsforthe electricityindustry,togetherwiththecontributedsharesofelectricityproductionfrom eachtechnology,arethenusedforanalysingtheeconomywideimpactsofcarbontax. 5.5.3 ModellingofFinalDemand Finaldemandcomprisesdemandforfinalconsumption,netexports,andinvestment. In this research, only final consumption and net exports are considered in terms of consumers’ response to changes in prices. Demand for investment is, however, modelledusinga“dynamic”versionofinput–outputanalysis(seeSection5.6). The final consumption and exports are modelled in a similar way to the electricity sector, in the form of nested structure of demand. However, instead of estimating elasticities from the production (cost) function, the utility (expenditure) function for ThisbasisiscurrentlyusedindeterminingtheshareofelectricityproductionintheNEM(see Sections2.1.5and2.2.2forfurtherdiscussion). 36 114 eachdemandcategoryisconstructed.Theconsumptionof goodsandservices(inthe formofenergyandmaterials)forbothdemandcategoriesisshowninFigure55. Figure55 Consumptionpatternforfinaldemand Consumption/Export Translog Ecoal Energy Material Translog CobbDouglas Eoil Egas El M1 ... E :Fuels El:Electricity M:Material M20 Goods& Services Functional form At the top level, demands for energy and material are characterised by the Translog function. Further, there are four types of fuels (that is, coal, oil, gas, and electricity) consumed as a final energy, which are also characterised by the Translog function. Also, there are twenty types of materials from which the consumer can choose. However, because of a large number of materials considered in this research, its demandisassumedtobecharacterisedastheCobbDouglasfunction.Theapplication ofthisnesteddemandpatterntoestimateelasticitiesisdiscussedinSection5.5.4. 5.5.4 EconometricSpecificationandParameterEstimation Thissectionpresentstheeconometricspecificationforestimatingownandcrossprice elasticitiesofsubstitutions,basedontheinputmixoftheelectricityindustry,asshown inFigure54,andthedemandpatternforconsumptionandexport,asshowninFigure 55(SeeSectionB.2inAppendixB,p.225,foradetaileddiscussionoftheeconometric specificationsadoptedinthissection).Asmentionedintheprevioussection,theinput mix for each type of electricity generation technology is based on a twolevel nested productionfunction.Thefirstnestingleveliscalledaninterfactormodelcomprising 115 capital,labour,electricity,aggregateenergy,andaggregatematerialinputs.Thesecond nestinglevelistheinterfuelorenergysubmodel(comprisingcoal,oil,andgas)and intermaterial or material submodel (comprising twenty materials). Similarly, the demandpatternoffinaldemandisalsobasedonatwolevelnestedstructure.Thefirst nestingleveliscalledaninterfactormodelcomprisingenergyandmaterial(asgoods and services). The second nesting level consistsof the energy submodel (comprising coal,oil,gas,andelectricity)andmaterialsubmodel(comprisingtwentymaterials). In order to perform an empirical analysis with this nested production/consumption structure,itisnecessarytoimposeaprioriweakhomotheticseparabilityrestrictionin energy and materials inputs. Weak homothetic separability requires that the macro production/utility function (interfactor model) be weakly separable37 and that the microproduction/utility functions (energy and material submodels) be homothetic. This restriction means that the marginal rate of substitution between each type of energy or material inputs is independent of the quantities of capital and labour demanded. Also, the imposition of this restriction opens up the possibility for two stage optimisation (1977, p. 91). This implies that the mix of inputs within each aggregate at the bottom level of the nested production structure (that is, energy and material submodels) is optimised in the first stage, and then this result is used togetherwithotherinputs(suchascapital,labour,andelectricity)toestimatetheinter factor model in the second stage. This procedure, in the context of this research, is explainedbelow. From Figure 54 and Figure 55, the production function for all types of electricity generationtechnologies(X)andtheutilityfunctionforfinaldemand(Y)canbewritten as: According to Berndt and Christensen (1973, p. 404), “a production function x=f(a, b) is weakly separablewithrespecttoagivenpartitionofthesetofallinputsinto–a1,a2,…,am–ifthemarginal rateoftechnicalsubstitutionbetweenaiandaj,whichareelementsofthesameseparableinputvectorar, isindependentofthequantitiesofallfactorsoutsidethataggregate,i.e.,independentoffactorb.” 37 116 f ª¬ K , L, E Ecoal , Eoil , Egas , El , M M 1 ,! , M 20 º¼ X Y f ª¬ E Ecoal , Eoil , Egas , Eelectricity , M M 1 ,! , M 20 º¼ (521) Here E Ei and M M i areaggregatorfunctionsforbothenergyandmaterialsub models,respectively,whichneedtobeoptimisedinthefirststage.Subsequently,the dualcost(expenditure)functionofequation521isalsoweaklyseparabletothesame inputsandcanbewrittenas: G g ª PK , PL , PE PEcoal , PEoil , PEgas , PEl , PM PM1 ,! , PM 20 º ¬ ¼ H g ª PE PEcoal , PEoil , PEgas , PEelectricity , PM PM1 ,! , PM 20 º ¬ ¼ (522) HerePEandPMrepresentaggregateenergyandmaterialpriceindices.Fromequation 522, the complete Translog cost (expenditure) functions38 for the interfactor model and energy submodel and CobbDouglas cost (expenditure) function39 for material submodelarethenexpressedinequations523to525,respectively. ln Gelec ln PE ln PM 1 ¦¦ J ij ln Pi ln Pj , i, j ^K , L, E , El , M ` 2 i j i 1 ln D 0 ¦ D i ln PEi ¦¦ J ij ln PEi ln PE j , i, j ^coal , oil , gas` 2 i j i ln D 0 ¦ D i ln Pi ln D 0 ¦ D i ln PM i , i ^M 1 ,! , M 20 ` (523) (524) (525) i The material submodel above is constrained by the CobbDouglas function because the parameters estimated from the Translog function are statistically insignificant (fromtheauthor’scalculation).Therefore,itisnotappropriatetoemploytheTranslog production(utility)functionforthematerialsubmodel. Using Shephard’s Lemma, the associated cost (expenditure) share equations for the interfactormodelandtheenergyandmaterialsubmodelscanbewrittenas: FordetailonthederivationofTranslogcostfunction,seeequationB25,AppendixB,p.228. FordetailonthederivationoftheCobbDouglascostfunction,seeequationB29,Appendix B,p.229. 38 39 Sielec 117 D i ¦ J ij ln Pj , i, j ^ K , L, E , El , M ` (526) j SiE D i ¦ J ij ln Pj , i, j ^coal , oil , gas` (527) D i , i ^M 1 ,! , M 20 ` (528) j SiM where Si : cost shares for the interfactor (elec) model and, energy (E) and material (M) submodels. Theestimationofthecompletemodelasshowninequation522isthenaccomplished usingthefollowingthreestageprocedure: i. Inthefirststage,eachelectricitygeneratorchoosesanoptimalquantityoffossil fuelsamongcoal,oil,andgaswhichminimisestheoverallcostofenergyinputs toproduceaspecifiedquantityofelectricity.Similarly,forfinaldemand,both demand categories chooseanoptimal quantityofenergy mixamong coal, oil, gas, and electricity, which minimises their expenditure on energy. Given the price indices of individual energy types and their associated cost shares, parameters D and J can be estimated from equation 527. These parameters arethenusedtoendogenouslydeterminetheaggregateenergypriceindexby substituting parameters and energy price indices into equation 524. This aggregate energy price index serves as an instrumental variable in the third stage. ii. In the second stage, each electricity generator and final demand category chooses an optimal quantity of each material component (M1, …, M20) within the material composite. Because the material submodel employs the Cobb Douglascostfunction,thereisnoneedforparameterestimation.Asshownin equation 528, cost shares for each material can be used as parameters to estimate aggregate material prices in equation 525. Like the first stage, this aggregate material price index serves as an instrumental variable in the third stage. iii. 118 Inthethirdstage,eachelectricitygeneratorchoosesanoptimalmixofcapital, labour, electricity, aggregate energy, and aggregate material to minimise the costofelectricityproduction.Similarly,consumerschooseamixofenergyand materials to minimise their budget on goods and services. Aggregate energy and material prices indices determined in the previous stages, together with capital, labour, electricity price indices and their associated cost shares, are usedtoestimateparametersfromequation526. The parameters for each cost (expenditure) share equation are estimated using the threestage ordinary least squares (3OLS) method. Eviews version 5.1 – an econometricssoftwareprogram–wasusedforthispurpose(Lilienetal.2005).Since the factor cost (expenditure) share equations must sum to unity, the sum of the disturbances across all equations will be zero for each observation. As a result, the disturbancecovariancematrixwillbesingularandoneequationmustbedeletedfrom the system of equations. Barten (1969) has shown that the maximum likelihood estimates of a system of share equations with one equation deleted are invariant to whicheverequationisdropped.Therefore,inthisresearch,thedecisionwasmade to omit equations of the gas share in total energy, of M20 in total materials, and the aggregate material share in the total factor from the energy and material submodels andinterfactormodel,respectively.Theremainingn1factorcostshareequationsare estimatedjointlyasamultivariateregressionsystembyiterationofaZellnerefficient procedureuntilconvergenceisachieved(Zellner1962). Using the procedure outlined above, the parameters estimated for the energy sub modelandinterfactormodelfortheelectricitysectorareshowninTable51andTable 52,respectively.Becausetheparametersforthematerialsubmodelaretakendirectly from their cost shares, this information (cost shares for the material submodel) is provided in Appendix C, pp. 263269, together with cost shares for the energy sub modelandinterfactormodel. 119 Table51 Parameterestimatesforelectricitysector:energysubmodel Internal combustion ESI Coalfired 0.6643* 0.7180* (647.27) (319.70) 0.1206* 0.0763* (36.37) (34.21) 0.2151 0.2057 0.0292* 0.1998* (2.10) (8.12) 0.2973* 0.2214* (50.49) (14.91) Gas,Gas 0.0980 0.0899 Coal,Oil 0.0851* 0.0342 (17.53) (1.56) Coal,Gas 0.1143 Oil,Gas 0.2123 Gasturbine (1980–1999) Combined Renewable cycle Interceptcoefficients( i ) Coal Oil Gas 0.0725 0.1656 0.2556 0.1061* (7.99) 0.8939 Slopecoefficients( ij ) Coal,Coal Oil,Oil 0.0725* (2.18) 0.0725 Notes: Figuresinparenthesesaretstatistics * Significantat95percentlevelofconfidence NotAvailable DetailedresultsforenergysubmodelareshowninTableE2,AppendixE,pp.283286. Table51presentstheresultsforcoalfiredandgasturbineonly,asthesetechnologies usemorethanonetypeofenergyinputforelectricityproduction.Internalcombustion and combinedcycle consume only one type of energy input, that is, oil and gas, respectively; whereas renewable does not consume any fossil energy. The results indicate that the energy submodel performs considerably well, since almost all estimatesaresignificantata95percentlevelofconfidence.Further,theseparameters arealsosatisfiedforpositivityandmonotonicityconditions40,sinceall D i arepositive and the estimation of cost shares from these parameters is also positive for all observations. See Section B.2.3 in Appendix B, p. 228, for assumptions of the production cost function model. 40 120 Table52 Parameterestimatesforelectricitysector:interfactormodel ESI Coalfired Internal combustion Gasturbine Combined cycle (1980–1999) Renewable Interceptcoefficients( i ) 0.4052* 0.3413* 0.2747* 0.4580* 0.2202* (15.94) (15.44) (19.28) (7.96) (24.23) (23.43) L 0.1953* 0.2139* 0.0381* 0.1197* 0.2070* 0.1553* (15.16) (18.69) (4.75) (4.14) (20.84) (7.74) E 0.1786* 0.2027* 0.5873* 0.2775* 0.4014* (15.54) (16.77) (38.85) (9.92) (30.16) 0.0679* 0.0699* 0.0167* 0.0494* 0.0940* (30.70) (28.83) (4.72) (7.03) (60.79) (2.70) M 0.1530 0.1722 0.0831 0.0954 0.0774 0.1154 K,K 0.0415 0.0024 0.1037* 0.1457 0.0457* 0.0047 (0.86) (0.06) (4.70) (1.34) (2.78) (0.09) L,L 0.0952* 0.0972* 0.0607* 0.2539* 0.2735* 0.0801* (3.05) (3.02) (3.33) (5.50) (9.72) (2.11) E,E 0.1483* 0.1569* 0.1209* 0.0001 0.1448* (7.55) (7.43) (5.04) (0.00) (2.38) 0.0648* 0.0676* 0.0342* 0.0402* 0.0079* (6.20) (5.15) (2.26) (5.57) (2.07) (2.95) 0.1043 0.0059 0.1201 0.0269 0.0117 0.0084 0.2826 0.0564 0.0244 0.0051 0.1311 0.0093 (0.26) K El 0.6960* 0.0333* Slopecoefficients( ij ) El,El M,M K,L 0.1018* (0.24) (1.25) (0.59) (1.04) (0.31) 0.0619* 0.0621* 0.1370* 0.0911 0.0922* (2.97) (2.85) (7.72) (1.72) (3.52) 0.0060 0.0083 0.0084 0.0063 0.0157* (1.34) (1.74) (0.95) (0.48) (5.46) (1.35) K,M L,E 0.0205 0.0336* 0.0411 0.0282* 0.0334 0.0187 0.0081 0.1345* 0.0358 0.1483* 0.0372 (2.41) (1.97) (1.59) (3.71) (5.52) L,El 0.0360* 0.0436* 0.0318* 0.0779* 0.0315* (4.08) (4.66) (2.62) (6.73) (4.53) (4.53) L,M E,El 0.0198 0.0351* 0.0015 0.0331* 0.0186 0.0066 0.2537 0.0301* 0.1617 0.0145 0.0048 (4.77) (4.17) (0.87) (2.97) (1.93) E,M El,M 0.0849 0.0597 0.0899 0.0697 0.0041 0.0678 0.0736 0.0944 0.2154 0.0066 K,E K,El 0.0325 0.0942* 0.1635 Notes: K–Capital;L–Labour;E–Energy;El–Electricity;M–Materials Figuresinparenthesesaretstatistics * Significantat95percentlevelofconfidence NotAvailable DetailedresultsforInterfactormodelareshowninTableE1,AppendixE,pp.276282. The interfactor model, as shown in Table 52, also performs reasonably well, as indicatedbyalargenumberofstatisticallysignificantcoefficientsata95percentlevel of confidence. The slope coefficients of capital–labour and capital–electricity for most of the generation technologies are statistically insignificant; therefore, such results must be interpreted with some caution. Again, the positivity and monotonicity conditionsaresatisfiedforeachobservation. 121 Similartotheelectricitysector,theparametersestimatedfortheenergysubmodeland interfactormodelforfinaldemandareshowninTable53andTable54,respectively. Because the parameters for the material submodel are taken directly from their cost shares, this information (cost shares for the material submodel) is provided in AppendixC,pp.263269,togetherwiththecostsharesfortheenergysubmodeland interfactormodel. Table53 Parameterestimatesforfinaldemand:energysubmodel Finalconsumption (1980–1999) Export Interceptcoefficients( i ) Coal Oil 0.0129* 0.8593* (2.49) (123.57) 0.3900* 0.1042* (24.31) (12.03) Electricity 0.4774* 0.0035* (52.62) (14.90) Gas 0.1197 0.0330 Slopecoefficients( ij ) Coal,Coal Oil,Oil 0.0219 0.2453* (0.58) (7.37) 0.1484* 0.1723* (3.51) (6.49) Electricity,Electricity 0.3453* 0.0006 (3.41) (0.18) Gas,Gas 0.3470 0.0571 Coal,Oil 0.0351* 0.0043 Coal,Electricity (1.71) (0.17) 0.1398* 0.0051* (2.63) (2.55) Coal,Gas 0.1266 0.2360 Oil,Electricity 0.0406 0.0011* Oil,Gas Electricity,Gas (1.26) (2.22) 0.2241 0.1755 0.4445 0.0034 Notes: Figuresinparenthesesaretstatistics * Significantat95percentlevelofconfidence NotAvailable DetailedresultsforEnergysubmodelareshowninTableE2,AppendixE,pp.283286. Table53presentstheresultsforenergyconsumptionandexports.Theresultsindicate that the energy submodel performs considerably well, since almost all estimates are significant at a 95 per cent level of confidence. Further, these parameters are also satisfied for positivity and monotonicity conditions, since all D i are positive and the 122 estimation of expenditure shares from these parameters are also positive for all observations. Table54 Parameterestimatesforfinaldemand:interfactormodel Finalconsumption (1980–1999) Export Interceptcoefficients( i ) 0.0260* Energy 0.1306* (63.77) (55.59) Materials 0.9740 0.8694 Energy,Energy 0.0247* Slopecoefficients( ij ) Materials,Materials Energy,Materials 0.0086* (14.37) (1.42) 0.0247 0.0086 0.0247 0.0086 Notes: E–Energy;M–Materials Figuresinparenthesesaretstatistics * Significantat95percentlevelofconfidence NotAvailable DetailedresultsforInterfactormodelareshowninTableE1,AppendixE,pp.276282. The interfactor model, as shown in Table 54, also performs reasonably well, as indicatedbyalargenumberofstatisticallysignificantcoefficientsata95percentlevel ofconfidence.Again,thepositivityandmonotonicityconditionsaresatisfiedforeach observation. All estimated parameters shown above can be used to determine price elasticities of demand,asoutlinedindetailinSectionB.2.5,AppendixB,p.231.Inbrief,thiscanbe achievedusingthemethodsimilartoBerndtandWood’s(1975),as: Kii SiV ii where V ii Kij S jV ij where V ij J ii Si2 Si Si2 J ij Si S j Si S j (529) (530) To complete the substitution module, the own and crossprice elasticities of substitution are then used in equations 519 and 520, as discussed earlier, for modifyingtheinput–outputtechnicalcoefficients. 123 5.6 EconomywideImpactModule As mentioned in Section 5.1, in this final module, the economywide impacts of a carbon tax are analysed. These impacts are analysed using an energyenvironment orientedinput–outputframeworkspecificallydevelopedforthisresearch. Following the substitution module, after the input–output technical coefficients, electricity generation mix, and final demand response have been modified, these changes will be incorporated into the baseyear input–output model to generate different types of economywide impacts. These impacts, which include economic, energy, environmental, and social aspects, would be generated for the carbon tax, basedonbothPPPandSRPforthesucceedingyear.Theresultwillthenbefedintothe first module again and impacts would be determined for the next year. The same procedurewouldbefolloweduntilimpactsaredeterminedforallyearstotheendof the study period, that is, 2020. The mathematical specifications for this module are discussed below. The derivation and detailed explanation of the input–output model areprovidedinSectionB.1.3andSectionB.1.5inAppendixB. First,theeconomicimpactsofcarbontaxaredetermined.Theseimpactsarequantified in terms of changes in gross domestic product, sectoral output/production, and inflation. These variables are selected because they constitute major areas of concern from economic and political perspectives. The starting point for this analysis (of economicimpacts)isthebasicinput–outputidentity,namely: X I An 1 Y (531) where X: columnvectorofsectoraloutputs; An: matrixofupdatedinput–outputtechnicalcoefficients;and Y: columnvectorofsectoralfinaldemands. Equation531canbedirectlyappliedfortheextensionofenergy,environmental,and social attributes. However, as discussed earlier in Section 5.5.2, the electricity 124 generation mix would be endogenously determined within the model. In order to allowthemodeltoexplicitlyaccountforthisinvestment,itwouldbemoreappropriate totreatinvestmentdemand,whichistraditionallylocatedasapartoffinaldemandY, tobeendogenouslydeterminedwithintheinput–outputmodelaswell.Followingthe methodproposedbyLenzen(1998),thiscanbewrittenas: X ª I An B º Y ¬ ¼ 1 (532) where B : matrixofweightedmeancapitalcoefficients;and Y*: vectorofsectoralfinaldemand,excludingdemandforcapitalinvestment. Another conventional yet important variable for analysing economic impact is economic growth, which is measured by the growth in GDP. By definition, GDP comprisesdomesticconsumption,investment,governmentspending(forconsumption and investment) and net exports. However, in this research, government spending is includedwithprivateconsumptionandinvestment.ThechangesinGDP,estimatedin this research, would be influenced by changes in domestic consumption and net exports(fromthesubstitutionmodule)andchangesindemandforcapitalinvestment. Thedemand(andsupply)forcapitalinvestmentcanbedeterminedfrom: Investmentdemand ¦BX ¦BX (533) i Investmentsupply (534) j Consequently,addingtheinvestmentdemanddeterminedfromequation533toother domestic consumption and net exports would determine the GDP for each year. Therefore, the differences in the GDP, sectoral outputs, and inflation (which was determinedinthepriceimpactmodule)forbothtypesofcarbontax(thatis,basedon PPPandSRP)canbecomparedandanalysed. Oncetheeconomicimpactisdetermined,thisinformation(particularlysectoraloutput variable)willbeusedtocalculateenergy,environmental,andsocialimpacts.Thebasic 125 economicinput–outputframeworkwillbeextendedtoexplicitlydeterminetheseother impactsfollowingthemethoddevelopedbyProopsetal.(1993). The primary energy consumption can be easily determined by referring back to equation 52, where energy intensity was defined. By reorganising the term, the primaryenergyrequirementintheeconomycanbegivenas: F CX (535) The CO2 emissions can also be easily determined by using the expression given in equation53.Theextensionofthatequation,bysubstitutingenergyconsumptionfrom equation534,canbewrittenas: E eF eCX (536) Further, a similar extension is also applied for analysing the social impacts. In this research, social impacts are assessed in terms of changes in the level of employment triggeredbytheintroductionofacarbontax.Althoughthelevelofemploymentisnot the only factor that reflects social impacts (other impacts could include, for example, incomedistribution,povertylevel,etc.),itisoftenconsideredasthecoreoftheabove noted and several other social problems (Atkinson et al. 1997). Therefore, it is appropriatetoassessthesocialimpactofcarbontaxintermsofemployment. The impact of carbon tax on employment can be straightforwardly assessed by extending the economic input–output model, in a similar way as was done for the assessmentofenergyimpact.Likeenergyintensity,labourintensity(orlabouroutput ratio) can be defined as the amount of labour for the production of one unit of economicoutput.Thiscanberepresentedas: l L X (537) where l: matrixrepresentingpeopleemployedperunitofoutputineachsector; L: vectorrepresentingthelevelofemployment;and X: vectorrepresentingsectoraloutput. 126 By assuming a specific rate of improvement in labour productivity41, the sectoral employmentintheeconomycanbedeterminedby: L lX (538) Theresultsfromthismodulearepresentedanddiscussedinthenextchapter. 5.7 DataSourcesandPreparation Themethodologicalframeworkasoutlinedinthischapterconsistsoftwotypesofcore models,namely,input–outputandproductionfunctionmodels.Asaresult,twosetsof dataareneededinthisresearch,onefortheinput–outputmodelandtheotherforthe production function model. This section provides a description of data sources and preparationofdataforuseinthesemodels. 5.7.1 DataPreparationforInput–outputModel Inordertoobtaindatarequiredfortheinput–outputmodelwhichisusedforemission allocationanddeterminationofpriceandothereconomywideimpacts,itisnecessary to estimate e, C, A, B, and l from published statistics. These data were generally not directlyavailableinanappropriateorconsistentform.Aconsiderableamountofdata preparationeffortwasthereforerequiredbeforetheanalysiscouldcommence. a) Thethirteenyearlyinput–outputtablesusedinthisresearchwerepublishedby the Australian Bureau of Statistics (ABS) (ABS various). These represent the years 1980 to 1984, 1987, 1990, 1993 to 1995, 1997, 1999 and 2002. The inter industry matrix in these tables ranged between 106 and 113 sectors. To make meaningful comparisons, the input–output tables needed to be adjusted for price variations over time using price indices obtained from the ABS (2003). Furthermore, the tables needed to be aggregated in order to ensure sectoral consistency and coherence with other data sources. This, however, required a Labourproductivityisareciprocaloflabouroutputratio.Itrepresentstheoutputthatcanbe producedbyoneperson. 41 127 considerableeffortintermsofinvestigatingthechangesthathavetakenplace in sector definitions and classification systems over the period 1980–2002. In viewofthefocusofthisresearch,varioussectorsweregroupedinaccordance withtheirenergyintensiveness,thatis,thehighlyenergyintensivesectorsare kept separate, while less energyintensive sectors are aggregated into one sector. These groupings are also made consistent with the ANZSIC42 sectoral classificationdefinedbyABS.Therefore,somegroupscompriseasinglesector, whileotherscompriseasmanyas24sectors(asinthecaseofthecommercial sector).Asummaryofthesegroupings,whichshowsthenumberofsubsectors that areaggregatedinto 28sectors considered inthisresearch, is presented in Table55(withdetailsofeachsubsectorshowninTableC1,AppendixC,pp. 234237). Table55 Sectorconsideredinthisresearch 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Coal sector Petroleum and coal products Gas sector Renewable electricity Coal-fired electricity Internal-combustion electricity Gas-turbine electricity Combined-cycle electricity Agriculture Raw materials mining Food industry Textile industry Wood and paper industry Chemical industry Summaryofsectoralclassification No.ofsub sectors 1 1 1 Sectorconsideredinthisresearch 15 16 17 18 19 20 21 22 23 24 25 26 27 28 1 10 4 12 611 79 9 Non-metal industry Iron and steel industry Non-ferrous metal industry Fabricated metal industry Machinery & equipment industry Other manufacturing industry Water supply Construction Road transport Railway transport Water transport Air transport Other transport Commercial services No.ofsub sectors 6 1 1 3 11 2 1 3 1 1 1 1 3 1724 b) Theelectricitysupplysector,asshowninSection3.1,isamajorcontributorto CO2emissionsinAustralia.This,however,currentlyappearsasasinglesector in the input–output tables. Given its importance in the estimation of CO2 This is referred to as the 1993 version of AustraliaNew Zealand Standard Industry Classification. 42 128 emissions,andinordertobeabletoexaminealternativescenariosforelectricity generation, this sector is disaggregated into five subsectors based on the technologies used for electricity generation. The five electricitygeneration technologies considered in this research are conventional coalfired, internal combustion, gasturbine, combinedcycle, and renewable. The renewable electricitygenerationisusedasaproxyforothertypesofelectricitygeneration technologies available in Australia, such as hydro, wind and photovoltaic. These renewable technologies do not consume energy directly for electricity production and also are highly material intensive, compared to fossilfuel power stations. Such a disaggregation of electricity supply sector in this research has allowed the inclusion of more than 97 per cent of electricity production capacity in Australia. The only data available for such disaggregation represent energy consumption by the type of electricity generation technology (as published annually by the Electricity Supply Association of Australia). No data on the consumption of materials by these generation technologies are available. Hence, this research has disaggregated capital,labouranddifferentmaterialsinputintheelectricitysectoronthebasis oftherecommendationsmadebyGayandProops(1993),Proopsetal.(1993), Timilsina(2001),andCruz(2002)asfollows: Capitalinputisapportionedtoeachelectricitygenerationtechnologybased onitscapitalcostdistributionfactor. Labour input is apportioned to each electricity generation technology in proportiontoitsshareinelectricityproduction. Inputsofmaterialsarevaried,dependingonthetypeofmaterial. Materials from agricultural, food, textiles, wood and paper, and water sectors are apportioned the same way as labour inputs, that is, in proportiontosharesinelectricityproduction; 129 Materials from the transport sector are apportioned based on the transport task provided to different electricity generation technologies (ApelbaumConsultingGroup1997); Materials from raw materials mining, chemical, nonmetal, iron and steel, nonferrous metal, fabricated metal, machinery and equipment, and commercial sectors are apportioned based on the “operation and maintenance(O&M)cost”distributionfactorofeachtechnology;and Material from construction sector is apportioned on the same basis as capitalinput,thatis,disaggregatebasedonthecapitalcostdistribution factorofeachelectricitygenerationtechnology. While the disaggregation and apportioning based on shares in electricity generation and transport needs are relatively straightforward; these are more complicated when based on capital and O&M distribution factors. These factors need to be constructed, based on the economic and technical characteristics of different electricitygeneration technologies,asshowninTable56. Table56 Economicandtechnicalcharacteristicsofpowerplants Initialinvestmentcost† † AnnualO&Mcost (units) CF IC ($A/kW) 1430 1500 475 870 2020 37 39 9 12 32 ($A/kW/year) † Plantlife ‡ Capitalrecoveryfactor GT CC RE (years) 30 30 28 30 50 (percent) 8.9 8.9 9.1 8.9 8.2 Annualcapitalcost‡ ($A/kW/year) 127 133 43 77 165 * ($AMn/year) 1094 9 26 8 236 ($AMn/year) 3757 32 123 53 1217 CapacityO&Mcost * Totalcapacitycost Installedcapacityin2002 (MW) * O&Mdistributionfactor * 31366 268 4313 1441 7387 0.793 0.007 0.026 0.012 0.162 Capitaldistributionfactor 0.720 0.006 0.034 0.020 0.220 Notes: CF:Coalfired,IC:Internalcombustion,GT:Gasturbine,CC:Combinedcycle,RE:Renewable; Interestrate=8percent[Follow:Naughten(2003)]; † Jones,Peng&Naughten(1994);Naughten(2003);Dalziell,Noble&OfeiMensah(1993); ‡ Author’scalculation; * Author’scalculationforthecapacityin2002(seeTableC2,AppendixC,pp.238239for capitalandO&Mdistributionfactorsfor1980–2002). 130 Thecapitalcostsoftheexistingcapacityarecalculatedbasedontheinstalledcapacity inthatyear,initialinvestmentcostforthetechnology,anditsexpectedplantlife.The capital distribution factor for each technology is expressed as its share in the total annualcapacitycostof the electricitysector.The O&Mcosts for existing capacity are calculatedbasedontheinstalledcapacityinthatyearandtheannualO&Mcostofthe technology.TheO&Mdistributionfactorforanytechnologyisexpressedasitssharein the total annual O&M costs of the existing electricity capacity in Australia. Table 56 shows the capital and O&M distribution factors for various technologies, using installed capacity in 2002 as an example. Detailed lists of these factors for each technologyforallotheryearsareprovidedinTableC2,AppendixC,pp.238239. Thediscussionsofarhasfocusedontheaggregationanddisaggregationofpublished input–outputtables,intothesectoralclassificationrequiredforthisresearch.Thishas resulted in the creation of a 28sector input–output table for this research. The main driver in this aggregation/disaggregation was the energy intensiveness of various sectors, that is, energy intensive sectors were kept as separate sectors (and in fact, in some cases, disaggregated, for example, the electricity sector), whereas lessenergy intensive sectors were aggregated (see Table 55). This is only a part of the effort for reorganisingtheinput–outputtablesrequiredforconstructinginput–outputtechnical coefficients(matrixA).Thedetailedtechnicalcoefficientsderivedfromeachofthe28 sectorinput–outputtableareshowninTableC3,AppendixC,pp.240252).However, inordertoendogenouslydeterminethedemandforcapitalinvestment,matrixBalso needstobeconstructed. c) Regardingtheconstructionofthecapitalcoefficient(B)matrix,theuseofgross fixedcapitalformationbyindustrieshadtobeestimatedfromaggregateddata availablefromABS(Lenzen1998).TheAustralianinput–outputtablesprovide, aspartofthefinaldemand,avectorYb (=BX)–oftotalsectoralsuppliesusedas grossfixedcapitalexpendituresbytheprivatesector,publicenterprisesandthe general government. These expenditures were allocated across the respective industry divisions at the broadest levels (that is, at the ANZSIC 1digit level) accordingtoaggregateddataontheconsumptionoffixedcapital(ABS2004f). 131 This was further disaggregated into the 28 sectors required for this research, accordingtodataonthegrossfixedcapitalexpendituresofdifferentindustries (ABS 2004a, 2004e, 2004g, 2004h, 2004j). This assumption might seem unsatisfactory,butthe error associated withthisdisaggregationof grossfixed capitalexpendituresisrelativelysmallinmostcases,since theseexpenditures constituteonlyasmallshare(about7percent)oftotaloutput(Lenzen1998). Theweightedmeanofthecapitalcoefficientsmatrixfromtwelveinput–output tablesisshowninTableC4,AppendixC,p.253. d) Regarding the construction of the sectoral energy intensities (C) matrix, information on primary energy use (F) – including black and brown coal, naturalgas,andpetroleum–measuredinphysicalunitswasrequired.Thisis availablefromannualsectoralenergyconsumptiondatapublishedbyABARE (ABARE2006a).Again,theprimaryenergyconsumedineachtypeofelectricity generationtechnologyisnotdirectlyavailablefromABARE.However,thiscan be estimated by apportioning the energy consumed in the electricity sector from ABARE, using the proportion of each fuel type consumed by each technology obtained from ESAA. In addition, energy consumed by the road transportsector,aspublishedbyABARE,includesbothprivateandcorporate vehicles (Akmal et al. 2004). In order to relate energy data from ABARE with thecorrespondinginput–outputtables,itwasrequiredtoseparatethesefigures on the basis of the estimates of energy consumption from other sources (ABS 2004l).Thiswouldresultinenergyconsumptiontables(inPJ)whichconsistof fourtypesofprimaryenergiesconsumedineachofthe28sectors.Theseenergy consumption tables will be divided with sectoral outputs from input–output tables to obtain the energy intensities (C) matrix. These matrices of historical energyintensities(matrixC)areshowninTableC5,AppendixC,pp.254256. e) Furthermore,theemissionfactorforeachprimaryenergyisobtainedfromthe AustralianGreenhouseOffice(NGGIC1996).Theseare95.7,90.4,69.3,and51.3 kg of CO2 for each GJ of brown coal, black coal, petroleum, and natural gas, respectively(alsoseeSection3.1.2). f) 132 Finally, the matrix of the labouroutput ratio can be constructed by using the numberofemployeesineachsectordividedbytheoutputofthesector.These sectoralemploymentfiguresaredirectlyavailablefromABS(ABS2004i). 5.7.2 DataPreparationforProductionFunctionModel In order to obtain data required for the production function model, which is used in thesubstitutionmodule,itisnecessarytoconstructtimeseriesdataonthefactorcost shares and pricesofeachinput requiredby theelectricitysectorforthe period 1980– 1999. These data are required for all models, namely, the interfactor model, energy submodel and material submodel (presented in Section 5.5.4). These data were however, generally not directly available in an appropriate or consistent form. A considerable amount of data preparation effort was therefore required before the analysis could commence. These data are compiled from three major sources – ABS, ABARE,andESAA. a) Forcostsharesoftheinterfactormodelandmaterialsubmodel,factorinputs (excludingenergy)foreachelectricitysupplytechnologyaretakenfromtwelve input–outputtablespublishedduringtheperiod1980–1999byABS(ABS2003, 2004b, 2004c). This is on the grounds that each column of input–output technicalcoefficientsinthetabledenotesthecoststructureoftheindustry.Each columnoftheinput–outputtabledescribesthecompositionofinputsrequired by a particular industry. These inputs are supplied from the outputs of other industries (in the form of intermediate inputs) and primary factors of production (in the form of valueadded) (also see Section B.1.2, Appendix B, p.217). The details of the organisation of these input–output tables, consistent withthisresearch, havebeendiscussedintheprevioussubsection.ABSdoes not publish input–outputtableson an annual basisand,therefore,cost shares for the missing years (namely, 1985, 1986, 1988, 1989, 1991, 1992, 1996, and 1998)werecalculatedonthebasisofaveragesbetweenthefirstandlastyearfor which an input–output table is available. For cost shares of the energy sub 133 model, the shares of energy inputs are taken from timeseries of annual data publishedbyESAA(ESAAvarious). For factor prices of the interfactor model, the timeseries data are required for the pricesofcapital,labour,andelectricity.Thepricesofaggregateenergyandaggregate material are endogenously determined from the energy submodel and material sub model,respectively(seeSection5.5.4). b) The price of capital is estimated on the basis suggested by the Industry Commission(1992),usingthefollowingequation: Pik ( I G ) Pk where Pk: capitalpriceindex; Pik: implicitcapitalpriceindex; I: realinterestrate;and : depreciationrate. The implicit capital price index is taken directly from ABS (ABS 2004d). The (539) interest rates used in this research are real rates, which take into account inflation,obtainedfromtheReserveBankofAustralia(RBA2004).Although,in reality,eachindustryshouldhavebeenattachedtodifferentinterestrates,due tothedifficultyinobtainingdata,thisresearchassumescommoninterestrates acrossallindustries.Economicdepreciationischosen,inthisresearch,tobe6.7 per cent per annum. This rate is chosen based on a study by Burbridge et al. (2000);inthisstudythisvalueisassumedasanaveragedepreciationrateused for depreciating the value of the electricity industry’s infrastructures in Australia. c) Thepriceoflabourisdeterminedbydividingthetotallabourcostwiththetotal number of persons employed in the electricity industry (Westoby & McGuire 1984). The labour cost for each industry is available from input–output tables 134 publishedbyABS,whiledataforthenumberofemployeesaretakenfromABS (ABS2004i)andESAA(ESAAvarious). d) For electricity prices, the timeseries of electricity price indices are developed from electricity prices published by ESAA (ESAA various). For prices of non electric energy, the prices of various forms of primary energies are obtained fromABARE(ABAREvarious;Tedescoetal.2004). e) For material prices, this research has used the producer price indices for each industry, published by ABS (ABS 2004k), as a proxy for prices of material inputs. Unfortunately, ABS does not publish the producer price index for agricultureorthewaterindustry.Thepriceindicesforthesetwoindustriesare assumedtobeequaltotheconsumerpriceindices. Allfactorpricesdiscussedabovehavebeenassumedasthesameacrossallelectricity generationsubsectorsandalsoconvertedintotimeseriesofindices,with1990asthe baseyear.Thedetailsofcostssharesandpriceindicesofallfactorinputsusedinthis researcharepresentedinTableC6toTableC8,AppendixC,pp.257269. 5.8 SummaryandConclusions Theobjectivesofthischapterwerei)todevelopamethodologicalframeworkbasedon an input–output model with a modified production function – for the analysis of the impactofcarbontaxonthewidereconomy,andii)describethesourcesofdataaswell asthemethodologyusedinthisresearchtodeveloprawdataintoaformthatcouldbe employed for constructing various empirical analyses in this research. The major conclusionsfromthischapteraresummarisedasfollows: x The methodological framework developed in this research comprises five interlinkedfunctionalmodules. a) Inthefirstmodule,thesectoralcarbondioxideemissionsandintensitiesare calculated, based on both the Polluter Pays Principle (PPP) and Shared Responsibility Principle (SRP). The CO2 emissions and intensities for the 135 PPParesimplycalculated,basedondirectenergyconsumptionrepresented inthetraditionalenergybalance.Ontheotherhand,theCO2emissionsand intensities for SRP are calculated from direct as well as indirect energy consumption, represented in materialsbalance. CO2 emissions and intensities for SRP are determined from the energyoriented input–output methoddevelopedonthebasisofthe“energycoefficient”approach. b) Inthesecondmodule,acarbontaxisintroducedbasedonsectoralcarbon dioxide intensities. This tax is introduced on the top of the existing value addedtax. c) In the third module, the impact of carbon tax, in terms of changes in sectoralprices,isestimated.ThisisestimatedusingthestandardLeontief’s input–output price model, which is appropriate for analysing changes in valueaddedtax. d) Inthefourthmodule,theelectricitysectorisallowedtosubstituteitsfactor inputs in response to changes in sectoral prices brought about by the application of a carbon tax. This is achieved by assuming a nested input structureforeachelectricitygenerationtechnologyandreplacementofthe Leontief’s production function with the Translog and CobbDouglas production functions. Further, the final demand category (including final consumption and exports) is also allowed to change its consumption patterns in response to increases in energy and material prices due to the introduction of a carbon tax. It is also assumed that the input–output relationshipsforotherproductionsectorsremainconstant. e) In the final module, based on the new input–output coefficients, the economywide impacts of carbon tax are assessed. These impacts are classified into energy, environmental, economic, and social impacts. The resultoftheseimpactsisdiscussedinthenextchapter. 136 CHAPTER6 6 ASSESSMENTOFTHEIMPACTSOFCARBONTAX InChapter5,amethodologicalframeworkforassessingtheimpactsofcarbontaxwas developed. The objective of this chapter is to employ this framework to assess the energy, environmental, economic and social impacts of carbon tax on the Australian economy. This assessment will be carried out separately, based on two approaches, namely, the energybalance approach (underpinned by PPP) and materialsbalance approach (underpinned by SRP). The method for carrying out the assessment by the firstapproachwasexplainedinSection5.2.1andforthesecond,inSection5.2.2. This chapter is organised as follows. Section 6.1 presents the outline of the generic framework used in this research for the assessment of the impacts of carbon tax. In particular,thisoutlineshowstheattributesintermsofwhichvariousimpactswillbe measured.Section6.2describestherangeofcarbontaxlevelsanalysedinthisresearch, along withtheunderlyingassumptions.Section6.3presentsandanalysesthe results, in terms of the attributes noted above, of various levels of carbon tax. While the analysesinSection6.3focusesonassessingtheenergy,environmental(CO2 emissions), economic, and social impacts of various levels of carbon tax in a situation in which there is no apriori limit of CO2 emissions, Section 6.4 places an apriori limit on CO2 emissions(equivalenttotheKyotoprotocollevel)andassessestheenergy,economic, andsocialimpactsofmeetingthisemissionlimit.Section6.5providesacomparisonof theseresults(particularlytheresultsofSection6.4)withthoseofotherstudies.Section 6.6 provides further analyses of these results in a wider policy context. Section 6.7 summarisesthemajorfindingsofthisChapter. 6.1 FrameworkforAssessingImpactsofCarbonTax This section provides an outline of the framework for assessing the energy, environmental,economic,andsocialimpactsofcarbontax.ItwasdiscussedinChapter 137 5 (especially in Section 5.5.2), that the application of a carbon tax would result in a change in the composition of fuel and technologymix for electricity generation. The impact of this change would then become evident in the wider realms, for example, changes in primary energy requirements, CO2 emissions, economic output, and employment. The key attributes employed in this research to measure these impacts areshowninFigure61. Attributesforassessingimpactsofcarbontax ImpactofCarbonTaxon: Figure61 ItisalsoimportanttonotethattheimpactofcarbontaxanalysedinSection6.3isnot meanttodemonstratehowmuchemissionreductionispossibleinresponsetocarbon tax.Instead,itismeanttodemonstratehowtheelectricityindustrywouldbeimpacted upon in response to different carbon tax rates, both from energybalance (PPP) and materialsbalance(SRP)approaches.Theeconomywideimpactsofdifferentcarbontax approaches for achieving a predetermined emissions level (that is, Kyoto target) is discussedinSection6.4(asnotedearlier). 138 6.2 AlternativeCarbonTaxRegimes A key focus of this research is to analyse the impacts of carbon tax based on the materialsbalance approach (that is, Shared Responsibility Principle)43 and on the energybalanceapproach(thatis,PolluterPaysPrinciple).Theseimpactsarecompared with the impacts that would be experienced in the businessasusual state of affairs, thatis,whenpresenttrendscontinueandnocarbontaxisintroduced.Thisbusiness asusualsituationiscalled,inthisresearch,theBaseCasescenario(BC).Twolevelsof carbontaxratesareanalysedinthisresearch,foreachoftheseapproaches.Theseare $10and$20pertonneofCO2emissions.Thesecarbontaxratesareinasimilarrangeto thoseconsideredinpreviouscarbontaxstudies(seeTable32). TheBaseCasescenario(BC)isbasedonthefollowingassumptions: i. Theeconomywouldgrowatanannualrateof3.1percentbetween2004to2010 and 2.3 per cent between 2010 to 2020 (Costello 2002). In this research, these ratesareappliedtoestimateincreasedconsumptionlevelsandnetexportsonly (as investment, which is a part of economic growth, is endogenously determinedwithinthemodel); ii. Energy efficiency would improve by 0.5 per cent per annum over the period 2004 to 2020, across all energy consumption sectors. This rate of growth is applied to determine changes in energy intensities (C matrix). This rate is in accord with those adopted by most developed countries (for example, Cruz 2002;Hoeller,Dean&Nicolaisen1991;Nakicenovic&Swart2000); iii. Labour productivitywouldimprove by 1.7 per cent peryearinthe2000sand 1.75percentinthe2010s(Costello2002).Theseratesareappliedtodevelopthe labouroutputratios(thatis,matrixl);and SeeSection3.3.3foradiscussionofcarbontax,basedontheSharedResponsibilityPrinciple. 43 139 iv. The existing nationbased Mandatory Renewable Energy Target (MRET) schemewouldexpirein2010.Thisisinaccordwiththecurrentgovernment’s intentionofnotextendingthescheme.TheMRETrequireselectricityretailersto source2percentoftotalelectricityfromrenewablesources(Roarty2001). Further,itshouldbenotedherethattheBaseCase(notedabove)isdevelopedinthis research with the sole objective of providing a basis for comparing the impacts of a carbontaxbasedonPPPandSRPprinciples,thatis,itactsasacomparisonbenchmark. In addition to the above cases (that is, PPP1, SRP1, PPP2, and SRP2)44, analysis is performed in Section 6.4 to assess the impacts of achieving a predetermined CO2 emissions reduction target. This target is set to allow total CO2 emissions from the electricity sector to increase to 108 per cent of 1990 levels by the year 2020. This emissionstargetisset,inthisresearch,tobeachievedfromtheelectricitysectoralone becauseofthefocusofthisresearch,namely,thattheelectricitysectorwouldreorient its technology and fuel mix for electricity generation in response to a carbon tax. For otherproductionsectors,thisresearchassumedazeroelasticityofsubstitution,which implies that these sectors will not adjust their production levels in response to the introduction of a carbon tax. This assumption means that the analysis will underestimatetheCO2reductionpotentialandoverestimatetheeconomiccoststothe economy.45Thisisbecausesuchanassumptiondoesnotallowotherproductionsectors (except the electricity sector) to substitute their emissionintensive expensive inputs (due to the carbon tax) with lowemission cheaper inputs. The highprice emission intensive inputs in these sectors are continuously used in the same (Leontief) proportioninwhichtheywereusedbeforethecarbontaxisimposed. DefinedinSection6.3 Amodelwasalsorun,asatest,byassumingotherproductionsectorstobeperfectsubstitutes inthe use of factorinputs in responsetochanges in price duetothecarbon tax. The results showthat,inthecaseofPPP1,themodeloverestimatestotaleconomiccosts(GDP)by0.09per cent($5.6billionin1990prices)andunderestimatesCO2reductionpotentialby15percent(58 Mt). 44 45 140 The target, analysed in this research, is deliberately selected reflecting the level requiredfortheAustralianeconomytomeettheinternationalobligationsoftheKyoto Protocol.46 6.3 AnalysisoftheImpactsofAlternativeCarbonTaxRegimes This section analyses energy, environmental, economic, and social impacts of alternative carbon tax regimes. This analysis is carried out separately for energy balance (Polluter Pays Principle) and materialsbalance (Shared Responsibility Principle)approaches.Fourcases,denotedPPP1,SRP1,PPP2,andSRP2,areanalysedin thisresearch.PPP1andSRP1refertothecaseofacarbontaxof$10 pertonneofCO2 emissions,basedontheenergybalance(PPP)andmaterialsbalance(SRP)approaches, respectively. PPP2 and SRP2 refer to the case of a carbon tax of $20 per tonne of CO2 emissions,basedontheenergybalance(PPP)andmaterialsbalance(SRP)approaches, respectively.Section6.3.1discussesenergyandenvironmentalimpacts.Theeconomic andsocialimpactsarediscussedinSection6.3.2.Theseimpactsareassessedbasedon attributespresentedearlierinFigure61. 6.3.1 EnergyandEnvironmentalImpacts This section estimates changes in primary energy requirements and associated CO2 emissionsinresponsetotheintroductionofcarbontax.Theseestimationsarebasedon the application of equations 534 and 535, as discussed in Section 5.6. As mentioned earlier,theintroductionofacarbontaxwouldresultinchangesinthecompositionof the fuel and technologymix for electricity generation. These changes would then influence the primary energies required to produce electricity, and hence CO2 emissions.Thereforethissectioncommenceswithadiscussionofchangesthatacarbon taxwouldinduceinthecompositionofelectricitygenerationtechnologyandfuelmix TheKyoto targetrequiredtheAustralianeconomytoreachthislevelby2008–12.However, thisresearchextendsthistargetto2020,sothatmorerealisticanalysiscanbeperformed(that is,meetingthetargetin15years). 46 141 (Section 6.3.1.1). This is followed by an analysis of the changes in primary energy requirements (Section 6.3.1.2). The issue of energy diversity is briefly discussed in Section6.3.1.3.Finally,theenvironmentalimpacts,intermsofCO2emissions,ofeach carbontaxregimeareanalysedinSection6.3.1.4. 6.3.1.1 ChangesintheCompositionofElectricityGenerationTechnology Thetechnologymixforelectricitygenerationwouldbeinfluencedbytheintroduction of carbon tax. Each approach to carbon tax (that is, based on PPP and SRP) would, however,resultinadifferentlevelofincreaseinthecostofelectricitygenerationand hence a different level of change in the technologymix. The increase in the cost of electricity would clearly depend on the CO2intensiveness of various inputs used for electricity production. The determination of the shares of electricity production by differenttechnologies(asdefinedinTable56)isbasedontheleastcostcriteria,thatis, thelowestcosttechnologywouldbeselectedfirst,andhighest,thelast.Thechangein electricitygenerationtechnologymixinresponsetotheintroductionofcarbontax,in this research, includes a switch from highemission technology (such as coalfired) to lowemissiontechnology(suchascombinedcycle)orrenewablegeneration.Electricity generatedfrominternalcombustionisassumed,inthisresearch,toretainitsshareof the overall generation, as this technology supplies electricity mainly in remote areas where electricity demand is rather insignificant. Further, the rate of switch between varioustechnologiesisconstrained,inthisresearch,toamaximumof2.6percentper year.Thisrateisusedbecausethisistheaveragerateofannualcapacityreplacement inAustraliaoverthelast30years(Creedy&Martin2000). The technologymix for electricity generation under different carbon tax rates is presentedinTable61. 0.2 1.7 3.6 8.6 IC GT CC RE 10.2 3.6 1.7 0.2 84.2 BC 10.2 3.6 1.7 0.2 84.2 PPP1 10.2 3.6 1.7 0.2 84.2 SRP1 2010 10.2 3.6 1.7 0.2 84.2 PPP2 10.2 5.9 1.7 0.2 81.9 SRP2 Table61 10.2 3.6 1.7 0.2 84.2 BC 10.2 3.6 1.7 0.2 84.2 PPP1 10.2 11.4 1.7 0.2 76.4 SRP1 2015 15.4 8.8 1.7 0.2 73.8 PPP2 15.4 13.7 1.7 0.2 68.9 SRP2 10.2 3.6 1.7 0.2 84.2 BC Technologymixforelectricitygeneration 10.2 14.0 1.7 0.2 73.8 PPP1 12.8 21.8 1.7 0.2 63.4 SRP1 2020 28.4 8.8 1.7 0.2 60.8 PPP2 28.4 13.7 1.7 0.2 55.9 SRP2 (Percent) 142 BCsfortheyears2010,2015and2020aredifferentfromtheyear2005becauseoftheexpirationoftheMRETschemein2010; CF:Coalfired,IC:Internalcombustion,GT:Gasturbine,CC:Combinedcycle,RE:Renewableelectricity; BC:BaseCase;PPP1&PPP2:carbontaxof$10and$20pertonneofCO2emissions,basedonthePPP(orenergybalanceapproach);SRP1&SRP2:carbontaxof$10 and$20pertonneofCO2emissions,basedonSRP(ormaterialsbalanceapproach); ThistableisobtainedfromdetailedresultspresentedinTablesF8,AppendixF,p.343. 85.8 BC 2005 CF Notes: 143 Thetableshowsthat: i. Ingeneral,theintroductionofacarbontaxwouldcausetheshareofcoalfired powergenerationtodecrease.Thisisbecausetheincreaseinthecarbontaxrate wouldincreasethecostofelectricitygeneratedfromcoalfiredtechnologyata higherratecomparedtootherlessCO2intensivetechnologies.Forexample,for the case PPP1, the share of coalfired power generation would decrease by 12 per cent (from 85.8 per cent in 2005, to 73.8 per cent in 2020); whereas for the casePPP2,itwoulddecreaseby25percent(to60.8percentin2020). ii. AcarbontaxbasedonSRPwouldgenerallyleadtoalargerreductionincoal fired power generation compared to that based on PPP, for the same level of tax. For example, for a carbon tax of $20 per tonne of CO2, the share of coal fired power generation would decrease to 55.9 and 60.8 per cent for the cases SRP2andPPP2,respectively.Further,inthecaseofSRP2,theshareofcoalfired powergenerationwouldstarttodeclineasearlyas2009(seeTable62),which showsareductionof3.9percent(from85.8percentin2005,to81.9percentin 2010). iii. A carbon tax of $10 per tonne of CO2, applied on the basis of PPP, does not result in the introduction of renewable power generation in the electricity market. For example, the share of renewable electricity in 2010, 2015, 2020 remains at 10.2 per cent. This is because renewable technology is unable to compete with any other technology at this tax rate. A tax of $20 per tonne of CO2,ontheotherhand,whilehavingnoeffectfortheyear2010(withashareof 10.2 per cent), would result in a sharp increase after the year 2013 (see Table 62). The share of renewable electricity, in the case of PPP2, would reach 28.4 percentintheyear2020. iv. A carbon tax based on SRP has more potential in attracting cleaner electricity generationtechnologytotheelectricitymarketcomparedtothatbasedonPPP. Forexample,foracarbontaxof$10pertonneofCO2,thesharesofrenewable electricitywouldincrease,from8.6percentin2005,to12.8and10.2percentin 144 2020forthecasesSRP1andPPP1,respectively.Thecorrespondingincreasesin thesharesofcombinedcycleelectricityforthecasesSRP1andPPP1arefrom3.6 percentin2005to21.8and14percent,respectively. These reductions in coalfired technology are due to the cost disadvantage this technologywouldsufferasaresultofcarbontax.Thiscostdisadvantagewouldresult in their replacement by either naturalgasbased combinedcycle or renewablebased technologies. The foregoing discussion also suggests that the question of changes in the electricity technologymix should be discussed together with the increase in electricity supply costs because the costs associated with changes in technologymix are likely to be reflected in the changes in the cost of electricity. The cost of electricity is expected to increase when the entry of new coalfired plants (which is currently the leastcost technology) is restricted due to the carbon tax and/or MRET scheme. It is also importanttonoteherethatthecostofelectricity,consideredinthisresearch,doesnot takeintoaccounttheautonomouscostreductionofnewtechnologiesastheybecome more mature in the future. In reality, it is expected that the future renewable technologywouldbecheaperthanthatatthepresenttime. The impact of the different cases of carbon tax on total electricity supply costs is presentedinTable62. Table61and62showsthat: i. IntheBaseCase(BC),thereductionintheshareofcoalfiredpowergeneration from 85.8 per centin2005to84.2 per centin each ofthe years2010, 2015and 2020isduetoamodestpenetrationbyrenewabletechnology,drivenmainlyby the MRET scheme. The increase in cost, over the period 2004–2020, of 0.22 ¢/kWh(from4.7¢/kWhin2004to4.92¢/kWhin2020)(Table62),inthiscaseis 145 attributed only to the replacement of cheaper technology with the expensive technologythroughenforcement.47 Table62 Electricitysupplycosts (¢/kWh,2004prices) SRP1 PPP1 BC PPP2 SRP2 2004 CF 4.70 CF 4.70 CF 4.70 CF 4.70 CF 4.70 2005 CF 4.74 CF 5.30 CF 5.59 CF 5.89 CF 6.48 2006 CF 4.77 CF 5.89 CF 6.46 CF 7.07 CF 8.20 2007 CF 4.81 CF 6.47 CF 7.32 CF 8.22 CF 9.87 2008 CF CF 4.84 4.88 CF CF 7.04 7.60 CF CF 8.15 8.97 CF CF 9.35 10.45 CF CF 11.48 13.04 2011 CF CF 4.92 4.92 CF CF 8.16 8.71 CF CF 9.77 10.56 CF CF 11.54 12.61 CC CC 14.53 15.96 2012 CF 4.92 CF 9.26 CF 11.34 CC 13.65 CC 17.32 2013 CF 4.92 CF 9.80 CC 12.08 CC 14.67 CC 18.63 2014 CF 4.92 CF 10.34 CC 12.81 RE 15.64 RE 19.86 2015 2016 CF CF 4.92 4.92 CF CF 10.87 11.39 CC CC 13.51 14.18 RE RE 16.56 17.43 RE RE 21.02 22.12 2017 CF 4.92 CC 11.91 CC 14.84 RE 18.27 RE 23.15 2018 2019 CF CF 4.92 4.92 CC CC 12.41 12.90 CC CC 15.47 16.09 RE RE 19.06 19.82 RE RE 24.12 25.03 2020 CF 4.92 CC 13.38 RE 16.67 RE 20.53 RE 25.90 2009 2010 Notes: CF:Coalfired,IC:Internalcombustion,GT:Gasturbine,CC:Combinedcycle,RE: Renewable; BC:BaseCase;PPP1&PPP2:carbontaxof$10and$20pertonneofCO2emissions,basedon thePPP;SRP1&SRP2:carbontaxof$10and$20pertonneofCO2emissions,basedonSRP; Foreachcase,thefirstcolumnisthetechnologythatpresentstheleastcosttechnologyfor thatyearandthesecondcolumnisthetotalelectricitysupplycost; ThistableisobtainedfromdetailedresultspresentedinTablesF9,AppendixF,p.345. ii. For PPP1, the combinedcyclebased electricity becomes costcompetitive compared with coalfired electricity in the year 2017. As a result, its share increasesby10.4percent(from3.6percentintheyear2005to14percentinthe year 2020) (see Table 61). The replacement of coalfired with the combined Thisincreaseincostof0.22¢/kWhintheBCcasedoesnotreflectthemarketbasedselection of electricity generation technology and, hence, the real cost is hidden somewhere in the economy. 47 146 cycle would increase the cost of electricity by 8.7 ¢/kWh (from 4.7 to 13.4 ¢/kWh)overtheperiod2004–2020. iii. For the case of PPP2, combinedcycle and renewable technologies would penetrate in the market in the years 2012 and 2014, respectively. This would resultinanincreaseintheshareofcombinedcycleby5.2percent(from3.6per cent in 2005 to 8.8 per cent in the year 2020), and renewable by 19.8 per cent (from 8.6 per cent in the year 2005 to 28.4 per cent in 2020) (Table 61). This change in electricity technologymix would increase its cost by 15.8 ¢/kWh (from4.7¢/kWhin2004,to20.5¢/kWhin2020)(Table62). iv. For the case of SRP1, combinedcycle and renewable electricity would become competitive in the years 2013 and 2020, respectively. As a result, the share of combinedcycleelectricitywouldincreaseby18.2percent(from3.6percentin 2005to21.8percentin2020),andrenewableby4.2percent(from8.6percent in2005to12.8percentin2020)(Table61).Thereplacementofcoalfiredwith combinedcycleandrenewablewouldincreasetheelectricitysupplycostby12 ¢/kWh over the period 2004–2020 (from 4.7 ¢/kWh in 2004 to 16.7 ¢/kWh in 2020)(Table62). v. For SRP2, combinedcycle and renewable electricity would penetrate in the market in the years 2010 and 2014, respectively. As a result, the share of combinedcycle would increase by 10.1 per cent (from 3.6 per cent in 2005 to 13.7percentin2020),andrenewableby19.8percent(from8.6percentin2005 to 28.4 per cent in 2020) (Table 61). This change in electricity technologymix would increase its cost by 22.2 ¢/kWh over the period 2004–2020 (from 4.7 ¢/kWhin2004to25.9¢/kWhin2020)(Table62). It can also be seen that when a higher level of tax (that is, $20 per tonne of CO2) is imposedbasedonthe directuseof fossilfuel (thatis,PPP2),there wouldbe an early change in the composition of the electricity technologymix. For example, electricity producedfromcombinedcycletechnologybecomesacosteffectiveoptionin2012and 2013 and, in 2014, it loses its position to renewable technology. In contrast, when 147 carbontaxisimposedbasedonthematerialsbalanceapproach(thatis,SRP2),thereisa steady transition from highly polluting coalfired technology to less polluting combinedcycleandthentorenewabletechnology.Thishappensbecausethemarginal costs of electricity generated from both combinedcycle (4.1–6.7 ¢/kWh) and other fossilfuelbasedtechnologies(3.5–4.0¢/kWh)areverysmall(seealsoTable22).When a carbon tax is introduced, the threshold of competition between different fossilfuel technologiesisalsosmall,particularlywhencomparingthemwiththemarginalcostof renewable technologies (7.3–54.9 ¢/kWh). If a tax of more than $20 is introduced, it would clearly show that – based on the energybalance approach – combinedcycle wouldneverbecomeacompetingtechnology. It is clear from discussion in this subsection that changes in the composition of the electricity technologymix, brought about by the application of different carbon tax approaches,wouldhavedifferentramificationsintermsofthefuelmixforelectricity generation, primary energy requirements, CO2 emissions and the consequential economywideimpacts.Theseimpactsarediscussedinthefollowingsubsections. 6.3.1.2 PrimaryEnergyConsumption Over the past 25 years (1980 to 2005), primary energy consumption for electricity productionhasbeenincreasingatanaveragerateofabout3percentperannum,from 1,138 PJ in 1980 to 2,404 PJ in 2005 (see Figure 62). This increasing trend is likely to continuetotheyear2020intheBC,althoughtherateofannualgrowthislikelytobe2 per cent between 2004 and 2020. This is equivalent to 3,248 PJ of primary energy in 2020 (see Figure 62). This reduction in the rate of growth from 3 per cent over the period1980–2004to2 percentoverthe period2004–2020is due to: i)aslowdown in economicactivityfrom3.3percentperyearduring1980–2004to2.5percentperyear during 2004–2020; and ii) improvements in energy efficiency of 0.5 per cent per year (seeassumptionsinSection6.2). Figure62comparestheprimaryenergymixforelectricityproductionforvariouscases analysedinthisresearch. 1980 BC 2000 BC BlackCoal 1990 BC Figure62 BC 2010 BC NaturalGas P P P 1 S RP 1 P P P 2 S RP 2 BrownCoal 2005 BC Petroleum 2015 P P P 1 S RP 1 P P P 2 S RP 2 Primaryenergyconsumptionforelectricityproduction BC Renewable 2020 P P P 1 S RP 1 P P P 2 S RP 2 148 Thisfigurepresentsthesummaryofresultsobtainedfromtheapplicationofequation534,asdetailedinChapter5,Section5.6.Fordetailresults–seeTablesF10, AppendixF,pp.346348. 0 500 1,000 1,500 2,000 2,500 3,000 3,500 Notes: (Petajoules) 149 Thefigureshowsthat: i. In the BC scenario (without carbon tax), coal continues to play an important roleintheelectricityindustry.48Forexample,itaccountsfor75percentofthe totalprimaryenergyconsumedin2020(thatis,2422outof3248PJ). ii. The impact of carbon tax on primary energy consumption is very significant. Forexample,theintroductionofcarbontaxwouldresultinareductionof10.2 (330PJ),19.9(647PJ),20.1(653PJ),and35.4(1148PJ)percentforPPP1,SRP1, PPP2,andSRP2,respectively,ascomparedtotheBC(3248PJ).Thisisduetoa switchfromhighemissiontolowemissionfossilfueltechnologyforelectricity production. iii. The role of coal in electricity production is considerably reduced with the introduction of a carbon tax. For example, a carbon tax of $10 and $20 per tonne, based on the energybalance approach (PPP1 and PPP2) would reduce theshareofcoalby13and24percent,respectively,fromtheyear2005when coalaccountedfor76percentoftotalprimaryenergyconsumedforelectricity production. When a carbon tax is imposed based on the materialsbalance approach,theshareofcoalwoulddecreaseby24and31percent,respectively, for SRP1 and SRP2. This shows that the rate of reduction in the use of coal is fasterwhentaxisimposedontotalfueluse(thatis,materialsbalance),which wouldresultinsubstantialincreaseinnaturalgas(from15percentin2005to 35percentin2020inthecaseSRP1)andrenewable(from9percentin2005to 28percentin2020inthecaseSRP2). iv. The extent of substitution of coal with either natural gas or renewable varies, depending on the rate of technology penetration in each carbon tax case. For example, in the case PPP1,theuse ofnaturalgas would be282PJ higher than the BC. This is because of the increased share of natural gasbased combined cycleinthetotalelectricitygeneration.Incontrast,theuseofrenewableenergy Thisresultreinforcestheinfluenceofthecoal–electricitycompact,asdiscussedinChapter2. 48 150 inthecasePPP2wouldbe406PJhigherthantheBCduetoanincreaseinthe shareofrenewabletechnologyforelectricityproduction.Similarly,inthecase of SRP1, the use of natural gas would be 441 PJ higher than the BC; while the useofrenewableenergyinthecaseofSRP2wouldbe265PJhigherthantheBC. 6.3.1.3 EnergyDiversity Energydiversityplaysanimportantrole,notjustinrelationtothesecurityofenergy supply,butalsointermsofthelevelofenvironmentalemissions.Thissectionanalyses the impact of various carbon tax regimes (PPP1, SRP1, PPP2 and SRP2) on energy diversity. Thecompositionofprimaryenergyconsumption(forelectricityproduction)isusedas amainindicatorforassessingenergydiversity.Asimplediversityindex,basedonthe classic Herfindahl measure of market concentration, is used to quantify energy diversity(Neff1997).TheHerfindahldiversificationindexisexpressedas: H ¦x 2 i (61) i where H: Herfindahlenergydiversificationindex;and xi: afractionoftotalenergysupplyfromeachisource. TheHerfindahlindexrangesbetween0and1,withanumberclosertozerosignifying largediversity,andnumbercloserto1alowdiversity. Inthisresearch,fivetypeofprimaryenergiesareconsidered.Theseincludeblackcoal, browncoal,naturalgas,petroleum,andrenewableenergy. 151 Table63 Primaryenergyconsumptionandenergydiversity 2020 1980 2000 SRP1 PPP2 PPP1 BC PrimaryEnergyConsumption(PJ) 1,138 2,180 3,248 2,918 2,601 2,595 Blackcoal(%) 47.9 49.8 45.9 39.1 31.8 32.2 Browncoal(%) 25.3 30.5 28.6 24.3 19.8 20.1 Naturalgas(%) 6.7 10.0 14.4 25.6 34.9 18.6 Petroleum(%) 4.5 1.1 0.9 0.8 0.7 0.7 Renewable(%) 15.6 8.6 10.2 10.2 12.8 28.4 HerfindahlIndex 0.57 0.66 0.59 0.48 0.40 0.39 SRP2 2,100 27.7 17.3 26.0 0.7 28.4 0.35 The fractions of different types of primary energy consumption for electricity production and associated energy diversity index are summarised in Table 63. The tableshowsthat: i. Duringtheperiod1980–2000,theshareoffossilfuels(thatis,blackandbrown coal,naturalgas,andpetroleum)intotalelectricityproductionincreasedfrom 84percentin1980,to91percentin2000.Overthisperiod,theshareofcoalin electricityproductionincreasedfrom73percentto80percent,andofgasfrom 7to10percent.Theshareofoildecreasedfrom4percentin1980to1percent in2000.Thesechangesinthesharesoffossilfuelshaveresultedinanincrease inthevalueoftheHerfindahlindexfrom0.57in1980,to0.66in2000. ii. Theshares ofvariousfuelsinelectricityproduction –intheBCscenario–are likelytochangeonlyslightlyby2020.Thesechangesareexpectedtobepartly due to the increasing use of natural gas in the recent years as combinedcycle power plants enter the electricity market, and partly to the increase in renewableelectricity,duetotheMRETscheme.Thischangeinfuelmixwould result in a Herfindahl index of 0.59 in the year 2020, thus signifying a small improvementinenergydiversity. iii. Each of the carbon tax cases would result in decreased shares of fossil fuels, particularly coal. This is replaced by natural gas and renewable for all cases, exceptanincreaseinrenewableenergyinthecaseofPPP1.Thiswouldresultin 152 fueldiversityindicesof0.48,0.40,0.39,and0.35forPPP1,SRP1,PPP2,andSRP2, respectively. iv. Themostnotableresultoftheanalysisinthissectionisthatthehigherthelevel of carbon tax, the higher the energy diversity. For example, for the case PPP1, the Herfindahl index would be 0.48 (compared to 0.59 in the BC case). When the level of tax is raised to $20 per tonne (PPP2), energy diversity would increase,(thevalueofindexwouldbe0.39). v. Also, a higher energy diversity would be achieved in the case of SRP as comparedtothePPP.Forexample,thediversityindicesinthecaseofSRP1and SRP2are0.4and0.35,respectively(thecorrespondingvaluesforPPP1andPPP2 are0.48and0.39,respectively). 6.3.1.4 CarbondioxideEmissions InthissectiontheimpactofcarbontaxonCO2emissionsispresented.Includedinthis presentationareCO2emissionsforthefourcases,namely,PPP1,SRP1,PPP2,andSRP2. These emissions are then compared with the emissions in the BC scenario. Also includedinthepresentationisacomparisonoffourcasesofCO2emissionswithCO2 emissionsatthe1990level(thatis,Kyototargets).Thiswouldenableanassessmentto bemadeofhoweachofthefourcasesofcarbontaxcompareswiththeKyototargets. TheresultsareshowninFigure63andTable64. 153 Figure63 (Milliontonnes) Carbondioxideemissionsfromfossilfuelcombustion 300 250 200 150 108%of1990levels, fromtheelectricitysector 100 50 1980 1985 1990 1995 2000 2005 2010 2015 2020 (Milliontonnes) a)Electricitysector 450 400 350 300 BC 250 PPP1 Kyototarget SRP1 200 PPP2 150 SRP2 1980 1985 1990 1995 2000 2005 2010 2015 2020 b)Economy Notes: Thisfigurepresentthesummaryofresultsobtainedfromtheapplicationofequation535,as detailedinChapter5,Section5.6.Fordetailedresults,seeTablesF11,AppendixF,pp.351 352. 154 Table64 BC 2005 2010 2015 2020 2005 2010 2015 2020 47 63 78 95 Notes: Percentagechangesincarbondioxideemissions PPP1 SRP1 PPP2 SRP2 BC PPP1 SRP1 PPP2 Electricitysector Economywide ComparisonwithBCscenario – – – – – – – 3.9 8.9 7.6 17.7 3.1 6.9 6.0 7.5 19.6 21.9 36.4 5.9 14.5 15.5 15.6 31.2 39.3 53.5 11.2 22.4 26.6 Comparisonwith1990level 47 47 47 44 38 38 38 38 57 49 51 35 54 50 44 45 65 44 39 14 69 59 44 43 65 34 18 9 84 64 43 35 SRP2 – 13.5 26.6 38.3 38 34 24 14 ThistablepresentsthepercentagechangesinCO2emissions,calculatedfrominformation containedinFigure6.3.Forbackgrounddataandfurtherdetails,seeTablesF11,AppendixF, pp.251252. Figure63andTable64showthat: i. In 1990, CO2 emissions from fossil fuel combustion in Australia (as estimated fromequation535)totalled234Mt.Theelectricityindustryaccountedforover 50percentoftheseemissions(128Mt).49 ii. IntheBCscenario,totalCO2emissionsfromfossilfuelcombustionareexpected toincreasesignificantly,reaching432Mtby2020.Thisrepresents184percent of 1990 emissions level (234 Mt). CO2 emissions from the electricity sector would increase to 250 Mt, which is approximately 58 per cent of total CO2 emissions. The strong growth in electricitysector CO2 emissions occurs even undertheexistingMRETscheme. iii. ThegrowthrateofCO2emissionsreducessubstantiallyduetotheintroduction of a carbon tax. For example, the CO2 emissions from the electricity sector wouldbe211,172,152,and116Mt,respectively,forPPP1,SRP1,PPP2,andSRP2 –thusrepresentingareductionintherangeof15.6to53.5percentfromtheBC NationalGreenhouseGasInventoryestimatesofCO2emissionsin1990fromfuelcombustion activitywere254Mt,withtheelectricitysectorcontributingto129Mt(AGO2005).However, thisresearchisconcernedwithpercentagereductionandthesmalldifferenceintheestimates doesnotaffecttheresults. 49 155 scenario.Thisisbecausetheapplicationofcarbontaxinducesashiftawayfrom carbonintensiveenergy. iv. Also,CO2emissionsreducemorewhenacarbontaxisappliedbasedonSRP, comparedwithwhenitisbasedonPPP.Forexample,CO2emissionsfromthe electricitysectordecline,by2020,by31.2and53.5percentoftheBClevel,for SRP1andSRP2.ThecorrespondingfiguresforPPP1 andPPP2are15.6and39.3 per cent, respectively. Further, it is noticed that the rate of CO2 emission reduction from SRP1 is closer to the emissions reduction achieved from PPP2. ThisissobecauseacarbontaxbasedonSRPalsotakesintoaccountofenergy embodied in materials and, therefore, penalise the emitters from indirect energy consumption. The introduction of such tax would increase the cost of electricityproductionatahigherratethanifacarbontaxisimposedunderPPP (see Table 62). As a result, it would allow cleaner electricity production technologytopenetratethemarketearlierthanifcarbontaxisbasedonPPP. v. ExceptforSRP2,theimpactintermsofCO2emissionreductionforothercases (thatis,PPP1,SRP1,andPPP2),willbegintobefeltonlyintheyearsafter2010. Forexample,inthecasePPP2,CO2emissionsfromtheelectricitysectorin2010 wouldbe51percent(anetincreaseof65Mt)abovethe1990emissionlevel,but woulddeclineto39percent(anetincreaseof50Mt)in2015and18percentin 2020(anetincreaseof23Mtcomparedwith1990).Thisisbecause,inthecase PPP2, combinedcycle and renewable technologies would penetrate in the electricitymarketin2012and2014,respectively. vi. InthecaseSRP2,CO2emissionsfromtheelectricitysectorfallbelowtheKyoto target. For example, the total CO2 emissions from the electricity sector from SRP2in2020wouldbe91percent(116Mt)ofthe1990level.Incontrast,inthe casePPP2,CO2emissionswouldbe118percent(152Mt)ofthe1990level.This impliesthat,inordertoachievetheKyototargetof108percent(138Mt)ofthe 1990levelfromtheelectricitysector,ahigherlevelofcarbontax(morethan$20 per tonne) would be required if carbon tax is based on PPP than when the carbontaxisbasedonSRP(thispointisfurtherdiscussedinSection6.4). vii. 156 Further,changesinthemixofelectricitytechnologyalone,whenacarbontaxof $20 per tonne of CO2 is applied based on SRP, would almost achieve total economywideKyototargetof108percent(253Mt)ofthe1990level(234Mt). Atthisrate,economywideCO2emissionswouldbejust14MtabovetheKyoto target (or 114 per cent of the 1990 level). This implies that if the response of carbon tax from other sectors is also captured (that is, by employing flexible production function for other sectors instead of the Leontief’s), it would have shown that even a carbon tax of less than $20 would be able to achieve the economywideKyototarget,whenacarbontaxisbasedonSRP. 6.3.2 EconomicandSocialImpacts This section analyses economic and social impacts of carbon tax (based on the application of equations 532 and 537, discussed in Section 5.6). These impacts, like energyandenvironmentalimpacts(analysedinSection6.3.1),aremainlydrivenbythe changesininvestmentdemandduetotheapplicationofacarbontaxthatisexpected to result in a change in electricitygeneration technology and fuel mix. This section starts with a discussion on the economic impacts of carbon tax, both on the overall economyandonindividualeconomicsectors(Section6.3.2.1).Then,thesocialimpacts (that is, the impact on employment) of each carbon tax case are presented in Section 6.3.2.2. 6.3.2.1 EconomicImpacts Theresultsobtained,usingthemethodologyexplainedinChapter5(Section5.6),are presentedinTable65andFigures64to610.Thefollowingdiscussionanalysesthese results. Overall Economic Output: the total economic output, as mentioned in Section 5.6, refers to the sum of the output of each economic sector to fulfil the demand for domestic final as well as intermediate consumption, investment, and net exports. However,intermediateconsumptionisnotincludedinGDPaccount.Theimpactofa carbon tax on economic output, in this research, is assumed to be influenced by the 157 changes in various final demand categories. This impact is shown in Table 65 and Figure64. Table65 Impactsofcarbontaxoneconomicoutput:2005–2020 BC PPP1 SRP1 PPP2 SRP2 ($Billion1990) † PPP1 SRP1 PPP2 SRP2 (percentagechangesfromBC) 6,325 6,270 6,205 6,223 6,106 0.88 1.90 1.62 12,592 12,446 12,279 12,321 12,023 1.16 2.49 2.16 4.52 Finalconsumption 4,940 4,887 4,822 4,842 4,725 1.08 2.39 2.00 4.37 Investment 1,666 1,665 1,663 1,666 1,663 0.08 0.21 0.03 0.20 Exports 1,135 1,113 1,086 1,091 1,045 2.01 4.31 3.88 7.96 Imports 1,417 1,395 1,367 1,376 1,326 1.55 3.52 2.90 6.41 Intermediateconsumption 6,267 6,177 6,075 6,098 5,917 1.45 3.07 2.71 5.59 GDP ‡ Totaloutput 3.46 Notes: † GDP=Finalconsumption+Investment+(Exports–Imports) ‡ Totaloutput=GDP+Intermediateconsumption Thistablesummarisesthepresentvalueofeachoftheeconomicvariable,fortheperiod2005– 2020,usingadiscountrateof8percent; TheresultspresentedinthistablearecalculatedfrominformationcontainedinTablesF1to F5,AppendixF,pp.288332,usingequation532asdetailedinChapter5,Section5.6. Theresultsuggestthat: i. In general, the introduction of a carbon tax would lead to a slowdown in economicactivity(thatis,GDP),withasignificantlygreaterimpactoccurringat ahighertaxrate(thatis,$20pertonne)(Figure64a).Forexample,acarbontax based on PPP1 would cause GDP over the period 2005–2020 to reduce by $56 billion(0.88percent),comparedtotheBCscenario;whereas,inthecasePPP2, theeconomywouldlose$102billion(1.62percent)ofGDP.50Also,acarbontax based on SRP would cause a higher negative impact on economic growth, comparedwiththeonebasedonPPP.Forexample,atacarbontaxrateof$10 per tonne, GDP in the case SRP1 would decline by $120 billion (1.9 per cent), andby$219billion(3.46percent)inthecaseofSRP2. The economic impact in the case of PPP, calculated in this research, is of an order of magnitudethatiscomparabletootherstudiesshowninTable32,Chapter3. 50 158 Figure64 Annualpercentagechangesineconomicparameters 0 0 2005 2010 2015 2020 -1 -1 2005 2010 2015 2020 -2 -2 -3 -3 -4 -4 -5 -5 -6 -7 -6 -8 -7 -9 -8 -10 a) Gross Domestic Product -9 -11 b) Total Output 0 0 2005 2010 2015 2005 2020 2010 2015 2020 -2 -2 -4 -4 -6 -6 -8 -8 -10 -10 -12 c) Final consumption d) Intermediate consumption -12 -14 0.4 0 -2 2005 2010 2015 2020 0.2 -4 -6 0.0 -8 -10 -0.2 2005 2010 2015 2020 -12 -0.4 -14 -16 -18 -0.6 e) Export -20 Notes: f) Investment -0.8 ThesefiguresshowannualpercentagechangeofeachcarbontaxcasecomparedwiththeBC; Fordetailedresults,seeTableF1toF5,AppendixF,pp.288332. ii. 159 The introduction of a carbon tax would have a larger effect on industry (in termsofintermediateconsumption,Figure64d)thanonhouseholds(interms of final consumption, Figure 64c). This would be the case for both types of carbontaxes(thatis,PPPandSRP).Forexample,asshowninTable65,whena carbon tax of $10 per tonne is imposed based on PPP, households and industrieswouldreducetheirconsumption,overtheperiod2005–2020,by1.08 and1.45percent,respectively.Thecorrespondingfiguresforsuchataxbased onSRPare2.39and3.07percent,respectively. iii. Theimpactofacarbontaxwouldbemostsignificant(inpercentageterms)for the export sector (Figure 64e). For example, in the case PPP1, while the economic output (GDP) over the period 2005–2020 declines by 0.88 per cent, exports reduce by 2.01 per cent. Also, a carbon tax based on SRP would have higherimpactonexportsthanataxthatisbasedonPPP.Whenacarbontaxof $10 per tonne is imposed based on SRP (i.e., SRP1), exports would decline by 4.31percent(comparedwith2.01percentinthecasePPP1). iv. Incontrasttotheimpactofcarbontaxonexportsandconsumption,investment wouldbeleastaffectedbytheintroductionofcarbontax.Forexample,overthe period2005–2020,thevalueofinvestmentwouldreducebyjust0.08($1billion) and 0.21($3billion) percentforthecasesPPP1andSRP1,respectively.Thisis because a reduction in coalfired electricity, due to the introduction of carbon tax, would be replaced by an investment in cleaner technologies, such as combinedcycle and renewable electricity. Interestingly, when the level of carbon tax increases, the impact on investment would be even lower (for example, it would be 0.03 per cent in the case of PPP2). This is because an increaseinthelevelofcarbontaxwouldsignificantlyacceleratetheinvestment incleanerelectricitytechnologies(atratesfasterthanthecasewithlowerlevels ofcarbontax)(seeTable62). v. ItisalsonoticedfromFigure64thattheeconomicimpactofacarbontaxof$10 per tonne based on SRP is of a similar magnitude to that of a tax of $20 per tonnebasedonPPP.Forexample,a$10pertonneofcarbontaxbasedonSRP 160 would cause GDP over the period 2005–2020 to reduce by 1.9 per cent, comparedtotheBCscenario;whereas,inthecasePPP2,theGDPwoulddecline by 1.62 per cent. This is so because a carbon tax based on PPP would be imposed on direct fuel consumption only; whereas, for SRP, it would impose on direct as well as indirect fuel consumption. As a result, a smaller tax rate basedonSRPwouldhaveasimilarimpactontheeconomy,comparedwitha highertaxratebasedonPPP. SectoralEconomicOutputs:Theimpactofcarbontaxoneconomicactivity(GDP),as discussedabove,istheaggregateofimpactsonindividualsectorsoftheeconomy.As discussed above, a carbon tax would result in a reduction in economic growth. However, not all sectors of the economy would be equally affected. The outputs of some sectors would, in fact, increase in response to the introduction of a carbon tax. TheresultsoftheimpactsonindividualsectoraloutputsarepresentedinFigures65to 610. 50 (-46.3) (-42.1) 40 (-34.6) 30 (-25.0) (-23.5) (-26.3) (-27.2) (-14.1) (-13.4) (-15.2) 20 (-19.3) 10 (-8.3) (5.1) (10.5) (-1.3) (-0.6) (9.8) 10 (4.6) (6.9) (2.7) 0 ($billion1990) (-8.4) (-7.8) (-4.7) (-6.2) (-7.1) (-4.2) (-5.2) 20 10,000 6,000 4,000 (-5,413) (-4,478) (-47) (-58) (636) (1,251) (628) (237) (638) (130) (-6) 2,000 0 2,000 ($million1990) (-1,183) (-1,845) (-1,073) (-1,011) (-382) (-89) (-33) (-78) 4,000 (2,371) (2,759) Figure66Sectoraldemandforinvestment 8,000 (-8,229) PPP1 SRP1 (-2.6) (-5.4) (-2.2) (-7.7) SRP2 PPP2 (-8.4) Figure65Sectoraloutputs 161 6,000 (4,905) (5,145) Thesefiguresshowchangesinpresentvalues(estimatedat8percentdiscountrate)overtheperiod2005–2020,correspondingtoeachcarbontaxscenario,as comparedwithBCscenario ThesefiguresaredevelopedfrominformationcontainedinTablesF1toF5,AppendixF,pp.288332. PPP1 SRP1 PPP2 SRP2 Notes: 18 14 12 10 (-8.6) (-8.6) 8 (-6.9) 6 (-4.9) (-4.8) (-4.9) 4 (2.0) (1.9) (0.8) (1.3) (0.5) (1.0) 2 0 2 ($billion1990) (-1.7) (-0.3) (-0.1) (-0.9) (-1.4) (-0.5) (-3.0) (-2.8) (-2.5) (-2.1) (-2.7) (-2.9) 4 40 (-33.4) PPP1 SRP1 PPP2 SRP2 30 (-27.1) 20 (-20.0) (-18.8) (-22.9) (-14.2) (-13.4) (-12.5) (-15.0) (-6.6) (-7.3) 10 (-0.7) (-1.2) (-3.6) (-1.8) (-2.0) (-1.0) (-1.0) (-0.5) (-5.0) (-2.5) (-2.8) (-1.4) (-6.8) 0 (4.2) (8.5) (7.9) 10 ($billion1990) (3.8) (5.6) (2.2) (1.1) (0.2) 20 162 Figure68Sectoraloutputsforintermediateconsumption Thesefiguresshowchangesinpresentvalues(estimatedat8percentdiscountrate)overtheperiod2005–2020,correspondingtoeachcarbontaxscenario,as comparedwithBCscenario ThesefiguresaredevelopedfrominformationcontainedinTablesF1toF5,AppendixF,pp.288332. 16 PPP1 SRP1 PPP2 (-11.5) (-8.1) (-7.4) (-6.7) (-5.7) (-8.7) (-5.6) Figure67Sectoraloutputsforfinalconsumption SRP2 (-16.4) Notes: 35 (-34.0) 25 20 (-19.3) (-16.3) 15 10 (-8.7) (-5.5) (-2.7) 5 0 ($billion1990) (-1.4) (-0.5) (-1.2) (-1.0) (-2.2) (-1.1) (-2.3) (-2.1) (-2.9) (-4.4) Figure69Sectoraloutputsforexports 2,500 (2,239) PPP1 SRP1 PPP2 SRP2 2,000 (1,841) 1,500 1,000 (811) (207) 0 163 (65) (179) (304) (435) (267) 500 ($million1990) (788) (845) (626) Figure610Sectoralsupplyofinvestmentgoods Thesefiguresshowchangesinpresentvalues(estimatedat8percentdiscountrate)overtheperiod2005–2020,correspondingtoeachcarbontaxscenario,as comparedwithBCscenario ThesefiguresaredevelopedfrominformationcontainedinTablesF1toF5,AppendixF,pp.288332. 30 PPP1 SRP1 PPP2 SRP2 Notes: 164 Thefollowingobservationscanbedrawnfromtheabovenotedfigures(Figures65to 610): i. Carbon tax would mainly affect the outputs of coal, gas, electricity, and constructionsectors.Forexample,inthecasePPP1,thetotaloutputofthecoal sector, over the period 2005–2020, would reduce by $14 billion (1990 prices) (Figure 65) as compared with the output in the BC scenario. Of this, over $7 billion would be due to the reduced demand for coal by other industries (Figure 68), $1.4 billion due to the reduction in exports (Figure 69), and $2.1 billionduetothereductioninhouseholdconsumption(Figure67). Althoughthetotal outputofthegassector,overthe period 2005–2020, would alsoreduce by $5.2billion(Figure 65),itsusebyotherindustrieswouldonly reduceby$0.7billion(Figure68),ascomparedtotheBCscenario.Infact,the demand for gas by other industries would increase after the year 2017 when combinedcycle technology penetrates the market (see Table 62). In a single year, in 2020, the demand for gas by other industries would increase by $515 million($4090millionfromPPP1less$3575millionfromBCscenario,seeTable F5, Appendix F, pp. 324325). The reduction in the use of domestic coal and increase in the use of gas are due partly to the replacement of conventional coalfired with natural gasbased combinedcycle electricity generation technology.Forexample,inthecaseofPPP1,theoutputofelectricityproduced from coalfired technology would reduce by $8.3 billion, while the electricity producedfromcombinedcyclewouldincreaseby$2.7billion,ascomparedto the BC scenario (Figure 65). Also, in the case of PPP2, while the output of electricityproducedfromcoalfiredtechnologywouldreduceby$25billion,it wouldbereplacedwithelectricityproducedfromcombinedcycle($5.1billion) and renewabletechnologies($6.9 billion), respectively, ascomparedtotheBC scenario (Figure 65). Because of these shifts in electricity generation technologies,therewouldbechangesinthepatternofdemandforinvestment. For example, over the period 2005–2020, renewable and combinedcycle electricity technologies would require investments of $5.1 and $1.3 billion, 165 respectively, while the demand for investment in coalfired power generation would reduce by $5.4 billion (Figure 66). As renewable power generation technology is the most capital intensive technology amongst the existing electricitytechnologies(seeTable56),itssubstitutionforcoalfiredtechnology would require increased outputs from construction and machinery and equipment sectors. However, such increases would not occur until after 2016, after renewable electricity penetrates into the electricity market. For example, overtheperiod2005–2020,thepresentvaluesofoutputsfromtheconstruction and the machinery and equipment sectors would decrease by about $65 and $207 million, respectively (Figure 610). However, in the year 2020 alone, the requirement of outputs from both – construction and machineryequipment – sectors would increase by $660 and $109 million, respectively ($121142 less $120482 million for construction sector and $53803 less $53694 million for machineryequipmentsector,seeTableF3,AppendixF,pp.306and310). ii. Byasimilarreasoning,theintroductionofcarbontaxbasedonSRPwouldalso affecttheoutput ofvarioussectors.Forexample,inthecaseofSRP1,the total output of the coal sector, over the period 2005–2020, would reduce by $27 billion(Figure65)ascomparedwiththeBCscenario.Ofthis,almost$14billion wouldbeduetothereduceddemandforcoalbyotherindustries(Figure68), $2.9billionduetothereductioninexports(Figure69),and$2.5billiondueto thereductioninhouseholdconsumption(Figure67). Althoughthetotal outputofthegassector,overthe period 2005–2020, would alsoreduceby$4.2billion(Figure65),itsusebyotherindustrieswouldinfact increase by $1.1 billion (Figure 68), as compared to the BC scenario. The reductionintheuseofdomesticcoalandincreaseintheuseofgasaredueto thesubstitutionofelectricityproducedfromconventionalcoalfiredtechnology withnaturalgasbasedcombinedcycletechnology.Forexample,theoutputof electricity produced from coalfired technology would reduce by $23 billion, whiletheelectricityproducedfromcombinedcycletechnologywouldincrease by$9.8billion,ascomparedtotheBC(Figure65).Becauseofthis,therewould 166 be changes in the annual investment demand. For example, over the period 2005–2020,combinedcycleelectricitygenerationtechnologieswouldrequirean investmentofabout$2.4billion,whilethedemandforinvestmentincoalfired power generation technology would reduce by $4.5 billion (Figure 66). As conventional coal power plant is more capital intensive as compared with natural gas basedpower plant (see Table 56), this would also result in reductions in the value of outputs from the construction and machinery and equipmentsectors.Forexample,overtheperiod2005–2020,thepresentvalues of outputs from the construction and the machinery and equipment sectors woulddecreaseby$2.2and$0.7billion,respectively(Figure610). iii. Irrespectiveofthemethodusedforapplyingcarbontax(i.e.,PPPorSRP),CO2 emission intensive sectors would have higher negative impacts than the ones withlessemissionsintensiveinputs.However,themagnitudeoftheseimpacts would vary depending on which method is adopted for determining carbon tax.Forexample,whiletheoutputofcoalandpetroleumsectors,andcoalfired electricitygenerationsectorwoulddeclineinbothcases,thedeclineinthecase ofcarbontaxbasedonSRPisalmosttwiceofthecorrespondingdeclinewhen carbontaxisbasedonPPP(Figure65). Further,theoutputofthegassector,usedbyotherindustries,wouldincrease in both cases. However, the magnitude of this increase would depend on the levelofpenetrationbynaturalgasbasedcombinedcycleelectricitygeneration. For example, the output of electricity from gasfired combinedcycle would increase by about $9.8 billion in the case SRP1, and by $2.7 billion in the case PPP1 (Figure 65). This would require the output of gas sector to increase by $1.1and$0.5billion,forSRP1andPPP1,respectively(Figure68). The changes in the outputs of construction and machinery and equipment sectors would depend on how carbon tax changes the cost competitiveness of variouselectricityoptionsandhowthisinducesashiftinelectricitygeneration technologies. If capital intensive technology, such as renewable, becomes competitive, as happen in the case of PPP2, then the outputs from both 167 construction($424million)andmachineryandequipment($15million)sectors wouldalsoincrease(Figure610).Ontheotherhand,theincreasedpenetration by less capital intensive technology such as combinedcycle, as in the case of SRP2,wouldresultinareductioninoutputsfromconstructionandmachinery andequipmentsectors,by$1.8and$0.8billion,respectively(Figure610). Sectoral Prices and Inflation: The introduction of carbon tax would result in an increaseinsectoralprices.Suchincreasewoulddependonthecarbonintensivenessof energy and materials that flow in the economy. Also, the weighted average of these sectoral pricescanbeusedasanindicatorofinflationintheeconomy(Valadkhani& Mitchell2002).Thissectiondiscussestheimpactofcarbontaxonthepricesofsectoral outputs and, more generally, inflation. The percentage increases in prices for the outputs of various sectors over the period 2005–2020 are presented in Table 66. The increaseingeneralinflationoverthisperiodisshowninFigure611. Table66 Increaseinsectoralprices:2005–2020 Coalsector Petroleumsector Gassector Electricitysector Agriculture,forestryandfishing Mining Food,beveragesandtobacco Textile,clothing,footwearandleather Wood,paperandprintingproducts Basicchemicals Nonmetallicmineralproducts Basicironandsteel Basicnonferrousmetals Fabricatedmetalproducts Machineryandequipment Miscellenousmanufacturing Water,sewerageanddrainage Construction Roadtransport Railwaytransport Watertransport Airtransport Othertransport,servicesandstorage Commercialservices Notes: PPP1 SRP1 12.1 21.9 8.0 184.6 6.3 10.6 7.6 3.9 6.0 9.1 16.7 34.1 37.6 11.2 4.0 2.0 7.6 5.4 21.1 11.3 25.0 17.6 5.5 3.4 23.9 44.3 21.7 254.7 18.1 27.2 23.9 12.3 18.0 19.3 36.7 65.6 75.4 34.5 12.9 7.0 22.7 18.1 31.7 28.5 44.8 26.6 17.5 12.5 (Percent) PPP2 SRP2 23.5 43.1 15.6 336.9 12.2 20.2 14.4 7.4 11.4 17.7 32.3 66.6 73.1 21.6 7.7 3.9 14.1 10.4 41.8 21.6 49.6 35.1 10.3 6.3 Thistablepresentstheresultsobtainedfromtheapplicationofequations514and515,as detailedinChapter5,Section5.4,p.106.Fordetailedresults,seeTableF6,AppendixF, p.333. Thevaluesinthistablerefertothepercentagechangesinsectoralprices,overtheperiod 2005–2020.Forexample,electricitypriceforPPP1in2020is184.6percenthigherthanthe pricein2005. 45.1 85.1 41.0 450.9 34.2 50.6 44.7 22.9 33.7 36.7 69.3 125.1 142.3 65.3 24.2 13.1 41.6 34.3 61.7 52.9 87.4 51.9 32.0 23.2 168 Index Figure611 Increasesininflationrates 1.4 1.3 1.2 1.1 1.0 2005 Notes: 2010 2015 2020 Thisfigurepresentstheresultsobtainedfromtheapplicationofequations514and515,as detailedinChapter5,Section5.4,p.106.Fordetailedresults,seeTableF6,AppendixF, p.334. Theindexvaluesinthisfigurecanbeinterpretedasapercentagechangesininflationfrom thebaseyear,2005.Forexample,theindexvalueof1.203inthecaseofSRP1in2020,isreadas anincreaseof20.3percentfromtheyear2005. Theresultssuggestthat: i. In general, carbon tax based on PPP would have a lesser impact on sectoral pricesandinflationratethanthatbasedonSRP.Forexample,whencarbontax of$10pertonneisapplied,itwouldcauseinflationtoincrease,overtheperiod 2005–2020, by 8.8 and 20.3 per cent, for PPP1 and SRP1, respectively (Figure 611).ThecorrespondingfiguresforPPP2andSRP2are16.5and37.5percent, respectively. ii. The increases in the prices of energy, manufacturing (particularly chemicals, metal,andnonmetalindustry),andtransportsectorsaresignificantlyhigherin the case of SRP as compared with PPP. For example, electricity price would increaseby185percentinthecaseofPPP1and255percentinthecaseofSRP1 (Table66).Also,pricesforroadtransport,basedonPPP1,wouldincreaseby21 percent,comparedto32percentforSRP1.Asimilarimpactoccursintheiron andsteelindustry,wherepriceswouldincreaseby34percentforPPP1and66 169 per cent for SRP1. This is due to the direct use of fossil energy as inputs for sectoral activities (such as coal for electricity production and steel making processes, and petroleum usedin road transport).The priceincreasesinthese sectors also reflect their contribution to CO2 emissions when applying the PolluterPaysPrinciple(seeTable33). iii. When carbon tax is imposed based on SRP, the commercial, food and textile industry, agriculture, mining, and water sectors become more susceptible to price increases. Further, the increase in prices of these sectors is much higher thantheincreasesthatwouldtakeplacewhencarbontaxisbasedonPPP.For example,pricesofthecommercialsectoroutputwouldincreaseby3and6per centforPPP1andPPP2,respectively;thecorrespondingincreasesforSRP1and SRP2are12.5and23percent,respectively(Table66).Also,foodprices,based onPPP1,wouldincreaseby8percent,comparedtoanincreaseof24percent for SRP1. A similar magnitude is also observed for the water sector, where water prices increase by 8 per cent for PPP1 and 23 per cent for SRP1. This is becausethesesectorsconsumelesseramountsofdirectfossilenergyasinputs and more of indirect energy embodied in materials for undertaking their sectoral activities. The price increases from these sectors also reflect their contribution to CO2 emissions when applying the Shared Responsibility Principle(seeTable33). Carbon Tax Revenue: The introduction of carbon tax is likely to generate significant revenueforthegovernment.This(fiscal)revenuecanbeestimatedbymultiplyingthe advaloremtaxratefacedbyeachindustry(equations511and512)withitssectoral output(equation532).Theestimatesofthisfiscalrevenue,overtheperiod2005–2020, expressedintermsofpresentvalues(in1990prices),areshowninTable67. 170 Table67 Fiscalrevenuefromcarbontax:2005–2020 PPP 1 1.Coal 2.Petroleum 3.Gas 4.RenewableElectricity 5.CoalfiredElectricity 6.InternalcombustionElectricity 7.GasturbineElectricity 8.CombinedcycleElectricity 9.Agriculture,forestryandfishing 10.Mining 11.Food,beveragesandtobacco 12.Textile,clothing,footwearandleather 13.Wood,paperandprintingproducts 14.Basicchemicals 15.Nonmetallicmineralproducts 16.Basicironandsteel 17.Basicnonferrousmetals 18.Fabricatedmetalproducts 19.Machineryandequipment 20.Miscellenousmanufacturing 21.Water,sewerageanddrainage 22.Construction 23.Roadtransport 24.Railwaytransport 25.Watertransport 26.Airtransport 27.Othertransport,servicesandstorage 28.Commercialservices Totalfiscalrevenuefromcarbontax Notes: 900 644 56 0 15,241 45 302 640 422 417 279 45 187 1,029 497 1,381 1,419 38 56 2 7 334 1,985 169 382 1,414 78 388 28,356 SRP 1 PPP2 SRP 2 ($Million 1990 prices) 1,671 1,312 172 523 19,699 53 326 1,275 1,630 1,778 2,773 443 1,526 2,222 1,294 2,724 3,005 1,365 2,568 57 333 3,204 2,533 585 599 1,841 2,236 16,089 73,834 1,671 1,215 103 0 27,375 87 586 1,550 830 819 549 88 368 2,026 979 2,720 2,792 75 110 3 14 660 3,911 329 750 2,790 153 769 53,320 2,856 2,358 306 1,147 33,715 98 608 2,603 3,045 3,282 5,109 812 2,834 4,175 2,438 5,158 5,647 2,558 4,761 105 601 6,014 4,841 1,067 1,139 3,532 4,076 29,971 134,857 PPP 1 SRP 1 PPP2 SRP2 (percentage contribution) 3.2 2.3 0.2 0.0 53.8 0.2 1.1 2.3 1.5 1.5 1.0 0.2 0.7 3.6 1.8 4.9 5.0 0.1 0.2 0.0 0.0 1.2 7.0 0.6 1.3 5.0 0.3 1.4 100.0 2.3 1.8 0.2 0.7 26.7 0.1 0.4 1.7 2.2 2.4 3.8 0.6 2.1 3.0 1.8 3.7 4.1 1.8 3.5 0.1 0.5 4.3 3.4 0.8 0.8 2.5 3.0 21.8 100.0 3.1 2.3 0.2 0.0 51.3 0.2 1.1 2.9 1.6 1.5 1.0 0.2 0.7 3.8 1.8 5.1 5.2 0.1 0.2 0.0 0.0 1.2 7.3 0.6 1.4 5.2 0.3 1.4 100.0 2.1 1.7 0.2 0.9 25.0 0.1 0.5 1.9 2.3 2.4 3.8 0.6 2.1 3.1 1.8 3.8 4.2 1.9 3.5 0.1 0.4 4.5 3.6 0.8 0.8 2.6 3.0 22.2 100.0 Thistablesummarisesthepresentvaluesofcarbontaxrevenuethatislikelytobecollected duringtheperiod2005–2020,usingadiscountrateof8percent.Fordetailedresults,seeTable F7,AppendixF,pp.335338. Thetableshowsthat: i. APPPbasedcarbontaxof$10and$20pertonneofCO2wouldyieldrevenues for the government of $28.4 and $53.3 billion, respectively, over the period 2005–2020.Outofthis,approximately54percentwouldbecollectedfromthe electricity industry alone, particularly from coalfired generators. Renewable electricity generators would understandably not yield any revenue for the government as they do not use coal. The commercial sector would contribute justover1per cent($388and$769millionforPPP1andPPP2,respectively)to the total tax revenue. In general, based on PPP, the contribution by various sectorstocarbontaxrevenueisinproportiontotheircontributiontoCO2. 171 ii. When carbon tax is based on SRP, carbon tax revenues of $73.8 and $134.9 billion are expected to be generated over the period 2005–2020, at tax rates of $10and$20pertonneofCO2,respectively.Here,theelectricityindustrywould beresponsibleforapproximately25percentofthetotaltaxrevenue.Although coalfiredgeneratorswouldstillberesponsibleformostoftherevenuepaidby theelectricityindustry($19.7and$33.7billionforSRP1andSRP2,respectively), renewableelectricitygeneratorswouldalsohavetopaytaxonaccountoftheir use of materials whose manufacture produces CO2 emissions. These revenues would be approximately $523 and $1147 million for SRP1 and SRP2, respectively. The commercial sector, which is a large consumer of electricity, duetoitslargevalueadded,wouldcontributeover20percenttothetotaltax revenue. iii. When a higher level of carbon tax is applied, the contribution to total tax revenue from the electricity industry would reduce. For example, when a carbontaxrateisincreasedfrom$10to$20pertonneofCO2,thecontribution totaxrevenuefromcoalfiredelectricitywouldreducefrom54to51percentin thecaseofPPP,and27to25percentinthecaseofSRP.Thisisbecauseahigher level of tax would cause a higher reduction in output from coalfired technology, which inturn leads to a higher reduction in CO2 emissions. As a result,theshareofrevenuethatwouldbecollectedfromcoalfiredtechnology wouldalsoreduce. Theaboveanalysisshowsthattherevenuesfromcarbontaxaresubstantialandthey could be used by the government for either subsidising or financing various sustainable development projects. However, the analysis of the use of carbon tax revenueanditsassociatedimpactsisnotinthescopeofthisresearch.51 For an analysis of the use of tax revenue, see, for example, Whalley and Wigle (1991) CornwellandCreedy(1997). 51 172 Net Impact of Carbon Tax: The net impact of carbon tax on the overall economy is showninTable68. Table68 Neteconomicimpactsofcarbontax:2005–2020 PPP1 SRP1 PPP2 SRP2 PPP1 ($Billion1990) LossofGDP† NetEconomicImpacts‡ PPP2 SRP2 (Percent) 55.6 120.4 102.2 218.7 28.4 73.8 53.3 134.9 27.2 46.6 48.9 83.9 Carbontaxrevenue SRP1 0.88 1.90 1.65 3.51 0.43 0.74 0.78 1.34 Notes: ThistablesummarisesresultspresentedinTables65(GDP)and67(carbontaxrevenue). † GDPloss,ascomparedwiththeBCoutcome. ‡ NeteconomicimpactsrefertonetofcarbontaxrevenueandGDPloss. Thetableshowsthat: i. Theoveralleconomicimpactofcarbontaxwouldbesignificantlylowerwhen gains from tax revenue are also considered. For example, in the case of PPP1, whiletheeconomywouldlosetotalof$55.6billionofGDP,itwouldalsogains $28.4 billion of tax revenue over the period 2005–2020. The net loss to the economywouldthereforebeonly$27.2billion,whichisapproximately0.43per centoftheGDPinthebaseyear.Thecorrespondingvaluesofnetlossestothe economyforPPP2,SRP1,andSRP2are0.78,0.74,and1.34percent,respectively. ii. Further,itisnoticedthatwhilethenetimpactontheeconomyishigherinthe caseofSRPascomparedwiththePPP(0.78and0.43percent,respectively,for taxof$10pertonne),overalltheimpactofSRPbasedcarbontaxisstilllowfor aneconomyofAustralia’ssizeandstrength. 6.3.2.2 SocialImpacts AsmentionedinSection5.6,socialimpactsareanalysedinthisresearchintermsofthe levelofemployment.Theunderlyinglogicisasfollows:theapplicationofcarbontax would cause changes in the level and composition of sectoral outputs, which would inturn influence the employment required to produce those outputs. The results 173 obtained,byusingthemethodologyexplainedinChapter5(Section5.6),arepresented inFigure612andFigure613. Figure612 Percentagechangesintotalemployment 0.0 -1.0 2005 2010 2015 2020 -2.0 -3.0 -4.0 -5.0 -6.0 Notes: Thisfigureshowspercentagechangesinthelevelofemployment,overtheperiod2005–2020, foreachcarbontaxcase,ascomparedwiththeBCscenario.Itpresentsresultsobtainedfrom theapplicationofequation537,asdetailedinChapter5,Section5.6.Fordetailresults,see TableF12,AppendixF,p.353. Figure613 Changesinsectoralemployment (persons) (1,801) (2,016) (3,941) (4,555) (-10,078) (-14,736) (-7,773) (-7,513) (3,059) (7,201) (206) (-343) (-944) (-2,313) (-58) (-1,020) (-975) (-1,295) (-647) (-780) (-7,460) (-8,790) (-5,030) (-5,105) 20,000 15,000 PPP1 Notes: 10,000 SRP1 5,000 0 PPP2 5,000 10,000 SRP2 Thisfigureshowschangesinthelevelofemployment(inpersons),overtheperiod2005–2020, foreachcarbontaxcase,comparedwiththeBC.Itpresentsresultsobtainedfromthe applicationofequation537,asdetailedinChapter5,Section5.6.Fordetailresults,seeTable F12,AppendixF,p.354. 174 Thesefiguresshowthat: i. The introduction of carbon tax has a marked impact on employment levels (Figure64a).Forexample,intheBCscenario(thatis,nocarbontax),thelevel ofemploymentintheyear2020wouldbe9,444,354persons(anincreaseof12 percentfrom2005)(TableF12,AppendixF,p.353).Theintroductionofcarbon taxwouldhoweverreducetheemploymentlevelsintherangeof2.8to5.5per cent(Figure612). ii. AcarbontaxbasedonPPPwouldhavelessimpactonthelevelofemployment ascomparedtothecaseofSRP.Forexample,atcarbontaxof$10pertonne,the employmentlevelswouldreduceby2.8and3.2percentinthecaseofPPPand SRP,respectively.Thisisequivalenttoabout34,000jobs.Atacarbontaxof$20 per tonne, job losses would be 5.1 and 5.5 per cent for the PPP and SRP, respectively. This is also equivalent to 35,000 jobs. The impact on the level of employment is lower in the case of PPP because of the higher penetration of cleaner electricity technologies, such as combinedcycle and renewable electricity(Figure613). iii. Whenacarbontaxisintroduced,employmentwouldshiftfromthecoalsector tothegassector.Forexample,theemploymentinthecoalsectorwoulddecline intherangeof4,500to8,800persons(Figure613).Someofthelabourfromthe coal sector (502,000 persons) would shift to the gas sector. However, most of thelabourfromthecoalsectorwouldbereducedinresponsetoareductionin coalconsumptionandexports(seeFigure67andFigure69). iv. Therewouldbeashiftofemploymentwithintheelectricitysector(thatis,from conventionalcoalfiredtocombinedcycleandrenewable).Forexample,dueto a large increase in combinedcycle power plants in SRP1, approximately 4,000 persons from coalfired sector would be shifted to the combinedcycle sector. Likewise, a large increase in the share of renewable energy in electricity production,inthecasesPPP2andSRP2,wouldcauseashiftof7,000and3,000 persons,respectively,fromconventionalcoaltorenewablepowerplants. 6.4 175 CarbonTaxtoAchieveAnAprioriEmissionTarget In the previous section, the energy, environmental, economic, and social impacts of carbontax,basedonPPPandSRP,wereanalysed.Inthatanalysis,noapriorilimitwas placedonthelevelofCO2emissions.Inthissection,anapriorilimitisplacedonCO2 emissions. This limit is broadly equivalent to Kyoto target, namely, 108 per cent increaseinCO2emissionsfromtheelectricitysectorascomparedwith1990levels,by theyear2020.52Thisemissionstargetissetonlyfortheelectricitysectorbecause,inthis research, only electricity sector is assumed to adapt (through changes in mix of technologiesandfuels)inresponsetocarbontax.Itwasnotedintheprevioussection that CO2 emissions from the electricity sector were 128 Mt in 1990. To achieve the specified target, the emissions would be allowed to increase to 138 Mt by 2020. This amountisequivalenttoareductionof45percentofCO2emissionsascomparedwith theBCscenario(intheBC,totalemissionsfromtheelectricitysectorareexpectedtobe 250Mt). Analysisisthencarriedout,inthisresearch,todeterminethelevelofcarbontaxthat would be required in order to meet this target, and the consequential economic and social impacts. The methodology underpinning this assessment was explained in Section5.6,Chapter5.Twosetsofanalysesarecarriedoutinthisresearch.Inthefirst set (Section 6.4.1), the level of carbon tax and associated impacts are determined in a situationwhereanearlyintroductionofcarbontaxisenvisaged(intheyear2005)53.In thesecondsetofanalysis(Section6.4.2), theintroductionof carbontax isdeferredto theyear2010,inrecognitionofthepoliticaldifficultyofintroducingacarbontaxinthe near future (that is, in the year 2005). As an illustration, emissions pathways of achievinganapriorilimitfromthesetwosets,forbothtypesofcarbontax(thatis,PPP andSRP),isshowninFigure614. Infact,theKyototargetrequiresthelevelofemissionstobeachievedby200812.Thistarget isassumedtobeextendedto2020inthisresearch,inordertoallowalongertimeframefor theanalysis. 53 The selection of this year is in accord with the stagewise progress of this doctoral dissertation. 52 176 Figure614 EmissionspathwayofachievingaprioriCO2limit 300 250 Earlyintroduction ofcarbontax Deferredintroduction ofcarbontax 200 150 108%of1990levels, fromtheelectricitysector 100 50 0 2000 BC 2005 PPPEarly 2010 SRPEarly 2015 2020 PPP Delay SRPDelay TheresultsofanalysesinthisSectionarepresentedinTable69andFigure615. 177 Table69 Impactsofcarbontaxtoachieveanaprioriemissiontarget BC PPP 25 Earlyaction SRP 15 Taxrate($/tonne) 0 †$ CO2emissions (Mtonnes) (8) Electricitysector 250 138 (28) Economy 432 300 † Electricitytechnologymix (percent) Coalfired 84.2 58.2 (2005) Combinedcycle 3.6 8.8 (2011) Renewable 10.2 31.0 (2013) †# 5 24 (380) Costofelectricity (¢/kWh) †# Shareofprimaryenergyforelectricityproduction Blackcoal 45.9 30.7 (15) Browncoal 28.6 19.1 (10) Oil 0.9 0.7 (0.2) (4) Gas 14.4 18.5 (21) Renewable 10.2 31.0 EconomicImpact($Bn1990) ‡# 6,325 6,200 (2.0) GDP ‡ 0 65 CarbontaxRevenue Electricitysector ‡§ Commercialsector ‡§ ‡# Neteconomicgrowth Neteconomiccost ‡# Sectoraloutput ($Bn) Electricity Steamturbine (8) (25) 139 296 (8) (26) 138 291 (8) (24) 58.2 (2005) 16.6 (2011) 23.2 (2016) 21 (320) 66.0 (2005) 6.2 (2014) 25.8 (2015) 31 (520) 66.0 (2005) 11.4 (2014) 20.6 (2017) 24 (380) 29.0 18.1 0.7 29.0 23.2 35.5 22.1 0.8 15.9 25.8 34.0 21.2 0.7 23.5 20.6 (17) (11) (0.2) (15) (13) (10) (7) (0.1) (2) (16) (12) (7) (0.1) (9) (10) 6,155 135 (2.7) 6,225 73 (1.6) 6,207 102 (1.9) (29) 0 36 (55) 25 (19) 40 (54) 29 0 1 (1) 48 (35) 1 (2) 23 (22) 6,325 6,266 60 (0.9) 6,290 35 (0.5) 6,298 27 (0.4) 6,308 17 (0.3) 58 55 (5.7) 54 (7.9) 55 (4.6) 55 (5.6) 49 43 (12.3) 7 (30.5) 42 (14.2) (5.2) 6 46 (7.7) 45 (8.5) 6 (14.8) 6 (2.7) (52.4) 4 (104.1) 66 (22.1) 2 (14.6) 3 (40.8) Renewables 6 Combinedcycle 2 Coal Otherenergy(oilandgas) Water Agriculture Mining Manufacturing Construction Transport Services Inflation(Index) †# Employment Electricity(persons) 138 294 Deferredaction PPP SRP 51 26 85 35 32 121 114 1,152 970 332 3,424 1.00 3 71 (17.0) 22 (37.4) 31 (3.6) 117 (3.4) 111 (3.2) 1,128 (2.1) 970 (0.1) 322 (3.2) 3,375 (1.4) 1.21 22 (36.2) 30 (6.5) 115 (5.1) 110 (4.0) 1,112 (3.4) 966 (0.4) 314 (5.3) 3,365 (1.7) 1.30 74 (13.1) 26 (26.4) 31 (2.9) 118 (2.8) 111 (2.6) 1,132 (1.7) 970 (0.1) 324 (2.6) 3,383 (1.2) 1.29 72 (15.2) 27 (23.8) 31 (4.6) 117 (3.6) 111 (2.9) 1,124 (2.4) 968 (0.2) 320 (3.7) 3,382 (1.2) 1.36 47,399 40,629 (14.3) 41,533 (12.4) 39,494 (16.7) 41,563 (12.3) Coalfired 40,713 Renewable 4,925 Combinedcycle 1,760 22,443 (44.9) 14,615 (196.7) 3,571 (102.8) 23,225 (43.0) 11,283 (129.1) 7,026 (299.1) 25,045 (38.5) 11,969 (143.0) 2,480 (40.9) 26,578 (34.7) 10,110 (105.3) 4,875 (176.9) (6) (3) (8) (4) Total(000persons) 9,444 8,890 9,135 8,719 9,090 Notes: InformationcontainedinthistableisassembledfromvariousTablesinAppendixF † Resultfortheyear2020 Resultovertheperiod2005–2020 ‡ Presentvalue,fortheperiod2005–2020,usingadiscountrateof8percent $ Numbersinbracketsshowpercentageincreasefromthe1990level # NumbersinbracketsshowpercentagechangesfromtheBC Numbersinbracketsrepresentyearinwhichtheparticulartechnologybecomescostefficient § Numbersinbracketsshowcontributionsofthesectortothetotal ¥ seefurtherdiscussiononeconomicimpactsinSection6.5. 178 Figure615 Economicimpactsofachievingemissionstargetfromelectricitysector (Annual,percent) 0 0 2005 2010 2015 2005 2020 2010 2015 2020 -2 -2 -4 -4 -6 -6 -8 b) Final consumption a) Gross Domestic Product -10 -8 0 0.6 2005 2010 2015 2020 0.4 -2 0.2 -4 0.0 -0.2 2005 2010 2015 -6 2020 -0.4 -8 -0.6 -0.8 -10 -1.0 c) Investment d) Intermediate consumption -1.2 -12 0 2005 2010 2015 2020 -2 -4 -6 -8 -10 -12 -14 -16 e) Export -18 Notes: ThesefiguresshowannualpercentagechangesascomparedwiththeBC; Fordetailedresults,seeTableF1toF5,AppendixF,pp.288332. 6.4.1 179 EarlyIntroductionofCarbonTax Forthecaseofearlyaction,theresultsfromTable69andFigure615suggestthat: i. A carbon tax of $25, based on PPP, would be required in order to limit CO2 emissionsfromtheelectricitysectorto138Mtby2020(apriorilimitsetinthis research). In this case, total nationwide CO2 emissions from fossil fuel combustion wouldincreaseby28percent(300 Mt)of1990level(234Mt).On theotherhand,basedonSRP,acarbontaxof$15 pertonneof CO2wouldbe required to achieve apriori CO2 emissions (that is, 138 Mt from the electricity sector).Inthiscase,economywideemissionsinthe2020wouldbe294Mt–25 per cent of 1990 levels. These reductions in CO2 emissions look rather favourable when compared with the increase (of 84 per cent) that would happenifnocarbontaxisintroduced. ii. In the case of carbon tax based on PPP, combinedcycle and renewable electricitywouldbecomecompetitivebytheyears2011and2013,respectively. By2020,theshareofelectricityproducedfromcoalfiredtechnologywouldbe reduced by 26 per cent (from 84 per cent in 2005, to 58 per cent in 2020). The reductionincoalfiredelectricitywouldbereplacedbyrenewable(21percent) andnaturalgasfiredcombinedcycle(5percent)electricity.Consequently,the cost of electricity supply would increase by almost fourtimes as compared to the BC value (5 ¢/kWh), reaching 24 ¢/kWh in 2020. These changes in technologymix would influence changes in demand for primary energy used for electricity production. The demand for brown coal and black coal would reduceby 10and15 percent,respectively. The demandforrenewable energy and natural gas resources would however increase by 21 and 4 per cent, respectively.Further,thistax(i.e.,$25pertonne)wouldcausethepresentvalue ofGDP,overtheperiod2005–2020,todecreaseby2percent($125billion),as comparedtotheBCscenario(alsoseeFigure615).MostofareductioninGDP ($120 billion) would come from final consumption. The changing mix of electricity generation technologies would result in a small reduction ($400 million) in demand for investment, over the period 2005–2020. In fact, the 180 demandforinvestmentwouldincreasefollowingthepenetrationofrenewable electricityintheelectricitymarketin2013(alsoseeFigure615).Also,thistax (thatis,$25pertonneofCO2)wouldcauseemploymentlevelin2020tobe6per centbelowtheemploymentlevelinBC(thatis,nocarbontax).Further,thistax would generate $65 billion of fiscal revenue for the government, of which 55 percent($36 billion) wouldbecollected fromtheelectricitysector alone. This alsosuggeststhatthenetoverallimpactofacarbontaxof$25pertonne,based onPPP,wouldbeapproximately$60billion($125billionlossinGDPand$65 gaininfiscalrevenue). iii. For a carbon tax based on the SRP ($15 per tonne, as noted above), the responsibility for CO2 emissions is fairly distributed across all (goods and services)sectorsoftheeconomy.Inthiscase,theanalysisshows,thecombined cycle and renewable electricity would become competitive by the years 2011 and 2016, respectively. By 2020, the share of electricity produced from coal would be reduced by 26 per cent (from 84 per cent in 2005, to 58 per cent in 2020). Such reduction in coalfired electricity is exactly the same as for PPP because, in both cases (that is PPP and SRP), this technology would start to phaseoutfromtheelectricitymarketatthesametimein2011whencombined cycletechnologybecomescostcompetitive.However,unlikePPP,thereduction in coalfired technology, in the case of SRP, would be equally replaced by combinedcycle and renewable (both 13 per cent) technology. Because of the large increase in electricity produced from combinedcycle (in this case as compared to the PPP), the demand for natural gas would also increase, providing 29 per cent of total primary energy requirements in the electricity sector in 2020. Consequently, the cost of electricity supply would increase by approximatelyjustabovethreetimesascomparedtotheBCscenario,reaching 21 ¢/kWh in 2020. Further, this tax (that is, $15 per tonne) would cause GDP, over the period 2005–2020, to decrease by 2.7 per cent ($170 billion), as compared to the BC (also see Figure 615). The impact on GDP in the case of SRPis higherthanthat inthe case ofPPPbecausea carbon tax based on PPP would affect economic sectors based on their direct fuel consumption only; 181 whereas, for SRP, it would be based on direct as well as indirect fuel consumption.MostofareductioninGDPwouldcomefromareductioninfinal consumption ($167 billion). The changing mix of electricity generation technologies would result in a small reduction ($3.7 billion) in demand for investment. However, as shown in Figure 615c, the trend in demand for investmentwouldincreaseafter2015,ascapitalintensiverenewableelectricity generation penetrates the electricity market. Also, this tax would reduce the employmentin2020by3percentoftheBClevel.Atotaltaxrevenueof$135 billion would be collected by the government, out of which 35 per cent ($48 billion) would be collected from the commercial sector. The net cost of this policy would therefore be $35 billion ($170 billion loss of GDP minus $135 billiongainsintaxrevenue). iv. AcomparisonofacarbontaxbasedonPPPandSRPsuggeststhat,inorderto meet an apriori CO2 emissions target for the electricity sector, a carbon tax basedonSRPispreferablethantheonebasedonPPP.Itwouldneedalower levelofcarbontaxtobeintroduced(thatis,$15pertonneascomparedwith$25 per tonne for PPP). Although a carbon tax based on SRP would cause high inflation54(1.9percentperyear),ascomparedtothePPP(1.3percentperyear), thecostofelectricityinthecaseofSRPwouldbelower(21¢/kWh),compared with PPP (24 ¢/kWh). The net economic impacts of carbon tax based on SRP wouldbe$25billionlowerthanthosebasedonPPP($60billionforPPPminus $35billionlossesforSRP).AcarbontaxbasedonSRPwouldalsohaveamilder impact in terms of job losses; 3 per cent jobs will be lost in SRP as compared with6percentinthecaseofPPP,overtheperiod2005–2020. The inflation is the weightedmean of price increases from all sectors over the period 2005– 2020,ascalculatedfromEquation515. 54 6.4.2 182 DeferredIntroductionofCarbonTax Whentheimplementationofcarbontaxisdeferredtotheyear2010,thecostofmeeting emissionstargetwouldbeconsiderablyhigherascomparedwiththecasewhencarbon tax is introduced early (in 2005) as discussed above. The impact of delaying the implementation of carbon tax is also shown in Table 69 and Figure 615. The main resultsarediscussedbelow: i. The tax rates required for achieving the target (i.e., 138 Mt of CO2 emissions from the electricity sector in 2020) would be much higher – $51 and $26 per tonneofCO2inthecaseofPPPandSRP,respectively(thecorrespondingvalues inthecaseofearlyintroductionofcarbontaxwere$25and$15,respectively). ii. ForacarbontaxbasedonPPP,renewableelectricitygenerationwouldbecome competitive by the year 2015, whereas combinedcycle would penetrate the electricity market only in 2014. This is because the marginal cost of electricity production from combinedcycle (4.16.7 ¢/kWh) is only slightly higher than conventionalcoaltechnology(3.54.0¢/kWh).Applyingcarbontaxdirectlyon fuelconsumptionwouldincreasethecostofelectricityfromconventionalcoal fired plants at a slightly higher rate than from combinedcycle plants. Therefore, the threshold between these technologies is smaller than when compared with renewable technologies (7.354.9 ¢/kWh). Therefore, by 2020, the share of electricity produced from coal would be reduced by 18 per cent (from84percentin2005,to66percentin2020).Thereductionintheshareof coalfired electricity would be almost made up by the increased share of renewable electricity (16 per cent). Accordingly, it would increase the cost of electricity supply by more than fivetimes as compared to the BC scenario, reaching 31 ¢/kWh in 2020. Further, this tax (i.e., $51 per tonne) would cause GDP, over the period 2005–2020, to decrease by 1.6 per cent ($100 billion), as comparedtotheBC.MostofareductioninGDPwouldcomefromareduction in final consumption ($96 billion). The changing mix of electricity generation technologieswouldresultinanegligiblereduction($415million)indemandfor investment. Also, this tax would cause employment in 2020 to be 8 per cent 183 belowtheemploymentinBC(thatis,nocarbontax).Thetotalrevenueforthe governmentwouldbe$73billion,outofwhich54percent($40billion)would be collected from the electricity sector alone. This also suggests that the net overall impact of a carbon tax of $51 per tonne, based on PPP, would be approximately $27 billion ($100 billion loss in GDP and $73 gain in fiscal revenue). iii. On the other hand, based on SRP, a carbon tax of $25 per tonne would be requiredtoachievethesameenvironmentalgoal(i.e.,138MtofCO2emissions fromtheelectricitysectorin2020).Thistaxlevelislowerthanthepreviouscase (thatis,basedonPPP)because,inthiscase,fossilfuelintensiveindustriesare not considered as solely responsible for CO2 emissions. Instead the responsibility is fairly attributed across all (goods and services) consuming sectorsoftheeconomy.Theanalysisshowsthatcombinedcycleandrenewable electricitywouldbecomecompetitivebytheyears2014and2017,respectively. By2020,theshareofelectricityproducedfromcoalwouldbereducedby18per cent(from84percentin2005,to66percentin2020).Areductionincoalfired electricitywouldbereplacedbyrenewable(10percent)andcombinedcycle(8 percent).Consequently,thecostofelectricitysupplywouldincreasebyalmost fourtimesascomparedtotheBC,reaching24¢/kWhin2020.Further,thistax (i.e., $26 per tonne) would cause GDP, over the period 2005–2020, to decrease by1.9percent($118billion),ascomparedtotheBC.TheimpactonGDPinthe caseofSRPishigherthanPPPbecauseacarbontaxbasedonPPPwouldaffect economicsectorsbasedontheirdirectfuelconsumptiononly;whereas,forSRP, itwouldimposebasedondirectaswellasindirectfuelconsumption.Mostofa reduction in GDP would come from a reduction in demand for final consumption($116billion).SimilartoPPP,thechangeinthemixofelectricity generation technologies would result in a small reduction ($2 billion) in demand for investment. However, as shown in Figure 615c, the trend in demand for investment increases beyond 2017, when capital intensive renewable technology begins to penetrate the market. Also, this tax would causetheemploymentin2020tobe4percentbelowwhatitwouldhavebeenif 184 nocarbontaxisintroduced.Thetotalrevenuethatthegovernmentcancollect fromcarbontaxinthiscasewouldbe$102billion,outofwhich29percent($29 billion) would come from the electricity sector and 22 per cent ($23 billion) would come from the commercial sector. The net cost of this policy would thereforebe$17billion($118billionlossofGDPminus$102billiongainsintax revenue). iv. AcomparisonofacarbontaxbasedonPPPandSRPsuggeststhat,inorderto meet an apriori CO2 emissions target for the electricity sector, a carbon tax basedonSRPispreferablethantheonebasedonPPP.Itwouldneeda lower levelofcarbontaxtobeintroduced(thatis,$26pertonneascomparedwith$51 per tonne for PPP). Although a carbon tax based on SRP would cause high inflation55(2.2percentperyear),ascomparedtothePPP(1.8percentperyear), thecostofelectricityinthecaseofSRPwouldbelower(24¢/kWh),compared with PPP (31 ¢/kWh). The net economic impacts of carbon tax based on SRP wouldbe$10billionlowerthanthosebasedonPPP($27billionforPPPminus $17billionlossesforSRP).AcarbontaxbasedonSRPwouldalsohaveamilder impact in terms of job losses; 4 per cent jobs will be lost in SRP as compared with8percentinthecaseofPPP,overtheperiod2005–2020. 6.4.3 EarlyActionvsDeferredAction:SomeEarlyResults Areview ofthe impacts ofearly anddeferred introductionofcarbon tax(inorderto achieveanapriorireductioninemissionsfromtheelectricitysector)–aspresentedin Sections 6.4.1 and 6.4.2 – appears to provide somewhat contradictory messages. For example, an early introduction of carbon tax seems to be desirable from the considerations of electricity price increases, inflation and employment levels. The electricityprices,intheyear2020,forexample,arelikelytobe24¢/kWhand21¢/kWh ascomparedwiththeBaseCasepriceof4.9¢/kWh,forPPPandSRP,respectively,in The inflation is the weightedmean of price increases from all sectors over the period 2005– 2020,ascalculatedfromEquation515. 55 185 thecase of earlyaction. Inthecase ofdeferred action,these prices are likelytobe 31 and24¢/kWhforPPPandSRP,respectively.Similarly,earlyactionislikelytoresultin lowerinflationarypressures(21and30percent),ascomparedwithdeferredaction(29 and36percent),forPPPandSRP,respectively.Intermsofthelevelsofemployment, the job losses in the case of early action are likely to be lower – 6 and 3 per cent, as comparedwith8and4percent,forPPPandSRP,respectively. From the perspective of the entire economy though, it appears that deferred introductionofcarbontaxismoredesirable.Theneteconomiccostofdeferredaction are $27 and $17 billion, for PPP and SRP, respectively. In comparison, the correspondingneteconomiccostofearlyactionare$60and$35billion(Table69). These results however present only one possible interpretation of the underlying argument and hence need to be interpreted with caution. For example, it is noticed fromFigure615athattheannualeconomiccostofcarbontaxinthecaseofearlyaction wouldbehigherthanthedeferredactiononlyintheperiodpriorto2015(forPPP)and 2017(forSRP).Butafter2015(forPPP)and2017(forSRP),thecostofdeferredaction wouldbehigherthanthecaseofearlyaction.Clearly,theshortandlongtermimpacts of early and deferred action appear to be different. Could a longer term analysis providedifferentoutcomes? Moreover,aquestionalsoarisesabouttheinfluenceofspecificapproach(forexample, Net Present Value) on the final results. For example, if the results were presented in Future Value terms (rather than the Present Value terms) would the results be similar? Answering these questions would require some further analysis. Such analysis is carriedoutinthenextsection. 6.4.4 EarlyActionvsDeferredAction:SomeFurtherAnalysis The analysis in the previous section showed that in present value terms the economic cost,overtheperiod2005–2020,ofdeferredactionis$27billionascomparedwith$60 billionforearlyaction,inthecaseofPPP.However,itisalsoclearfromFigure615a that, during the period 2005–2010, when carbon tax has not yet been introduced 186 (deferred action), the economic cost of such inaction would appear as an economic benefit(in terms ofnolossinGDP).In contrast,when carbontax isadopted in 2005, the economy would immediately face economic losses. One can therefore argue that the use of present value as an indicator of economic cost favours deferred action. Theoretically, the concept of present value gives more importance (or weights) to the valuesthatareclosertothepresentperiodthantothevaluesthatwouldoccurinthe laterperiods.Thismeansthatthefurtherintothefuturethecostoccurs(whichislikely tobethecaseforglobalwarminginducedimpacts),thelowertheweightattachedtoit. Forexample,anyhypotheticalcostthatoccursin2020wouldbevaluedat32percent in 2005, assuming discount rate of 8 per cent.56 Referring to Figure 615a, this means that thecostofearly actionduringthe period2005–2010 would be much higher than thecostofdeferredactionduringtheperiod2015–2020. Incontrast,theconceptoffuturevaluegivesmoreimportancetothevaluesinthefuture years,thantothevaluesintheearlieryears.Ifeconomicimpactsaremeasuredinterms oftheir futurevalues, itis possiblethatthecostofearly action would be lessthanthe case of deferred action. However, as shown in Table 610, the cost of deferred action would still be less than that of early action. But the gap between early and deferred actionbecomesnarrowerwhenimpactsareassessedintermsoftheirfuturevalue.For example,inpresentvalueterms,thecostofearlyactionis119percenthigherthanthe cost of deferred action, in the case of PPP. However, the difference reduces to 44 per centwhenexpressedinfuturevalueterms.ThecorrespondingfiguresforSRPwouldbe 109and55percent,respectively. The present value in 2005 is achieved by multiplying the future value in 2020 with Present ValueFactor(PVF)usingthediscountrate(i)of8percentfortheperiod(t)of15years. 56 187 Table610 Comparisonofeconomiccosts:PresentandFuturevalues Earlyaction Deferredaction ($billion) PPP SRP Notes: Percentagedifference (EarlyDeferred) Presentvalue 60 27 119 Futurevalue 456 317 44 Presentvalue 35 17 109 Futurevalue 445 287 55 Presentvaluereferstotheyear2005;Futurevaluereferstotheyear2020. Bothpresentandfuturevaluesarecalculated,fortheperiod2005–2020,assumingadiscount rateof8percent. PresentvalueforeachcategoryistakenfromTable69;Futurevalueiscalculatedfromnetof GDPandtaxrevenueforeachcarbontaxcase,containedinTableF13,AppendixF,p.355. Further,itisalsoclearfromFigure615athattherateofincreaseinneteconomiccostsof deferred action is higher than in the case with early action. Although the cost of deferred action emerges five years later (that is, in 2010, instead of 2005 for early action),itisexpectedtoovertaketheannualcostofearlyactionby2015and2017,for PPP and SRP, respectively. This implies that if the time period for analysis is further extended, the present value of the cost of deferred action would be higher than the corresponding costs of early action. An analysis is carried out in this research by extendingthetimeframetotheyear2040.Itisassumedthataftermeetingtheapriori emissions target in 2020 (equivalent to 138 Mt of CO2 emissions from the electricity sector),acarbontaxineachcase(thatis,PPPandSRPforearlyanddeferredactions)is retainedattheirexistinglevelsinordertomaintainCO2emissionsatthislevel(thatis, 138Mt)until2040.TheresultsofthisanalysisareshowninTable611. 188 Table611Comparisonofeconomiccosts:Shortterm(2020)andLongterm(2040) Earlyaction Deferredaction ($billion) PPP SRP Notes: Difference ($billion) Shortterm 60 27 32 Longterm 303 327 24 Shortterm 35 17 18 Longterm 333 352 18 (10) (8) Shorttermreferstotheperiod2005–2020;Longtermreferstotheperiod2005–2040. Valueinbrackets,inthecaseoflongterm,areadjustedvalues,toallowadirectcomparison withthevaluesfortheshortterm.Thevalueof$10billion,forexample,isobtainedby dividing$24billionwiththenumberofyearsoverthelongterm(thatis,35years)andthen multiplyingitwiththenumberofyearsfortheshortterm(thatis,15years). Bothshortandlongtermimpactsarecalculatedintermsofpresentvalues,overthespecified period,assumingadiscountrateof8percent. PresentvalueforshorttermistakenfromTable69;Presentvalueforlongtermiscalculated fromnetofGDPandtaxrevenueforeachcarbontaxcase,containedinTableF13,Appendix F,p.355. Thetableshowsthatwhiletheneteconomiccostofearlyaction,duringtheshortterm (thatis,overtheperiod2005–2020),wouldbehigherthanthecostofdeferredaction, over the longterm (that is, over the period 2005–2040), the cost of deferred action wouldbecomehigher.Forexample,inthecaseofPPP,theneteconomiccostofearly action would be $32billion higher than the cost of deferred action, when considering these costs over the shortterm. However, over the longterm, the cost of early action wouldbe$24billionlessthanthecostofdeferredaction.Similarsituationwouldalso occur in the case of SRP, with the cost of early action $18 billion less than that of deferred action (see Table 611). To allow a comparison of economic costs from differentcarbontaxregimesdiscussedthroughoutinthisChapter(thatis,PPP1,PPP2, SRP1, SRP2, PPPEarly, PPPDelay, SRPEarly, and SRPDelay), the net economic costs over the longterm are adjusted so that they reflects the net costs that would occur over the period 2005–2020. The adjusted economic costs of early action, over the period 2005– 2020,wouldthereforebe$10and$8billionlessthanthecostofdeferredaction,inthe caseofPPPandSRP,respectively. Tosummarise,overtheshortterm(thatis,theperiodupto2020),theeconomiccostof earlyactionwouldbehigherthanthecostofdeferredaction.Thisisbecausethezero economiclossduringtheperiod2005–2010fromdeferredactionwouldnotbefeltby 189 the economy, to any appreciable extent, during the period 2010–2020. This impact wouldhoweverbegintoaccelerateclosertotheyear2020andwouldovertakethecost duetoearlyactionintheyearsbeyond2020.Overall,therefore,earlyactionappearsto bemoredesirablethandeferredaction. 6.5 ComparisonwithOtherStudies Thissectioncomparestheimpactsofcarbontax,estimatedinthisresearchinSection 6.4,withotherstudies.Table612providesasummaryoftheseresults. Thetableshowsthat,ingeneral,theintroductionofcarbontaxwouldhaveanegative impactontheAustralianeconomy.Theseimpactsarewithintherangeof0.3to2.5per cent reduction in GDP, compared with the base scenario of each study. For example, accordingtoIndustryCommission(1991a),ataxof$21.75pertonneofCO2wouldbe requiredtomeettheTorontotargetandthatthisleveloftaxwouldresultina2.1per cent loss of the Australian economic growth over the period 19912005. According to McDougal(1993),acarbontaxof$19pertonneofCO2wouldresultinaGDPlossof 0.9percentovertheperiod19932005.Thisresearchhasalsoshownthat,tomeetthe Kyototarget(whichissetonlyfortheelectricitysector),theGDPwouldreduceby0.9 percent(forPPP)and0.6percent(forSRP). Sources: Notes: g 2.2 1.8 24 1 1 22 14 Early (implement in2005) Delay (implement in2010) F(forSRP) 22 1 1 22 14 28 26 45 1.7% e 77 17 5.7 0.1 3.7 2.1 1.4 31 9 58 0.9% f 25 13.1 4.6 0.1 3.1 1.7 1.2 26 6 66 0.4% f 51 22 7.9 0.7 5.6 3.6 1.8 23 17 58 0.6% f 15 15.2 5.6 0.4 4.0 2.5 1.2 21 11 66 0.3% f 26 35%by 30%of1990 31%of1990 32%of1990 32%of1990 2050 levelby2020 levelby2020 levelby2020 levelby2020 Delay (implement in2010) F(forPPP) 190 Services A:IndustryCommission(1991a);B:McDougall(1993);C:NIEIR(1995);D:McKibbinandPearce(1996);E:Ahammadetal.(2006);F:Thisresearch(Table69). a:reduceGHGemissionsto20percentbelow1988levelbytheyear2005;b:1988prices;c:1987prices;d:consideredcarbontaxincombinationwithotherpolicy measures;e:$1.25/tonnein1995andincreasesgraduallyuntilitreaches$13.8/tonnein2005,thenmaintainedatthisrateto2010;f:presentvaluewith8percent discountrate;g:reductionofGDPby0.62percentin2004,0.13percentin2014,andincreaseinGDPby0.01percentin2024 Manufacturing Nonferrousmetal Construction Electricity Coal 27 Renewable 2.5% e 99 26 4.3%pa g $(61bn) d 1.2513.8 40%by 2050 Gas $(179bn) 14 target E Early Delay Early (implement (implement (implement in2010) in2030) in2005) 46 20.8 4.8 1.3 6.5 2.1to0.2 0.2 0.9% c 19 target 1990levelby 2005 D Coal 26.2 7.6 3.1 2.1% ChangeinGDP b 21.75 target a Toronto a Toronto Toronto a C B ComparisonsofresearchresultsfromcarbontaxstudiesforAustralia A Table612 Emissiontax($/tonne CO2) CO2emissionsreduction Sectoraloutput Electricity (%) mix 191 Further, these studies have shown that the introduction of carbon tax would particularlyadverselyaffectfossilfuelindustries.Forexample,Ahammadetal.(2006) estimatedthat,by2050,coalfiredelectricitygenerationwouldrepresentaround45to 46 per cent of electricity generation. Most of the reduction in coalfired electricity wouldbereplacedbyrenewableelectricity;renewablewouldaccountfor27to28per centoftotalelectricityproduction.Despitethisshiftinelectricitymix,thesamestudy estimated that the overall electricity production would decline by 14 per cent. This researchhasalsoshownthattheelectricityproductionwouldreduceby5to9percent, withsubstantialreductionincoalfiredpowergeneration(approximately58and66per cent for early and delayed action, respectively). The reduction in coalfired electricity would be replaced largely by gasfired electricity (for SRP) and renewable electricity (for PPP). Industry Commission (1991a) and McDougall (1993) also estimated reductionsincoalbasedelectricityof26and21percent,respectively. Not only would the fossil fuel production sectors be heavily affected, fossil fuel consumptionsectors,suchasenergyintensivemetalsprocessingindustries,wouldalso beaffectedbycarbontax.Forexample,McDougall(1993)estimatedthat,inresponseto acarbontaxof$19pertonneofCO2,theoutputsofnonferrousmetalindustrywould declineby6.5percent.Ahammadetal.(2006)alsoestimatedthattheoutputsofnon ferrousmetalindustrywoulddeclineby22to24percent.Thisresearchestimatedthat the outputs of this industry would reduce in the range of 3 to 7 per cent. While the outputs of the energyintensive industries faced significant decline in most cases, the output of the construction sector would have a negligible impact. For example, McDougall (1993) estimated that the outputs of this sector would increase by 1.3 per cent. This research estimated that the construction sector would face a reduction in output, over the period 2005–2020, of between 0.1 and 0.7 per cent. The Industry Commission’s (1991a) analysis indicates a 3.1 per cent reduction in the output of the constructionsector. Oneoftheresultsofthisresearch,namely,thatearlyintroductionofcarbontaxisless desirable than its deferred introduction (as discussed in Section 6.4.3), resonates with theresultsofAhammadetal.(2006).AccordingtoAhammadetal.(2006),thecostof 192 earlyactionwouldbehigher(2.5percentGDPloss)thanthatofthedelayedaction(1.7 percentGDPloss). Further analysis however showed that this (in the context of this research) was due mainlytotheuseoftheconceptofpresentvaluetoexpressthenetcostsofcarbontax, and also due to the rather short timeperiod (that is, 2005–2020) considered in this research.Theanalysisalsoshowedthatanextensioninthetimeperiodforanalysis,to theyear2040,wouldmakeitattractivetointroducecarbontaxearly. 6.6 PolicyImplicationsofCarbonTax:Someadditional discussion In the previous sections of this chapter, the economywide impacts of a carbon tax, basedonPPPandSRP,wereassessed.Theseimpactswereassessedwithoutimposing any apriori limits on the amounts of CO2 emissions (Section 6.3). Also assessed (in Section 6.4) were the economywide impacts of a carbon tax, based on PPP and SRP, for meeting an apriori emission target – equivalent to 108 per cent increase in CO2 emissionsfromtheelectricitysector,ascomparedwith1990levels,bytheyear2020.In this section, the implications of these taxes is further analysed within a wider policy context. InthePPPapproach,directfossilfuelconsumersareconsideredassolelyresponsible forCO2emissions.Theelectricitysectorisresponsibleformost(about50percent)of the total CO2 emissions. Adopting a carbon tax based on this principle implies that, withintheelectricitysector,electricityproducedfromcoalfiredtechnologywouldbe taxedmorethanthatproducedfromcombinedcycletechnology.Renewableelectricity technologiesdonotconsume fossilfuelsand,therefore,attractnopenalty.Therefore, the adoption of this type of carbon tax would trigger big changes in investment patterns, especially in the form of investments in cleaner electricity production technologies,withinashortrun.Thiswouldbringasignificantshorttermreductionin CO2 emissions. However, because of the sudden change in technologymix for electricityproduction,itwouldsignificantlydriveuptheelectricityprices.Itwouldbe 193 difficult for the economy and society to adapt quickly to such a change. This would furtherprovoketheoppositiontocarbontaxanddelayitsintroduction,ashasalways beenthecaseinAustralia(seeSection3.2,Chapter3formorediscussion). Based on the SRP approach, indirect fossil fuel consumers are also considered as a responsible party for CO2 emissions. In this approach, the electricity sector is responsibleforabout2030percentoftotalnationwideCO2emissions.Thecommercial sector,amajorconsumerofmaterialsandelectricity,isresponsibleforonethirdofCO2 emissions. Renewable electricity technologies are also considered as responsible for CO2emissionsonaccountoftheemissionsthatareembeddedinthematerialsusedto build these technologies and the materials consumed by these technologies during theiroperation.Adoptingacarbontaxbasedonthisprincipleimpliesthattheclimate changeproblemisnottheconcernofdirectpollutersofCO2only,buttheresponsibility of the whole economy. This type of carbon tax provides fairness; it penalises each sector based on their direct and indirect contribution to CO2 emissions. By implementingthistypeofcarbontax,therewouldbeanincentiveforallsectorstoseek cleanerenergysources.Therefore,theadoptionofthistypeofcarbontaxwouldleadto significantly higher reduction in CO2 emissions, as compared with an equivalent tax basedonPPP.Adoptingthistypeofcarbontaxwould,however,havehighereconomic andsocialimpacts,buttheseimpacts,foraneconomyofAustralia’ssizeandstrength, should not be considered high, especially if one takes note of the fact that this tax would result in higher reduction in CO2 emissions. Table 613 also shows that the economicandsocialimpactsarisingfromaSRPbasedcarbontaxareinfactlowerthan would be the case of a tax based on PPP – $83 million (565 minus 482) less in net economiccostsand2299(5291minus2992)lessjobslosses,foracarbontaxof$10per tonneofCO2. Further,theanalyseshasshownthatifanapriorilimit(roughlyequaltoKyototarget) is set for CO2 emissions from the electricity sector, a much higher level of carbon tax wouldbeneededinthecaseofPPP($25pertonne)andmuchlowerlevelofcarbontax wouldbeneededinthecaseofSRP($15pertonne).Whiletheneteconomiccostofa carbon tax based on PPP would be considerable ($60 billion, over the period 2005– 194 2020),suchcostinthecaseofSRPwouldbelower($35billion,overtheperiod2005– 2020).Theanalysesinthisresearchalsoshowthatdelayingtheintroductionofcarbon tax has considerably higher economic and social costs. In contrast, the unquestioning pursuance of economic growth objectives (as in the BC scenario) would cause significantincreaseinCO2emissions(84percentabovethe1990levels). Itisalwaysdifficulttochooseamongcompetingobjectivesandoptions.Thisresearch hasattemptedtodevelopinsightsintothetradeoffsbetweeneconomic,environmental, and social objectives that might assist the policy makers as they endeavour to make policychoicestoachieveabalancedandsustainablegrowth.Selectsuchtradeoffsare summarisedinTable613. Table613 Summaryofenvironmentaleconomicsocialtradeoffs $10pertonne $20pertonne apriori (Early) apriori (Delay) PPP SRP PPP PPP PPP TotalCO2savings(Mtonnes) 48 (11) 97 (22) 115 (27) 165 (38) 131 (30) 138 (32) 135 (31) 140 (33) Neteconomiccosts($Bn) 27 (0.4) 47 (0.7) 49 (0.8) 84 (1.3) 60 (0.9) 35 (0.5) 70 (1.1) 43 (0.7) Lossinemployment(000persons) 255 (2.7) 289 (3.1) 455 (4.8) 490 (5.2) 555 (5.9) 309 (3.3) 726 (7.7) 355 (3.8) Neteconomiccosts($Mn/Mt) SRP SRP SRP 565 482 426 507 454 252 516 303 Lossinemployment(persons/Mt) 5291 2992 3965 2963 4234 2239 5360 2528 Notes: Theinformationcontainedinthefirstthreerowsinthistableisassembledfromvarious tablesinthisChapter. Thelasttworowssummariseenvironmentaleconomicsocialtradeoffs.Forexample,undera carbontaxof$10pertonneinthecaseofPPP,1MtonneofreductioninCO2wouldimply $565millionofneteconomiccost,and5291foregonejobs. NumberinbracketsindicatespercentagedifferencesascomparedwiththeBCscenario. ThetableshowsthattheearlyintroductionofcarbontaxbasedonSRPprincipleoffers a relatively more attractive approach to simultaneously meeting environmental, economic, and social objectives. Adopting this approach would lead to highest emissions reductions, from lowest money spent, and the lowest number of jobs foregone. For example, every million tonne of reduction of CO2 would incur an economiclossof$252millionandalossof2239jobs.Further,introducingcarbontax based on SRP in 2010 (that is, deferred action) would still be superior to other approaches. For example, every million tonne of reduction in CO2 would incur an economic loss of $303 million and loss of 2528 jobs in the economy. However, 195 comparedtotheearlyaction,areductionofeverymilliontonneofCO2,inthedeferred action,wouldcost$51million(303minus252)moreand289(2528minus2239)more jobs losses. If carbon tax based on PPP is adopted immediately, it would cost an additional$202(454minus252)millionandresultin1995(4234minus2239)morejobs lossesforeverymilliontonneofreductioninCO2. Therefore,acarbontaxbasedonSRPprincipleshouldbeadoptedimmediately.Ifthe decisionforadoptingcarbontaxisdeferred,itwouldberatherdifficulttoachievenot onlyenvironmentalobjectivesbuteconomicandsocialobjectivesaswell. 6.7 SummaryandConclusions In this chapter, a carbon tax policy based on two different principles – Polluterpays (PPP) and Sharedresponsibility (SRP) – is analysed, and its impact on energy, environment,economy,andsocietyareassessed.Themajorconclusionsofthischapter aresummarisedasfollows: x In the absence of carbon tax (BC scenario), total CO2 emissions from the electricity sector are expected to increase, by the year 2020, by 95 per cent (to 250 Mt) above the 1990 level (128 Mt). Electricity produced from coal is expectedtodominatetheelectricitymixin2020,contributingnearly84percent to total electricity generation. The small increase in the share of renewable electricity due to the ongoing MRET scheme would increase the cost of electricity production from 4.7 ¢/kWh in 2004, to 4.92 ¢/kWh in 2020. The economy would grow at an average rate of 2.57 per cent per year to the year 2020, reaching $808 billion (1990 prices) in 2020. The economywide employmentwouldincreaseatanannualaveragerateof0.8percentreaching 9,444thousandpersonsin2020. x The analysis of the impacts of carbon tax, using a uniform tax rate, based on PPPandSRPshowsthat: A carbon tax based on SRP would result in an increase in the cost of electricity at a higher rate than that based on PPP. For a carbon tax of $20 196 per tonne, the cost of electricity production would reach, in the year 2020, 20.5¢/kWhinthecaseofPPP,and25.9¢/kWhinthecaseofSRP(in 2004 prices)(Table62).Thisisbecause,inthecaseofPPP,theelectricitysector(a directfossilfuelconsumer)isconsideredasthemainresponsiblepartyfor CO2 emissions, whereas in the case of SRP, indirect fossil fuel consumers, including renewable electricity sector, are also considered responsible for CO2emissions. The introduction of carbon tax would yield, for the government, revenues of$28and$53billion(1990prices),forPPP1andPPP2,respectively,overthe period2005–2020.ThecorrespondingfiguresforSRP1andSRP2are$74and $135 billion (see Table 67). Of these, the electricity sector would be responsible for approximately 50 and 20 per cent of total revenue, in the caseofPPPandSRP,respectively.Therevenuefromcarbontaxishigherin thecaseofSRPbecause,inthiscase,revenuewouldbecollectedfromboth directaswellasindirectfossilfuelconsumers,comparedwiththecollection ofrevenuefromjustdirectfossilfuelconsumersinthecaseofPPP. A carbon tax based on SRP would cause a larger reduction in coalfired power generation than would be the case with PPP. For example, for a carbon tax of $20 per tonne based on SRP, coalfired electricity would reduceby28percentascomparedtotheBCscenario,representing56per cent of total electricity generation in 2020. The same carbon tax rate in the caseofPPPwouldinsteadcausetheshareofcoalfiredelectricitytoreduce by23percent. The growth rate of CO2 emissions reduces substantially due to the introductionofcarbontax,withmorereductionsforthcomingwhencarbon taxisappliedbasedonSRP,ascomparedwiththecasewhenitisapplied basedonPPP.Forexample,foracarbontaxof$20pertonne,CO2emissions fromtheelectricitysectorwoulddeclineby53percent(or134Mt)fromthe BC level, when carbon tax is applied based on SRP. The corresponding figure for the PPP is 39.3 per cent (98 Mt). This is so because a carbon tax 197 basedonSRPalsotakesintoaccounttheenergyembodiedinmaterialsand, therefore, penalises the emitters from indirect energy consumption. The introductionofsuchataxwouldincreasethecostofelectricityproduction atahigherratethanifacarbontaxisimposedunderPPP(seeTable62).As a result, it would allow cleaner electricity production technology to penetratethemarketearlierthanifcarbontaxisbasedonPPP. The application of $10 per tonne of carbon tax would have net economic cost, over the period 2005–2020, of 0.4 and 0.7 per cent, in the case of PPP andSRP,respectively.Thecorrespondingvaluesforataxof$20pertonne are0.8and1.3percent.Thisisbecause,whenahigherlevelofcarbontaxis imposed, the cost of electricity from coal would increase considerably, which would induce more investment in cleaner electricity technologies. Because of this investment, carbon tax based on PPP would have slightly lesseconomicimpactthanthatbasedonSRP. Areductionineconomicoutputfromtheintroductionofcarbontaxwould alsocauseareductioninthelevelofemployment,intherangeof2.8to5.5 percent,withslightlymorereductioninthecaseofSRPthaninthecaseof PPP. For a carbon tax of $10 per tonne, the employment would reduce by 2.8percent(fromtheBCscenario)forthePPP,whileitwouldreduceby3.2 percent fortheSRP.However,thechangesin technologymixinducedby carbon tax would cause a shift of employment from the coal to the gas sector and from coalfired electricity technology to combinedcycle and renewabletechnology. x Ifanaprioriemissionslimit(equivalentto108percentof1990level)issetfor the electricity sector (that is, if CO2 emissions from the electricity sector are limitedto138Mtby2020),taxratesof$25and$15pertonneofCO2wouldbe required in the case of PPP and SRP approaches, respectively. The total economywide CO2 emissions in these cases would range between 291 (SRP) and300(PPP)Mt–approximately24(SRP)and28(PPP)percenthigherthan 198 the1990economywideCO2emissions(234Mt)andabout30percentlessthan theBCscenario(432Mt). AhigherleveloftaxwouldberequiredinthecaseofPPPbecause,basedon this principle, only direct fossil fuel consumers would be penalised; whereas, in the case of SRP, both direct and indirect fossil fuel consumers would be penalised. Therefore, a higher level of tax is needed for PPP to accelerateinvestmentincleanerelectricitytechnology. The accelerated rate of investment in cleaner electricity technology in the caseofPPPwouldcausethecost(in2004prices)ofelectricitytoincrease,by theyear2020,to24¢/kWhascomparedwith21¢/kWhinthecaseofSRP. A carbon tax based on PPP would have higher net economic and social impacts ascompared witha taxbased on SRP. The net economic lossesin the case of PPP ($60 billion) would exceed such losses in the case of SRP ($35 billion) by $25 billion. Further, 245 thousand more jobs (2.6 per cent) wouldbelostunderthePPPcase,ascomparedwiththeSRP. If the introduction of carbon tax is deferred by 5 years (that is, the tax is introducedintheyear2010),theoverallimpactswouldbemuchhigher.For example, to achieve the apriori limit, a tax of $51 per tonne in the case of PPP, and $26 per tonne in the case of SRP would be required. This would further accelerate investment in cleaner electricity technologies. Consequently,thecostofelectricitywouldbehigherthanwouldbethecase ifcarbontaxisintroducedimmediately.Thecostofelectricity,inthecaseof PPP and SRP, are expected to reach 31 and 24 ¢/kWh by the year 2020, comparedwith24and21¢/kWhinthecaseofearlyaction. The social impacts of deferred action would be higher, with 45,000 and 171,000morejobslosses,inthecaseofSRPandPPP,respectively.Interms of the economic impacts, an initial estimate, using present value for the period2005–2020,showsthatdelayingtheintroductionofcarbontaxwould save$18and$32billion,forSRPandPPP,respectively. 199 x This research has also demonstrated the pitfalls associated with the use of conventionalmethodsfor quantifying the impactsofcarbontax.Forexample, thisresearchhasshownthattheuseoftheconceptsofpresentvalueandfuture valuearelikelytoprovidesignificantlydifferentpolicyrecommendations.Ina similarvein,theextensionofthelifespanofanalysistotheyear2040islikely toresultinthestrengtheningofthecaseforanearlyintroductionofcarbontax. x The analysis in this chapter suggests that a carbon tax based on SRP offers a relatively more attractive approach to simultaneously meeting environmental, economic, and social objectives. By adopting such an approach immediately, every million tonne of reduction in CO2 would incur a cost $252 million and wouldresultin2239joblosses.Ifhowevertheadoptionofsuchanapproachis deferred, it would cost an additional $51 million and result in 289 more jobs lossestoachieveeverymilliontonneofreductionofCO2.Ifacarbontax,based on PPP, is adopted immediately, it would cost an additional $202 million and resultin1995morejoblossesforeverymilliontonneofCO2reduction. x Therefore, a carbon tax, based on SRP principle, should be introduced immediately.Ifthisdecisionisdeferred,itwouldberatherdifficulttoachieve notonlyenvironmentalobjectivesbuteconomicandsocialobjectivesaswell. 200 CHAPTER7 7 CONCLUSIONSANDRECOMMENDATIONSFOR FURTHERRESEARCH 7.1 Conclusions Themajorconclusionsofthisresearch,insummary,areasfollows: x Carbondioxide emissions (a major greenhousegas) from the electricity industryinAustraliaaresubstantialandincreasing. In1990,CO2emissionsfromfossilfuelcombustioninAustraliatotalled234 Mt. The electricity industry accounted for 55 per cent (128 Mt) of these emissions. The contribution of electricity industry to total CO2 emissions increasedto58percentin2004(184Mt).Thisrepresentsanincreaseof44 percent(from128to184MtinCO2emissionsfromtheelectricitysector),as compared with an increase of 35 per cent (from 234 to 316 Mt) in CO2 emissionsfromfossilfuelcombustion. Ifcurrenttrendscontinue,CO2emissionsfromfossilfuelcombustionwould reach 432 Mt by the year 2020 – an increase of 84 per cent above the 1990 level. Over the same period, CO2 emissions from the electricity sector are expectedtoincreaseby95percent(to250Mt)abovethe1990level. x Coalfired power stations account for approximately 95 per cent of total CO2 emissionsfromtheelectricitysector. Coal has always been the dominant fuel for electricity production in Australia, accounting, on average, for about 80 per cent of total electricity production over the last several decades. If present policy trends (for example,a continuinggovernmentfundingforthedevelopmentofcarbon 201 capturetechnologywitharelativelysmallmandatorytargetforrenewable energy)continue,theshareofcoalisexpectedtodeclineonlyslightlybythe year2020–to75percent. The abundance of indigenous coal resources provided initial incentive for the establishment of the coal–electricity compact. Over time, this compact wasstrengthenedbyeconomicandpoliticalinterests.Bythemid1900s,the ownershipoftheearlierpartprivateelectricityinterestsinvariousstatesin Australia had transferred to the state governments. These governments developedtheirpowerstationsbasedoncoalfieldslocatedwithinthestate. This marked the beginning of the technological lockin of coalbased infrastructures.Inthesecondhalfofthetwentiethcentury,aseriesoflarge coalfired power stations were built, with government subsidies, in anticipationofamineralsboom.Thisfurtherconsolidatedthetechnological lockinofcoalbasedtechnology. The economic and political interests soon transformed the technological lockin into an institutional lockin. The use of significant public funds in the form of subsidies in the development of power stations in the earlier decades has allowed the direct involvement of political interests into the electricity industry. The influence of these interests became evident in the investment strategies, including the selection of fuel (coal) for electricity generation. Even in the recent restructure of the electricity industry, rules which govern the national electricity market (for example, dispatching criteria) indirectly favour coalbased electricity generation. This demonstrates the significance of the institutional lockin of the coal– electricitycompactinAustralia. x Thecoal–electricitycompacthastraditionallyexertedastronginfluenceonthe developmentofenvironmentalpoliciesinAustralia,includingthegreenhouse gasreductionpolicies. 202 In the initial years of the international dialogue regarding climate change issue, Australia acted as a global leader in proposing strategies to combat this problem. A carbon tax was among the initial strategies that the Australiangovernmenthadconsideredinits“interimplanningtarget”,inthe early1990s,forreducinggreenhousegases.Later,however,astheeconomic impacts of carbon tax became clearer, especially on fossil fuel industries, Australiadrasticallychangeditsenvironmentalstance. The key policy initiatives thereafter (for example, National Greenhouse Response Strategy, Greenhouse Challenge Program, and Energy White Paper) firmly established the stance that favoured economic objectives over environmental objectives. Such initiatives have relied mainly on voluntary initiatives for the reduction of greenhousegases. Overall, Australia’s greenhousegasreductionpolicieswerecharacterisedbyafragmentedarray of shortterm commercial and economic interests and generally lacked considerationoflongtermenvironmentalsustainability. The use of marketbased approach, particularly carbon tax, has been continually rejected by the Australian federal political parties, on the grounds that it would impede economic growth. Perspectives on these expected impacts have created a “carbon tax phobia” among the coal electricity interests, which have significantly influenced the government’s greenhousepolicythinking. x A major premise of this research is that the opposition to carbon tax in Australiaisbasedonlessthanadequateunderstandingaboutitsvariousfacets, includingalternativeconceptionsofcarbontaxanditseconomywideimpacts. Traditionally, the notion of carbon tax – as generally debated – is formulated on the basis of Polluter Pays Principle (PPP). Based on this principle, the polluter (emitter) is defined as the consumer of primary energy(calleddirectenergy)wherecombustiontakesplace.CO2emissions resultingfromthecombustionprocessesarethereforeconsideredasthesole 203 responsibility of such a consumer. A carbon tax, by this reasoning, is expected to result in changing the behaviour of such a consumer (for example, coalbased electricity industry) – away from the use of CO2 producing fuels. The application of carbon tax, based on this principle, is consideredinequitablebysomeonthegroundsthatittendstopenalisebig fossilfuel industries (such as coalbased electricity industry) and not industries who consume the output produced by such products (for example,householdsandcommercialsectors). This criticism could be overcome to a large extent, it is argued in this research,byconsideringanalternativeconceptionofcarbontax–basedon Shared Responsibility Principle (SRP). This principle assigns the responsibility for CO2 emissions not only to the consumer of primary energy, but also the consumer of the products and services (for example, electricity consumed by commercial sectors or material inputs used by electricity sector for electricity production) whose production would have caused CO2 emissions (such inputs are called indirect energy inputs). This principle therefore provides a more complete representation of energy economyenvironmental interactions. This method also promotes fairness (intermsofemissionsaccreditation)betweenallactorsinvolved. x Againstthisbackground, thisresearch analysedtheeconomywideimpactsof carbon tax, based on PPP and SRP, for reducing CO2 emissions in Australia. These impacts included impacts on energy and nonenergy sectors of the economy. Theenergyimpactsareanalysedintermsofthechangesinthecomposition of fuel and technologymix for electricity generation, arising from the increases in the cost of electricity due to the introduction of carbon tax. These changes are quantified in terms of primary energies required to produceelectricity,andhenceCO2emissions. 204 Nonenergy economywide impacts are analysed in terms of net economic costs(thatis,thenetoflossofGDPandfiscalrevenuegain), inflation,and employment. Twocasesareconsideredinthisresearch: a) noapriorilimitonCO2emissions.Forthiscase,foursubcasesdenoted PPP1, SRP1, PPP2, and SRP2, are analysed. PPP1 and SRP1 refer to the case of a carbon tax of $10 per tonne of CO2 emissions, based on PPP andSRP,respectively.PPP2andSRP2refertothecaseofacarbontaxof $20pertonneofCO2emissions,basedonPPPandSRP,respectively. b) apriori limit – equivalent to 108 per cent of CO2 emissions from the electricity sector, as compared with 1990 level (that is 138 Mt), by the year2020. Thevariousimpactsarequantified,inthisresearch,intermsofdifferences from the values that would be obtained in the businessasusual state of affairs,calledtheBaseCasescenario(BC). x Themajorimpactsofcarbontax(basedonPPPandSRP)ontheenergysector inasituationofnoaprioriemissionslimitarepresentedbelow: The technologymix for electricity generation would be appreciably influencedbytheintroductionofcarbontax.Particularly,carbontaxwould resultinadeclineintheshareofcoalfiredelectricitytechnology.Acarbon tax based on SRP would generally lead to a larger reduction (between 21 and28percent)incoalfiredpowergeneration,comparedtothatbasedon PPP,forthesameleveloftax.Forexample,intheBaseCase(BC),coalfired generationisexpectedtocomprise84percentoftotalgenerationintheyear 2020.InthecaseofSRP1andSRP2,thispercentageisexpectedtoreduceto 63 and 56 per cent, respectively. The corresponding values for PPP are 74 and61percent. 205 The reduction in coalfired electricity would be replaced mainly by renewable technology. For example, in the case of a carbon tax of $20, for bothPPP2andSRP2,theshareofrenewableisexpectedtoincreaseto28per centin2020(ascomparedwith10percentinBC).Ontheotherhand,inthe caseofa carbontaxof $10 (forbothPPP1andSRP1),coalfiredtechnology wouldbereplacedmainlybynaturalgasbasedcombinedcycletechnology; theshare ofcombinedcycletechnologywould, intheyear2020, be 14per centforPPP1and22percentforSRP1(ascomparedwith4percentinBC). These changes in technologymix would significantly increase the cost of electricity, more in the case of SRP, especially at higher tax rates. For example,in thecaseof PPP,the costof electricity,in2020,wouldincrease from4.7¢/kWhin2004,to13.4(PPP1)and20.5(PPP2)¢/kWh.TheBCvalue in2020isestimatedtobe4.9¢/kWh.ThecorrespondingvaluesforSRP1and SRP2areexpectedtobe16.7and25.9¢/kWh,respectively. Carbontaxisexpectedtoresultinasignificantdeclineintherequirements ofprimaryenergyforelectricityproduction.Suchdeclinesareestimatedto be 10.2, 19.9, 20.1, and 35.4 per cent for PPP1, SRP1, PPP2, and SRP2, respectively. Theuseofcoal(bothblackandbrowncoal)inelectricityproductionwould reduceconsiderably,withmorereductionsinthecaseofSRP(24and31per cent,forSRP1andSRP2,respectively)thaninthecaseofPPP(13and24per cent,forPPP1andPPP2,respectively).Theextentofsubstitutionofcoalwith either naturalgasor renewable varies,depending onthe rate ofchangein technologymixfor eachcaseof carbontax.For example, inthe casePPP1, theuseofnaturalgaswouldbe282PJhigherthantheBC.Thisisbecauseof the increased share of natural gasbased combinedcycle in the total electricity generation. In contrast, the use of renewable energy in the case PPP2wouldbe406PJhigherthantheBCduetoanincreaseintheshareof renewable technology for electricity production. Similarly, in the case of SRP1,theuseofnaturalgaswouldbe441PJhigherthantheBC;whilethe 206 useofrenewableenergyinthecaseofSRP2wouldbe265PJhigherthanthe BC. ThegrowthrateofCO2emissionsfromtheelectricitysectorwouldreduce substantially due to the introduction of carbon tax, with more reductions forthcoming when carbon tax is applied based on SRP, as compared with thecasewhenitisappliedbasedonPPP.InthecaseSRP2,forexample,the CO2emissionsfromtheelectricitysector(116Mt)wouldfallbeloweventhe Kyototarget(138Mt).Incontrast,CO2emissionsinthecasePPP2wouldbe 118percent(152Mt)ofthe1990level.Thisimpliesthat,inordertoachieve the Kyoto target of 108 per cent (138 Mt) of the 1990 level from the electricity sector, a higher level of carbon tax (more than $20 per tonne) wouldberequiredifcarbontaxisbasedonPPPthanwhenthecarbontaxis basedonSRP. x Major nonenergy impacts of carbon tax, based on PPP and SRP, with no a prioriCO2emissionslimitaresummarisedbelow: In general, the introduction of carbon tax would lead to a slowdown in economicactivity(thatis,GDP).Forexample,inthecaseofSRP,carbontax wouldcausetheeconomicoutputtoreduceintherangeof1.9($120billion) to3.5($219billion)percentofitsexpectedvalueintheBC($6325billion), over the period 2005–2020. The corresponding reductions for PPP are 0.9 ($56billion)and1.6($102billion)percent. However,overthisperiod,theintroductionofcarbontaxwouldyield,for thegovernment,ataxrevenueofbetween$28and$53billioninthecaseof PPP,and$74to$135billion,inthecaseofSRP.Foracarbontaxbasedon PPP, more than 50 per cent of tax revenue would be collected from the electricitysectoralone,particularlyfromcoalfiredgenerators.Inthecaseof SRP, the commercial sector (a major electricity and materials consumer) would be penalised significantly. Its share of tax revenue would increase from1percent(forPPP)toover20percentforSRP. 207 Considering both economic impacts, namely, the reduction in GDP and gainintaxrevenue,theneteconomiccostsfromtheintroductionofcarbon taxwouldbeintherangeof$27to$49billionforPPP,and$47to$84billion forSRP. A reduction in economic output due to the introduction of carbon tax wouldalsocauseareductioninthelevelofemployment,intherangeof2.8 to5.5percent,withslightlymorereductioninthecaseofSRPthaninthe caseofPPP.Foracarbontaxof$10pertonne,theemploymentwouldbe2.8 per cent less, as compared with the BC scenario, for PPP,and 3.2 per cent less for SRP. Further, the technologymix induced by the introduction of carbon tax would cause a shift of employment from the coal sector to the gas sector, and from coalfired electricity sector, to combinedcycle and renewableelectricitysectors. x Themajorimpactsofcarbontax–inasituationofanaprioriCO2emissions limit equivalent to 108 per cent CO2 emissions from the electricity sector as comparedwith1990level(thatis138Mt)bytheyear2020–arenotedbelow: Whenacarbontaxisintroducedin2005(earlyaction),taxratesof$25and $15 per tonne of CO2 would be required in the PPP and SRP approaches, respectively. The total economywide CO2 emissions in these cases would rangebetween291(SRP)and300(PPP)Mt–approximately24(SRP)and28 (PPP)percenthigherthanthe1990economywideCO2emissions(234Mt) and about 30 per cent less than the BC scenario (432 Mt). This carbon tax (bothPPPandSRP)wouldcausetheshareofcoalfiredpowergenerationto reduce to 58 per cent of total generation. In the case of PPP, the share of renewable and naturalgasfired combinedcycle electricity would increase to 31 and 9 per cent, respectively. The corresponding shares in the case of SRPwouldbe23and17percent.Consequently,thiswouldcausethecost ofelectricitytoincreaseto23.9¢/kWh,inthecaseofPPP,and21.3¢/kWhin thecaseofSRP.CarbontaxbasedonSRPwouldhaverelativelymildernet economicandsocialimpactsascomparedwithataxbasedonPPP.Thisis 208 because,forSRP,thehigherimpactonGDP($170billionreduction)would be offset by high revenues ($135 billion) received by the Government. The overallneteconomiclosseswouldbe$35and$60billion,forSRPandPPP, respectively. Further, 245 thousand more jobs (2.6 per cent) would be lost underthePPP,ascomparedwithSRP. When a carbon tax is introduced in 2010 (deferred action), the impacts wouldbemuchhigher–ataxof$51pertonnewouldbeneededinthecase ofPPPtoachievetheaprioriCO2emissionstarget.InthecaseofSRP,atax of $26 per tonne would be needed to meet the CO2 emissions target. The costofelectricity,inthecaseofPPPandSRP,areexpectedtoreach30.8and 24.3¢/kWhintheyear2020,comparedwith23.9and21.3¢/kWhinthecase ofearlyaction.Thesocialimpactsofdeferredactionwouldalsobehigher. Nearly45,000and171,000morejobslosseswouldoccurinthecaseofSRP and PPP, respectively. However, the overall economic impacts of deferred action, expressed in present value terms, for the period 2005–2020, are $18 and$32billionlowerascomparedwiththecaseofearlyaction,forSRPand PPP,respectively.Onemightthereforeinferthatadelayedintroductionof carbontaxismoredesirable.Suchinferencewouldhoweverbeerroneous, this research has shown. For example, if the overall economic impacts are expressedinfuturevalueterms,oriftheperiodofanalysisisextendedtothe year 2040, entirely different inferences could be drawn – such analysis suggeststhattheearlyintroductionofcarbontaxisabetterproposition. x Overall, the analysis in this research suggests that a carbon tax based on SRP offers a relatively more attractive approach to simultaneously meeting environmental,economic,andsocialobjectives.Byadoptingsuchanapproach immediately,everymilliontonneofreductioninCO2wouldincuracost$252 millionandwouldresultin2239joblosses.Ifhowevertheadoptionofsuchan approachisdeferred,itwouldcostanadditional$51millionandresultin289 morejobslossestoachieveeverymilliontonneofreductionofCO2.Ifacarbon tax, based on PPP, is adopted immediately, it would cost an additional $202 209 million and result in 1995 more job losses for every million tonne of CO2 reduction. x Therefore, this research recommends an early introduction of a carbon tax, basedonSRP.Ifthedecisionforintroducingsuchataxisdeferred,itwouldbe ratherdifficulttoachievenotonlyenvironmentalobjectivesbuteconomicand socialobjectivesaswell. 7.2 SomeRecommendationsforFurtherResearch Somesuggestionsforfurtherresearchincludethefollowing: a) Theeconomicimpactsofcarbontaxanalysedinthisresearchpresentsonlyone side of the story, that is, costs imposed on the economy if a carbon tax is introduced, or simply – the cost of action. The cost of inaction, and the consequentialdamagethatcouldbecausedbyincreasedglobalwarming,was not considered in this research. Such cost may include cost of remedy or economic adaptation to the new environmental settings which would result from the climate change. It is suggested that future research should analyse both–theeconomicandenvironmentalcostsofactionaswellasinaction.This would enhance the policy maker’s appreciation for the wide impacts of their policychoices. b) This research has applied essentially topdown approaches (for example, Input–outputandProductionfunction)fortheanalysisoftheimpactsofcarbon tax.Theenergysystemhasbeenrepresentedintheformofenergyandmaterial flowsintheeconomy.Anintegrationofbottomupapproach(suchasReference EnergyMaterialSystemAnalysis,seeSection4.3.3),withtopdownapproaches developed in this research, could allow a wide range of environmental policy options (for example, supply and demandside management, material substitution,materialrecycling,etc.)tobeassessed.However,lackofdatamay beamajorchallengeforsuchanapproach. c) 210 The analysis of embodied energy has been computed, in this research, from monetaryinput–outputtables.Formoreaccurateanalysis,Input–Outputtables expressedinphysicalunits(forexample,kWh,ton,m3,m2,etc.)shouldbeused. However,thislevelofdetailiscurrentlyunavailableforAustralia. d) Themultilevelproduction(cost)functionmodelemployedinthisresearchwas applied for the electricity industry only. Although the utility (expenditure) function model was also applied in this research to allow for the changes in finaldemand(suchasconsumptionandexports),thisstilllimitstheassessment of full economic response to the introduction of carbon tax. Future research shouldemploysuchanalysisforallproductionsectorsoftheeconomy(notjust electricity). This can be done by applying a “flexible” form of production function for all production sectors (as was done, in this research, for the electricitysector). e) In this research, the electricity sector has been disaggregated into five generation technologies to allow for technological shifts between emission intensiveandcleanertechnologies.Similarapproachofdisaggregationforother economic sectors could also be considered. This would deepen the scope of technological adjustments in the economy, for example, in response to the increases in the prices of emissionintensive technologies due to the introduction of carbon tax. For example, road transport can be disaggregated intodifferenttypesofvehiclemodes,suchascars,buses,trucks,trains,etc.,in ordertoallowshiftsbetweendifferenttypesofvehiclesinresponsetoacarbon tax. f) Thisresearchusedacommoninterestratetoestimatesthepriceofcapital(for use in the production function model) for different types of electricity technologies(seeSection5.7.2,p.132).Inreality,differenttypesoftechnologies arelikelytobefacedwithdifferentinterestrates.Theuseofsuchrateswould improvethequalityofanalysis. g) 211 This research has analysed carbon tax based on CO2 emissions. It is recommendedthatothertypesofemissions(suchasSO2,N2O,NOx,CH4,etc.) should also be included in the analysis. Further, if all types of environmental emissions (and negative externalities) are considered, it would be worthwhile to analyse the impact of replacing existing tax system (that is, tax based on labour or income) with a comprehensive environmental tax (that is, tax based onenvironmentaldisruptions). h) Thepossiblealternativeusesofcarbontaxrevenue havenotbeenanalysedin this research. Such analysis could provide valuable insights for formulating policyprioritiesfordevelopingsustainabilityenhancingprojects. i) This research has considered the impacts arising from the introduction of a (domestic) carbon tax in Australia. For climate change (which is a global problem),aworldwideanalysisshouldbecarriedout;thiscouldprovidebetter insights for developing multilateral responses to redress the environmental problems. j) Although this research has analysed the impacts of carbon tax, the ideas developed in this research (that is, the idea of Shared Responsibility Principle based on materialsbalance framework) could also be applied to analyse alternative environmental policies, such as, emissions trading. In this case, it canbedoneviatheconceptof“reallocation”ofpermitsandtheimpactsofsuch reallocation. 212 APPENDIXA ExampleofEmissionsAllocation:PPPvs.SRP This appendix presents a simplified numerical example for apportioning the responsibility for CO2 emissions to various economic sectors based on the Polluter PaysPrinciple(PPP)andtheSharedResponsibilityPrinciple(SRP). Assumesahypotheticaleconomyconsistingoffoursectors:primaryenergy,electricity, industry (I), and household (H). Two types of primary energy – fossil (F) and renewable (R) – are available in the economy. Electricity is produced from this hypothetical economy using two types of technologies – fossilfuelbased (ESIF) and renewablebased(ESIR).Emissionsfactorsforfossilandrenewableenergyareassumed tobe100and0ktonnesperPJ,respectively. WithreferencetoPPP,asdiscussedinSection3.3.2,energyconsumedintheeconomy canberepresentedinanenergybalanceframework,asshowninFigureA1.Here,the flowofenergyisrelativelystraightforward,beginningwithprimaryenergyextraction from the environment, to energy conversion (in power plants), and ending with its consumptionsinvariousenduses(forexample,cookinginhouseholds,motivepower inindustries). FigureA1 Energybalanceframework 213 Emissions,basedonPPP,areasfollows: kt PJ ESI R 20 PJ u 0 ESI F 80 PJ u100 I H 50 PJ u100 kt PJ 0Mt kt PJ 8Mt 5Mt 0Mt TotalEmissions=13Mt As shown in the above calculation, fossilfuel consumers are responsible for most of theemissionsintheeconomy(thatis,fossilfuelbasedelectricityproductionsectoris responsible for 62 per cent (8 Mt), and industrial sector for 38 per cent (5 Mt), of emissions). Incontrast,emissionsallocationaccordingtoSRPcanberepresentedinanmaterials balance framework, as shown in Figure A2. Here, in addition to energy flows as shown in energybalance framework, material flows in the economy are also shown. For example, renewable electricity industry is shown as the consumer of primary renewable energy, electricity from its own production, and materials from industrial output. For simplicity, it is assumed that the production of primary energy does not require any input. The input pattern of each production and consumption sector withinmaterialsbalanceframeowrkisshowninFigureA3. 214 FigureA2 Materialsbalanceframework FigureA3 Specificationofproduction/consumptionpattern FromFigureA3,inordertoproduce1TWhofelectricityfromrenewabletechnology, 0.1TWh of electricity and 0.56tons of material are consumed; fossilfuel based technologyconsumes0.1TWhofelectricityand0.3tonsofmaterial;onetonofmaterial production would require 1.6TWh of electricity and 0.07tons of material; and each householdwouldconsume0.2TWhofelectricityand0.07tonsofmaterialfor$1oftheir consumptionexpenditure. 215 Emissions,basedonSRP,areasfollows: ESI R ª§ kt kt · § ·º «¨ 20 PJ u 0 PJ u 0.1¸ ¨ 50 PJ u 100 PJ u 0.56 ¸ » ¹ © ¹¼ ¬© ESI F ª§ kt kt · § ·º «¨ 80 PJ u 100 PJ u 0.1¸ ¨ 50 PJ u 100 PJ u 0.3 ¸ » ¹ © ¹¼ ¬© I H 3.1Mt 2.1Mt ª§ kt kt kt · § · § ·º «¨ 80 PJ u 100 PJ u 0.8 ¸ ¨ 20 PJ u 0 PJ u 0.8 ¸ ¨ 50 PJ u 100 PJ u 0.07 ¸ » ¹ © ¹ © ¹¼ ¬© 6.7Mt ª§ kt kt kt · § · § ·º «¨ 80 PJ u 100 PJ u 0.1¸ ¨ 20 PJ u 0 PJ u 0.1¸ ¨ 50 PJ u 100 PJ u 0.07 ¸ » 1.1Mt ¹ © ¹ © ¹¼ ¬© TotalEmissions=13Mt As shown in the above calculation, emissions based on SRP are allocated differently from emissionsthatarebasedonPPP. SRPconsidersboth directandindirectenergy consumption. Here, industrial, renewable electricity, fossilfuel based electricity, and householdsareresponsiblefor52,24,16,and8percent,respectivelyoftotalemissions intheeconomy.Thecontributiontoemissionsofrenewableelectricityisgreaterthan fossilfuel based electricity. This is because the former consumes more emission intensivematerialsperunitofelectricityproducedthanthelatter. 216 APPENDIXB DescriptionofInput–outputandProductionFunctionModels This appendix describes the key elements of input–output model and production functionmodel–twomodelsusedinthisresearch. B.1 Input–outputModel Thissectionpresentsthefundamentalstructureofinput–outputmodel.Thisstructure servesasthebasisforallinput–outputanalysisinthisresearch.Thedescriptioninthis section mainly draws from wellestablished literature on this topic, for example, Miernyk (1965), BulmerThomas (1982), and Miller & Blair (1985). First, a brief backgroundofinput–outputmodelisprovided.Then,therelationshipbetweeninput– output table and national accounts is discussed. This is followed by a discussion of basicinput–outputmodel.Next,theinput–outputpricemodelisdiscussed.Finally,a dynamicversionofinput–outputmodelispresented. B.1.1 BackgroundofInput–outputModel Input–outputmodelhasitsoriginsintheeighteenthcentury–‘TableauÉconomique’of FrançoisQuesnay(1758).Quesnayshowedhowsalesandexpenditurescouldbetraced in an economy in a systematic way. The next major contribution in this regard was made by Léon Walras (1874), who developed a general equilibrium model in an attempt to solve simultaneously the demand and supply balance of all economic sectors.Thisworkemployedasetofproductioncoefficientsthatrelatedthequantities of factors required to produce a unit of a particular product to the levels of total productionofthatproduct.Bothworksdemonstratedthepracticalusefulnessofbeing abletodescribeinterindustrylinkages.However,thelackofsophisticatedmethodsto compilecomprehensivedatarequiredforanalysisandthedifficultiesinmanipulating vastamountsofinformationlimitedthepotentialusefulnessofthistypeofanalysis.It was only when Wassily Leontief (1936) presented an input–output system of the US 217 economy and developed a more rigorous analytical framework that the use of this techniquebecamepopular.Somuchsothatovertheyearsthismethodhasbecomeone ofthemostwidelyappliedmethodineconomics. B.1.2 Input–outputTableandNationalAccounts The basic Leontief input–output analysis is generally constructed from observed economic data for a specific geographic region. It includes the activities of industries thatbothproducegoods(outputs)andconsumegoodsfromotherindustries(inputs) in the process of production. The fundamental information with which one deals in input–outputanalysisiscontainedininput–outputtable. The input–output table constitutes a concise and systematic database that provides usefulinformationonacompletesetofincomeandproductsaccountinaneconomy. This input–output table describes the flow of goods and services between all the individual sectors of an economy over a particular time period. The schematic of input–outputtableispresentedinFigureB1. SchematicrepresentationofInput–outputtable TotalOutput Producers(i) FigureB1 218 Each rows of this table describes the allocation of a sector’s output throughout the economy. The output of sectors from row i that are distributed to other production sectorsineachcolumnjarecalledintermediategoods.Thisislocatedinquadrant‘A’ ofinput–outputtable.Thisinterindustryflowisregardedasthecoreofinput–output analysis.Further,theoutputofsectorithatdistributedtofinalmarkets(suchasoutput required for final consumption, investment, and exports) are called final demand goods. These final demand sectors represent household consumption, government consumption, consumption for investment purposes, and exports. This final demand category constitutes the gross national product of the economy and is located in quadrant ‘B’ of input–output table. If the economy is divided into n sectors, the relationshipofeachrowinFigureB1canbeexpressedas: Xi n ¦x ij Yi (B1) j 1 where Xi: totaloutput(production)ofsectori; xij: outputofsectoriusedbysectorj(orintermediategoods);and Yi: totalfinaldemandforsectori. Ontheotherhand,eachcolumnoftheinput–outputtabledescribesthecompositionof inputsrequiredbyaparticularindustry.Theseinputsaresuppliedbyotherindustries (intheformofintermediateinputs),fromprimaryfactorsofproduction(intheformof valueadded), and from imports. The primary production factor and purchases of imported inputs are located in quadrant ‘C’. If the imports row in quadrant ‘C’ is movedtotheappropriateexportscolumninquadrant‘B’tomakea‘net’exports,the onlyremainingvalueaddedwouldrepresentsthegrossnationalincome(i.e.,income totheownersofprimaryproductionfactors)intheeconomy.SimilartoequationB1, therelationshipofeachcolumninFigureB1canbeexpressedas: Xj n ¦x ij i 1 where Vj (B2) 219 Xj: totalinputofsectorj; xij: outputofsectoriusedbysectorj(orintermediategoods);and Vj: totalvalueaddedforsectorj. TheexpressionsinequationB1andequationB2constitutetherelationshipbetween input–output table and the national account in terms of gross national income and grossnationalproducts.Thisrelationshipwouldallowtheanalysistobecarriedoutat adisaggregatedmicroeconomiclevelandatanaggregatemacroeconomiclevelatthe sametime(Proops,Faber&Wagenhals1993). Inordertocompletethediscussiononthestructureofinput–outputtable,itisworth mentioning that the elements in quadrant ‘D’ (the intersection of the final demand column and the valueadded row) represent payments by final consumers for value addeditems(Miller&Blair1985). B.1.3 BasicInput–outputModel TheexpressioninequationB1providesausefulrepresentationofeconomicactivities atdisaggregatelevels.However,itisinsufficientforthepurposeofempiricaleconomic analysis (Proops, Faber & Wagenhals 1993). For example, it is not possible for using expressioninequationB1todeterminethesectoraloutputandinputrequirementsto meetacertainlevelofeconomicgrowthfromdemandsidepolicyinitiatives. InordertomakeuseoftheexpressioninequationB1forempiricaleconomicanalysis, it is necessary to modify the economic representation in input–output table into an appropriate functional form. This is typically accomplished by assuming a linear production function57 called Leontief production function (further discussion on productionfunctionispresentedinSectionB.2). In basic microeconomics theory, a production function denotes that maximum output that couldbeproducedfromagivensetofinputswiththehelpoftheexistingtechnology(Miller &Blair1985). 57 220 Thisassumptionimpliesthatthereexistsafixedrelationshipbetweenasector’soutput anditsinputs.Inotherwords,itimpliesafixedproportionalityofinputswithoutputs in each sector. As a result, the input–output model ignores the economies of scale in productionaswellasthepossibilityofsubstitutionbetweenfactorsofproduction. Assuming Leontief production function, the inputs to a particular sector can be expressedbythelinearrelations: xij aij X j aij xij Xj (B3) where aij: Input–output(technicalortechnological)coefficients. These coefficients define the inputs purchased by sector j from sector i per monetary unitofsector’sjoutput.Thetechnicalcoefficientsareassumedtobeconstantininput– outputanalysis. BysubstitutingrelationshipB3intoequationB1,theoutputequationbecomes: Xi n ¦a ij X j Yi (B4) j 1 Here the output of sector i is the sum of final demand for that sector and its intermediate demand required by sector j. The equation B4 illustrates the interdependence between all sectors in an economy in terms of interindustry flows (Miller & Blair 1985). For a n sector economy, equation B4 will have a system of n (linear) simultaneous equations, describing the use of each sector’s output in the economy.ThesystemofnsimultaneousequationsforexpressionB4canbewrittenin amatrixformas: ª X1 º «X » « 2» « # » « » ¬Xn ¼ ª a11 «a « 21 « # « ¬ an1 a12 a22 # an 2 ! a1n º ª X 1 º ª Y1 º ! a2 n »» «« X 2 »» ««Y2 »» % # » « # » «#» » « » « » ! ann ¼ ¬ X n ¼ ¬Yn ¼ (B5) 221 TheequationB5canbesimplifiedinitscondensedmatrixformas: X AX Y X AX Y (B6) where X: columnvectorsofsectoraloutputs; Y: columnvectorsofsectoralfinaldemand; A: matrixoftechnicalcoefficients. Usingthebasicconceptsofmatrixalgebra,with‘I’astheunitidentitymatrix,equation B5canbereorganisedtogive: X I A 1 Y (B7) Equation B7 is the fundamental matrix representation of input–output model. The inverse matrix ( I A) 1 is known as the ‘Leontief inverse matrix’. This matrix is a complicated expression indicating all of the direct and indirect requirements for productionintheeconomy(Cruz2002).Tomaketheabovestatementclearer,equation B7isdecomposedintoinfiniteseriesofmatrixproductsas: X I A A X Y AY A Y A Y ! A Y 2 A3 ! Af Y 2 3 f (B8) (B9) AspointedoutbyProopsetal.(1993,p.112),Y–theentityontherighthandsideto theequationB9–representsthedirecteffectrequiredtofulfiltheincreaseinthefinal demand,whereastherestoftheentitiesrepresentindirecteffectoftheincreaseinfinal demand. B.1.4 PricesinInput–outputModel Thediscussionofinput–outputmodelinSectionB.1.3focusedonoutputidentity(that is, it focused on total output derived from equation B1). In fact, the specification of input–output model allows the consideration of duality – quantity and price – problem.Theflowswithintheinput–outputtable,asdiscussedearlier,arerepresented 222 in value terms (that is, quantity x price). Therefore, the price identity can also be representedintheinput–outputmodel. Using primaldual relationship within input–output model, equation B2 can be writteninpriceformas: n ¦ a P V Pj ij i j (B10) i 1 where Pj: pricesofsectorjproducts; Pi: priceofinputipaidbysectorj;and Vj: ratioofsector’sjvalueaddedtoitstotaloutput. From equation B10, the price of any particular sector j depends on the use of intermediateinputsandtheuseofprimaryinputsasafactorofproduction. SimilartoequationB5,thecompletepricesystemcanbewritteninmatrixnotationas: ª P1 º «P » « 2» «#» « » ¬ Pn ¼ ª a11 «a « 12 « # « ¬ a1n a21 ! an1 º ª P1 º ªV1 º a22 ! an 2 »» «« P2 »» ««V2 »» # % # » «#» «#» » « » « » a2 n ! ann ¼ ¬ Pn ¼ ¬Vn ¼ (B11) EquationB11canbesimplifiedinitscondensedmatrixform,similartoequationB6 as: P AcP V P AcP V (B12) where P: vectorofsectoralpriceindices;and V: matrixwhosegenericelements–vij–representtheratioofsectoralvalueadded tototaloutput. Usingthebasicconceptsofmatrixalgebra,with‘I’astheidentitymatrix,equationB12 canbereorganisedas: 223 P I Ac 1 V (B13) EquationB13istheLeontief’spricemodel.Thismodelcanbeusedto‘assesstheimpact on prices throughout the economy of an increase in valueadded costs in one or more sectors’ (Dixon&Rimmer2000;Kula1998;Melvin1979;Miller&Blair1985,p.356). Additionally, the impact of changes in the cost of a particular product (instead of valueaddedcosts)onothersectorpricescanbeanalysedwithininput–outputmodel. Thiscanbedoneby exogenouslyspecifyingsuchproductpricesandexcludingthem from the traditional Leontief’s price model discussed above (Miller & Blair 1985; Valadkhani&Mitchell2002).Forinstance,theimpactofchangesinenergyprice(PE) on other material prices (PM) can be analysed by assuming PE as exogenous and estimating PM endogenously. Thus, according to Valadkhani and Mitchell (2002), equationB12canbeseparatedintoexogenousandendogenouscomponents: ª PE º «P » ¬ M¼ c ª AEE « Ac ¬ EM c º ª PE º ª VE º AME c »¼ «¬ PM »¼ «¬VM »¼ AMM (B14) With PE omitted from the traditional price model, in order to find PM, equation B14 canbewrittenas: PM c PE AMM c PM VM AEM (B15) SimilartoequationB13,equationB15canbewrittenas: PM 1 1 ª I AMM c AEM c PE º ª I AMM c VM º ¬ ¼ ¬ ¼ (B16) Equation B16 can be used to assess the impact of changes in price of one or more sectorthroughouttheeconomy. B.1.5 CapitalStocksinInput–outputModel The discussion of input–output model so far has focused on current flows of goods, needed for current production. The technical coefficients ‘A’ reflect the (fixed) relationshipbetweenthesecurrentflows.However,goodsproducedintheeconomyat aparticulartimenotonlyfulfilcurrentdemandbutalsocontributetothebuildupof 224 capitalstock.Inthebasicinput–outputmodel,thiscapitalstockisconsideredasapart offinaldemand(inquadrant‘B’,inFigureB1).Itislumpedtogetherinasinglesector called“grossfixedcapitalexpenditure(investment)”.Sincetheseinvestmentgoodsare ultimately used as inputs in production processes, they can be treated as a part of intermediatedemand(forcapital)ratherthanoffinaldemand.Followingthemethod proposed by Lenzen (1998), the investment vector needs to be internalised into the intermediatedemandmatrixandsubtractedfromthefinaldemandmatrix. Lettheoutputofsector ithatisheldbysectorjascapitalstockbedenotedaszij.An extensionofequationB1,byexplicitlyconsideringinvestment,canbewrittenas: Xi n n ¦x ¦z ij j 1 ij Yi (B17) j 1 Here, Yi referstoallfinaldemandcategoriesexcludingthedemandforinvestment. Again,assumingaLeontiefproductionfunction,thecapitalstockheldbyaparticular sectorcanbeexpressedbythelinearrelations: zij zij kij X j kij Xj (B18) where kij: capitalcoefficients. These capital coefficients are defined as the quantities of capital required by sector j thataresuppliedfromsectoripermonetaryunitofsector’sjoutput(Miernyk1965). Similartothetableoftechnicalcoefficients,atableofcapitalcoefficientsshowscapital requirementsperunitofcapacitybyindustryoforigin,foreachindustryintheinput– outputmodel. BysubstitutingrelationshipB18intoequationB17,theoutputequationbecomes: Xi n n j 1 j 1 ¦ aij X j ¦ kij X j Yi (B19) 225 Heretheoutputofsectoriisthesumfinaldemandforthatsector,theoutputrequired forproductiondemandforallsectors,andtheoutputrequiredforinvestmentdemand forallsectors. For a n sector economy, equation B19 will have a system of n (linear) simultaneous equations,describingtheuseofeachsector’soutputthroughouttheeconomy.Thiscan bewritteninacondensedmatrixformas: X AX KX Y X AX KX Y (B20) where X: columnvectorsofsectoraloutputs; Y*: columnvectorsofsectoralfinaldemandexcludingdemandforinvestment; A: matrixoftechnicalcoefficients;and K: matrixofcapitalcoefficients. Usingthebasicconceptsofmatrixalgebra,with‘I’astheunitidentitymatrix,equation B20canbereorganisedtogive: X 1 ª¬ I A K º¼ Y (B21) Becausethe‘K’matrix,derivedfrominput–outputtable,givestheoriginofinvestment inputs to each sector in the year of the survey, there can be severe distortions in the analysisifthismatrixisadoptedforoneyear.Toavoidsuchdistortion,Miernyk(1965) andPeet(1993)suggestedtheuseofweightedmeancapitalcoefficientsderivedfrom several input–output tables. This would levelise the use of investment input, over a certainperiod,forvariousproductionprocessesintheeconomy. B.2 ProductionFunctionModel Thissectiondescribestheconceptualunderpinningsoftheproductionfunctionmodel employedinthisresearch.Themodeldescribesinthissectionmainlydrawsfromwell knownliteratureonproductionfunctionmodels,forexample,Christensenetal.(1971; 1973), Binswanger (1974), Berndt and Wood (1975), and Jorgenson (2000). First, a 226 comparison is made between the general Leontief production function and other neoclassicalproductionfunctions.Then,abriefbackgroundofneoclassicalproduction function is given. This is followed by a discussion of production function model that couldusetheconceptofdualitybetween‘cost’and‘production’forempiricalanalysis. Then the econometric specification of the cost function model employed in this researchisdiscussed.Finally,thederivationofelasticitiesfromthecostfunctionmodel ispresented. B.2.1 Leontiefvs.NeoclassicalProductionFunctions In microeconomics theory, a production function denotes that maximum output that couldbeproducedfromagivensetofinputswiththehelpoftheexistingtechnology (Miller&Blair1985).Ageneralformofproductionfunctionwhichrelatestheinputsof capital,labour,energy,andmaterialstotheproductioninanysector(oranycolumnof input–outputtable)canbewrittenas: X f xK , x L , x E , xM (B22) where X: totalsectoraloutput; xK : capitalinput; xL : labourinput; xE : energyinput;and xM : materialinput. AsmentionedinSectionB.1,theinput–outputmodelassumesafixedproportionality of input–output (technical) coefficients. This assumption implies a linear (and fixed) relationshipbetweenasector’soutputanditsinputs.Thistypeofproductionfunction iscalledaLeontiefproductionfunction.Fromthedefinitionoftechnicalcoefficientsin equationB3,theLeontiefproductionfunctioncanbewrittenas: X §x x x x · f¨ K, L, E, M ¸ © c K c L a E aM ¹ §x x x x · min ¨ K , L , E , M ¸ © c K c L a E aM ¹ (B23) 227 FortheproductionfunctiongiveninequationB23,whenthedenominatorisnotzero, the ratios of all elements will be constant and equal to X. This clearly reflects the assumptionofconstantreturntoscale.ThisLeontiefproductionfunctionisshownin Figure B2 (a). The isoquants (curve of constant output), using a combination of two inputs,areshownasrightangledstraightlines.Here,theproportionofinputsx1and x2toproduceaparticularlevelofoutputisconstant.Inputsubstitutionisnotpossible. Whenonefactorinputisdecreased,itcannotbesubstitutedwithotherinput.Rather, the producer has to decrease the level of production, for instance, shift of isoquant from‘b’to‘a’. FigureB2 Productionfunctions:(a)Leontief;(b)Neoclassical Ontheotherhand,aneoclassicalproductionfunctioncanberepresentedasinFigure B2 (b). Here, in contrast with the Leontief production function, input substitution is possible.Thisisindicatedbytheisoquantshowingalternativeinputcombinationsthat can producethesameamountofoutput.The negativeslopesofthe isoquantsmeans that when one input is decreased, it will be substituted with other input in order to maintainthesamelevelofproduction. Hence, the neoclassical production function is more flexible than the Leontief productionfunction.Itreflectseconomicrationalisingbehaviourparticularlyinthatit allowstheproducer(andconsumer)tosubstitutesoneinputwithanother. 228 B.2.2 BackgroundofNeoclassicalProductionFunction TheneoclassicalproductionfunctionwasfirstdevelopedbyCobbandDouglasinthe year 1928 (Cobb & Douglas 1928). The CobbDouglas production function relates physical output to capital and labour inputs. This type of production function has a constant (equalto 1) elasticityofsubstitution.Thenext majorcontribution wasmade byArrowetal.intheyear1961(Arrowetal.1961).Theproductionfunctiondeveloped byArrowetal.alsohasaconstantelasticityofsubstitution,butitwasnotrestrictedto unity. This type of production function is known as the Constant Elasticity of Substitution(CES)productionfunction.Thelimitationofbothfunctionalforms(Cobb Douglas and CES), especially the underlying constant elasticity of substitution, have arbitrarily restricted the patterns of producer behaviour (Jorgenson 2000). This limitation has led to the development of a more flexible form of production function that allows the elasticity of substitution between inputs to vary. This type of production function is called the Transcendental Logarithmic (Translog) production functiondevelopedbyChristensenetal.(1971;1973).Sinceitsinception,theTranslog hasbecomethemostfrequentlyappliedfunctionalformforestimatingtheelasticities ofsubstitution. B.2.3 ProductionCostFunction Ratherthantodirectlyemployaproductionfunctionwhichdescribestherelationship betweenquantityofoutputandinput(seeequationB22),itismoreusefultousethe dualcostfunctionwhichsetsupsuchrelationshipintermsofcostsandprices.Thisis mainly because each production sector chooses its level of output based on factor prices.Thereforefactorprices,ratherthanquantitiesofinputs,shouldbeconsideredas independent variables. Also, the costprice data are easily available as compared to quantitydata.Ifthefactorpricesareavailable,thetheoryofdualitybetweencostand production (Shephard 1953) implies that, given costminimising behaviour, the characteristicsofproductionimpliedbyequation(B22)canberepresentedbyaunit outputcostfunctionintheformof: G g PK , PL , PE , PM (B24) 229 where G: costofproducing1unitofoutput; PK : priceofcapital; PL : priceoflabour; PE : priceofenergy;and PM : priceofmaterial. The cost function is theoretically consistent if it satisfies the following assumptions (Jorgenson2000): Positivity:Thecostfunctionispositiveforpositiveinputpricesandapositive levelofoutput.Thismeansthatthefittedcostsharesininputdemandfunction arenonnegative. Homogeneity: The cost function is homogenous of degree one in the input prices.Thismeansthatanequiproportionateincreaseinthefactorpricesofall inputswillincreasecostsbythesameproportionateamount. Monotonicity:Thecostfunctionisnondecreasingintheinputpricesandinthe levelofoutput.Thisimpliesthatparametersestimatedfromcostfunctionmust bepositive. Concavity: The cost function is concave in the factor prices. This implies that the Hessian matrix within the range of factor prices is negative semidefinite, i.e.estimatedownpriceelasticitymustbenegative. B.2.4 EconometricSpecification The Translog cost function is a secondorder approximation in logarithms to an arbitrary cost function and it imposes no prior restrictions on the elasticities of substitutionandthepriceelasticitiesofdemand.ThefunctioninequationB24canbe expressedas: 230 ln D 0 ¦ D i ln Pi ln G i 1 ¦¦ J ij ln Pi ln Pj , i, j ^K , L, E , M ` 2 i j (B25) where unitcost; G: Pi,Pj: factorprices;and D , J : parameterstobeestimated. The assumption of linear homogeneity in factor prices, as discussed earlier, imposes thefollowingparameterrestrictions: ¦D i 1, ij ¦J i ¦J i 0, ij (B26) j J ij z J ji , iz j BylogarithmicallydifferentiatingequationB25,weget: w ln G w ln Pi wG Pi wPi G D i ¦ J ij ln Pj , i, j ^ K , L, E , M ` (B27) j Shephard’sLemmadealswiththepartialderivativeofthecostfunctionwithrespectto the price of the ith input, i.e., wG wPi X i (Diewert 1974). Applying this lemma to equationB27leadstothefactorsharesystem: Pi X i G Si D i ¦ J ij ln Pj , i, j ^ K , L, E , M ` (B28) j where Si: costsharesoftheithinputforunitproduction. Duetotherestrictionoflinearhomogeneityinfactorprices,allcostsharesalsosumup tounity,i.e., ¦S i 1 wheni=K,L,E,M. i ItisalsoworthwhiletofurthermentionherethattheTranslogcostfunctionturnsinto the CobbDouglas form if substitution elasticities are restricted to unity. This, 231 accordingtoBinswanger(1974),ariseswhenparameters J ij inequationB25equalto zero.Accordingly,thelogarithmiccostfunctioninCobbDouglassformcanbewritten as: ln D 0 ¦ D i ln Pi , i, j ^ K , L, E , M ` ln G (B29) i Again,bylogarithmicallydifferentiatingequationB29,weget: w ln G w ln Pi wG Pi wPi G D i , i, j ^ K , L, E , M ` (B30) ApplyingShephard’sLemmatoequationB30,costsharesequationyields: Pi X i G D i , i, j ^ K , L, E , M ` Si (B31) B.2.5 Elasticities Afterall parameters discussedinthe previoussection have been estimated,theown andcrosspriceselasticitiesofsubstitutioncanbederivedfromAllenpartialElasticities ofSubstitution(AES). Uzawa(1962)proposedthatAESbetweeninputsiandjis: V ij G Gij Gi G j , V ij V ji (B32) where Gi wG and Gij wPi w 2G wPi wPj Therefore,theAESderivedfromtheTranslogcostfunctioncanbedefinedas; V ii V ij J ii Si2 Si Si2 J ij Si S j Si S j , i, j ^ K , L, E , M ` and i z j (B33) 232 From equation B33, it shows that these AES are not constrained to be constant with parameters J ij ,butitvarieswiththevaluesofcostshares. Berndt and Wood (1975) suggested that the price elasticity of demand ( K ) derived fromtheTranslogcostfunctioncanbeexpressedas; Kii Kij SiV ii S jV ij , i, j ^ K , L, E , M ` (B34) Contrarily to equation B34, Binswanger (1974) suggested that the price elasticities of demandderivedfromCobbDouglascostfunctioncanbeexpressedas: Kii V i 1 Si 1 , i, j ^ K , L, E , M ` Kij V j S j (B35) Although the price elasticities of demand derived from CobbDouglas production function have limitations as compared with those derived on the basis of Translog function, they are still superior than assuming zero elasticities as is the case with Leontiefproductionfunction. 233 APPENDIXC DatasetsrequiredforThisResearch This appendix presents all dataset required for this research. The data sources and preparationmethodisdiscussedinSection5.7.ItcontainsthefollowingTables: Table Title Page C1 Sectoralclassificationof28sectorinput–output 234 C2 CapitalandO&Mdistributionfactors 238 C3 Matricesofinput–outputtechnicalcoefficients 240 C4 Matrixofcapitalcoefficients 253 C5 Matricesofsectoralenergyintensities 254 C6 InputfactorcostsandpricesforInterfactormodel 257 C7 InputfactorcostsandpricesforEnergysubmodel 260 C8 InputfactorcostsandpricesforMaterialsubmodel 262 Primaryenergy Petroleumrefining GasIndustry Renewableelectricity Coalfiredelectricity Internalcombustion Gasturbine Combinedcycle Agriculture 0101Sheep 0102Cerealgrains 0103Meatcattle 0104Milkcattleandpigs 0101Sheep 0102Cerealgrains 0103Meatcattle 0104Milkcattleandpigs 1993 1100Coal;oilandgas 2501Petroleumandcoal 3602Gassupply 3601Electricity 0101Sheep 0102Grains 0103Beefcattle 0104Dairycattle 0105Pigs 0105Poultry 0105Poultry 0106Poultry 0106Agriculturenec 0106Agriculturenec 0107Otheragriculture 0200Servicestoagriculture 0200Servicestoagriculture 0200Servicesto 0300Forestryandlogging 0300Forestryandlogging 0300Forestryandlogging 0400Fishingandhunting 0400Fishingandhunting 0400Commercialfishing 1101Ferrousmetalores 1101Ferrousmetalores 1301Ironores 1102Nonferrousmetalores 1102Nonferrousmetalores 1302Nonferrousmetalores 1400Otherminerals 1400Mineralsnec 1400Othermining 1600Servicestominingnec 1600Servicestominingnec 1500Servicestomining 2101Meatproducts 2101Meatproducts 2101Meatandmeatproducts 2102Milkproducts 2102Milkproducts 2102Dairyproducts 2103Fruit,vegetableproducts 2103Fruit,vegetableproducts 2103Fruitandvegetable 2104Margarine;oils,fatsnec 2104Margarine;oils,fatsnec 2104Oilsandfats 2105Flourmill,cerealproducts 2105Flourmill,cerealproducts 2105Flourmillproductsand 2106Bread,cakes,biscuits 2106Bread,cakes,biscuits 2106Bakeryproducts 2107Confectionery,etcproducts 2107Confectionery,etcproducts 2107Confectionery 2108Foodproductsnec 2108Foodproductsnec 2108Otherfoodproducts 2109Softdrinks,cordialsetc 2109Softdrinks,cordialsetc 2109Softdrinks,cordialsand 2110Beerandmalt 2110Beerandmalt 2110Beerandmalt 2111Alcoholicbeveragesnec 2111Alcoholicbeveragesnec 2111Wineandspirits 2201Tobaccoproducts 2201Tobaccoproducts 2112Tobaccoproducts 19841990 1200Coal,oilandgas 2708Petroleum,coalproducts 3602Gas 3601Electricity 0101Sheep 0102Grains 0103Beefcattle 0104Dairycattle 0105Pigs 0106Poultry 0107Otheragriculture 0200Servicesto 0300Forestryandlogging 0400Commercialfishing 1301Ironores 1302Nonferrousmetalores 1400Othermining 1500Servicestomining 2101Meatandmeatproducts 2102Dairyproducts 2103Fruitandvegetable 2104Oilsandfats 2105Flourmillproductsand 2106Bakeryproducts 2107Confectionery 2108Otherfoodproducts 2109Softdrinks,cordialsand 2110Beerandmalt 2111Wineandspirits 2112Tobaccoproducts 1100Coal;oilandgas 2501Petroleumandcoal 3602Gassupply 3601Electricity 19941999 2002 234 0101Sheep 0102Grains 0103Beefcattle 0104Dairycattle 0105Pigs 0106Poultry 0107Otheragriculture 0200Servicesto 0300Forestryandlogging 0400Commercialfishing 1301Ironores 1302Nonferrousmetalores 1400Othermining 1500Servicestomining 2101Meatandmeatproducts 2102Dairyproducts 2103Fruitandvegetable 2104Oilsandfats 2105Flourmillproductsand 2106Bakeryproducts 2107Confectionery 2108Otherfoodproducts 2109Softdrinks,cordialsand 2110Beerandmalt 2113 Wine,spiritsandtobacco 1100Coal;oilandgas 2501Petroleumandcoal 3602Gassupply 3601Electricity Sectoralclassificationof28sectorgroupsforAustraliannationalinput–outputtables 19801983 1200Coal,oilandgas 2708Petroleum,coalproducts 3602Gas 3601Electricity TableC1 (continuedonnextpage) 11 Foodindustry 10 Rawmaterialsmining 1 2 3 4 5 6 7 8 9 SECTORS (continuedonnextpage) 15 Nonmetallicmineral products 14 Basicchemicals 13 Wood&paperindustry Sectoralclassificationof28sectorgroupsforAustraliannationalinput–outputtables(continued) 235 19801983 19841990 1993 19941999 2002 2301Cottonginningetc 2301Cottonginningetc 2201Woolscouring 2302Manmadefibresetc 2302Manmadefibresetc 2202Textilefibres,yarnsand 2201Textilefibres,yarnsand 2201Textilefibres,yarnsand 2303Cottonfabricsetc 2303Cottonfabricsetc 2304Wool,worstedfabricsetc 2304Wool,worstedfabricsetc 2305Textilefinishing 2305Textilefinishing 2306Floorcoveringsetc 2306Floorcoveringsetc 2307Textileproductsnec 2307Textileproductsnec 2202Textileproducts 2202Textileproducts 2203Textileproducts 2401Knittingmills 2401Knittingmills 2204Knittingmillproducts 2203Knittingmillproducts 2203Knittingmillproducts 2402Clothing 2402Clothing 2205Clothing 2204Clothing 2204Clothing 2403Footwear 2403Footwear 2206Footwear 2205Footwear 2205Footwear 3401Leatherproducts 3401Leatherproducts 2207Leatherandleather 2206Leatherandleather 2206Leatherandleather 2501Sawmillproducts 2501Sawmillproducts 2301Sawmillproducts 2301Sawmillproducts 2301Sawmillproducts 2502Veneers,mfd.woodboards 2502Veneers,mfd.woodboards 2302Plywood,veneerand 2503Joinery,woodproductsnec 2503Joinery,woodproductsnec 2303Otherwoodproducts 2302Otherwoodproducts 2302Otherwoodproducts 2504Furnitureandmattresses 2504Furnitureandmattresses 2902Furniture 2902Furniture 2902Furniture 2601Pulp,paper,paperboard 2601Pulp,paper,paperboard 2304Pulp,paperand 2303Pulp,paperand 2303Pulp,paperand 2602Bagsandcontainers 2602Bagsandcontainers 2305Paperboard 2304Papercontainersand 2304Papercontainersand 2603Paperproductsnec 2603Paperproductsnec 2306Otherpaperproducts 2604Publishing,printing 2604Publishing,printing 2401Printingandservicesto 2401Printingandservicesto 2401Printingandservicesto 2605Printing,stationeryetc 2605Printing,stationeryetc 2402Publishing;recordedmedia 2402Publishing;recordedmedia 2402Publishing;recordedmedia 2701Chemicalfertilisers 2701Chemicalfertilisers 2502Fertilisers 2702Basicchemicalsnec 2702Basicchemicalsnec 2503Otherbasicchemicals 2502Basicchemicals 2502Basicchemicals 2703Paints 2703Paints 2504Paints 2503Paints 2503Paints 2704Pharmaceuticalsnec 2704Pharmaceuticalsnec 2505Medicinaland 2504Medicinaland 2504Medicinaland 2705Soapanddetergentsnec 2705Soapanddetergentsnec 2506Soapandotherdetergents 2505Soapanddetergents 2505Soapanddetergents 2706Cosmeticsetc 2706Cosmeticsetc 2507Cosmeticsandtoiletry 2506Cosmeticsandtoiletry 2506Cosmeticsandtoiletry 2707Chemicalproductsnec 2707Chemicalproductsnec 2508Otherchemicalproducts 2507Otherchemicalproducts 2507Otherchemicalproducts 3402Rubberproducts 3402Rubberproducts 2509Rubberproducts 2508Rubberproducts 2508Rubberproducts 3403Plastic,relatedproducts 3403Plastic,relatedproducts 2510Plasticproducts 2509Plasticproducts 2509Plasticproducts 2801Glassandglassproducts 2801Glassandglassproducts 2601Glassandglassproducts 2601Glassandglassproducts 2601Glassandglassproducts 2802Clayproducts,refractories 2802Clayproducts,refractories 2602Ceramicproducts 2602Ceramicproducts 2602Ceramicproducts 2803Cement 2803Cement 2603Cementandlime 2603Cement,limeandconcrete 2603Cement,limeandconcrete 2804Readymixedconcrete 2804Readymixedconcrete 2604Concreteslurry 2805Concreteproducts 2805Concreteproducts 2605Plasterandotherconcrete 2604Plasterandotherconcrete 2604Plasterandotherconcrete 2806Nonmetallicmin.products 2806Nonmetallicmin.products 2606Othernonmetallic 2605Othernonmetallic 2605Othernonmetallic TableC1 12 Textileindustry SECTORS(Cont.) TableC1 Roadtransport Railwaytransport Watertransport AirTransport Othertransport,services andstorage 5101Roadtransport 5201Rail,transportnec 5301Watertransport 5401Airtransport 5701Servicestotransport 4901Mechanicalrepairs 4902Repairsnec 4901Mechanicalrepairs 4902Repairsnec 5101Roadtransport 5201Rail,transportnec 5301Watertransport 5401Airtransport 5402Otherrepairs 2901Prefabricatedbuildings 6101Roadtransport 6201Rail,pipelineandother 6301Watertransport 6401Airandspacetransport 6601Servicesto 5401Mechanicalrepairs 3701Water,sewerage,drainage 3701Water,sewerage,drainage 3701Watersupply;sewerage anddrainageservices 4101Residentialbuilding 4101Residentialbuilding 4101Residentialbuilding 4102Constructionnec 4102Constructionnec 4102Otherconstruction (continuedonnextpage) 23 24 25 26 27 22 Construction 21 Water,sewerage& drainage SECTORS(Cont.) 2903Othermanufacturing 3701Watersupply;sewerage anddrainageservices 2903Othermanufacturing 3701Watersupply;sewerage anddrainageservices 5402Otherrepairs 2901Prefabricatedbuildings 6101Roadtransport 6201Rail,pipelineandother 6301Watertransport 6401Airandspacetransport 6601Servicesto 5401Mechanicalrepairs 4101Residentialbuilding 4102Otherconstruction 4201 Constructiontradeservices 2901Prefabricatedbuildings 6101Roadtransport 6201Rail,pipelineandother 6301Watertransport 6401Airandspacetransport 6601Servicesto 4502 Wholesalemechanical 5101 Retailmechanicalrepairs 4503 Otherwholesalerepairs 5103 Otherretailrepairs 2810Othermachineryand 2810Othermachineryand 4101Residentialbuilding 4102Otherconstruction 2002 2701Ironandsteel 2702Basicnonferrousmetal 2703Structuralmetalproducts 2704Sheetmetalproducts 2705Fabricatedmetalproducts 2801Motorvehiclesand 2802Shipsandboats 2803Railwayequipment 2804Aircraft 2805Photographicand 2806Electronicequipment 2807Householdappliances 2808Otherelectricalequipment 2809Agricultural,miningandc 19941999 236 2701Ironandsteel 2702Basicnonferrousmetal 2703Structuralmetalproducts 2704Sheetmetalproducts 2705Fabricatedmetalproducts 2801Motorvehiclesand 2802Shipsandboats 2803Railwayequipment 2804Aircraft 2805Photographicand 2806Electronicequipment 2807Householdappliances 2808Otherelectricalequipment 2809Agricultural,miningandc Sectoralclassificationof28sectorgroupsforAustraliannationalinput–outputtables(continued) 19801983 19841990 1993 2901Basicironandsteel 2901Basicironandsteel 16 Basicironandsteel 2701Ironandsteel 2902Nonferrousmetalsetc 17 Basicnonferrousmetals 2902Nonferrousmetalsetc 2702Basicnonferrousmetal 18 Fabricatedmetalproducts 3101Structuralmetalproducts 3101Structuralmetalproducts 2703Structuralmetalproducts 3102Sheetmetalproducts 3102Sheetmetalproducts 2704Sheetmetalproducts 3103Metalproductsnec 3103Metalproductsnec 2705Fabricatedmetalproducts 3201Motorvehiclesnec 3201Motorvehiclesnec 2801Motorvehiclesand 19 Machineryand 3202Shipsandboats 3202Shipsandboats 2802Shipsandboats equipment 3203Railwayrollingstocketc 3203Railwayrollingstocketc 2803Railwayequipment 3204Aircraft 3204Aircraft 2804Aircraft 3301Scientificetcequipment 3301Scientificetcequipment 2805Photographicand 3302Electronicequipment 3302Electronicequipment 2806Electronicequipment 3303Householdappliances 3303Householdappliances 2807Householdappliances 3304Electricalequipmentnec 3304Electricalequipmentnec 2808Otherelectricalequipment 3305Agriculturalmachinery 3305Agriculturalmachinery 2809Agriculturalmachinery 3306Constructionetcmachinery 3306Constructionetcmachinery 2810Miningandconstruction 3307Machinery,equipmentetc 3307Machinery,equipmentnec 2811Othermachineryand 3404Signs,writingequipment 3404Signs,writingequipment 20 Miscellenous 3405Manufacturingnec 3405Manufacturingnec 2903Othermanufacturing manufacturing Note: 28 7101Publicadministration 7201Defence 8101Health 8201Education,librariesetc 8301Welfareetcservices 9101Entertainmentetc 9201Restaurants,hotels,clubs 9301Personalservices 7101Publicadministration 7201Defence 8101Health 8201Education,librariesetc 8301Welfareetcservices 9101Entertainmentetc 9201Restaurants,hotels,clubs 9301Personalservices 1993 19941999 2002 4501Wholesaletrade 4501Wholesaletrade 4501 Wholesaletrade 5101Retailtrade 5101Retailtrade 5101Retailtrade 7101Communicationservices 7101Communicationservices 7101 Communicationservices 7301Banking 7301Banking 7301Banking 7302Nonbankfinance 7302Nonbankfinance 7302Nonbankfinance 7303Financialassetinvestors 7401Insurance 7401Insurance 7401 Insurance 7501Servicestofinance,investm 7501Servicestofinance,investm 7501 Servicestofinance, 7701Ownershipofdwellings 7701Ownershipofdwellings 7701 Ownershipofdwellings 7702Otherpropertyservices 7702Otherpropertyservices 7702 Otherpropertyservices 7801Scientificresearch,technica 7801Scientificresearch,technica 7801 Scientificresearch, 7802Legal,accounting,marketin7802Legal,accounting,marketin7802 Legal,accounting, 7803Otherbusinessservices 7803Otherbusinessservices 7803 Otherbusinessservices 8101Governmentadministration8101Governmentadministration8101 Government 8201Defence 8201Defence 8201 Defence 8601Healthservices 8601Healthservices 8601Healthservices 8401Education 8401 Education 8401Education 9201Libraries,museumsandthe 9201Libraries,museumsandthe 9201 Libraries,museumsand 8701Communityservices 8701Communityservices 8701 Communityservices 9101Motionpicture,radioandte9101Motionpicture,radioandte9101 Motionpicture,radioand 9301Sport,gamblingandrecreat 9301Sport,gamblingandrecreat 9301 Sport,gamblingand 5701Accommodation,cafesand 5701Accommodation,cafesand 5701 Accommodation,cafesand 9501Personalservices 9501Personalservices 9501 Personalservices 9601Otherservices 9601Otherservices 9601 Otherservices 237 ThecolumnonthelefthandsideofthisTablerepresentssectoralclassificationinthisresearch.Theothercolumnsrepresentsectoralclassification(withcodesand titles)takenfromtheAustralianBureauofStatistics(ABSvarious). 19841990 4701Wholesaletrade 4801Retailtrade 5901Communication 6101Banking 6102Nonbankfinance 6103Investmentetc 6104Insuranceetc 6105Businessservicesnec 6106Ownershipofdwellings Sectoralclassificationof28sectorgroupsforAustraliannationalinput–outputtables(continued) 19801983 4701Wholesaletrade 4801Retailtrade 5601Communication 6101Banking 6102Nonbankfinance 6103Investmentetc 6104Insuranceetc 6105Businessservicesnec 6106Ownershipofdwellings TableC1 Commercialservices SECTORS(Cont.) 238 TableC2Capitaldistributionfactorsforeachelectricitygenerationtechnology CF IC GT CC RE 1980 0.6623 0.0118 0.0129 0.3129 1981 0.6765 0.0126 0.0120 0.2989 1982 0.6901 0.0123 0.0147 0.2829 1983 0.6958 0.0126 0.0146 0.2770 1984 0.7062 0.0117 0.0143 0.2678 1985 0.7080 0.0110 0.0139 0.2672 1986 0.7103 0.0109 0.0136 0.2652 1987 0.7142 0.0110 0.0142 0.2606 1988 0.7120 0.0102 0.0140 0.0016 0.2622 1989 0.7136 0.0102 0.0140 0.0016 0.2606 1990 0.7054 0.0111 0.0160 0.0016 0.2658 1991 0.7002 0.0107 0.0171 0.0017 0.2704 1992 0.6965 0.0105 0.0196 0.0016 0.2718 1993 0.7072 0.0093 0.0190 0.0016 0.2629 1994 0.7153 0.0093 0.0194 0.0015 0.2544 1995 0.7205 0.0089 0.0193 0.0016 0.2497 1996 0.7205 0.0089 0.0193 0.0016 0.2497 1997 0.7231 0.0085 0.0204 0.0020 0.2459 1998 0.7277 0.0066 0.0204 0.0019 0.2435 1999 0.7250 0.0062 0.0237 0.0102 0.2349 2000 0.7218 0.0073 0.0261 0.0101 0.2347 2001 0.7222 0.0062 0.0253 0.0168 0.2294 2002 0.7195 0.0064 0.0337 0.0201 0.2203 Notes: CF:Coalfired,IC:Internalcombustion,GT:Gasturbine,CC:Combinedcycle,RE: Renewable; TheinformationcontainedinthisTableiscalculatedfromeconomicandtechnical characteristicsofpowerplants(giveninTable56)andannualinstalledcapacityofeach technology,publishedbytheElectricitySupplyAssociationofAustralia(ESAAvarious). 239 TableC2O&Mdistributionfactorsforeachelectricitygenerationtechnology CF IC GT CC RE 1980 0.7428 0.0134 0.0104 0.2335 1981 0.7545 0.0141 0.0096 0.2218 1982 0.7658 0.0137 0.0117 0.2088 1983 0.7704 0.0140 0.0115 0.2041 1984 0.7792 0.0130 0.0113 0.1966 1985 0.7808 0.0122 0.0110 0.1961 1986 0.7827 0.0121 0.0107 0.1945 1987 0.7859 0.0121 0.0111 0.1908 1988 0.7845 0.0113 0.0110 0.0009 0.1922 1989 0.7858 0.0113 0.0111 0.0009 0.1910 1990 0.7787 0.0123 0.0127 0.0010 0.1953 1991 0.7746 0.0118 0.0135 0.0010 0.1991 1992 0.7715 0.0117 0.0155 0.0010 0.2003 1993 0.7806 0.0103 0.0150 0.0009 0.1931 1994 0.7872 0.0103 0.0153 0.0009 0.1863 1995 0.7915 0.0098 0.0152 0.0009 0.1825 1996 0.7915 0.0098 0.0152 0.0009 0.1825 1997 0.7938 0.0094 0.0160 0.0012 0.1796 1998 0.7980 0.0073 0.0160 0.0011 0.1776 1999 0.7968 0.0068 0.0186 0.0060 0.1718 2000 0.7938 0.0081 0.0205 0.0059 0.1717 2001 0.7953 0.0069 0.0199 0.0099 0.1681 2002 0.7930 0.0071 0.0265 0.0118 0.1615 Notes: CF:Coalfired,IC:Internalcombustion,GT:Gasturbine,CC:Combinedcycle,RE: Renewable; TheinformationcontainedinthisTableiscalculatedfromeconomicandtechnical characteristicsofpowerplants(giveninTable56)andannualelectricitygenerationfrom eachtechnology,publishedbytheElectricitySupplyAssociationofAustralia(ESAAvarious). 0.0003 0.0003 0.0003 0.0001 11 0.0009 0.0002 12 0.0008 0.0004 0.0010 0.0003 0.0838 0.0987 0.0027 0.0034 0.0005 0.0002 0.0094 0.0021 0.0011 0.0013 0.0041 0.0115 0.0010 0.0005 0.0056 0.0066 0.0002 0.0003 0.0049 0.0653 0.0019 0.0005 0.0043 0.0012 0.0043 0.0009 0.0044 0.0002 0.0006 0.0007 0.0000 0.0003 0.0010 0.0004 0.0003 0.0001 0.0002 0.2565 0.0280 0.1183 7 8 0.0141 0.0653 0.0009 0.0019 0.0030 0.0019 0.0147 0.0071 0.0116 0.0008 0.0010 0.0001 0.0001 0.0004 0.0065 0.0461 0.0404 0.0020 0.0004 0.0656 0.0001 0.0051 0.0000 0.0010 0.0396 0.0001 0.0000 9 11 0.0087 0.0034 0.1286 0.0844 0.0163 0.0009 0.0080 0.0016 0.0078 0.0086 0.0141 0.0017 0.0196 0.0254 0.0020 0.0032 0.0498 0.0033 0.0003 0.0013 0.0086 0.0289 0.0103 0.0007 0.0011 0.0003 0.0016 0.0089 0.0036 0.0233 0.0210 0.0319 0.0045 0.1515 0.0010 0.0028 0.0797 0.0004 0.0003 0.3280 0.0004 0.0001 0.0211 0.0069 0.0002 0.0001 0.0040 0.0013 0.0309 0.0076 0.0001 0.0011 13 0.0004 0.0003 0.0019 0.0784 0.0878 0.0010 0.0021 0.0029 0.0023 0.0020 0.0039 0.0010 0.0013 0.0070 0.0210 0.0005 0.0009 0.0012 0.0089 0.0005 0.0017 0.0019 0.0051 0.0001 0.0065 0.0004 0.0047 0.0008 0.0035 0.0052 0.2329 0.0274 0.0416 0.0058 0.0016 0.2764 0.0136 0.0475 0.0248 0.0001 0.0001 0.0056 0.0071 0.0000 0.0001 0.0011 0.0013 0.0049 0.0090 0.0005 0.0006 0.0002 0.0010 12 15 0.0011 0.0025 0.0772 0.0641 0.0024 0.0058 0.0022 0.0028 0.0029 0.0131 0.0012 0.0026 0.0155 0.0682 0.0023 0.0042 0.0024 0.0040 0.0018 0.0010 0.0075 0.0032 0.0021 0.0180 0.0070 0.0035 0.0048 0.0893 0.0141 0.0142 0.2765 0.0415 0.0147 0.0010 0.0124 0.0019 0.0072 0.0971 0.0006 0.0001 0.0002 0.0003 0.0102 0.0169 0.0001 0.0001 0.0019 0.0032 0.0145 0.0263 0.0023 0.0104 0.0011 0.0092 14 17 0.0006 0.0002 0.0421 0.0304 0.0284 0.0055 0.0008 0.0012 0.0140 0.0217 0.0005 0.0001 0.0151 0.0088 0.0026 0.0006 0.0071 0.0008 0.0018 0.0055 0.0118 0.0029 0.2490 0.0047 0.0385 0.1321 0.0177 0.0035 0.0030 0.0008 0.0130 0.0115 0.0034 0.0002 0.0036 0.0003 0.0414 0.3570 0.0001 0.0000 0.0004 0.0003 0.0241 0.0165 0.0002 0.0001 0.0046 0.0031 0.0202 0.0410 0.0010 0.0008 0.0442 0.0118 16 19 0.0015 0.0009 0.0679 0.0581 0.0039 0.0013 0.0018 0.0020 0.0037 0.0022 0.0008 0.0004 0.0096 0.0073 0.0009 0.0004 0.0092 0.1745 0.0007 0.0010 0.0831 0.0279 0.2322 0.0386 0.0768 0.0315 0.0052 0.0033 0.0100 0.0092 0.0239 0.0324 0.0008 0.0008 0.0064 0.0037 0.0001 0.0002 0.0001 0.0000 0.0001 0.0001 0.0056 0.0033 0.0000 0.0000 0.0011 0.0006 0.0056 0.0022 0.0015 0.0006 0.0001 0.0001 18 21 22 0.0013 0.0006 0.0011 0.0031 0.0689 0.0877 0.0918 0.0011 0.0003 0.0017 0.0052 0.0021 0.0016 0.0057 0.0008 0.0035 0.0003 0.0111 0.0070 0.0033 0.0305 0.0003 0.0041 0.0111 0.0743 0.0473 0.0004 0.0003 0.0135 0.0279 0.0971 0.0108 0.0013 0.0254 0.0118 0.0004 0.0083 0.0005 0.0054 0.1056 0.0186 0.0037 0.0626 0.0698 0.0190 0.0290 0.0008 0.0011 0.0012 0.0124 0.0003 0.0018 0.0765 0.0005 0.0110 0.0020 0.0001 0.0011 0.0001 0.0004 0.0000 0.0046 0.0258 0.0011 0.0000 0.0002 0.0000 0.0009 0.0049 0.0002 0.0053 0.0220 0.0151 0.0003 0.0003 0.0056 0.0005 0.0001 20 Matrixofinput–outputtechnicalcoefficients(A) 0.0009 0.0007 10 TableC3 24 0.0425 0.0132 0.1290 0.1079 0.0009 0.0008 0.0015 0.0037 0.0024 0.0024 0.0006 0.0634 0.0186 0.0048 0.0001 0.0050 0.0550 0.0739 0.0003 0.0013 0.0005 0.0039 0.0003 0.0017 0.0000 0.0000 0.0010 0.0002 0.0034 0.0350 0.0377 0.0043 0.0011 0.0016 0.0045 0.0148 0.0004 0.0006 0.0002 0.0030 0.0000 0.0002 0.0017 0.0092 0.0000 0.0001 0.0003 0.0017 0.1131 0.0297 0.0009 0.0002 0.0002 0.0073 23 26 0.0010 0.0014 0.1154 0.0892 0.1333 0.0007 0.0012 0.0612 0.0073 0.0463 0.0006 0.0000 0.0038 0.0054 0.0081 0.0000 0.0311 0.0640 0.0005 0.0004 0.0029 0.0008 0.0003 0.0000 0.0000 0.0103 0.0161 0.0062 0.0060 0.0006 0.0016 0.0089 0.0022 0.0004 0.0001 0.0003 0.0002 0.0000 0.0103 0.0019 0.0001 0.0000 0.0019 0.0004 0.0910 0.1401 0.0009 0.0004 0.0070 25 0.0005 28 (1980) 0.0001 0.0006 0.0062 0.1254 0.1598 0.0007 0.0013 0.0009 0.0053 0.0020 0.0043 0.0110 0.0069 0.0054 0.0015 0.0126 0.1951 0.0171 0.0004 0.0022 0.0038 0.0063 0.0001 0.0013 0.0001 0.0003 0.0024 0.0019 0.0032 0.0267 0.0091 0.0124 0.0012 0.0027 0.0008 0.0032 0.0001 0.0010 0.0002 0.0001 0.0109 0.0072 0.0001 0.0001 0.0021 0.0014 0.0083 0.0071 0.0003 0.0008 27 240 ABS(various) Input–outputcoefficientsshowninthisTableiscalculatedfromanadaptedversionofinput–outputtable,fortheyear1980,publishedbytheAustralianBureauof Statistics,inaccordancewithsectoralclassificationinthisresearch; seeTableC1,pp.234237fordescriptionofsector1to28. 0.0006 0.0004 0.0904 0.1060 27 0.0027 0.0001 28 0.0300 0.0249 0.0006 0.0021 0.0012 0.0015 22 0.0069 0.0002 23 0.0071 0.0042 0.0418 0.0032 0.0017 0.0008 21 0.0005 0.0006 0.0003 0.0010 0.0009 0.0004 0.0017 0.0071 0.0005 0.0003 24 0.0056 0.0010 0.0008 0.0009 0.0121 0.0010 18 0.0037 0.0000 19 0.0207 0.0007 20 0.0001 0.0000 25 0.0006 0.0053 26 0.0019 0.0002 0.0009 0.0011 0.0001 0.0001 0.0005 0.0012 0.0003 0.0001 16 0.0053 0.0001 17 0.0001 0.0012 0.0004 0.0004 0.0011 0.0005 0.0005 0.0006 0.0012 0.0008 0.0033 0.0006 0.0007 0.0004 13 0.0032 0.0006 14 0.0105 0.0130 0.0004 0.0002 0.0001 0.0001 (continuedonnextpage) 0.0002 0.0001 15 0.0005 0.0000 10 0.0538 0.0015 0.0001 0.0000 0.0001 7 0.0002 0.0001 8 9 0.0042 0.0000 0.2705 0.1288 0.0008 0.2056 0.0042 0.0000 4 0.0018 0.0006 5 0.0097 0.0034 6 0.0001 0.0000 0.0273 0.3295 0.0077 6 0.0853 5 0.0214 0.0005 4 2 0.0047 0.0813 3 0.0000 0.0006 3 0.1540 2 1 0.0280 0.3524 1 Sources: Notes: 0.0007 0.0029 0.0129 0.0004 0.0059 0.0001 0.0036 0.0228 0.0001 0.0004 0.0073 0.0069 0.0064 0.0005 0.0047 0.0032 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 0.0156 0.0037 0.0007 0.0015 0.0003 0.0014 0.0016 0.0061 0.0019 0.0001 0.0010 0.0081 0.0002 0.0016 0.0008 0.0005 0.0002 0.0005 0.2562 7 8 0.0091 0.0029 0.0009 0.0081 0.0002 0.0016 0.0011 0.0068 0.0010 0.0000 0.0005 0.0041 0.0002 0.0019 0.0004 0.0002 0.0002 0.0007 0.3094 0.0374 0.0196 0.0032 0.0043 0.0003 0.0004 0.0003 0.0006 0.0015 0.0159 0.0018 0.0001 0.0010 0.0079 0.0001 0.0007 0.0007 0.0005 0.0001 0.0002 0.1088 0.4598 0.0091 0.1579 6 9 10 0.0072 0.0226 0.0096 0.0107 0.0004 0.0020 0.0196 0.0247 0.0137 0.0032 0.0086 0.0568 0.0011 0.0039 0.0242 0.0016 0.0003 0.0944 0.0042 0.0043 0.0221 0.0002 0.0007 0.0690 0.1629 0.0030 0.0009 0.0015 0.0132 0.0008 0.0060 0.0015 0.0149 0.0001 0.0001 0.0008 0.0116 0.0021 0.0063 0.0506 0.0003 0.0879 0.0004 0.0440 0.0010 0.0050 0.0000 0.0002 0.0915 0.0106 0.0010 0.0016 0.0038 0.0013 0.0031 0.0017 0.0266 0.0010 0.0004 0.0281 0.0035 0.0029 0.0230 0.0328 0.0091 0.3239 0.0004 0.1507 0.0014 0.0073 0.0001 0.0002 0.0009 0.0085 0.0014 11 13 0.0039 0.0022 0.0025 0.0022 0.0016 0.0008 0.0013 0.0209 0.0076 0.0053 0.0053 0.0088 0.0122 0.2245 0.0418 0.0034 0.0235 0.0005 0.0015 0.0015 0.0077 0.0001 0.0002 0.0896 0.0960 0.0019 0.0010 0.0032 0.0003 0.0005 0.0005 0.0016 0.0088 0.0001 0.0004 0.0007 0.0013 0.2690 0.0056 0.0253 0.0002 0.0397 0.0156 0.0017 0.0090 0.0001 0.0003 0.0002 0.0010 0.0091 0.0132 0.0007 0.0006 12 15 0.0141 0.0058 0.0025 0.0027 0.0009 0.0041 0.0026 0.0726 0.0196 0.0038 0.0029 0.0036 0.0015 0.0143 0.0393 0.0849 0.0001 0.1004 0.0010 0.0034 0.0175 0.0001 0.0005 0.0834 0.0656 0.0029 0.0023 0.0021 0.0011 0.0018 0.0020 0.0011 0.0166 0.0032 0.0084 0.0072 0.0023 0.0122 0.0138 0.2735 0.0048 0.0007 0.0093 0.0125 0.0020 0.0105 0.0001 0.0003 0.0015 0.0108 0.0235 0.0254 0.0025 0.0114 14 0.0446 0.0147 0.0233 0.0008 0.0007 0.0015 0.0023 0.0004 0.0163 0.2412 0.0487 0.0121 0.0068 0.0034 0.0027 0.0124 0.0174 0.0001 0.0330 0.0030 0.0046 0.0238 0.0002 0.0007 0.0464 0.0314 0.0011 16 18 0.0038 0.0041 0.0017 0.0015 0.0006 0.0008 0.0007 0.0100 0.2355 0.0822 0.0813 0.0086 0.0062 0.0094 0.0221 0.0044 0.0001 0.0001 0.0008 0.0011 0.0054 0.0000 0.0002 0.0424 0.0709 0.0190 0.0060 0.0012 0.0002 0.0049 0.0006 0.0001 0.0102 0.0052 0.1669 0.0038 0.0009 0.0003 0.0007 0.0166 0.0037 0.0000 0.3074 0.0002 0.0034 0.0173 0.0001 0.0005 0.0120 0.0005 0.0539 0.0068 0.0009 0.0016 17 20 21 0.0060 0.0012 0.0050 0.0007 0.0478 0.0002 0.0003 0.0074 0.0117 0.0120 0.0126 0.0042 0.0194 0.0188 0.0690 0.0005 0.0023 0.0571 0.0008 0.0009 0.0048 0.0000 0.0001 0.0009 0.0003 0.0025 0.0013 0.0004 0.0128 0.0037 0.0016 0.0004 0.0330 0.0138 0.0004 0.0043 0.0220 0.0061 0.0001 0.0006 0.0013 0.0063 0.0323 0.0003 0.0010 0.0565 0.0724 0.0613 0.0020 0.0012 0.0018 0.0009 0.0010 0.0003 0.0004 0.0068 0.0365 0.0303 0.0241 0.1615 0.0031 0.0078 0.0286 0.0025 0.0000 0.0002 0.0007 0.0006 0.0030 0.0000 0.0001 0.0002 0.0064 0.0006 0.0023 0.0058 0.0242 0.0005 0.0004 19 23 0.0020 0.0008 0.0012 0.0339 0.0002 0.0001 0.0005 0.0161 0.0005 0.0000 0.0004 0.0526 0.0037 0.0027 0.0411 0.0007 0.0002 0.0004 0.0009 0.0003 0.0014 0.0000 0.0000 0.1112 0.1709 0.0038 0.0018 0.0018 0.0038 0.0005 0.0013 0.0307 0.0285 0.0085 0.1005 0.0731 0.0022 0.0628 0.0312 0.1019 0.0010 0.0107 0.0013 0.0002 0.0013 0.0000 0.0000 0.0003 0.0028 0.0197 0.0994 0.0004 0.0008 22 Matrixofinput–outputtechnicalcoefficients(A)(continued) 0.0002 0.0014 0.0396 0.0384 0.0001 0.0001 TableC3 25 26 0.0075 0.1182 0.0012 0.0010 0.0005 0.0073 0.0005 0.0034 0.0005 0.0000 0.0033 0.0319 0.0094 0.0101 0.0059 0.0000 0.0005 0.0006 0.0021 0.0106 0.0001 0.0003 0.0471 0.0007 0.0628 0.0017 0.0005 0.0000 0.0000 0.0055 0.0000 0.0009 0.0680 0.0024 0.0189 0.0066 0.0004 0.0018 0.0004 0.0019 0.0000 0.0001 0.1279 0.1114 0.0920 0.0018 0.0005 0.0041 0.0150 0.0014 0.0051 0.0672 0.0052 0.0020 0.0000 0.0041 0.0783 0.0175 0.0398 0.0044 0.0003 0.0028 0.0007 0.0017 0.0021 0.0107 0.0001 0.0003 0.0013 0.0078 0.0346 0.0827 0.1506 0.0003 0.0011 0.0005 24 28 (1981) 0.0046 0.0011 0.0050 0.0061 0.0021 0.0127 0.0108 0.0054 0.0016 0.0003 0.0056 0.0188 0.0031 0.0257 0.0124 0.0018 0.0009 0.0002 0.0026 0.0015 0.0076 0.0001 0.0002 0.1273 0.1666 0.0019 0.0007 0.0009 0.0006 0.0003 0.0012 0.0068 0.0001 0.0000 0.0037 0.2043 0.0008 0.0030 0.0092 0.0018 0.0001 0.0011 0.0020 0.0103 0.0001 0.0003 0.0008 0.0073 0.0080 0.0004 0.0009 27 241 ABS(various) Input–outputcoefficientsshowninthisTableiscalculatedfromanadaptedversionofinput–outputtable,fortheyear1981,publishedbytheAustralianBureauof Statistics,inaccordancewithsectoralclassificationinthisresearch; seeTableC1,pp.234237fordescriptionofsector1to28. 0.0489 0.0384 0.0059 0.0014 0.0006 0.0006 0.0004 0.0011 0.0030 0.0024 0.0024 0.0001 0.0013 0.0104 0.0002 0.0013 0.0010 0.0006 5 0.1202 0.0360 0.0099 (continuedonnextpage) 0.0404 0.0006 0.0013 0.0009 0.0007 0.0023 0.0008 0.0031 0.0009 0.0003 0.0178 0.0022 0.0004 0.0019 0.0044 0.0009 0.0000 0.0005 28 0.0308 0.0115 0.0619 0.0005 0.0046 0.0000 0.0000 0.0000 0.0000 0.0000 0.0011 0.0000 0.0001 0.0000 0.0001 0.0000 0.0000 0.0010 0.0000 0.0000 0.0001 0.0000 0.0002 0.0005 0.0034 0.0595 0.0008 8 9 10 11 0.0012 0.0063 0.0001 0.0002 0.2161 0.0001 0.0003 0.0000 0.0000 0.0018 0.0091 0.0001 0.0003 4 4 5 6 7 3 2 1 0.0479 0.3806 0.2041 2 0.0052 0.0319 0.0505 3 0.0000 0.0001 0.0009 1 Sources: Notes: 0.0009 0.0031 0.0166 0.0004 0.0068 0.0002 0.0038 0.0315 0.0001 0.0005 0.0024 0.0075 0.0066 0.0008 0.0046 0.0034 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 0.0132 0.0042 0.0009 0.0019 0.0003 0.0015 0.0017 0.0063 0.0023 0.0001 0.0012 0.0094 0.0002 0.0020 0.0009 0.0006 0.0002 0.0007 0.2658 7 8 0.0071 0.0032 0.0010 0.0086 0.0002 0.0017 0.0013 0.0067 0.0012 0.0000 0.0007 0.0051 0.0003 0.0022 0.0005 0.0003 0.0002 0.0008 0.2934 0.0463 0.0269 0.0029 0.0053 0.0004 0.0006 0.0003 0.0007 0.0016 0.0169 0.0021 0.0001 0.0011 0.0088 0.0001 0.0009 0.0009 0.0005 0.0001 0.0003 0.1237 0.4805 0.0219 0.1848 6 9 10 0.0078 0.0360 0.0115 0.0125 0.0004 0.0022 0.0067 0.0258 0.0163 0.0011 0.0093 0.0684 0.0014 0.0049 0.0327 0.0020 0.0004 0.1188 0.0051 0.0034 0.0189 0.0002 0.0006 0.0744 0.2168 0.0034 0.0011 0.0017 0.0143 0.0009 0.0059 0.0014 0.0162 0.0001 0.0001 0.0008 0.0141 0.0023 0.0066 0.0527 0.0003 0.0920 0.0006 0.0428 0.0012 0.0065 0.0001 0.0002 0.0904 0.0104 0.0012 0.0015 0.0036 0.0013 0.0028 0.0015 0.0307 0.0008 0.0002 0.0271 0.0034 0.0031 0.0240 0.0324 0.0099 0.3041 0.0004 0.1557 0.0011 0.0061 0.0001 0.0002 0.0008 0.0077 0.0015 11 13 0.0040 0.0021 0.0027 0.0023 0.0016 0.0009 0.0013 0.0207 0.0078 0.0057 0.0052 0.0091 0.0111 0.2211 0.0411 0.0037 0.0230 0.0005 0.0018 0.0014 0.0076 0.0001 0.0002 0.0888 0.0967 0.0013 0.0010 0.0032 0.0003 0.0005 0.0005 0.0021 0.0088 0.0001 0.0004 0.0012 0.0017 0.2616 0.0062 0.0258 0.0004 0.0382 0.0107 0.0008 0.0041 0.0000 0.0001 0.0002 0.0011 0.0109 0.0129 0.0009 0.0009 12 15 0.0134 0.0056 0.0028 0.0029 0.0009 0.0043 0.0025 0.0702 0.0174 0.0024 0.0030 0.0035 0.0011 0.0170 0.0382 0.0934 0.0001 0.0940 0.0011 0.0026 0.0146 0.0001 0.0005 0.0858 0.0702 0.0028 0.0019 0.0023 0.0011 0.0018 0.0020 0.0010 0.0164 0.0028 0.0062 0.0070 0.0026 0.0131 0.0142 0.2717 0.0049 0.0006 0.0082 0.0102 0.0015 0.0080 0.0001 0.0002 0.0012 0.0106 0.0225 0.0234 0.0031 0.0147 14 0.0464 0.0135 0.0232 0.0008 0.0007 0.0012 0.0024 0.0004 0.0164 0.2615 0.0313 0.0126 0.0069 0.0037 0.0030 0.0145 0.0163 0.0001 0.0274 0.0035 0.0055 0.0303 0.0003 0.0009 0.0544 0.0298 0.0015 16 18 0.0034 0.0042 0.0019 0.0016 0.0007 0.0008 0.0007 0.0097 0.2290 0.0663 0.0901 0.0090 0.0059 0.0100 0.0214 0.0048 0.0001 0.0001 0.0008 0.0010 0.0053 0.0000 0.0002 0.0482 0.0730 0.0152 0.0065 0.0022 0.0003 0.0056 0.0010 0.0002 0.0119 0.0102 0.1524 0.0074 0.0013 0.0005 0.0013 0.0279 0.0055 0.0000 0.2614 0.0005 0.0053 0.0290 0.0003 0.0009 0.0176 0.0003 0.0796 0.0072 0.0020 0.0020 17 20 21 0.0052 0.0012 0.0049 0.0007 0.0457 0.0002 0.0003 0.0102 0.0112 0.0089 0.0116 0.0033 0.0098 0.0186 0.0624 0.0005 0.0022 0.0374 0.0008 0.0005 0.0029 0.0000 0.0001 0.0009 0.0003 0.0025 0.0013 0.0004 0.0108 0.0032 0.0014 0.0003 0.0310 0.0108 0.0004 0.0043 0.0197 0.0057 0.0001 0.0006 0.0013 0.0065 0.0355 0.0003 0.0011 0.0570 0.0667 0.0622 0.0018 0.0012 0.0018 0.0009 0.0009 0.0003 0.0003 0.0067 0.0333 0.0237 0.0221 0.1707 0.0029 0.0083 0.0291 0.0025 0.0000 0.0002 0.0006 0.0006 0.0031 0.0000 0.0001 0.0001 0.0063 0.0006 0.0024 0.0056 0.0191 0.0007 0.0004 19 23 0.0012 0.0006 0.0007 0.0199 0.0001 0.0000 0.0002 0.0212 0.0002 0.0000 0.0002 0.0341 0.0023 0.0016 0.0257 0.0004 0.0001 0.0003 0.0005 0.0002 0.0009 0.0000 0.0000 0.1033 0.1129 0.0026 0.0020 0.0018 0.0040 0.0003 0.0012 0.0284 0.0307 0.0083 0.1051 0.0746 0.0021 0.0655 0.0309 0.1000 0.0009 0.0104 0.0013 0.0003 0.0014 0.0000 0.0000 0.0002 0.0011 0.0112 0.0712 0.0005 0.0005 22 Matrixofinput–outputtechnicalcoefficients(A)(continued) 0.0001 0.0015 0.0555 0.0455 0.0001 0.0002 TableC3 25 26 0.0072 0.1363 0.0013 0.0011 0.0005 0.0072 0.0005 0.0101 0.0004 0.0000 0.0028 0.0308 0.0100 0.0114 0.0078 0.0001 0.0007 0.0006 0.0024 0.0132 0.0001 0.0004 0.0445 0.0007 0.0444 0.0011 0.0003 0.0000 0.0000 0.0081 0.0000 0.0005 0.0570 0.0017 0.0133 0.0043 0.0002 0.0013 0.0003 0.0014 0.0000 0.0000 0.1558 0.1249 0.0680 0.0023 0.0006 0.0051 0.0191 0.0019 0.0058 0.0736 0.0065 0.0016 0.0000 0.0048 0.0716 0.0213 0.0521 0.0052 0.0004 0.0032 0.0008 0.0023 0.0028 0.0152 0.0001 0.0005 0.0011 0.0088 0.0491 0.0737 0.1364 0.0004 0.0014 0.0004 24 28 (1982) 0.0046 0.0013 0.0049 0.0059 0.0020 0.0108 0.0126 0.0065 0.0012 0.0002 0.0051 0.0157 0.0030 0.0264 0.0126 0.0016 0.0009 0.0001 0.0025 0.0015 0.0083 0.0001 0.0003 0.1255 0.1642 0.0016 0.0007 0.0007 0.0007 0.0003 0.0010 0.0061 0.0000 0.0001 0.0030 0.1921 0.0007 0.0031 0.0090 0.0016 0.0001 0.0010 0.0020 0.0109 0.0001 0.0003 0.0006 0.0071 0.0084 0.0004 0.0010 27 242 ABS(various) Input–outputcoefficientsshowninthisTableiscalculatedfromanadaptedversionofinput–outputtable,fortheyear1982,publishedbytheAustralianBureauof Statistics,inaccordancewithsectoralclassificationinthisresearch; seeTableC1,pp.234237fordescriptionofsector1to28. 0.0680 0.0495 0.0055 0.0018 0.0008 0.0009 0.0004 0.0014 0.0035 0.0028 0.0031 0.0001 0.0017 0.0130 0.0002 0.0018 0.0013 0.0008 5 0.1296 0.0383 0.0147 (continuedonnextpage) 0.0311 0.0008 0.0026 0.0017 0.0013 0.0039 0.0013 0.0050 0.0014 0.0005 0.0191 0.0031 0.0007 0.0037 0.0084 0.0017 0.0001 0.0009 28 0.0336 0.0194 0.1103 0.0005 0.0046 0.0001 0.0000 0.0000 0.0002 0.0000 0.0024 0.0000 0.0004 0.0000 0.0002 0.0001 0.0002 0.0037 0.0000 0.0000 0.0004 0.0000 0.0002 0.0006 0.0036 0.0847 0.0009 8 9 10 11 0.0024 0.0133 0.0001 0.0004 0.2435 0.0004 0.0024 0.0000 0.0001 0.0018 0.0099 0.0001 0.0003 4 4 5 6 7 3 2 1 0.0330 0.3856 0.1963 2 0.0072 0.0550 0.0686 3 0.0000 0.0002 0.0020 1 Sources: Notes: 0.0009 0.0037 0.0173 0.0007 0.0078 0.0002 0.0043 0.0361 0.0001 0.0007 0.0042 0.0086 0.0067 0.0008 0.0056 0.0044 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 0.0113 0.0036 0.0012 0.0023 0.0004 0.0019 0.0021 0.0057 0.0015 0.0001 0.0012 0.0109 0.0002 0.0025 0.0009 0.0006 0.0003 0.0008 0.2801 7 8 0.0050 0.0023 0.0010 0.0088 0.0003 0.0017 0.0022 0.0053 0.0011 0.0001 0.0009 0.0083 0.0002 0.0022 0.0007 0.0004 0.0002 0.0007 0.2522 0.0503 0.0425 0.0023 0.0042 0.0005 0.0006 0.0003 0.0008 0.0018 0.0149 0.0013 0.0001 0.0011 0.0098 0.0001 0.0010 0.0008 0.0005 0.0001 0.0003 0.1182 0.5115 0.0275 0.2031 6 9 10 0.0068 0.0298 0.0105 0.0120 0.0004 0.0023 0.0082 0.0216 0.0140 0.0014 0.0072 0.0588 0.0012 0.0044 0.0240 0.0017 0.0004 0.1095 0.0049 0.0030 0.0195 0.0002 0.0003 0.0947 0.2092 0.0044 0.0014 0.0021 0.0178 0.0012 0.0085 0.0019 0.0219 0.0001 0.0001 0.0009 0.0141 0.0025 0.0081 0.0547 0.0002 0.1093 0.0004 0.0592 0.0016 0.0105 0.0001 0.0002 0.0972 0.0105 0.0012 0.0018 0.0039 0.0013 0.0033 0.0017 0.0320 0.0006 0.0002 0.0262 0.0050 0.0028 0.0243 0.0308 0.0099 0.2886 0.0003 0.1572 0.0011 0.0071 0.0001 0.0001 0.0007 0.0079 0.0017 11 13 0.0042 0.0021 0.0034 0.0027 0.0019 0.0012 0.0016 0.0211 0.0072 0.0051 0.0050 0.0122 0.0089 0.2202 0.0424 0.0036 0.0222 0.0005 0.0021 0.0015 0.0100 0.0001 0.0002 0.0955 0.1135 0.0018 0.0011 0.0037 0.0004 0.0005 0.0006 0.0014 0.0099 0.0001 0.0005 0.0010 0.0028 0.2697 0.0068 0.0250 0.0004 0.0415 0.0124 0.0008 0.0051 0.0000 0.0001 0.0002 0.0012 0.0080 0.0140 0.0010 0.0012 12 15 0.0147 0.0061 0.0035 0.0033 0.0011 0.0056 0.0029 0.0695 0.0197 0.0023 0.0026 0.0044 0.0009 0.0193 0.0360 0.0989 0.0001 0.0981 0.0012 0.0028 0.0183 0.0002 0.0003 0.0981 0.0817 0.0029 0.0018 0.0029 0.0013 0.0021 0.0025 0.0013 0.0173 0.0020 0.0057 0.0074 0.0045 0.0105 0.0164 0.2707 0.0058 0.0005 0.0081 0.0125 0.0017 0.0110 0.0001 0.0002 0.0013 0.0108 0.0226 0.0254 0.0038 0.0179 14 0.0572 0.0140 0.0276 0.0012 0.0010 0.0016 0.0035 0.0006 0.0177 0.2607 0.0295 0.0135 0.0083 0.0039 0.0041 0.0170 0.0186 0.0001 0.0432 0.0045 0.0048 0.0312 0.0003 0.0006 0.0568 0.0338 0.0021 16 18 0.0033 0.0038 0.0024 0.0019 0.0008 0.0010 0.0008 0.0101 0.2205 0.0642 0.0862 0.0106 0.0063 0.0121 0.0225 0.0052 0.0001 0.0001 0.0010 0.0010 0.0066 0.0001 0.0001 0.0522 0.0866 0.0142 0.0066 0.0026 0.0003 0.0064 0.0012 0.0002 0.0114 0.0068 0.1517 0.0066 0.0015 0.0004 0.0014 0.0224 0.0047 0.0000 0.2764 0.0005 0.0050 0.0326 0.0003 0.0006 0.0160 0.0004 0.0740 0.0083 0.0023 0.0026 17 20 21 0.0050 0.0011 0.0056 0.0007 0.0518 0.0003 0.0003 0.0099 0.0100 0.0076 0.0105 0.0034 0.0113 0.0195 0.0638 0.0005 0.0019 0.0310 0.0008 0.0005 0.0033 0.0000 0.0001 0.0008 0.0003 0.0025 0.0013 0.0004 0.0105 0.0028 0.0012 0.0003 0.0251 0.0122 0.0003 0.0042 0.0153 0.0050 0.0001 0.0004 0.0012 0.0060 0.0391 0.0003 0.0007 0.0605 0.0749 0.0620 0.0017 0.0010 0.0019 0.0008 0.0009 0.0003 0.0004 0.0064 0.0266 0.0216 0.0199 0.1730 0.0026 0.0086 0.0273 0.0023 0.0000 0.0001 0.0007 0.0006 0.0037 0.0000 0.0001 0.0001 0.0051 0.0004 0.0025 0.0065 0.0177 0.0008 0.0005 19 23 0.0009 0.0004 0.0006 0.0160 0.0001 0.0000 0.0002 0.0187 0.0001 0.0000 0.0001 0.0246 0.0016 0.0014 0.0178 0.0003 0.0001 0.0002 0.0004 0.0001 0.0008 0.0000 0.0000 0.1147 0.0891 0.0028 0.0018 0.0022 0.0046 0.0004 0.0016 0.0274 0.0303 0.0095 0.1010 0.0769 0.0018 0.0595 0.0301 0.0920 0.0007 0.0106 0.0014 0.0003 0.0020 0.0000 0.0000 0.0003 0.0009 0.0121 0.0577 0.0006 0.0004 22 Matrixofinput–outputtechnicalcoefficients(A)(continued) 0.0002 0.0012 0.0693 0.0406 0.0001 0.0002 TableC3 25 26 0.0067 0.1289 0.0014 0.0011 0.0005 0.0079 0.0005 0.0093 0.0002 0.0000 0.0028 0.0427 0.0083 0.0112 0.0066 0.0001 0.0007 0.0006 0.0024 0.0156 0.0001 0.0003 0.0463 0.0006 0.0475 0.0015 0.0004 0.0000 0.0000 0.0087 0.0000 0.0005 0.0561 0.0019 0.0184 0.0049 0.0003 0.0018 0.0003 0.0022 0.0000 0.0000 0.1658 0.1359 0.0831 0.0022 0.0005 0.0055 0.0207 0.0020 0.0066 0.0808 0.0064 0.0015 0.0000 0.0042 0.0757 0.0185 0.0539 0.0047 0.0003 0.0027 0.0008 0.0023 0.0029 0.0189 0.0002 0.0003 0.0012 0.0068 0.0525 0.0731 0.1225 0.0005 0.0015 0.0006 24 28 (1983) 0.0035 0.0011 0.0048 0.0056 0.0019 0.0116 0.0129 0.0059 0.0010 0.0003 0.0046 0.0173 0.0027 0.0245 0.0113 0.0014 0.0009 0.0001 0.0023 0.0015 0.0097 0.0001 0.0002 0.1290 0.1664 0.0016 0.0006 0.0008 0.0007 0.0003 0.0012 0.0058 0.0000 0.0000 0.0026 0.1819 0.0006 0.0033 0.0078 0.0015 0.0001 0.0010 0.0021 0.0135 0.0001 0.0002 0.0005 0.0071 0.0082 0.0004 0.0010 27 243 ABS(various) Input–outputcoefficientsshowninthisTableiscalculatedfromanadaptedversionofinput–outputtable,fortheyear1983,publishedbytheAustralianBureauof Statistics,inaccordancewithsectoralclassificationinthisresearch; seeTableC1,pp.234237fordescriptionofsector1to28. 0.0819 0.0561 0.0044 0.0014 0.0010 0.0010 0.0005 0.0016 0.0045 0.0023 0.0021 0.0001 0.0017 0.0160 0.0002 0.0021 0.0013 0.0008 5 0.1167 0.0322 0.0202 (continuedonnextpage) 0.0306 0.0008 0.0031 0.0020 0.0014 0.0048 0.0015 0.0049 0.0012 0.0005 0.0169 0.0036 0.0007 0.0044 0.0079 0.0017 0.0001 0.0010 28 0.0447 0.0316 0.1236 0.0006 0.0044 0.0002 0.0001 0.0000 0.0004 0.0001 0.0043 0.0000 0.0007 0.0000 0.0008 0.0002 0.0004 0.0082 0.0000 0.0000 0.0008 0.0001 0.0002 0.0007 0.0029 0.1000 0.0013 8 9 10 11 0.0002 0.0015 0.0000 0.0000 0.2372 0.0005 0.0030 0.0000 0.0001 0.0018 0.0118 0.0001 0.0002 4 4 5 6 7 3 2 1 0.0288 0.3538 0.2386 2 0.0075 0.0824 0.0764 3 0.0001 0.0007 0.0024 1 Sources: Notes: 0.0011 0.0040 0.0193 0.0006 0.0102 0.0002 0.0044 0.0292 0.0001 0.0008 0.0025 0.0080 0.0042 0.0003 0.0029 0.0138 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 0.0136 0.0005 0.0021 0.0043 0.0006 0.0036 0.0011 0.0045 0.0008 0.0001 0.0018 0.0139 0.0004 0.0033 0.0014 0.0009 0.0003 0.0016 0.2783 7 8 0.0068 0.0003 0.0021 0.0182 0.0005 0.0036 0.0014 0.0045 0.0007 0.0001 0.0016 0.0123 0.0004 0.0033 0.0013 0.0008 0.0003 0.0016 0.2796 0.0585 0.0610 0.0029 0.0006 0.0009 0.0012 0.0005 0.0016 0.0010 0.0122 0.0007 0.0001 0.0015 0.0118 0.0002 0.0015 0.0012 0.0008 0.0001 0.0007 0.1227 0.4923 0.0166 0.0803 6 9 10 0.0030 0.0158 0.0081 0.0129 0.0003 0.0028 0.0053 0.0186 0.0095 0.0014 0.0070 0.0374 0.0010 0.0035 0.0240 0.0013 0.0004 0.1359 0.0044 0.0029 0.0205 0.0002 0.0003 0.0788 0.1505 0.0022 0.0003 0.0019 0.0173 0.0010 0.0089 0.0006 0.0136 0.0001 0.0001 0.0009 0.0110 0.0027 0.0054 0.0453 0.0002 0.0711 0.0006 0.0412 0.0012 0.0086 0.0001 0.0001 0.1087 0.0073 0.0003 0.0017 0.0092 0.0007 0.0025 0.0007 0.0268 0.0007 0.0003 0.0260 0.0037 0.0029 0.0261 0.0332 0.0123 0.2847 0.0001 0.1414 0.0011 0.0078 0.0001 0.0001 0.0007 0.0059 0.0022 11 13 0.0019 0.0007 0.0027 0.0088 0.0012 0.0017 0.0009 0.0174 0.0056 0.0042 0.0084 0.0107 0.0147 0.1989 0.0424 0.0038 0.0236 0.0013 0.0031 0.0015 0.0101 0.0001 0.0002 0.1013 0.1181 0.0012 0.0003 0.0032 0.0010 0.0016 0.0005 0.0006 0.0092 0.0003 0.0003 0.0029 0.0008 0.2724 0.0077 0.0242 0.0002 0.0402 0.0063 0.0007 0.0051 0.0000 0.0001 0.0002 0.0013 0.0028 0.0071 0.0015 0.0023 12 15 0.0091 0.0023 0.0025 0.0157 0.0011 0.0012 0.0010 0.0505 0.0254 0.0033 0.0030 0.0044 0.0011 0.0300 0.0427 0.1126 0.0001 0.0746 0.0013 0.0027 0.0187 0.0002 0.0003 0.1013 0.0965 0.0012 0.0006 0.0031 0.0045 0.0017 0.0014 0.0005 0.0121 0.0026 0.0075 0.0061 0.0018 0.0103 0.0143 0.2597 0.0048 0.0010 0.0061 0.0093 0.0016 0.0114 0.0001 0.0002 0.0013 0.0089 0.0214 0.0101 0.0037 0.0209 14 0.0577 0.0145 0.0121 0.0010 0.0119 0.0008 0.0019 0.0002 0.0114 0.2673 0.0364 0.0132 0.0045 0.0035 0.0035 0.0119 0.0100 0.0001 0.0499 0.0002 0.0034 0.0236 0.0002 0.0004 0.0338 0.0069 0.0061 16 18 0.0019 0.0011 0.0025 0.0043 0.0003 0.0002 0.0003 0.0096 0.2039 0.0734 0.0896 0.0113 0.0095 0.0106 0.0264 0.0069 0.0001 0.0019 0.0009 0.0010 0.0068 0.0001 0.0001 0.0691 0.0957 0.0141 0.0119 0.0009 0.0066 0.0026 0.0012 0.0000 0.0086 0.0029 0.1725 0.0038 0.0011 0.0003 0.0016 0.0124 0.0012 0.0000 0.2269 0.0001 0.0052 0.0365 0.0003 0.0006 0.0091 0.0005 0.1190 0.0048 0.0144 0.0017 17 20 21 0.0013 0.0003 0.0038 0.0062 0.0301 0.0001 0.0001 0.0093 0.0082 0.0069 0.0113 0.0037 0.0157 0.0219 0.0716 0.0083 0.0038 0.0311 0.0017 0.0005 0.0036 0.0000 0.0001 0.0004 0.0001 0.0016 0.0010 0.0002 0.0020 0.0020 0.0007 0.0001 0.0128 0.0043 0.0002 0.0019 0.0104 0.0026 0.0000 0.0004 0.0007 0.0029 0.0202 0.0002 0.0003 0.0640 0.0778 0.0434 0.0008 0.0003 0.0018 0.0024 0.0010 0.0003 0.0001 0.0052 0.0294 0.0205 0.0196 0.1677 0.0036 0.0074 0.0303 0.0044 0.0000 0.0003 0.0004 0.0006 0.0042 0.0000 0.0001 0.0001 0.0024 0.0004 0.0016 0.0031 0.0381 0.0007 0.0003 19 23 0.0006 0.0001 0.0015 0.0425 0.0006 0.0000 0.0034 0.0037 0.0000 0.0000 0.0022 0.0145 0.0011 0.0039 0.0209 0.0001 0.0000 0.0002 0.0002 0.0003 0.0021 0.0000 0.0000 0.0974 0.1168 0.0012 0.0005 0.0022 0.0058 0.0003 0.0016 0.0244 0.0269 0.0076 0.0889 0.0608 0.0017 0.0555 0.0282 0.0909 0.0006 0.0143 0.0013 0.0002 0.0016 0.0000 0.0000 0.0002 0.0003 0.0111 0.0701 0.0007 0.0001 22 Matrixofinput–outputtechnicalcoefficients(A)(continued) 0.0001 0.0006 0.0642 0.0248 0.0002 0.0001 TableC3 25 26 0.0012 0.0874 0.0020 0.1085 0.0004 0.0032 0.0100 0.0056 0.0000 0.0000 0.0068 0.0483 0.0034 0.0129 0.0050 0.0000 0.0007 0.0006 0.0001 0.0009 0.0000 0.0000 0.0009 0.0002 0.0025 0.0891 0.0003 0.0000 0.0037 0.0044 0.0000 0.0006 0.0638 0.0012 0.0090 0.0091 0.0005 0.0008 0.0002 0.0015 0.0000 0.0000 0.1212 0.1220 0.0907 0.0010 0.0011 0.0007 0.0156 0.0025 0.0000 0.0757 0.0072 0.0016 0.0000 0.0100 0.1939 0.0045 0.0291 0.0078 0.0003 0.0038 0.0042 0.0027 0.0030 0.0207 0.0002 0.0003 0.0012 0.0038 0.0738 0.0882 0.1097 0.0002 0.0000 0.0002 24 28 (1984) 0.0005 0.0007 0.0054 0.0140 0.0022 0.0125 0.0107 0.0061 0.0008 0.0002 0.0051 0.0169 0.0037 0.0274 0.0116 0.0013 0.0010 0.0002 0.0030 0.0017 0.0116 0.0001 0.0002 0.1367 0.1663 0.0023 0.0002 0.0030 0.0239 0.0003 0.0007 0.0119 0.0078 0.0001 0.0000 0.0015 0.0900 0.0008 0.0022 0.0055 0.0006 0.0000 0.0007 0.0022 0.0156 0.0001 0.0003 0.0009 0.0108 0.0109 0.0006 0.0018 27 244 ABS(various) Input–outputcoefficientsshowninthisTableiscalculatedfromanadaptedversionofinput–outputtable,fortheyear1984,publishedbytheAustralianBureauof Statistics,inaccordancewithsectoralclassificationinthisresearch; seeTableC1,pp.234237fordescriptionofsector1to28. 0.0955 0.0690 0.0049 0.0002 0.0016 0.0016 0.0008 0.0028 0.0024 0.0017 0.0011 0.0002 0.0025 0.0193 0.0003 0.0026 0.0020 0.0012 5 0.1140 0.0272 0.0070 (continuedonnextpage) 0.0224 0.0002 0.0045 0.0033 0.0024 0.0071 0.0007 0.0031 0.0014 0.0005 0.0205 0.0055 0.0010 0.0051 0.0106 0.0018 0.0003 0.0016 28 0.0508 0.0390 0.1454 0.0068 0.0127 0.0002 0.0053 0.0000 0.0007 0.0002 0.0070 0.0037 0.0018 0.0001 0.0016 0.0008 0.0009 0.0196 0.0000 0.0000 0.0047 0.0001 0.0002 0.0013 0.0033 0.1063 0.0016 8 9 10 11 0.0002 0.0013 0.0000 0.0000 0.2190 0.0005 0.0035 0.0000 0.0001 0.0020 0.0136 0.0001 0.0002 4 4 5 6 7 3 2 1 0.0358 0.3112 0.2439 2 0.0068 0.0940 0.0284 3 0.0001 0.0018 0.0047 1 Sources: Notes: 0.0020 0.0055 0.0267 0.0007 0.0154 0.0002 0.0066 0.0369 0.0002 0.0013 0.0031 0.0113 0.0023 0.0009 0.0027 0.0154 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 0.0169 0.0004 0.0014 0.0046 0.0005 0.0030 0.0007 0.0049 0.0005 0.0001 0.0015 0.0133 0.0004 0.0029 0.0011 0.0009 0.0003 0.0011 0.2617 7 8 0.0042 0.0001 0.0007 0.0097 0.0007 0.0015 0.0014 0.0030 0.0008 0.0002 0.0021 0.0191 0.0002 0.0014 0.0016 0.0012 0.0001 0.0005 0.1291 0.0601 0.0785 0.0031 0.0004 0.0005 0.0011 0.0005 0.0011 0.0007 0.0122 0.0006 0.0001 0.0016 0.0146 0.0002 0.0011 0.0012 0.0009 0.0001 0.0004 0.0962 0.4666 0.0278 0.1358 6 9 10 0.0045 0.0053 0.0077 0.0143 0.0004 0.0037 0.0056 0.0239 0.0086 0.0030 0.0083 0.0415 0.0013 0.0041 0.0297 0.0016 0.0006 0.1018 0.0043 0.0026 0.0198 0.0001 0.0001 0.0928 0.1340 0.0014 0.0004 0.0017 0.0198 0.0016 0.0093 0.0005 0.0169 0.0001 0.0001 0.0009 0.0099 0.0045 0.0059 0.0575 0.0002 0.0789 0.0006 0.0423 0.0014 0.0104 0.0001 0.0001 0.1122 0.0078 0.0004 0.0012 0.0071 0.0007 0.0022 0.0004 0.0284 0.0006 0.0003 0.0246 0.0032 0.0027 0.0199 0.0301 0.0119 0.2867 0.0003 0.1285 0.0010 0.0079 0.0000 0.0000 0.0015 0.0037 0.0025 11 13 0.0011 0.0006 0.0021 0.0069 0.0013 0.0018 0.0006 0.0181 0.0045 0.0044 0.0074 0.0124 0.0204 0.1998 0.0374 0.0039 0.0206 0.0013 0.0032 0.0013 0.0097 0.0001 0.0000 0.0960 0.1249 0.0009 0.0003 0.0017 0.0015 0.0011 0.0003 0.0001 0.0143 0.0002 0.0002 0.0013 0.0005 0.2624 0.0041 0.0134 0.0001 0.0640 0.0202 0.0006 0.0049 0.0000 0.0000 0.0004 0.0014 0.0010 0.0053 0.0015 0.0019 12 15 0.0076 0.0022 0.0021 0.0118 0.0013 0.0013 0.0007 0.0524 0.0235 0.0041 0.0031 0.0055 0.0015 0.0358 0.0429 0.1166 0.0001 0.0535 0.0011 0.0022 0.0173 0.0001 0.0001 0.1074 0.1134 0.0011 0.0006 0.0024 0.0033 0.0018 0.0013 0.0004 0.0123 0.0026 0.0073 0.0056 0.0018 0.0121 0.0132 0.2412 0.0041 0.0008 0.0064 0.0143 0.0013 0.0097 0.0000 0.0000 0.0037 0.0110 0.0083 0.0095 0.0037 0.0216 14 0.0628 0.0145 0.0115 0.0010 0.0044 0.0011 0.0022 0.0001 0.0139 0.2713 0.0494 0.0149 0.0065 0.0076 0.0038 0.0133 0.0119 0.0001 0.0637 0.0002 0.0028 0.0214 0.0001 0.0001 0.0164 0.0074 0.0092 16 18 0.0019 0.0012 0.0020 0.0038 0.0003 0.0002 0.0002 0.0105 0.1850 0.0817 0.0851 0.0127 0.0128 0.0101 0.0264 0.0084 0.0001 0.0011 0.0007 0.0008 0.0060 0.0000 0.0000 0.0605 0.1079 0.0086 0.0131 0.0006 0.0030 0.0028 0.0009 0.0000 0.0086 0.0021 0.1574 0.0027 0.0009 0.0004 0.0013 0.0100 0.0007 0.0000 0.2376 0.0000 0.0059 0.0455 0.0002 0.0002 0.0141 0.0012 0.0710 0.0034 0.0286 0.0016 17 20 21 0.0010 0.0002 0.0023 0.0032 0.0234 0.0001 0.0001 0.0096 0.0068 0.0053 0.0080 0.0031 0.0370 0.0175 0.0631 0.0043 0.0028 0.0458 0.0010 0.0004 0.0031 0.0000 0.0000 0.0002 0.0001 0.0011 0.0009 0.0002 0.0013 0.0019 0.0006 0.0001 0.0123 0.0038 0.0001 0.0019 0.0083 0.0022 0.0000 0.0002 0.0005 0.0027 0.0209 0.0001 0.0001 0.0715 0.0700 0.0402 0.0005 0.0003 0.0014 0.0020 0.0012 0.0003 0.0001 0.0050 0.0241 0.0208 0.0200 0.1472 0.0041 0.0070 0.0302 0.0050 0.0000 0.0003 0.0004 0.0005 0.0036 0.0000 0.0000 0.0004 0.0039 0.0001 0.0011 0.0018 0.0250 0.0006 0.0003 19 23 0.0003 0.0001 0.0010 0.0372 0.0005 0.0000 0.0014 0.0037 0.0000 0.0000 0.0019 0.0091 0.0014 0.0037 0.0144 0.0001 0.0000 0.0001 0.0002 0.0003 0.0021 0.0000 0.0000 0.0996 0.1237 0.0008 0.0005 0.0019 0.0057 0.0004 0.0017 0.0249 0.0251 0.0079 0.0813 0.0760 0.0013 0.0533 0.0302 0.0882 0.0004 0.0095 0.0009 0.0003 0.0020 0.0000 0.0000 0.0002 0.0005 0.0092 0.0557 0.0003 0.0000 22 Matrixofinput–outputtechnicalcoefficients(A)(continued) 0.0003 0.0015 0.0570 0.0166 0.0001 0.0002 TableC3 25 26 0.0007 0.0497 0.0018 0.1832 0.0004 0.0039 0.0067 0.0072 0.0000 0.0000 0.0093 0.0827 0.0099 0.0155 0.0056 0.0000 0.0005 0.0007 0.0002 0.0012 0.0000 0.0000 0.0005 0.0002 0.0022 0.0781 0.0004 0.0000 0.0025 0.0059 0.0000 0.0007 0.0636 0.0013 0.0099 0.0105 0.0007 0.0008 0.0003 0.0021 0.0000 0.0000 0.1179 0.1543 0.1097 0.0006 0.0006 0.0008 0.0196 0.0023 0.0000 0.0712 0.0079 0.0013 0.0000 0.0103 0.1598 0.0060 0.0285 0.0072 0.0004 0.0036 0.0028 0.0021 0.0031 0.0240 0.0001 0.0001 0.0022 0.0014 0.0680 0.0792 0.0891 0.0001 0.0000 0.0001 24 28 (1987) 0.0004 0.0007 0.0051 0.0146 0.0023 0.0110 0.0101 0.0071 0.0007 0.0002 0.0052 0.0203 0.0033 0.0283 0.0121 0.0013 0.0030 0.0001 0.0061 0.0015 0.0118 0.0001 0.0001 0.1493 0.1775 0.0017 0.0004 0.0020 0.0153 0.0003 0.0008 0.0066 0.0073 0.0001 0.0000 0.0017 0.0873 0.0011 0.0025 0.0053 0.0009 0.0000 0.0006 0.0023 0.0178 0.0001 0.0001 0.0007 0.0083 0.0092 0.0003 0.0008 27 245 ABS(various) Input–outputcoefficientsshowninthisTableiscalculatedfromanadaptedversionofinput–outputtable,fortheyear1987,publishedbytheAustralianBureauof Statistics,inaccordancewithsectoralclassificationinthisresearch; seeTableC1,pp.234237fordescriptionofsector1to28. 0.0787 0.0546 0.0061 0.0001 0.0010 0.0017 0.0007 0.0023 0.0015 0.0018 0.0008 0.0002 0.0021 0.0192 0.0003 0.0023 0.0016 0.0012 5 0.1382 0.0190 0.0244 (continuedonnextpage) 0.0972 0.0001 0.0016 0.0017 0.0010 0.0034 0.0002 0.0016 0.0006 0.0003 0.0082 0.0030 0.0010 0.0024 0.0048 0.0010 0.0001 0.0006 28 0.0517 0.1457 0.0783 0.0007 0.0243 0.0017 0.0083 0.0004 0.0063 0.0013 0.0340 0.0040 0.0081 0.0010 0.0142 0.0070 0.0081 0.0882 0.0003 0.0004 0.0252 0.0011 0.0002 0.0008 0.0030 0.0344 0.0018 8 9 10 11 0.0001 0.0007 0.0000 0.0000 0.2018 0.0004 0.0032 0.0000 0.0000 0.0019 0.0150 0.0001 0.0001 4 4 5 6 7 3 2 1 0.0180 0.2042 0.2845 2 0.0052 0.1172 0.0050 3 0.0001 0.0023 0.0009 1 Sources: Notes: 0.0009 0.0037 0.0230 0.0010 0.0153 0.0002 0.0079 0.0330 0.0001 0.0003 0.0029 0.0110 0.0017 0.0005 0.0048 0.0142 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 0.0157 0.0003 0.0021 0.0027 0.0003 0.0029 0.0006 0.0048 0.0005 0.0000 0.0012 0.0090 0.0003 0.0025 0.0014 0.0019 0.0003 0.0012 0.2601 7 8 0.0053 0.0001 0.0014 0.0078 0.0003 0.0019 0.0007 0.0034 0.0004 0.0000 0.0010 0.0075 0.0002 0.0017 0.0012 0.0015 0.0002 0.0008 0.1733 0.0084 0.0002 0.0023 0.0098 0.0001 0.0031 0.0003 0.0044 0.0001 0.0000 0.0003 0.0025 0.0003 0.0027 0.0004 0.0005 0.2834 0.0004 0.0013 0.0784 0.0450 0.0148 0.0028 0.0003 0.0008 0.0007 0.0005 0.0010 0.0009 0.0129 0.0007 0.0001 0.0017 0.0131 0.0001 0.0009 0.0020 0.0027 0.0001 0.0004 0.0946 0.2889 0.0054 0.2847 0.3447 6 9 10 0.0033 0.0079 0.0139 0.0128 0.0003 0.0019 0.0082 0.0346 0.0078 0.0026 0.0197 0.0439 0.0010 0.0043 0.0412 0.0029 0.0001 0.0012 0.0885 0.0045 0.0021 0.0179 0.0001 0.0002 0.0924 0.1218 0.0011 0.0003 0.0025 0.0146 0.0015 0.0100 0.0005 0.0195 0.0000 0.0002 0.0008 0.0162 0.0047 0.0044 0.0549 0.0039 0.0001 0.0910 0.0013 0.0415 0.0013 0.0112 0.0000 0.0001 0.0898 0.0051 0.0003 0.0010 0.0032 0.0002 0.0007 0.0001 0.0326 0.0001 0.0010 0.0183 0.0015 0.0016 0.0194 0.0252 0.0083 0.0000 0.2884 0.0000 0.1321 0.0008 0.0070 0.0000 0.0001 0.0008 0.0022 0.0022 11 13 0.0008 0.0003 0.0025 0.0060 0.0008 0.0013 0.0005 0.0226 0.0075 0.0031 0.0118 0.0100 0.0120 0.1917 0.0447 0.0034 0.0000 0.0192 0.0009 0.0032 0.0011 0.0095 0.0000 0.0001 0.1178 0.1218 0.0006 0.0002 0.0017 0.0011 0.0022 0.0008 0.0009 0.0140 0.0004 0.0004 0.0015 0.0009 0.2335 0.0104 0.0247 0.0000 0.0000 0.0339 0.0000 0.0077 0.0005 0.0046 0.0000 0.0001 0.0003 0.0011 0.0011 0.0033 0.0015 0.0015 12 15 0.0043 0.0010 0.0012 0.0035 0.0004 0.0004 0.0003 0.0718 0.0090 0.0021 0.0124 0.0022 0.0008 0.0232 0.0311 0.1175 0.0001 0.0011 0.0675 0.0005 0.0019 0.0164 0.0001 0.0002 0.1053 0.0790 0.0008 0.0003 0.0017 0.0024 0.0011 0.0008 0.0002 0.0148 0.0023 0.0124 0.0058 0.0012 0.0060 0.0168 0.2110 0.0032 0.0000 0.0025 0.0091 0.0160 0.0009 0.0078 0.0000 0.0001 0.0018 0.0041 0.0068 0.0082 0.0036 0.0228 14 0.0667 0.0124 0.0176 0.0012 0.0043 0.0010 0.0022 0.0001 0.0171 0.1586 0.1164 0.0063 0.0040 0.0051 0.0035 0.0200 0.0174 0.0000 0.0002 0.0606 0.0002 0.0009 0.0076 0.0000 0.0001 0.0095 0.0093 0.0038 16 18 0.0019 0.0011 0.0015 0.0032 0.0002 0.0001 0.0002 0.0115 0.1690 0.0749 0.1048 0.0093 0.0085 0.0150 0.0235 0.0095 0.0000 0.0004 0.0039 0.0008 0.0005 0.0045 0.0000 0.0001 0.0511 0.1102 0.0062 0.0059 0.0008 0.0016 0.0023 0.0008 0.0000 0.0093 0.0038 0.1371 0.0020 0.0005 0.0002 0.0011 0.0184 0.0017 0.0002 0.0017 0.2531 0.0001 0.0046 0.0391 0.0002 0.0005 0.0143 0.0002 0.0160 0.0021 0.0198 0.0014 17 20 21 0.0004 0.0001 0.0019 0.0019 0.0262 0.0000 0.0000 0.0101 0.0202 0.0164 0.0163 0.0056 0.0135 0.0131 0.0465 0.0051 0.0000 0.0021 0.0603 0.0005 0.0003 0.0026 0.0000 0.0000 0.0003 0.0001 0.0037 0.0015 0.0003 0.0027 0.0045 0.0011 0.0001 0.0206 0.0086 0.0002 0.0039 0.0313 0.0074 0.0002 0.0001 0.0016 0.0015 0.0053 0.0454 0.0002 0.0006 0.0715 0.0833 0.0766 0.0006 0.0001 0.0017 0.0019 0.0012 0.0004 0.0001 0.0061 0.0436 0.0176 0.0230 0.1039 0.0031 0.0117 0.0356 0.0031 0.0000 0.0001 0.0003 0.0005 0.0003 0.0028 0.0000 0.0000 0.0001 0.0003 0.0002 0.0008 0.0008 0.0191 0.0007 0.0002 19 23 0.0004 0.0003 0.0044 0.0615 0.0011 0.0000 0.0055 0.0066 0.0000 0.0000 0.0023 0.0546 0.0023 0.0068 0.0274 0.0006 0.0000 0.0001 0.0000 0.0004 0.0006 0.0056 0.0000 0.0001 0.1214 0.1811 0.0006 0.0003 0.0012 0.0084 0.0010 0.0005 0.0001 0.0315 0.0276 0.0049 0.0748 0.0705 0.0018 0.0429 0.0217 0.0878 0.0000 0.0009 0.0085 0.0013 0.0004 0.0037 0.0000 0.0000 0.0001 0.0001 0.0105 0.0543 0.0010 0.0002 22 Matrixofinput–outputtechnicalcoefficients(A)(continued) 0.0000 0.0022 0.0242 0.0140 0.0001 0.0003 TableC3 25 26 0.0004 0.0745 0.0034 0.2024 0.0003 0.0044 0.0097 0.0063 0.0000 0.0000 0.0104 0.0577 0.0081 0.0097 0.0057 0.0000 0.0000 0.0000 0.0008 0.0002 0.0014 0.0000 0.0000 0.0005 0.0006 0.0035 0.0584 0.0003 0.0000 0.0029 0.0066 0.0000 0.0006 0.0517 0.0002 0.0055 0.0102 0.0000 0.0019 0.0005 0.0002 0.0020 0.0000 0.0000 0.1190 0.1854 0.1164 0.0004 0.0009 0.0009 0.0196 0.0019 0.0000 0.0658 0.0055 0.0018 0.0001 0.0463 0.0554 0.0121 0.0279 0.0111 0.0004 0.0001 0.0052 0.0000 0.0035 0.0034 0.0294 0.0001 0.0004 0.0008 0.0013 0.0289 0.0323 0.0932 0.0002 0.0000 0.0002 24 28 (1990) 0.0003 0.0006 0.0076 0.0125 0.0016 0.0117 0.0054 0.0062 0.0008 0.0002 0.0046 0.0195 0.0031 0.0268 0.0120 0.0024 0.0001 0.0030 0.0003 0.0066 0.0013 0.0113 0.0000 0.0001 0.1173 0.2105 0.0014 0.0002 0.0031 0.0133 0.0002 0.0006 0.0068 0.0076 0.0000 0.0000 0.0021 0.1067 0.0006 0.0015 0.0049 0.0009 0.0001 0.0001 0.0006 0.0018 0.0157 0.0001 0.0002 0.0002 0.0038 0.0042 0.0004 0.0013 27 246 ABS(various) Input–outputcoefficientsshowninthisTableiscalculatedfromanadaptedversionofinput–outputtable,fortheyear1990,publishedbytheAustralianBureauof Statistics,inaccordancewithsectoralclassificationinthisresearch; seeTableC1,pp.234237fordescriptionofsector1to28. 0.0741 0.0540 0.0047 0.0001 0.0013 0.0009 0.0005 0.0018 0.0013 0.0015 0.0007 0.0001 0.0016 0.0124 0.0002 0.0016 0.0019 0.0025 5 0.1350 0.0109 0.0365 (continuedonnextpage) 0.0874 0.0000 0.0028 0.0012 0.0007 0.0035 0.0002 0.0014 0.0006 0.0001 0.0098 0.0029 0.0008 0.0024 0.0120 0.0021 0.0000 0.0001 0.0008 28 0.0528 0.0628 0.1153 0.0003 0.0210 0.0013 0.0051 0.0002 0.0002 0.0006 0.0122 0.0011 0.0007 0.0006 0.0019 0.0010 0.0031 0.0666 0.0001 0.0000 0.0001 0.0031 0.0004 0.0002 0.0008 0.0001 0.0030 0.0479 0.0016 8 9 10 11 0.0001 0.0008 0.0000 0.0000 0.1654 0.0002 0.0016 0.0000 0.0000 0.0014 0.0122 0.0000 0.0002 4 4 5 6 7 3 2 1 0.0098 0.3850 0.3712 2 0.0039 0.0531 0.0036 3 0.0001 0.0020 0.0016 1 Sources: Notes: 0.0010 0.0026 0.0184 0.0008 0.0053 0.0001 0.0069 0.0247 0.0001 0.0005 0.0021 0.0044 0.0010 0.0008 0.0037 0.0119 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 0.0137 0.0004 0.0008 0.0039 0.0001 0.0061 0.0026 0.0024 0.0006 0.0000 0.0008 0.0096 0.0001 0.0005 0.0030 0.0032 0.0000 0.0001 0.3495 7 8 0.0036 0.0001 0.0004 0.0097 0.0001 0.0032 0.0041 0.0014 0.0007 0.0000 0.0010 0.0110 0.0000 0.0003 0.0035 0.0036 0.0000 0.0000 0.1809 0.0076 0.0002 0.0009 0.0162 0.0000 0.0069 0.0013 0.0024 0.0002 0.0000 0.0002 0.0027 0.0001 0.0006 0.0008 0.0009 0.3958 0.0000 0.0001 0.0380 0.0285 0.0069 0.0029 0.0004 0.0004 0.0011 0.0001 0.0026 0.0039 0.0083 0.0010 0.0000 0.0013 0.0147 0.0000 0.0002 0.0046 0.0048 0.0000 0.0000 0.1495 0.1997 0.0034 0.1378 0.2219 6 9 10 0.0021 0.0095 0.0114 0.0184 0.0003 0.0034 0.0100 0.0156 0.0075 0.0021 0.0168 0.0428 0.0014 0.0035 0.0367 0.0037 0.0002 0.0012 0.0872 0.0020 0.0040 0.0320 0.0001 0.0003 0.1101 0.1418 0.0024 0.0005 0.0035 0.0293 0.0029 0.0109 0.0057 0.0295 0.0001 0.0006 0.0025 0.0172 0.0047 0.0066 0.0659 0.0071 0.0000 0.0780 0.0005 0.0417 0.0012 0.0097 0.0000 0.0001 0.1148 0.0035 0.0003 0.0016 0.0070 0.0016 0.0009 0.0001 0.0336 0.0001 0.0016 0.0239 0.0028 0.0031 0.0256 0.0336 0.0091 0.0000 0.2717 0.0000 0.1209 0.0009 0.0070 0.0000 0.0001 0.0029 0.0061 0.0027 11 13 0.0007 0.0003 0.0033 0.0127 0.0012 0.0014 0.0003 0.0179 0.0096 0.0046 0.0102 0.0148 0.0098 0.1869 0.0476 0.0042 0.0000 0.0187 0.0005 0.0031 0.0008 0.0065 0.0000 0.0001 0.0795 0.1292 0.0015 0.0002 0.0017 0.0011 0.0022 0.0004 0.0000 0.0076 0.0004 0.0005 0.0021 0.0014 0.2191 0.0130 0.0226 0.0001 0.0000 0.0664 0.0000 0.0134 0.0004 0.0028 0.0000 0.0000 0.0006 0.0020 0.0010 0.0045 0.0010 0.0013 12 15 0.0030 0.0007 0.0018 0.0074 0.0008 0.0004 0.0001 0.0801 0.0112 0.0017 0.0168 0.0030 0.0018 0.0224 0.0453 0.1173 0.0001 0.0016 0.0835 0.0004 0.0017 0.0134 0.0000 0.0001 0.1029 0.0866 0.0006 0.0005 0.0021 0.0040 0.0017 0.0008 0.0001 0.0076 0.0026 0.0088 0.0121 0.0016 0.0076 0.0217 0.2231 0.0049 0.0000 0.0051 0.0027 0.0123 0.0008 0.0061 0.0000 0.0001 0.0039 0.0101 0.0113 0.0099 0.0033 0.0247 14 0.1294 0.0109 0.0063 0.0016 0.0081 0.0016 0.0024 0.0001 0.0163 0.1771 0.0774 0.0078 0.0064 0.0039 0.0043 0.0265 0.0223 0.0000 0.0003 0.0613 0.0002 0.0007 0.0058 0.0000 0.0001 0.0137 0.0127 0.0037 16 18 0.0022 0.0008 0.0015 0.0048 0.0009 0.0002 0.0034 0.0097 0.1261 0.0605 0.1543 0.0088 0.0077 0.0189 0.0270 0.0092 0.0000 0.0005 0.0061 0.0007 0.0004 0.0033 0.0000 0.0000 0.0938 0.0970 0.0063 0.0082 0.0012 0.0015 0.0040 0.0011 0.0000 0.0100 0.0051 0.0771 0.0030 0.0009 0.0002 0.0014 0.0274 0.0025 0.0002 0.0023 0.2700 0.0001 0.0044 0.0353 0.0001 0.0003 0.0297 0.0012 0.0307 0.0032 0.0225 0.0015 17 20 21 0.0006 0.0002 0.0025 0.0048 0.0156 0.0000 0.0002 0.0065 0.0457 0.0190 0.0328 0.0465 0.0154 0.0231 0.0552 0.0094 0.0000 0.0029 0.0577 0.0012 0.0003 0.0026 0.0000 0.0000 0.0004 0.0002 0.0047 0.0035 0.0005 0.0013 0.0052 0.0020 0.0001 0.0274 0.0120 0.0003 0.0050 0.0406 0.0102 0.0002 0.0002 0.0025 0.0011 0.0043 0.0349 0.0001 0.0003 0.0769 0.0947 0.0923 0.0006 0.0001 0.0021 0.0027 0.0023 0.0008 0.0001 0.0042 0.0457 0.0150 0.0260 0.1094 0.0018 0.0128 0.0315 0.0046 0.0000 0.0003 0.0004 0.0005 0.0003 0.0021 0.0000 0.0000 0.0003 0.0020 0.0000 0.0011 0.0019 0.0263 0.0006 0.0004 19 23 0.0004 0.0003 0.0042 0.0574 0.0013 0.0000 0.0019 0.0049 0.0000 0.0000 0.0022 0.0317 0.0015 0.0051 0.0147 0.0004 0.0000 0.0001 0.0004 0.0003 0.0004 0.0032 0.0000 0.0000 0.1476 0.1544 0.0005 0.0003 0.0009 0.0092 0.0008 0.0003 0.0003 0.0218 0.0188 0.0028 0.0615 0.0695 0.0020 0.0464 0.0141 0.0930 0.0000 0.0005 0.0069 0.0007 0.0002 0.0013 0.0000 0.0000 0.0001 0.0003 0.0064 0.0562 0.0005 0.0001 22 Matrixofinput–outputtechnicalcoefficients(A)(continued) 0.0002 0.0018 0.0355 0.0297 0.0002 0.0027 TableC3 25 26 0.0001 0.1686 0.0030 0.0897 0.0003 0.0034 0.0027 0.0024 0.0000 0.0000 0.0083 0.0488 0.0036 0.0056 0.0048 0.0000 0.0000 0.0007 0.0004 0.0001 0.0008 0.0000 0.0000 0.0005 0.0004 0.0048 0.0728 0.0004 0.0000 0.0013 0.0067 0.0000 0.0009 0.0655 0.0007 0.0060 0.0125 0.0000 0.0030 0.0007 0.0002 0.0016 0.0000 0.0000 0.1154 0.1223 0.1035 0.0002 0.0013 0.0005 0.0196 0.0016 0.0000 0.0143 0.0028 0.0015 0.0000 0.0366 0.0345 0.0043 0.0143 0.0067 0.0006 0.0001 0.0031 0.0000 0.0015 0.0014 0.0117 0.0000 0.0001 0.0008 0.0001 0.0210 0.0307 0.0844 0.0001 0.0000 0.0002 24 28 (1993) 0.0003 0.0012 0.0079 0.0156 0.0016 0.0119 0.0060 0.0054 0.0008 0.0002 0.0044 0.0178 0.0031 0.0254 0.0122 0.0026 0.0000 0.0036 0.0004 0.0068 0.0011 0.0088 0.0000 0.0001 0.1595 0.2207 0.0023 0.0005 0.0063 0.0353 0.0005 0.0007 0.0042 0.0092 0.0000 0.0000 0.0025 0.1080 0.0019 0.0027 0.0053 0.0014 0.0001 0.0001 0.0000 0.0006 0.0020 0.0163 0.0001 0.0001 0.0000 0.0002 0.0135 0.0048 0.0005 0.0012 27 247 ABS(various) Input–outputcoefficientsshowninthisTableiscalculatedfromanadaptedversionofinput–outputtable,fortheyear1993,publishedbytheAustralianBureauof Statistics,inaccordancewithsectoralclassificationinthisresearch; seeTableC1,pp.234237fordescriptionofsector1to28. 0.0311 0.0250 0.0040 0.0001 0.0005 0.0012 0.0001 0.0038 0.0048 0.0007 0.0008 0.0000 0.0011 0.0120 0.0001 0.0003 0.0038 0.0039 5 0.0775 0.0059 0.0180 (continuedonnextpage) 0.0793 0.0006 0.0044 0.0053 0.0004 0.0056 0.0000 0.0012 0.0007 0.0000 0.0024 0.0005 0.0003 0.0023 0.0148 0.0021 0.0000 0.0000 0.0001 28 0.0852 0.0414 0.0946 0.0002 0.0428 0.0007 0.0060 0.0001 0.0001 0.0001 0.0057 0.0008 0.0005 0.0003 0.0014 0.0005 0.0020 0.0340 0.0000 0.0000 0.0001 0.0020 0.0002 0.0000 0.0001 0.0001 0.0016 0.0321 0.0006 8 9 10 11 0.0002 0.0015 0.0000 0.0000 0.2187 0.0001 0.0005 0.0000 0.0000 0.0022 0.0174 0.0001 0.0002 4 4 5 6 7 3 2 1 0.0053 0.5064 0.3914 2 0.0095 0.0903 0.0028 3 0.0001 0.0008 0.0022 1 Sources: Notes: 0.0007 0.0016 0.0148 0.0007 0.0042 0.0001 0.0060 0.0260 0.0000 0.0003 0.0028 0.0034 0.0009 0.0004 0.0016 0.0075 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 0.0147 0.0003 0.0005 0.0031 0.0000 0.0043 0.0010 0.0026 0.0004 0.0000 0.0010 0.0156 0.0001 0.0004 0.0043 0.0039 0.0000 0.0001 0.3293 7 8 0.0040 0.0001 0.0003 0.0079 0.0000 0.0023 0.0018 0.0015 0.0006 0.0000 0.0013 0.0205 0.0000 0.0002 0.0056 0.0051 0.0000 0.0000 0.1474 0.0093 0.0002 0.0007 0.0143 0.0000 0.0055 0.0006 0.0029 0.0001 0.0000 0.0003 0.0046 0.0001 0.0005 0.0013 0.0012 0.4922 0.0000 0.0001 0.0333 0.0295 0.0066 0.0035 0.0004 0.0003 0.0010 0.0000 0.0020 0.0015 0.0090 0.0006 0.0000 0.0015 0.0232 0.0000 0.0002 0.0063 0.0058 0.0000 0.0000 0.1245 0.2032 0.0041 0.0499 0.0870 6 9 10 0.0016 0.0199 0.0067 0.0173 0.0001 0.0018 0.0109 0.0126 0.0096 0.0008 0.0129 0.0382 0.0009 0.0025 0.0305 0.0035 0.0001 0.0002 0.1421 0.0015 0.0025 0.0215 0.0001 0.0002 0.1115 0.1479 0.0025 0.0006 0.0023 0.0356 0.0034 0.0049 0.0089 0.0252 0.0001 0.0007 0.0039 0.0207 0.0034 0.0054 0.0598 0.0022 0.0000 0.0934 0.0002 0.0334 0.0010 0.0081 0.0000 0.0001 0.1018 0.0044 0.0003 0.0013 0.0067 0.0011 0.0008 0.0000 0.0314 0.0002 0.0010 0.0248 0.0032 0.0037 0.0277 0.0373 0.0087 0.0000 0.2813 0.0000 0.1146 0.0008 0.0066 0.0000 0.0001 0.0042 0.0032 0.0022 11 13 0.0009 0.0003 0.0024 0.0118 0.0009 0.0011 0.0003 0.0170 0.0121 0.0067 0.0119 0.0180 0.0074 0.1778 0.0490 0.0046 0.0000 0.0274 0.0005 0.0020 0.0007 0.0059 0.0000 0.0000 0.0750 0.1164 0.0030 0.0002 0.0017 0.0011 0.0015 0.0004 0.0000 0.0075 0.0004 0.0004 0.0027 0.0015 0.2386 0.0119 0.0288 0.0001 0.0000 0.0421 0.0000 0.0109 0.0004 0.0035 0.0000 0.0000 0.0015 0.0023 0.0009 0.0034 0.0008 0.0011 12 15 0.0046 0.0007 0.0012 0.0063 0.0009 0.0003 0.0001 0.0849 0.0084 0.0056 0.0159 0.0027 0.0020 0.0209 0.0421 0.1105 0.0001 0.0016 0.0790 0.0003 0.0015 0.0127 0.0001 0.0001 0.0999 0.0732 0.0028 0.0006 0.0017 0.0037 0.0015 0.0006 0.0000 0.0087 0.0020 0.0097 0.0136 0.0019 0.0081 0.0208 0.2185 0.0045 0.0000 0.0046 0.0082 0.0080 0.0007 0.0062 0.0000 0.0000 0.0062 0.0266 0.0094 0.0070 0.0024 0.0298 14 0.1162 0.0092 0.0017 0.0011 0.0063 0.0009 0.0018 0.0000 0.0164 0.2199 0.0771 0.0073 0.0092 0.0028 0.0031 0.0245 0.0218 0.0000 0.0002 0.0660 0.0002 0.0006 0.0053 0.0000 0.0000 0.0164 0.0099 0.0030 16 18 0.0024 0.0005 0.0011 0.0035 0.0005 0.0002 0.0037 0.0107 0.1368 0.0471 0.1305 0.0112 0.0067 0.0173 0.0246 0.0096 0.0000 0.0005 0.0078 0.0005 0.0004 0.0031 0.0000 0.0000 0.0789 0.0901 0.0090 0.0091 0.0010 0.0015 0.0018 0.0009 0.0000 0.0091 0.0061 0.1636 0.0020 0.0011 0.0002 0.0012 0.0262 0.0022 0.0002 0.0026 0.2038 0.0000 0.0043 0.0367 0.0002 0.0003 0.0451 0.0019 0.0203 0.0027 0.0187 0.0011 17 20 21 0.0005 0.0001 0.0008 0.0019 0.0053 0.0000 0.0000 0.0033 0.0217 0.0087 0.0161 0.0210 0.0056 0.0097 0.0259 0.0025 0.0000 0.0014 0.0804 0.0005 0.0001 0.0010 0.0000 0.0000 0.0003 0.0001 0.0036 0.0035 0.0003 0.0005 0.0055 0.0017 0.0003 0.0311 0.0118 0.0003 0.0047 0.0439 0.0098 0.0002 0.0001 0.0028 0.0010 0.0043 0.0363 0.0002 0.0003 0.0681 0.0523 0.0907 0.0008 0.0001 0.0013 0.0019 0.0015 0.0007 0.0000 0.0036 0.0400 0.0131 0.0231 0.1206 0.0013 0.0102 0.0261 0.0026 0.0000 0.0001 0.0025 0.0004 0.0002 0.0016 0.0000 0.0000 0.0005 0.0010 0.0000 0.0007 0.0004 0.0189 0.0005 0.0002 19 23 0.0004 0.0003 0.0048 0.0716 0.0005 0.0000 0.0021 0.0060 0.0000 0.0000 0.0054 0.0357 0.0020 0.0075 0.0247 0.0005 0.0000 0.0001 0.0002 0.0004 0.0006 0.0051 0.0000 0.0000 0.1507 0.2014 0.0004 0.0002 0.0008 0.0223 0.0016 0.0009 0.0003 0.0228 0.0138 0.0011 0.0681 0.0534 0.0033 0.0481 0.0164 0.0946 0.0000 0.0011 0.0076 0.0002 0.0002 0.0016 0.0000 0.0000 0.0001 0.0007 0.0065 0.0627 0.0000 0.0001 22 Matrixofinput–outputtechnicalcoefficients(A)(continued) 0.0007 0.0023 0.0364 0.0156 0.0002 0.0022 TableC3 25 26 0.0002 0.1711 0.0029 0.1164 0.0002 0.0037 0.0024 0.0025 0.0001 0.0000 0.0331 0.0349 0.0036 0.0102 0.0062 0.0000 0.0000 0.0004 0.0007 0.0001 0.0010 0.0000 0.0000 0.0006 0.0006 0.0035 0.0741 0.0001 0.0000 0.0009 0.0076 0.0000 0.0028 0.0397 0.0008 0.0064 0.0116 0.0000 0.0006 0.0004 0.0002 0.0017 0.0000 0.0000 0.0973 0.1338 0.1030 0.0007 0.0011 0.0004 0.0164 0.0010 0.0000 0.0179 0.0029 0.0019 0.0001 0.0554 0.0615 0.0027 0.0156 0.0070 0.0007 0.0001 0.0038 0.0000 0.0013 0.0016 0.0132 0.0001 0.0001 0.0008 0.0002 0.0001 0.0164 0.0286 0.1084 0.0003 0.0000 0.0001 24 28 (1994) 0.0007 0.0013 0.0068 0.0175 0.0012 0.0116 0.0061 0.0056 0.0009 0.0003 0.0053 0.0201 0.0032 0.0267 0.0122 0.0026 0.0000 0.0034 0.0005 0.0062 0.0012 0.0097 0.0000 0.0001 0.1120 0.2260 0.0010 0.0002 0.0023 0.0146 0.0003 0.0007 0.0013 0.0050 0.0001 0.0001 0.0030 0.1074 0.0014 0.0020 0.0044 0.0011 0.0001 0.0001 0.0000 0.0005 0.0014 0.0115 0.0000 0.0001 0.0002 0.0009 0.0072 0.0052 0.0003 0.0011 27 248 ABS(various) Input–outputcoefficientsshowninthisTableiscalculatedfromanadaptedversionofinput–outputtable,fortheyear1994,publishedbytheAustralianBureauof Statistics,inaccordancewithsectoralclassificationinthisresearch; seeTableC1,pp.234237fordescriptionofsector1to28. 0.0278 0.0224 0.0043 0.0001 0.0003 0.0010 0.0000 0.0026 0.0019 0.0008 0.0005 0.0000 0.0012 0.0194 0.0001 0.0002 0.0053 0.0048 5 0.0954 0.0060 0.0069 (continuedonnextpage) 0.0836 0.0004 0.0025 0.0047 0.0002 0.0036 0.0000 0.0011 0.0004 0.0001 0.0018 0.0004 0.0002 0.0014 0.0103 0.0016 0.0000 0.0000 0.0000 28 0.0591 0.0256 0.0725 0.0006 0.0356 0.0003 0.0035 0.0001 0.0000 0.0000 0.0037 0.0001 0.0002 0.0003 0.0007 0.0003 0.0009 0.0190 0.0000 0.0000 0.0000 0.0012 0.0001 0.0000 0.0000 0.0001 0.0012 0.0522 0.0004 8 9 10 11 0.0001 0.0011 0.0000 0.0000 0.1910 0.0000 0.0003 0.0000 0.0000 0.0014 0.0120 0.0001 0.0001 4 4 5 6 7 3 2 1 0.0052 0.5012 0.0150 2 0.0042 0.0633 0.0019 3 0.0001 0.0007 0.0054 1 Sources: Notes: 0.0004 0.0013 0.0122 0.0005 0.0031 0.0001 0.0045 0.0350 0.0000 0.0003 0.0035 0.0084 0.0569 0.0000 0.0017 0.0101 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 0.0095 0.0001 0.0019 0.0042 0.0001 0.0077 0.0009 0.0016 0.0006 0.0000 0.0009 0.0226 0.0002 0.0013 0.0055 0.0039 0.0000 0.0001 0.3264 7 8 0.0045 0.0000 0.0017 0.0174 0.0001 0.0071 0.0016 0.0017 0.0008 0.0000 0.0013 0.0310 0.0001 0.0012 0.0075 0.0054 0.0000 0.0001 0.1270 0.0060 0.0001 0.0024 0.0182 0.0000 0.0097 0.0005 0.0018 0.0002 0.0000 0.0003 0.0068 0.0002 0.0017 0.0016 0.0012 0.5107 0.0000 0.0001 0.0776 0.0615 0.0136 0.0024 0.0001 0.0010 0.0015 0.0001 0.0039 0.0015 0.0071 0.0011 0.0000 0.0016 0.0391 0.0001 0.0007 0.0094 0.0068 0.0000 0.0001 0.1305 0.1819 0.0031 0.0747 0.0748 6 9 10 0.0057 0.0121 0.0052 0.0127 0.0001 0.0011 0.0110 0.0249 0.0070 0.0012 0.0122 0.0639 0.0005 0.0027 0.0229 0.0027 0.0001 0.0004 0.0819 0.0009 0.0019 0.0167 0.0001 0.0002 0.1378 0.1584 0.0044 0.0002 0.0030 0.0271 0.0017 0.0049 0.0080 0.0287 0.0001 0.0005 0.0055 0.0336 0.0019 0.0049 0.0645 0.0015 0.0000 0.1216 0.0006 0.0368 0.0007 0.0060 0.0000 0.0001 0.1073 0.0063 0.0001 0.0025 0.0121 0.0005 0.0022 0.0000 0.0513 0.0000 0.0001 0.0211 0.0018 0.0024 0.0203 0.0253 0.0067 0.0000 0.2648 0.0041 0.1103 0.0007 0.0067 0.0000 0.0001 0.0023 0.0015 0.0019 11 13 0.0021 0.0001 0.0057 0.0227 0.0006 0.0012 0.0003 0.0222 0.0089 0.0032 0.0122 0.0092 0.0087 0.1917 0.0459 0.0025 0.0000 0.0149 0.0001 0.0003 0.0009 0.0078 0.0000 0.0001 0.0922 0.1248 0.0039 0.0001 0.0046 0.0035 0.0005 0.0015 0.0000 0.0110 0.0004 0.0005 0.0010 0.0014 0.2467 0.0064 0.0176 0.0001 0.0000 0.0728 0.0000 0.0118 0.0005 0.0042 0.0000 0.0001 0.0011 0.0024 0.0003 0.0023 0.0005 0.0014 12 15 0.0166 0.0002 0.0015 0.0073 0.0013 0.0012 0.0001 0.1010 0.0073 0.0019 0.0134 0.0049 0.0014 0.0126 0.0148 0.1262 0.0001 0.0998 0.0001 0.0016 0.0142 0.0001 0.0002 0.1165 0.0685 0.0051 0.0002 0.0033 0.0126 0.0018 0.0018 0.0000 0.0116 0.0005 0.0024 0.0047 0.0051 0.0061 0.0139 0.2284 0.0019 0.0000 0.0062 0.0034 0.0076 0.0010 0.0089 0.0000 0.0001 0.0039 0.0192 0.0085 0.0069 0.0016 0.0184 14 0.0946 0.0223 0.0248 0.0011 0.0049 0.0006 0.0019 0.0000 0.0159 0.2198 0.0135 0.0064 0.0060 0.0010 0.0022 0.0142 0.0121 0.0001 0.0000 0.0688 0.0000 0.0019 0.0165 0.0001 0.0002 0.0229 0.0070 0.0032 16 18 0.0017 0.0022 0.0031 0.0127 0.0003 0.0010 0.0044 0.0121 0.1701 0.0557 0.1295 0.0131 0.0037 0.0118 0.0193 0.0111 0.0000 0.0000 0.0037 0.0001 0.0006 0.0057 0.0000 0.0001 0.0730 0.0853 0.0313 0.0038 0.0016 0.0029 0.0020 0.0012 0.0000 0.0123 0.0076 0.1954 0.0035 0.0075 0.0004 0.0024 0.0149 0.0086 0.0002 0.0004 0.2503 0.0000 0.0057 0.0505 0.0002 0.0007 0.0219 0.0008 0.0083 0.0014 0.0099 0.0005 17 20 21 0.0012 0.0000 0.0014 0.0038 0.0045 0.0005 0.0000 0.0039 0.0223 0.0092 0.0154 0.0204 0.0112 0.0109 0.0605 0.0012 0.0000 0.0062 0.0490 0.0001 0.0003 0.0025 0.0000 0.0000 0.0001 0.0000 0.0057 0.0041 0.0002 0.0006 0.0057 0.0028 0.0005 0.0391 0.0172 0.0004 0.0058 0.0568 0.0165 0.0001 0.0002 0.0074 0.0013 0.0015 0.0130 0.0000 0.0002 0.0822 0.0657 0.1281 0.0009 0.0000 0.0020 0.0020 0.0001 0.0006 0.0000 0.0032 0.0420 0.0141 0.0149 0.1337 0.0007 0.0054 0.0194 0.0029 0.0000 0.0001 0.0009 0.0001 0.0004 0.0040 0.0000 0.0001 0.0004 0.0009 0.0001 0.0003 0.0006 0.0113 0.0002 0.0007 19 23 0.0004 0.0001 0.0018 0.0455 0.0004 0.0000 0.0017 0.1285 0.0000 0.0000 0.0066 0.0553 0.0010 0.0051 0.0223 0.0004 0.0000 0.0001 0.0001 0.0004 0.0003 0.0029 0.0000 0.0000 0.1543 0.2393 0.0002 0.0000 0.0007 0.0188 0.0013 0.0007 0.0005 0.0184 0.0180 0.0015 0.0705 0.0681 0.0027 0.0573 0.0156 0.0954 0.0000 0.0011 0.0133 0.0002 0.0001 0.0013 0.0000 0.0000 0.0001 0.0009 0.0034 0.0318 0.0000 0.0000 22 Matrixofinput–outputtechnicalcoefficients(A)(continued) 0.0011 0.0016 0.0234 0.0318 0.0004 0.0008 TableC3 25 26 0.0001 0.1495 0.0023 0.1298 0.0001 0.0019 0.0010 0.0016 0.0001 0.0000 0.0132 0.0387 0.0008 0.0073 0.0038 0.0000 0.0000 0.0001 0.0005 0.0001 0.0005 0.0000 0.0000 0.0004 0.0002 0.0724 0.1130 0.0001 0.0000 0.0006 0.0050 0.0000 0.0019 0.0603 0.0005 0.0058 0.0066 0.0000 0.0000 0.0007 0.0002 0.0014 0.0000 0.0000 0.1974 0.0957 0.1337 0.0012 0.0011 0.0005 0.0181 0.0009 0.0000 0.0228 0.0024 0.0036 0.0000 0.0590 0.0787 0.0028 0.0181 0.0080 0.0004 0.0002 0.0030 0.0000 0.0013 0.0035 0.0309 0.0001 0.0004 0.0015 0.0002 0.0001 0.0097 0.0137 0.0944 0.0005 0.0000 0.0001 24 28 (1995) 0.0023 0.0009 0.0093 0.0226 0.0015 0.0042 0.0065 0.0083 0.0009 0.0002 0.0046 0.0187 0.0031 0.0269 0.0106 0.0022 0.0000 0.0041 0.0007 0.0147 0.0007 0.0059 0.0000 0.0001 0.1398 0.2653 0.0037 0.0000 0.0022 0.0226 0.0005 0.0003 0.0021 0.0093 0.0001 0.0001 0.0030 0.0927 0.0012 0.0027 0.0048 0.0007 0.0001 0.0002 0.0000 0.0005 0.0013 0.0112 0.0000 0.0001 0.0002 0.0011 0.0054 0.0030 0.0002 0.0007 27 249 ABS(various) Input–outputcoefficientsshowninthisTableiscalculatedfromanadaptedversionofinput–outputtable,fortheyear1995,publishedbytheAustralianBureauof Statistics,inaccordancewithsectoralclassificationinthisresearch; seeTableC1,pp.234237fordescriptionofsector1to28. 0.0629 0.0450 0.0030 0.0000 0.0013 0.0014 0.0001 0.0052 0.0018 0.0005 0.0009 0.0000 0.0013 0.0317 0.0001 0.0009 0.0076 0.0055 5 0.1354 0.0043 0.0061 (continuedonnextpage) 0.0061 0.0001 0.0047 0.0252 0.0003 0.0034 0.0000 0.0009 0.0007 0.0002 0.0070 0.0007 0.0001 0.0027 0.0224 0.0003 0.0000 0.0000 0.0001 28 0.0877 0.0368 0.2663 0.0016 0.0127 0.0019 0.0048 0.0002 0.0014 0.0000 0.0065 0.0001 0.0003 0.0009 0.0003 0.0016 0.0206 0.0000 0.0000 0.0000 0.0017 0.0001 0.0000 0.0001 0.0000 0.0003 0.0262 0.0002 8 9 10 11 0.0004 0.0035 0.0000 0.0000 0.2133 0.0005 0.0047 0.0000 0.0001 0.0011 0.0099 0.0000 0.0001 4 4 5 6 7 3 2 1 0.0097 0.5823 0.0125 2 0.0117 0.0603 0.0019 3 0.0001 0.0012 0.0066 1 Sources: Notes: 0.0009 0.0023 0.0167 0.0006 0.0034 0.0000 0.0077 0.0383 0.0001 0.0004 0.0047 0.0096 0.0191 0.0005 0.0023 0.0111 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 0.0075 0.0006 0.0024 0.0066 0.0002 0.0058 0.0009 0.0021 0.0006 0.0000 0.0026 0.0204 0.0004 0.0017 0.0076 0.0058 0.0000 0.0001 0.3295 7 8 0.0028 0.0003 0.0018 0.0289 0.0002 0.0043 0.0015 0.0018 0.0007 0.0000 0.0031 0.0241 0.0003 0.0013 0.0090 0.0069 0.0000 0.0001 0.1138 0.0041 0.0004 0.0027 0.0327 0.0000 0.0064 0.0005 0.0021 0.0002 0.0000 0.0007 0.0058 0.0005 0.0019 0.0022 0.0017 0.4297 0.0001 0.0001 0.1259 0.0868 0.0209 0.0016 0.0009 0.0010 0.0022 0.0003 0.0025 0.0016 0.0085 0.0011 0.0000 0.0045 0.0349 0.0002 0.0007 0.0130 0.0100 0.0000 0.0000 0.1009 0.1969 0.0027 0.1884 0.2064 6 9 10 0.0025 0.0057 0.0067 0.0145 0.0002 0.0010 0.0101 0.0189 0.0099 0.0006 0.0169 0.0585 0.0010 0.0044 0.0256 0.0027 0.0001 0.0004 0.1029 0.0007 0.0018 0.0161 0.0000 0.0002 0.1178 0.1576 0.0033 0.0003 0.0024 0.0230 0.0016 0.0038 0.0053 0.0251 0.0000 0.0000 0.0052 0.0210 0.0025 0.0056 0.0660 0.0011 0.0000 0.1183 0.0005 0.0409 0.0005 0.0045 0.0000 0.0001 0.1291 0.0052 0.0007 0.0030 0.0176 0.0007 0.0030 0.0000 0.0502 0.0000 0.0002 0.0198 0.0033 0.0029 0.0215 0.0329 0.0056 0.0001 0.2341 0.0026 0.0999 0.0011 0.0100 0.0000 0.0001 0.0025 0.0016 0.0019 11 13 0.0013 0.0006 0.0076 0.0267 0.0010 0.0012 0.0002 0.0207 0.0086 0.0027 0.0110 0.0090 0.0077 0.1754 0.0540 0.0023 0.0000 0.0123 0.0002 0.0002 0.0009 0.0076 0.0000 0.0001 0.1107 0.1427 0.0044 0.0007 0.0078 0.0053 0.0056 0.0020 0.0000 0.0110 0.0004 0.0005 0.0021 0.0019 0.1926 0.0093 0.0167 0.0002 0.0000 0.0698 0.0000 0.0096 0.0007 0.0058 0.0000 0.0001 0.0020 0.0017 0.0004 0.0023 0.0006 0.0010 12 15 0.0153 0.0011 0.0020 0.0094 0.0021 0.0013 0.0001 0.1070 0.0059 0.0014 0.0174 0.0061 0.0014 0.0113 0.0198 0.1269 0.0001 0.0894 0.0001 0.0019 0.0168 0.0000 0.0002 0.1225 0.0792 0.0046 0.0004 0.0034 0.0143 0.0026 0.0017 0.0000 0.0106 0.0003 0.0031 0.0054 0.0045 0.0053 0.0136 0.2237 0.0016 0.0000 0.0043 0.0025 0.0056 0.0010 0.0086 0.0000 0.0001 0.0088 0.0188 0.0057 0.0054 0.0011 0.0163 14 0.0988 0.0199 0.0023 0.0018 0.0086 0.0039 0.0028 0.0000 0.0201 0.1939 0.0249 0.0084 0.0082 0.0027 0.0041 0.0198 0.0121 0.0001 0.0000 0.0794 0.0000 0.0028 0.0249 0.0001 0.0003 0.0309 0.0145 0.0036 16 18 0.0017 0.0011 0.0039 0.0168 0.0004 0.0013 0.0035 0.0135 0.1506 0.0503 0.0977 0.0151 0.0073 0.0145 0.0250 0.0113 0.0000 0.0001 0.0033 0.0001 0.0008 0.0070 0.0000 0.0001 0.0613 0.1179 0.0208 0.0056 0.0017 0.0033 0.0147 0.0011 0.0000 0.0105 0.0034 0.2317 0.0020 0.0063 0.0015 0.0024 0.0166 0.0063 0.0003 0.0003 0.2499 0.0000 0.0054 0.0475 0.0001 0.0006 0.0155 0.0008 0.0078 0.0024 0.0070 0.0005 17 20 21 0.0007 0.0007 0.0014 0.0043 0.0074 0.0005 0.0000 0.0032 0.0157 0.0075 0.0149 0.0168 0.0090 0.0114 0.0350 0.0007 0.0000 0.0058 0.0253 0.0001 0.0003 0.0023 0.0000 0.0000 0.0001 0.0000 0.0054 0.0042 0.0002 0.0688 0.0005 0.0042 0.0022 0.0001 0.0298 0.0160 0.0006 0.0054 0.0601 0.0106 0.0001 0.0003 0.0057 0.0009 0.0026 0.0233 0.0001 0.0003 0.0706 0.0533 0.1616 0.0010 0.0002 0.0032 0.0031 0.0003 0.0008 0.0000 0.0039 0.0449 0.0109 0.0186 0.1406 0.0013 0.0069 0.0212 0.0031 0.0000 0.0001 0.0012 0.0001 0.0006 0.0052 0.0000 0.0001 0.0004 0.0005 0.0002 0.0004 0.0004 0.0106 0.0002 0.0005 19 23 0.0002 0.0001 0.0016 0.0598 0.0003 0.0000 0.0010 0.1085 0.0000 0.0000 0.0090 0.0369 0.0016 0.0055 0.0205 0.0005 0.0000 0.0001 0.0003 0.0002 0.0003 0.0025 0.0000 0.0000 0.1607 0.2319 0.0002 0.0001 0.0008 0.0159 0.0015 0.0006 0.0003 0.0159 0.0181 0.0006 0.0647 0.0685 0.0027 0.0477 0.0160 0.0863 0.0000 0.0020 0.0115 0.0002 0.0002 0.0015 0.0000 0.0000 0.0001 0.0007 0.0048 0.0313 0.0000 0.0000 22 Matrixofinput–outputtechnicalcoefficients(A)(continued) 0.0007 0.0021 0.0197 0.0316 0.0002 0.0006 TableC3 25 26 0.0001 0.2017 0.0027 0.1347 0.0001 0.0020 0.0009 0.0012 0.0001 0.0000 0.0281 0.0274 0.0019 0.0062 0.0041 0.0000 0.0000 0.0005 0.0004 0.0001 0.0006 0.0000 0.0000 0.0006 0.0003 0.0634 0.0870 0.0001 0.0000 0.0005 0.0065 0.0000 0.0032 0.0592 0.0007 0.0048 0.0054 0.0000 0.0000 0.0004 0.0002 0.0014 0.0000 0.0000 0.1904 0.0893 0.1484 0.0009 0.0001 0.0004 0.0100 0.0004 0.0000 0.0193 0.0051 0.0034 0.0001 0.0664 0.0906 0.0062 0.0148 0.0071 0.0001 0.0002 0.0022 0.0000 0.0009 0.0030 0.0266 0.0001 0.0003 0.0010 0.0003 0.0001 0.0087 0.0157 0.1172 0.0003 0.0000 0.0001 24 28 (1997) 0.0013 0.0004 0.0091 0.0268 0.0014 0.0037 0.0050 0.0071 0.0006 0.0001 0.0043 0.0168 0.0037 0.0258 0.0095 0.0015 0.0000 0.0033 0.0005 0.0100 0.0006 0.0056 0.0000 0.0001 0.1612 0.2554 0.0010 0.0001 0.0021 0.0294 0.0009 0.0004 0.0015 0.0079 0.0001 0.0000 0.0044 0.0772 0.0021 0.0044 0.0043 0.0010 0.0001 0.0003 0.0000 0.0003 0.0012 0.0108 0.0000 0.0001 0.0002 0.0009 0.0050 0.0033 0.0001 0.0005 27 250 ABS(various) Input–outputcoefficientsshowninthisTableiscalculatedfromanadaptedversionofinput–outputtable,fortheyear1997,publishedbytheAustralianBureauof Statistics,inaccordancewithsectoralclassificationinthisresearch; seeTableC1,pp.234237fordescriptionofsector1to28. 0.1011 0.0734 0.0024 0.0002 0.0017 0.0023 0.0002 0.0040 0.0019 0.0007 0.0009 0.0000 0.0036 0.0281 0.0003 0.0011 0.0105 0.0080 5 0.1301 0.0045 0.0105 (continuedonnextpage) 0.0197 0.0008 0.0040 0.0234 0.0001 0.0072 0.0000 0.0012 0.0006 0.0000 0.0040 0.0005 0.0002 0.0022 0.0183 0.0001 0.0000 0.0000 0.0001 28 0.0805 0.0245 0.2407 0.0015 0.0148 0.0023 0.0060 0.0002 0.0016 0.0000 0.0066 0.0000 0.0006 0.0008 0.0004 0.0020 0.0293 0.0000 0.0000 0.0000 0.0012 0.0001 0.0000 0.0001 0.0001 0.0003 0.0433 0.0002 8 9 10 11 0.0002 0.0021 0.0000 0.0000 0.2123 0.0006 0.0054 0.0000 0.0001 0.0014 0.0121 0.0000 0.0002 4 4 5 6 7 3 2 1 0.0164 0.6226 0.0505 2 0.0138 0.0361 0.0019 3 0.0001 0.0011 0.0241 1 Sources: Notes: 0.0005 0.0023 0.0142 0.0006 0.0038 0.0000 0.0084 0.0358 0.0000 0.0003 0.0119 0.0066 0.0441 0.0004 0.0020 0.0201 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 0.0211 0.0009 0.0053 0.0603 0.0003 0.0089 0.0015 0.0012 0.0071 0.0009 0.0021 0.0036 0.0279 0.0003 0.0001 0.0076 0.0005 0.0022 0.0166 0.0001 0.0048 0.0012 0.0023 0.0007 0.0026 0.0179 0.0003 0.0019 0.0066 0.0056 0.1101 0.0754 0.0024 0.0001 0.0015 0.0059 0.0002 0.0032 0.0027 0.0008 0.0010 0.0038 0.0261 0.0002 0.0013 0.0097 0.0082 0.0000 0.0001 0.3067 0.1704 0.0050 0.0159 5 7 8 0.0023 0.0002 0.0013 0.0563 0.0001 0.0029 0.0020 0.0017 0.0008 0.0031 0.0209 0.0002 0.0011 0.0077 0.0066 0.0000 0.0001 0.0989 0.0046 0.0004 0.0027 0.0898 0.0001 0.0060 0.0010 0.0025 0.0003 0.0012 0.0079 0.0004 0.0023 0.0029 0.0025 0.1293 0.0001 0.0001 0.1181 0.0880 0.0332 0.0019 0.0006 0.0011 0.0062 0.0002 0.0024 0.0019 0.0085 0.0011 0.0041 0.0280 0.0002 0.0010 0.0104 0.0088 0.0000 0.0000 0.1048 0.2652 0.0024 0.2405 0.3723 6 9 10 0.0024 0.0033 0.0049 0.0220 0.0001 0.0009 0.0375 0.0113 0.0079 0.0006 0.0153 0.0489 0.0005 0.0037 0.0239 0.0026 0.0004 0.0006 0.0988 0.0009 0.0019 0.0194 0.0001 0.0002 0.1055 0.1401 0.0029 0.0002 0.0020 0.0431 0.0003 0.0107 0.0060 0.0216 0.0001 0.0051 0.0220 0.0034 0.0049 0.0676 0.0011 0.0001 0.1105 0.0004 0.0431 0.0004 0.0042 0.0000 0.0001 0.1175 0.0040 0.0003 0.0022 0.0274 0.0003 0.0024 0.0333 0.0002 0.0177 0.0031 0.0044 0.0241 0.0299 0.0049 0.0002 0.2252 0.0025 0.1230 0.0010 0.0104 0.0000 0.0001 0.0022 0.0012 0.0032 11 13 0.0013 0.0005 0.0059 0.0453 0.0002 0.0010 0.0004 0.0143 0.0088 0.0029 0.0101 0.0051 0.0079 0.1593 0.0618 0.0020 0.0002 0.0146 0.0002 0.0003 0.0008 0.0084 0.0000 0.0001 0.0827 0.1325 0.0046 0.0004 0.0052 0.0075 0.0025 0.0017 0.0095 0.0004 0.0005 0.0018 0.0016 0.1946 0.0069 0.0176 0.0002 0.0001 0.0598 0.0103 0.0006 0.0060 0.0000 0.0001 0.0023 0.0019 0.0003 0.0017 0.0010 0.0019 12 15 0.0131 0.0007 0.0018 0.0157 0.0002 0.0011 0.0582 0.0074 0.0012 0.0180 0.0081 0.0038 0.0120 0.0193 0.1424 0.0004 0.0660 0.0001 0.0018 0.0178 0.0000 0.0002 0.1221 0.0857 0.0032 0.0002 0.0027 0.0211 0.0004 0.0012 0.0069 0.0002 0.0027 0.0050 0.0032 0.0040 0.0119 0.1988 0.0013 0.0002 0.0050 0.0037 0.0062 0.0007 0.0074 0.0000 0.0001 0.0054 0.0241 0.0042 0.0053 0.0016 0.0302 14 0.1083 0.0143 0.0025 0.0015 0.0130 0.0019 0.0022 0.0136 0.2168 0.0257 0.0078 0.0086 0.0025 0.0041 0.0198 0.0121 0.0005 0.0678 0.0025 0.0257 0.0001 0.0003 0.0324 0.0139 0.0063 16 18 0.0013 0.0009 0.0033 0.0246 0.0002 0.0009 0.0035 0.0096 0.1396 0.0547 0.0979 0.0095 0.0048 0.0142 0.0222 0.0125 0.0001 0.0023 0.0001 0.0007 0.0068 0.0000 0.0001 0.0559 0.1258 0.0161 0.0055 0.0011 0.0044 0.0055 0.0006 0.0064 0.0032 0.1729 0.0014 0.0062 0.0006 0.0016 0.0134 0.0052 0.0008 0.0003 0.3380 0.0038 0.0385 0.0001 0.0005 0.0103 0.0008 0.0052 0.0018 0.0096 0.0008 17 20 21 0.0005 0.0003 0.0005 0.0044 0.0013 0.0003 0.0015 0.0077 0.0041 0.0064 0.0098 0.0049 0.0057 0.0263 0.0003 0.0000 0.0015 0.0528 0.0001 0.0014 0.0000 0.0000 0.0047 0.0075 0.0002 0.0534 0.0006 0.0024 0.0024 0.0002 0.0269 0.0168 0.0006 0.0053 0.0569 0.0096 0.0005 0.0003 0.0045 0.0011 0.0023 0.0233 0.0001 0.0003 0.0701 0.0544 0.1602 0.0009 0.0001 0.0024 0.0095 0.0001 0.0006 0.0029 0.0360 0.0097 0.0151 0.1299 0.0010 0.0046 0.0194 0.0027 0.0001 0.0000 0.0025 0.0001 0.0005 0.0046 0.0000 0.0001 0.0003 0.0003 0.0002 0.0003 0.0003 0.0071 0.0004 0.0005 19 23 0.0001 0.0001 0.0012 0.1171 0.0002 0.0010 0.0680 0.0000 0.0060 0.0258 0.0019 0.0046 0.0169 0.0004 0.0000 0.0000 0.0000 0.0002 0.0002 0.0023 0.0000 0.0000 0.1780 0.2304 0.0003 0.0000 0.0007 0.0277 0.0012 0.0005 0.0004 0.0093 0.0142 0.0007 0.0669 0.0538 0.0015 0.0456 0.0158 0.0846 0.0000 0.0019 0.0069 0.0002 0.0001 0.0014 0.0000 0.0000 0.0001 0.0002 0.0044 0.0184 0.0000 0.0000 22 Matrixofinput–outputtechnicalcoefficients(A)(continued) 0.0003 0.0024 0.0130 0.0211 0.0003 0.0011 TableC3 25 26 0.2444 0.0022 0.2372 0.0016 0.0009 0.0009 0.0201 0.0470 0.0025 0.0047 0.0044 0.0000 0.0001 0.0006 0.0000 0.0000 0.0004 0.0002 0.0319 0.0894 0.0001 0.0003 0.0054 0.0013 0.0448 0.0019 0.0024 0.0028 0.0000 0.0003 0.0001 0.0007 0.0000 0.0000 0.1864 0.1006 0.0998 0.0008 0.0001 0.0004 0.0123 0.0008 0.0663 0.0042 0.0027 0.0001 0.0542 0.0751 0.0034 0.0114 0.0060 0.0005 0.0022 0.0010 0.0023 0.0235 0.0001 0.0003 0.0005 0.0003 0.0001 0.0051 0.0103 0.0584 0.0004 0.0001 24 28 (1999) 0.0010 0.0003 0.0077 0.0353 0.0014 0.0025 0.0056 0.0054 0.0005 0.0001 0.0042 0.0182 0.0028 0.0233 0.0101 0.0013 0.0001 0.0041 0.0003 0.0152 0.0006 0.0059 0.0000 0.0001 0.1964 0.2633 0.0013 0.0001 0.0025 0.0714 0.0003 0.0006 0.0032 0.0081 0.0001 0.0000 0.0047 0.0991 0.0014 0.0055 0.0068 0.0026 0.0003 0.0004 0.0000 0.0007 0.0015 0.0156 0.0000 0.0002 0.0003 0.0008 0.0052 0.0026 0.0004 0.0008 27 251 ABS(various) Input–outputcoefficientsshowninthisTableiscalculatedfromanadaptedversionofinput–outputtable,fortheyear1999,publishedbytheAustralianBureauof Statistics,inaccordancewithsectoralclassificationinthisresearch; seeTableC1,pp.234237fordescriptionofsector1to28. 28 0.0649 0.0386 0.3043 0.0014 0.0171 0.0027 0.0105 0.0017 0.0059 0.0006 0.0013 0.0007 0.0023 0.0424 0.0002 0.0011 0.0001 0.0000 0.0001 0.0003 0.0004 0.0390 0.0004 8 9 10 11 0.0003 0.0034 0.0000 0.0000 0.2154 0.0007 0.0073 0.0000 0.0001 0.0012 0.0124 0.0000 0.0001 4 4 5 6 7 3 2 1 0.0249 0.5914 0.0895 2 0.0099 0.0458 0.0021 3 0.0002 0.0024 0.0645 1 Sources: Notes: 0.0016 0.0035 0.0194 0.0010 0.0070 0.0004 0.0085 0.0447 0.0003 0.0205 0.0057 0.0306 0.0013 0.0014 0.0217 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 0.0004 0.0018 0.0022 0.0283 0.0007 0.0015 0.0617 0.0007 0.0011 0.0011 0.0098 0.0047 0.0022 0.0025 0.0185 0.0007 0.0001 0.0004 0.0262 0.0034 0.0037 0.0224 0.0004 0.0034 0.0725 0.0112 0.0026 0.0005 0.0068 0.0682 0.0014 0.0055 0.0186 0.0120 0.0508 0.1956 0.0014 0.0002 0.0004 0.0015 0.0001 0.0004 0.0283 0.0006 0.0007 0.0001 0.0018 0.0177 0.0002 0.0006 0.0048 0.0031 0.0002 0.0002 0.2510 0.2708 0.0102 0.0087 5 7 8 0.0056 0.0012 0.0016 0.0543 0.0003 0.0015 0.0735 0.0070 0.0019 0.0003 0.0049 0.0495 0.0006 0.0023 0.0135 0.0087 0.0001 0.0001 0.1074 0.0034 0.0006 0.0010 0.0258 0.0000 0.0009 0.0127 0.0026 0.0002 0.0000 0.0006 0.0064 0.0004 0.0014 0.0017 0.0011 0.0663 0.0001 0.0001 0.0475 0.1419 0.0183 0.0010 0.0006 0.0003 0.0013 0.0001 0.0003 0.0175 0.0056 0.0006 0.0001 0.0016 0.0165 0.0001 0.0004 0.0045 0.0029 0.0000 0.0000 0.0194 0.4056 0.1649 0.1213 0.0558 6 9 10 0.0024 0.0074 0.0035 0.0175 0.0019 0.0223 0.0094 0.0106 0.0010 0.0114 0.0358 0.0012 0.0048 0.0220 0.0020 0.0005 0.0007 0.1423 0.0008 0.0012 0.0131 0.0000 0.0003 0.1190 0.1590 0.0013 0.0004 0.0013 0.0227 0.0003 0.0078 0.0065 0.0210 0.0002 0.0006 0.0041 0.0221 0.0024 0.0052 0.0843 0.0008 0.0001 0.1958 0.0002 0.0371 0.0003 0.0029 0.0000 0.0001 0.1466 0.0026 0.0015 0.0017 0.0262 0.0002 0.0023 0.0021 0.0355 0.0001 0.0004 0.0113 0.0052 0.0035 0.0302 0.0282 0.0070 0.0003 0.2861 0.0027 0.1172 0.0007 0.0076 0.0000 0.0001 0.0049 0.0021 0.0024 11 13 0.0018 0.0014 0.0042 0.0375 0.0002 0.0014 0.0015 0.0195 0.0130 0.0051 0.0125 0.0103 0.0107 0.1902 0.0729 0.0039 0.0003 0.0214 0.0005 0.0008 0.0007 0.0076 0.0000 0.0001 0.1179 0.1773 0.0030 0.0015 0.0037 0.0168 0.0008 0.0027 0.0005 0.0082 0.0007 0.0018 0.0023 0.0033 0.1521 0.0080 0.0289 0.0008 0.0002 0.0894 0.0066 0.0004 0.0049 0.0000 0.0001 0.0035 0.0041 0.0007 0.0031 0.0015 0.0021 12 15 0.0180 0.0021 0.0010 0.0151 0.0025 0.0012 0.0028 0.0522 0.0173 0.0032 0.0085 0.0138 0.0029 0.0125 0.0307 0.1469 0.0005 0.0542 0.0001 0.0012 0.0131 0.0000 0.0003 0.1458 0.1136 0.0040 0.0010 0.0020 0.0234 0.0009 0.0020 0.0025 0.0097 0.0005 0.0047 0.0128 0.0066 0.0052 0.0165 0.2098 0.0043 0.0006 0.0083 0.0029 0.0068 0.0012 0.0136 0.0000 0.0003 0.0082 0.0498 0.0099 0.0076 0.0020 0.0286 14 0.1686 0.0215 0.0029 0.0012 0.0137 0.0008 0.0031 0.0020 0.0294 0.1991 0.0342 0.0084 0.0079 0.0029 0.0096 0.0141 0.0089 0.0010 0.0819 0.0001 0.0021 0.0233 0.0001 0.0005 0.0317 0.0091 0.0065 16 18 0.0031 0.0021 0.0024 0.0248 0.0001 0.0006 0.0056 0.0123 0.1437 0.0500 0.0979 0.0121 0.0062 0.0146 0.0273 0.0120 0.0003 0.0033 0.0011 0.0006 0.0069 0.0000 0.0001 0.0605 0.1772 0.0167 0.0061 0.0006 0.0039 0.0014 0.0007 0.0013 0.0123 0.0087 0.2045 0.0029 0.0040 0.0007 0.0034 0.0086 0.0034 0.0011 0.0003 0.4579 0.0023 0.0257 0.0001 0.0005 0.0147 0.0019 0.0034 0.0025 0.0073 0.0010 17 20 21 0.0012 0.0019 0.0012 0.0098 0.0064 0.0005 0.0012 0.0059 0.0250 0.0152 0.0183 0.0549 0.0081 0.0205 0.0576 0.0024 0.0001 0.0128 0.0404 0.0043 0.0002 0.0025 0.0000 0.0000 0.0003 0.0035 0.0140 0.0006 0.0311 0.0379 0.0046 0.0038 0.0008 0.0336 0.0227 0.0011 0.0060 0.0614 0.0111 0.0009 0.0005 0.0013 0.0016 0.0019 0.0219 0.0001 0.0004 0.1146 0.0882 0.1900 0.0014 0.0004 0.0017 0.0082 0.0002 0.0006 0.0007 0.0046 0.0426 0.0111 0.0144 0.1575 0.0013 0.0094 0.0176 0.0051 0.0002 0.0001 0.0008 0.0007 0.0003 0.0038 0.0000 0.0001 0.0007 0.0021 0.0002 0.0005 0.0007 0.0165 0.0004 0.0012 19 23 0.0003 0.0003 0.0009 0.1385 0.0003 0.0056 0.0016 0.0346 0.0001 0.0003 0.0032 0.0358 0.0028 0.0061 0.0171 0.0005 0.0001 0.0002 0.0012 0.0002 0.0020 0.0000 0.0000 0.1860 0.2790 0.0007 0.0001 0.0009 0.0191 0.0019 0.0014 0.2910 0.0135 0.0170 0.0008 0.0453 0.0363 0.0053 0.0350 0.0255 0.0550 0.0001 0.0009 0.0023 0.0023 0.0002 0.0024 0.0000 0.0000 0.0000 0.0001 0.0045 0.0907 0.0000 22 Matrixofinput–outputtechnicalcoefficients(A)(continued) 0.0005 0.0021 0.0310 0.0509 0.0003 0.0008 TableC3 25 26 0.0003 0.1983 0.0015 0.2398 0.0006 0.0023 0.0038 0.0058 0.0915 0.0029 0.0078 0.0052 0.0000 0.0012 0.0000 0.0005 0.0000 0.0000 0.0004 0.0003 0.0206 0.0592 0.0001 0.0001 0.0006 0.0087 0.0003 0.0783 0.0014 0.0030 0.0506 0.0000 0.0011 0.0000 0.0004 0.0000 0.0000 0.2028 0.1254 0.0914 0.0009 0.0003 0.0005 0.0271 0.0011 0.0005 0.1005 0.0088 0.0045 0.0006 0.0338 0.0998 0.0045 0.0143 0.0074 0.0009 0.0030 0.0010 0.0019 0.0215 0.0001 0.0004 0.0009 0.0003 0.0001 0.0246 0.0677 0.1053 0.0005 0.0001 24 28 (2002) 0.0013 0.0009 0.0062 0.0352 0.0010 0.0032 0.0125 0.0053 0.0011 0.0003 0.0057 0.0225 0.0034 0.0277 0.0140 0.0019 0.0002 0.0044 0.0002 0.0222 0.0005 0.0055 0.0000 0.0001 0.3025 0.3492 0.0009 0.0001 0.0018 0.0555 0.0011 0.0035 0.0079 0.0055 0.0002 0.0003 0.0036 0.1260 0.0020 0.0059 0.0085 0.0030 0.0006 0.0005 0.0010 0.0012 0.0132 0.0000 0.0003 0.0007 0.0034 0.0107 0.0049 0.0004 0.0009 27 252 ABS(various) Input–outputcoefficientsshowninthisTableiscalculatedfromanadaptedversionofinput–outputtable,fortheyear2002,publishedbytheAustralianBureauof Statistics,inaccordancewithsectoralclassificationinthisresearch; seeTableC1,pp.234237fordescriptionofsector1to28. 28 0.0837 0.0812 0.3282 0.0010 0.0218 0.0008 0.0071 0.0010 0.0234 0.0042 0.0001 0.0051 0.0004 0.0010 0.0311 0.0001 0.0002 0.0001 0.0000 0.0000 0.0004 0.0005 0.0853 0.0003 8 9 10 11 0.0002 0.0022 0.0000 0.0000 0.0282 0.0003 0.0030 0.0000 0.0001 0.0009 0.0105 0.0000 0.0002 4 4 5 6 7 3 2 1 0.0069 0.6177 0.0011 2 0.0252 0.0610 0.0022 3 0.0001 0.0010 1 Sources: Notes: 0.0000 0.0000 0.0151 0.0269 27 0.0006 0.0000 28 0.0366 0.0036 6 0.0000 0.0000 0.0139 0.0167 0.0002 0.0002 0.0003 0.0004 0.0003 0.0004 0.2861 0.3385 0.0011 0.0014 0.0769 0.0909 0.0000 0.0000 0.0027 0.0032 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0016 0.0020 0.0000 0.0000 0.0006 0.0007 0.0000 0.0000 0.0000 0.0000 5 0.0000 0.0180 0.0002 0.0004 0.0004 0.3669 0.0015 0.0986 0.0000 0.0035 0.0000 0.0000 0.0000 0.0021 0.0001 0.0008 0.0000 0.0000 7 9 0.0000 0.0005 0.0104 0.0290 0.0001 0.0001 0.0002 0.0002 0.0002 0.0003 0.1960 0.1091 0.0009 0.0013 0.0527 0.0583 0.0000 0.0002 0.0019 0.0056 0.0000 0.0001 0.0000 0.0001 0.0000 0.0002 0.0012 0.0034 0.0000 0.0005 0.0004 0.0005 0.0000 0.0018 0.0000 0.0007 8 11 0.0004 0.0001 0.0290 0.0056 0.0001 0.0000 0.0001 0.0000 0.0002 0.0000 0.0937 0.0193 0.0011 0.0002 0.0510 0.0105 0.0001 0.0000 0.0040 0.0009 0.0000 0.0000 0.0000 0.0000 0.0001 0.0000 0.0036 0.0007 0.0004 0.0001 0.0003 0.0001 0.0019 0.0003 13 0.0000 0.0001 0.0025 0.0060 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0085 0.0205 0.0001 0.0002 0.0046 0.0111 0.0000 0.0000 0.0004 0.0009 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0003 0.0007 0.0000 0.0001 0.0000 0.0001 0.0002 0.0004 0.0001 0.0002 12 15 0.0001 0.0001 0.0058 0.0080 0.0000 0.0000 0.0000 0.0000 0.0000 0.0001 0.0199 0.0284 0.0002 0.0003 0.0107 0.0152 0.0000 0.0000 0.0009 0.0013 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0007 0.0010 0.0001 0.0001 0.0001 0.0001 0.0004 0.0005 0.0002 0.0002 14 17 0.0001 0.0003 0.0059 0.0116 0.0000 0.0001 0.0000 0.0001 0.0001 0.0002 0.0208 0.0489 0.0002 0.0006 0.0110 0.0253 0.0000 0.0001 0.0010 0.0028 0.0000 0.0000 0.0000 0.0000 0.0000 0.0001 0.0007 0.0013 0.0001 0.0002 0.0001 0.0003 0.0004 0.0011 0.0002 0.0003 16 19 0.0001 0.0001 0.0058 0.0034 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0188 0.0124 0.0002 0.0001 0.0100 0.0067 0.0000 0.0000 0.0008 0.0006 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0007 0.0004 0.0001 0.0001 0.0001 0.0001 0.0004 0.0002 0.0002 0.0001 18 21 22 0.0001 0.0000 0.0001 0.0058 0.0173 0.0054 0.0000 0.0001 0.0000 0.0000 0.0002 0.0000 0.0000 0.0001 0.0000 0.0176 0.1544 0.0197 0.0002 0.0008 0.0002 0.0094 0.0577 0.0101 0.0000 0.0000 0.0000 0.0006 0.0020 0.0009 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0008 0.0031 0.0007 0.0001 0.0001 0.0001 0.0001 0.0006 0.0001 0.0004 0.0005 0.0003 0.0002 0.0003 0.0002 20 Weightedmeancapitalcoefficientsmatrix(B) 0.0009 0.0002 10 TableC4 24 0.0001 0.0004 0.0075 0.0396 0.0000 0.0001 0.0001 0.0003 0.0001 0.0003 0.0567 0.2853 0.0004 0.0018 0.0186 0.0954 0.0000 0.0002 0.0012 0.0056 0.0000 0.0000 0.0000 0.0000 0.0000 0.0001 0.0015 0.0079 0.0001 0.0003 0.0003 0.0013 0.0003 0.0013 0.0004 0.0018 23 26 0.0001 0.0002 0.0083 0.0164 0.0000 0.0001 0.0001 0.0001 0.0000 0.0001 0.0537 0.1316 0.0004 0.0008 0.0182 0.0429 0.0000 0.0001 0.0010 0.0028 0.0000 0.0000 0.0000 0.0000 0.0000 0.0001 0.0016 0.0034 0.0001 0.0002 0.0002 0.0006 0.0003 0.0006 0.0003 0.0009 25 27 28 0.0001 0.0003 0.0114 0.0181 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.1056 0.0782 0.0006 0.0008 0.0334 0.0368 0.0001 0.0001 0.0024 0.0031 0.0000 0.0000 0.0000 0.0000 0.0001 0.0001 0.0024 0.0027 0.0001 0.0002 0.0005 0.0004 0.0004 0.0010 0.0008 0.0006 253 (19801999) ABS(various) CapitalcoefficientsshowninthisTableareaweightedaverageofcapitalcoefficientsforvariousinput–outputtables,publishedbytheAustralianBureauof Statistics,inaccordancewithsectoralclassificationinthisresearch; seeTableC1,pp.234237fordescriptionofsector1to28. 0.0001 0.0006 0.0001 0.0003 0.0002 0.0006 24 0.0004 0.0000 25 0.0002 0.0000 26 0.0002 0.0000 0.1553 0.5569 0.0007 0.0022 22 0.1355 0.0114 23 0.0016 0.0001 21 0.0022 0.0053 0.0594 0.1496 0.0000 0.0000 18 0.0069 0.0004 0.0000 0.0000 0.0000 0.0000 16 0.0001 0.0000 17 0.0001 0.0000 19 0.0727 0.0063 20 0.0002 0.0000 0.0027 0.0032 0.0001 0.0001 0.0000 0.0000 13 0.0043 0.0005 14 0.0006 0.0000 0.0006 0.0012 11 12 0.0006 0.0000 15 0.0002 0.0000 0.0004 0.0000 0.0002 0.0001 4 8 9 0.0009 0.0001 7 3 10 0.0026 0.0002 2 3 4 1 5 6 2 1 Sources: Notes: 2 1 0.0062 2 0.0039 1 Energy 2 1 0.0052 0.0060 0.0019 0.0153 0.0134 0.0001 3 0.0022 0.0174 0.0150 0.0001 3 0.0192 0.0160 0.0030 0.0002 3 0.0038 0.0227 0.0183 0.0006 3 0.0045 0.0268 0.0217 0.0006 3 4 4 4 4 4 (continuedonnextpage) 0.0004 0.0048 Petroleum Energy 0.0008 0.0013 0.0029 BrownCoal 0.0001 NaturalGas BlackCoal 0.0049 0.0057 0.0003 0.0038 0.0008 0.0012 0.0022 BrownCoal NaturalGas Petroleum Energy 0.0001 BlackCoal 0.0009 0.0053 0.0017 0.0019 0.0003 BrownCoal 0.0001 NaturalGas Petroleum BlackCoal 0.0058 0.0064 0.0003 0.0042 Petroleum Energy 0.0006 0.0020 0.0018 BrownCoal 0.0001 NaturalGas BlackCoal 2 1 0.0004 0.0066 0.0070 0.0026 0.0022 0.0005 0.0053 BrownCoal NaturalGas 2 0.0001 1 Petroleum Energy BlackCoal 0.0028 0.0935 0.0089 0.0253 0.0564 5 0.0033 0.1005 0.0293 0.0093 0.0587 5 0.1167 0.0108 0.0046 0.0369 0.0644 5 0.0046 0.1186 0.0093 0.0347 0.0700 5 0.0052 0.1202 0.0077 0.0371 0.0702 5 0.1659 0.1659 6 0.1708 0.1708 6 0.1763 0.1763 6 0.2128 0.2128 6 0.2069 0.2069 6 0.0020 0.1040 0.1019 7 0.0037 0.1116 0.1079 7 0.1208 0.1180 0.0027 7 0.0011 0.1160 0.1148 7 0.0075 0.1344 0.1269 7 8 8 8 8 8 0.0020 0.0020 9 0.0021 0.0021 9 0.0019 0.0019 9 0.0017 0.0017 9 0.0016 0.0016 9 0.0015 0.0016 0.0001 0.0000 0.0000 10 0.0017 0.0018 0.0001 0.0001 0.0000 10 0.0021 0.0001 0.0020 0.0001 0.0000 10 0.0024 0.0025 0.0001 0.0001 0.0000 10 0.0030 0.0031 0.0001 0.0001 0.0000 10 TableC5 0.0003 0.0011 0.0006 0.0003 11 0.0003 0.0010 0.0005 0.0002 11 0.0011 0.0005 0.0003 0.0002 11 0.0004 0.0011 0.0005 0.0002 11 0.0006 0.0012 0.0004 0.0002 11 0.0001 0.0005 0.0004 0.0000 12 0.0001 0.0005 0.0004 0.0000 12 0.0005 0.0004 0.0001 0.0000 12 0.0001 0.0006 0.0004 0.0000 12 0.0002 0.0006 0.0004 0.0000 12 0.0002 0.0016 0.0009 0.0002 0.0004 13 0.0003 0.0017 0.0002 0.0008 0.0004 13 0.0017 0.0008 0.0004 0.0002 0.0003 13 0.0005 0.0018 0.0009 0.0002 0.0003 13 0.0006 0.0020 0.0009 0.0002 0.0003 13 14 14 14 14 0.0035 0.0062 0.0025 0.0002 0.0032 0.0060 0.0026 0.0002 0.0055 0.0019 0.0034 0.0002 0.0036 0.0057 0.0020 0.0002 0.0040 0.0061 0.0019 0.0002 14 0.0008 0.0114 0.0073 0.0032 15 0.0009 0.0126 0.0078 0.0039 15 0.0129 0.0078 0.0013 0.0038 15 0.0017 0.0145 0.0090 0.0038 15 0.0019 0.0137 0.0082 0.0036 15 0.0003 0.0217 0.0022 0.0192 16 0.0004 0.0229 0.0020 0.0205 16 0.0240 0.0018 0.0007 0.0216 16 0.0012 0.0266 0.0016 0.0238 16 0.0020 0.0249 0.0009 0.0220 16 0.0082 0.0164 0.0041 0.0041 17 0.0075 0.0168 0.0049 0.0045 17 0.0167 0.0038 0.0089 0.0041 17 0.0087 0.0155 0.0032 0.0036 17 0.0086 0.0150 0.0029 0.0035 17 0.0001 0.0005 0.0004 0.0000 18 0.0001 0.0005 0.0004 0.0000 18 0.0005 0.0004 0.0001 0.0000 18 0.0001 0.0005 0.0004 0.0000 18 0.0001 0.0005 0.0004 0.0000 18 0.0000 0.0002 0.0001 0.0000 19 0.0000 0.0002 0.0001 0.0000 19 0.0002 0.0001 0.0000 0.0000 19 0.0000 0.0002 0.0002 0.0000 19 0.0001 0.0002 0.0001 0.0000 19 Matrixofsectoralenergyintensities(C) 0.0000 0.0000 0.0000 20 0.0000 0.0000 0.0000 20 0.0000 0.0000 0.0000 20 0.0001 0.0000 0.0000 20 0.0000 0.0000 0.0000 20 0.0001 0.0002 0.0001 21 0.0002 0.0002 0.0001 21 0.0003 0.0001 0.0002 21 0.0002 0.0003 0.0001 0.0001 21 0.0002 0.0004 0.0001 0.0001 21 0.0007 0.0007 0.0000 22 0.0008 0.0008 0.0000 22 0.0009 0.0000 0.0009 22 0.0010 0.0010 0.0000 22 0.0011 0.0011 22 0.0194 0.0194 23 0.0166 0.0166 23 0.0161 0.0161 23 0.0161 0.0161 23 0.0165 0.0165 23 0.0055 0.0055 0.0000 0.0000 24 0.0043 0.0043 0.0000 24 0.0046 0.0045 0.0000 24 0.0048 0.0048 0.0000 24 0.0052 0.0052 0.0000 24 0.0228 0.0240 0.0000 0.0013 25 0.0142 0.0143 0.0001 25 0.0128 0.0128 25 0.0176 0.0176 25 0.0171 0.0171 25 0.0134 0.0134 26 0.0121 0.0121 26 0.0125 0.0125 26 0.0117 0.0117 26 0.0122 0.0122 26 0.0000 0.0004 0.0003 27 0.0000 0.0007 0.0006 27 0.0006 0.0005 0.0001 27 0.0001 0.0005 0.0004 27 0.0001 0.0005 0.0004 27 0.0000 0.0002 0.0001 0.0000 28 (1984) 0.0001 0.0002 0.0001 0.0000 28 (1983) 0.0002 0.0001 0.0001 0.0000 28 (1982) 0.0001 0.0002 0.0001 0.0000 28 (1981) 0.0001 0.0002 0.0001 0.0000 28 (1980) 254 2 1 0.0090 2 0.0060 1 Energy 0.0104 0.0115 0.0007 0.0108 0.0101 3 0.0005 0.0085 0.0080 3 0.0066 0.0060 0.0005 3 0.0006 0.0080 0.0073 3 0.0008 0.0120 0.0112 3 4 4 4 4 4 (continuedonnextpage) 0.0007 0.0076 Petroleum Energy 0.0011 0.0006 0.0058 BrownCoal 0.0004 NaturalGas BlackCoal 2 1 0.0010 0.0088 0.0099 0.0005 0.0044 0.0006 0.0057 BrownCoal NaturalGas Petroleum Energy 0.0002 BlackCoal 0.0010 0.0080 0.0005 0.0046 0.0006 BrownCoal 0.0003 NaturalGas Petroleum BlackCoal 0.0083 0.0096 0.0005 0.0068 Petroleum Energy 0.0000 0.0013 0.0010 0.0049 BrownCoal 0.0004 NaturalGas BlackCoal 2 1 0.0000 0.0006 0.0057 0.0064 0.0013 0.0035 0.0005 0.0055 BrownCoal NaturalGas 2 0.0002 1 Petroleum Energy BlackCoal 0.0017 0.1113 0.0096 0.0336 0.0664 5 0.0015 0.1047 0.0316 0.0087 0.0629 5 0.1010 0.0078 0.0015 0.0307 0.0611 5 0.0022 0.1064 0.0100 0.0322 0.0620 5 0.0015 0.0993 0.0097 0.0303 0.0578 5 0.2158 0.2158 6 0.1714 0.1714 6 0.1828 0.1828 6 0.2443 0.2443 6 0.1581 0.1581 6 0.0019 0.1708 0.1689 7 0.0022 0.1288 0.1266 7 0.1301 0.1281 0.0020 7 0.0021 0.1365 0.1344 7 0.0068 0.1355 0.1287 7 0.0307 0.0307 8 0.0301 0.0301 8 0.0360 0.0360 8 0.0411 0.0411 8 8 0.0021 0.0021 0.0000 9 0.0021 0.0021 0.0000 9 0.0022 0.0000 0.0022 9 0.0018 0.0018 0.0000 9 0.0021 0.0021 9 TableC5 0.0020 0.0032 0.0010 0.0001 0.0001 10 0.0020 0.0042 0.0002 0.0019 0.0001 10 0.0037 0.0015 0.0019 0.0002 0.0001 10 0.0019 0.0033 0.0011 0.0002 0.0001 10 0.0016 0.0021 0.0003 0.0001 0.0000 10 0.0002 0.0011 0.0007 0.0003 11 0.0002 0.0012 0.0007 0.0003 11 0.0011 0.0007 0.0002 0.0003 11 0.0002 0.0011 0.0007 0.0000 0.0003 11 0.0002 0.0012 0.0007 0.0003 11 0.0001 0.0005 0.0004 0.0000 12 0.0001 0.0006 0.0005 0.0000 12 0.0006 0.0005 0.0001 0.0000 12 0.0001 0.0005 0.0004 0.0001 12 0.0001 0.0005 0.0004 0.0001 12 0.0001 0.0010 0.0007 0.0000 0.0003 13 0.0001 0.0012 0.0000 0.0007 0.0003 13 0.0012 0.0007 0.0001 0.0000 0.0003 13 0.0001 0.0013 0.0008 0.0000 0.0004 13 0.0002 0.0015 0.0008 0.0001 0.0004 13 14 14 14 14 0.0032 0.0054 0.0021 0.0001 0.0033 0.0055 0.0021 0.0001 0.0054 0.0020 0.0033 0.0001 0.0032 0.0057 0.0023 0.0001 0.0031 0.0056 0.0023 0.0002 14 0.0005 0.0079 0.0052 0.0000 0.0022 15 0.0005 0.0087 0.0000 0.0057 0.0024 15 0.0084 0.0056 0.0005 0.0000 0.0023 15 0.0006 0.0107 0.0072 0.0000 0.0029 15 0.0006 0.0114 0.0083 0.0026 15 0.0002 0.0172 0.0024 0.0146 16 0.0002 0.0212 0.0027 0.0183 16 0.0222 0.0026 0.0002 0.0194 16 0.0002 0.0207 0.0026 0.0180 16 0.0002 0.0243 0.0037 0.0204 16 0.0037 0.0184 0.0098 0.0049 17 0.0041 0.0201 0.0106 0.0053 17 0.0196 0.0101 0.0042 0.0053 17 0.0040 0.0146 0.0065 0.0040 17 0.0046 0.0171 0.0073 0.0052 17 0.0001 0.0004 0.0003 18 0.0001 0.0004 0.0003 18 0.0004 0.0003 0.0001 18 0.0001 0.0004 0.0004 0.0000 18 0.0001 0.0005 0.0004 0.0000 18 0.0000 0.0001 0.0001 19 0.0000 0.0001 0.0001 19 0.0002 0.0001 0.0000 0.0000 19 0.0000 0.0002 0.0001 0.0000 19 0.0000 0.0002 0.0001 0.0000 19 0.0001 0.0001 20 0.0001 0.0001 20 0.0001 0.0001 20 0.0001 0.0001 20 0.0001 0.0001 20 21 0.0001 0.0002 0.0001 21 0.0001 0.0002 0.0001 21 0.0002 0.0001 0.0001 21 0.0001 0.0002 0.0001 21 0.0001 0.0002 0.0001 Matrixofsectoralenergyintensities(C)(continued) 0.0007 0.0007 0.0000 22 0.0008 0.0008 0.0000 22 0.0008 0.0000 0.0007 22 0.0008 0.0008 0.0000 22 0.0007 0.0007 0.0000 22 0.0133 0.0133 0.0000 23 0.0182 0.0182 0.0000 23 0.0178 0.0000 0.0178 23 0.0166 0.0166 23 0.0176 0.0176 23 0.0033 0.0033 0.0000 24 0.0046 0.0046 0.0000 24 0.0050 0.0000 0.0050 0.0000 24 0.0054 0.0054 0.0000 0.0000 24 0.0058 0.0058 0.0000 0.0000 24 0.0165 0.0177 0.0000 0.0011 25 0.0095 0.0104 0.0000 0.0009 25 0.0114 0.0000 0.0103 0.0010 25 0.0228 0.0243 0.0000 0.0015 25 0.0210 0.0225 0.0000 0.0015 25 0.0127 0.0127 26 0.0139 0.0139 26 0.0130 0.0130 26 0.0120 0.0120 26 0.0126 0.0126 26 0.0000 0.0003 0.0003 27 0.0000 0.0003 0.0003 27 0.0003 0.0002 0.0000 27 0.0000 0.0004 0.0003 27 0.0000 0.0003 0.0003 27 0.0000 0.0001 0.0001 0.0000 28 (1995) 0.0000 0.0001 0.0001 0.0000 28 (1994) 0.0002 0.0001 0.0000 0.0000 28 (1993) 0.0000 0.0002 0.0001 0.0000 28 (1990) 0.0000 0.0002 0.0001 0.0000 28 (1987) 255 2 1 Sources: Notes: 0.004 0.005 0.005 0.000 3 0.000 0.005 0.004 3 0.0007 0.0105 0.0097 3 4 4 4 0.078 0.004 0.000 0.026 0.048 5 0.001 0.115 0.007 0.040 0.066 5 0.0014 0.1126 0.0070 0.0363 0.0679 5 0.157 0.157 6 0.164 0.164 6 0.2037 0.2037 6 0.152 0.142 0.010 7 0.001 0.236 0.234 7 0.0016 0.2291 0.2275 7 0.111 0.111 8 0.168 0.168 8 0.0540 0.0540 8 0.001 0.000 0.001 9 0.002 0.002 0.000 9 0.0020 0.0020 0.0000 9 TableC5 0.002 0.000 0.001 0.000 0.000 10 0.002 0.003 0.001 0.000 0.000 10 0.0022 0.0032 0.0008 0.0001 0.0000 10 0.000 0.000 0.000 0.000 11 0.000 0.001 0.001 0.000 11 0.0001 0.0011 0.0006 0.0003 11 0.000 0.000 0.000 0.000 12 0.000 0.001 0.000 0.000 12 0.0001 0.0006 0.0005 0.0000 12 0.000 0.000 0.000 0.000 13 0.000 0.001 0.001 0.000 13 0.0001 0.0012 0.0008 0.0000 0.0003 13 14 14 0.002 0.001 0.001 0.000 0.002 0.005 0.002 0.000 0.0023 0.0047 0.0024 0.0001 14 0.004 0.000 0.002 0.000 0.001 15 0.000 0.007 0.005 0.000 0.002 15 0.0005 0.0080 0.0053 0.0000 0.0022 15 0.007 0.002 0.000 0.005 16 0.000 0.017 0.002 0.015 16 0.0002 0.0181 0.0026 0.0153 16 0.007 0.004 0.002 0.002 17 0.004 0.018 0.010 0.005 17 0.0039 0.0189 0.0101 0.0049 17 0.000 0.000 0.000 18 0.000 0.000 0.000 18 0.0001 0.0004 0.0003 18 0.000 0.000 0.000 19 0.000 0.000 0.000 19 0.0000 0.0001 0.0001 0.0000 19 0.000 0.000 0.000 20 0.000 0.000 20 0.0001 0.0001 20 21 0.000 0.000 0.000 21 0.000 0.000 0.000 21 0.0001 0.0002 0.0001 Matrixofsectoralenergyintensities(C)(continued) 0.000 0.000 0.000 22 0.001 0.001 0.000 22 0.0007 0.0007 0.0000 22 0.008 0.000 0.008 23 0.017 0.017 0.000 23 0.0145 0.0145 0.0000 23 0.002 0.000 0.002 24 0.004 0.004 0.000 24 0.0037 0.0037 0.0000 0.0000 24 0.014 0.000 0.013 0.001 25 0.014 0.015 0.000 0.001 25 0.0170 0.0183 0.0000 0.0013 25 0.020 0.020 26 0.013 0.013 26 0.0137 0.0137 26 27 0.000 0.000 0.000 27 0.000 0.000 0.000 27 0.0000 0.0003 0.0003 ABARE(2006a)andABS(various). TheenergyintensitiespresentedintheseTablesarecalculatedbasedonEquation52,fromenergyconsumption(publishedbytheAustralianBureauof AgriculturalandResourceEconomics)andsectoraloutputdata(publishedbytheAustralianBureauofStatistics); seeTableC1,pp.234237fordescriptionofsector1to28. 0.003 Energy 0.001 0.004 0.000 0.002 0.000 BrownCoal 0.000 NaturalGas Petroleum BlackCoal 0.010 0.012 0.001 0.008 Petroleum Energy 0.002 0.000 0.006 BrownCoal 0.000 NaturalGas BlackCoal 2 1 0.0088 0.0101 0.0009 0.0078 0.0013 0.0006 0.0059 BrownCoal NaturalGas 2 0.0004 1 Petroleum Energy BlackCoal 0.000 0.000 0.000 0.000 28 (2002) 0.000 0.000 0.000 0.000 28 (1999) 0.0000 0.0001 0.0001 0.0000 28 (1997) 256 257 TableC6 InputfactorcostsandpricesforInterfactormodel:Coalfired PK PL PE P El PM SK SL SE SEl SM 1980 1981 1982 1983 0.4347 0.5530 0.6591 0.5731 0.8279 0.8910 1.0793 1.1096 1.3139 1.3405 1.5234 1.5455 1.0024 1.0314 1.0961 1.2334 0.8678 0.8872 0.9018 0.9400 0.2621 0.2915 0.2185 0.2190 0.2276 0.2262 0.2541 0.2662 0.3104 0.3103 0.3428 0.3128 0.0703 0.0732 0.0717 0.0755 0.1296 0.0989 0.1130 0.1265 1984 1985 1986 1987 1988 1989 1990 1991 1992 0.6020 0.7633 0.8500 0.8126 0.8201 1.0981 1.0000 0.7923 0.6037 0.9930 1.0207 1.0491 1.0796 1.0520 1.0252 1.0000 1.0184 1.0371 1.3963 1.3846 1.2866 1.1421 0.9502 0.9312 1.0000 0.9966 0.9689 1.2120 1.1983 1.1547 1.1039 1.0708 1.0402 1.0000 0.9919 1.0070 0.9285 0.9387 0.9490 0.9603 0.9725 0.9849 1.0000 1.0026 1.0053 0.2549 0.2697 0.2849 0.3011 0.3291 0.3578 0.3882 0.4056 0.4229 0.2444 0.2409 0.2370 0.2324 0.2083 0.1858 0.1669 0.1678 0.1683 0.2721 0.2595 0.2471 0.2352 0.2349 0.2334 0.2291 0.2241 0.2187 0.0744 0.0773 0.0802 0.0831 0.0817 0.0799 0.0773 0.0776 0.0777 0.1542 0.1526 0.1507 0.1483 0.1460 0.1430 0.1385 0.1248 0.1123 1993 1994 1995 1996 1997 1998 1999 0.5457 0.5769 0.6793 0.6508 0.5506 0.5328 0.5361 1.0567 0.9831 1.2883 1.3696 1.4617 1.4392 1.4175 0.9865 0.9291 0.8466 0.8995 0.8499 0.8421 0.7949 0.9995 0.9729 0.9134 0.8574 0.8261 0.8536 0.8655 1.0105 0.9738 1.0714 1.0965 1.1240 1.1331 1.1446 0.4398 0.4580 0.3716 0.3702 0.3647 0.3628 0.3600 0.1680 0.1552 0.1874 0.1696 0.1534 0.1468 0.1403 0.2126 0.2058 0.2023 0.2018 0.1990 0.1931 0.1871 0.0774 0.0766 0.0781 0.0742 0.0699 0.0745 0.0796 0.1022 0.1043 0.1606 0.1843 0.2130 0.2229 0.2331 Sources:ABS(2004d;2004i;various),(ESAAvarious). Notes: Pi=Priceoffactori,Si=Costshareoffactori; K=Capital,L=Labour,E=Primaryenergy,El=Electricity,M=Materials. TableC6InputfactorcostsandpricesforInterfactormodel:Internalcombustion PK PL PE P El PM SK SL SE SEl SM 1980 1981 1982 1983 1984 1985 1986 0.4347 0.5530 0.6591 0.5731 0.6020 0.7633 0.8500 0.8279 0.8910 1.0793 1.1096 0.9930 1.0207 1.0491 1.7791 1.8878 1.9332 2.1410 2.1122 2.0665 1.2626 1.0024 1.0314 1.0961 1.2334 1.2120 1.1983 1.1547 0.8935 0.9134 0.8998 0.9249 0.9436 0.9493 0.9550 0.1481 0.1438 0.1133 0.1065 0.1113 0.1495 0.1963 0.0522 0.0490 0.0658 0.0612 0.0557 0.0621 0.0677 0.7158 0.7468 0.7463 0.7567 0.7553 0.6935 0.6225 0.0161 0.0158 0.0185 0.0174 0.0170 0.0198 0.0227 0.0677 0.0446 0.0561 0.0583 0.0607 0.0751 0.0908 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 0.8126 0.8201 1.0981 1.0000 0.7923 0.6037 0.5457 0.5769 0.6793 0.6508 0.5506 0.5328 0.5361 1.0796 1.0520 1.0252 1.0000 1.0184 1.0371 1.0567 0.9831 1.2883 1.3696 1.4617 1.4392 1.4175 1.0997 0.8137 0.8870 1.0000 1.1911 1.1991 1.2030 1.1055 1.0190 1.0672 1.0976 0.9282 1.0637 1.1039 1.0708 1.0402 1.0000 0.9919 1.0070 0.9995 0.9729 0.9134 0.8574 0.8261 0.8536 0.8655 0.9615 0.9734 0.9855 1.0000 1.0080 1.0161 1.0268 1.0178 1.0711 1.0886 1.1076 1.1195 1.1342 0.2671 0.2843 0.3009 0.3166 0.2817 0.2458 0.2126 0.2157 0.1553 0.1626 0.1692 0.1812 0.1933 0.0692 0.0534 0.0410 0.0343 0.0305 0.0265 0.0229 0.0235 0.0234 0.0203 0.0179 0.0208 0.0246 0.5319 0.5397 0.5445 0.5438 0.6093 0.6697 0.7172 0.7110 0.7569 0.7416 0.7212 0.6951 0.6655 0.0247 0.0212 0.0181 0.0159 0.0141 0.0122 0.0106 0.0116 0.0097 0.0089 0.0081 0.0104 0.0139 0.1071 0.1014 0.0954 0.0894 0.0645 0.0457 0.0368 0.0382 0.0547 0.0666 0.0836 0.0925 0.1026 Sources:ABS(2004d;2004i;various),(ESAAvarious). Notes: Pi=Priceoffactori,Si=Costshareoffactori; K=Capital,L=Labour,E=Primaryenergy,El=Electricity,M=Materials. (continuedonnextpage) 258 TableC6InputfactorcostsandpricesforInterfactormodel:Gasturbine PK PL PE P El PM SK SL SE SEl SM 1980 1981 1982 1983 0.4347 0.5530 0.6591 0.5731 0.8279 0.8910 1.0793 1.1096 0.8923 0.9330 0.9964 1.1739 1.0024 1.0314 1.0961 1.2334 0.9512 0.9726 0.9816 1.0157 0.2607 0.1938 0.1579 0.2183 0.1975 0.2557 0.2676 0.2264 0.3916 0.4058 0.4280 0.3996 0.0610 0.0827 0.0755 0.0642 0.0892 0.0620 0.0710 0.0915 1984 1985 1986 1987 1988 1989 1990 1991 1992 0.6020 0.7633 0.8500 0.8126 0.8201 1.0981 1.0000 0.7923 0.6037 0.9930 1.0207 1.0491 1.0796 1.0520 1.0252 1.0000 1.0184 1.0371 1.2568 1.2736 1.1873 1.0855 1.0355 0.9741 1.0000 1.1022 1.0781 1.2120 1.1983 1.1547 1.1039 1.0708 1.0402 1.0000 0.9919 1.0070 0.9481 0.9568 0.9656 0.9752 0.9828 0.9903 1.0000 1.0035 1.0070 0.2497 0.3274 0.4128 0.5058 0.4822 0.4566 0.4264 0.4724 0.5186 0.1951 0.1581 0.1232 0.0959 0.0999 0.1034 0.1051 0.0921 0.0799 0.3831 0.3354 0.2822 0.2264 0.2557 0.2868 0.3218 0.3018 0.2805 0.0594 0.0515 0.0429 0.0343 0.0387 0.0434 0.0487 0.0426 0.0369 0.1127 0.1276 0.1389 0.1376 0.1234 0.1098 0.0980 0.0912 0.0841 1993 1994 1995 1996 1997 1998 1999 0.5457 0.5769 0.6793 0.6508 0.5506 0.5328 0.5361 1.0567 0.9831 1.2883 1.3696 1.4617 1.4392 1.4175 1.0924 1.0495 1.0315 1.0602 1.0422 0.8993 0.8818 0.9995 0.9729 0.9134 0.8574 0.8261 0.8536 0.8655 1.0128 0.9619 1.0348 1.0552 1.0775 1.0797 1.0838 0.5638 0.6043 0.4048 0.3857 0.3624 0.3792 0.3921 0.0700 0.0601 0.0996 0.0822 0.0692 0.0621 0.0557 0.2573 0.2287 0.3373 0.3632 0.3861 0.3554 0.3252 0.0322 0.0297 0.0415 0.0361 0.0315 0.0318 0.0316 0.0767 0.0773 0.1167 0.1328 0.1508 0.1715 0.1954 Sources:ABS(2004d;2004i;various),(ESAAvarious). Notes: Pi=Priceoffactori,Si=Costshareoffactori; K=Capital,L=Labour,E=Primaryenergy,El=Electricity,M=Materials. TableC6InputfactorcostsandpricesforInterfactormodel:Combinedcycle PK PL PE P El PM SK SL SE SEl SM 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 0.8201 1.0981 1.0000 0.7923 0.6037 0.5457 0.5769 0.6793 0.6508 0.5506 0.5328 0.5361 1.0520 1.0252 1.0000 1.0184 1.0371 1.0567 0.9831 1.2883 1.3696 1.4617 1.4392 1.4175 1.0625 0.9845 1.0000 1.0918 1.0640 1.0794 1.0429 1.0330 1.0594 1.0356 0.8959 0.8608 1.0708 1.0402 1.0000 0.9919 1.0070 0.9995 0.9729 0.9134 0.8574 0.8261 0.8536 0.8655 0.9595 0.9776 1.0000 1.0009 1.0019 1.0048 0.9391 1.0873 1.1208 1.1580 1.1586 1.1622 0.2150 0.2164 0.2176 0.2189 0.2200 0.2208 0.2274 0.1786 0.1716 0.1614 0.1842 0.2064 0.2082 0.2036 0.1990 0.1944 0.1898 0.1852 0.1780 0.2022 0.1682 0.1417 0.1326 0.1209 0.3989 0.4084 0.4179 0.4274 0.4369 0.4463 0.4496 0.4566 0.4977 0.5329 0.4891 0.4392 0.0968 0.0945 0.0922 0.0899 0.0876 0.0853 0.0879 0.0843 0.0739 0.0646 0.0676 0.0686 0.0811 0.0771 0.0733 0.0694 0.0658 0.0625 0.0572 0.0783 0.0886 0.0993 0.1265 0.1648 Sources:ABS(2004d;2004i;various),(ESAAvarious). Notes: Pi=Priceoffactori,Si=Costshareoffactori; K=Capital,L=Labour,E=Primaryenergy,El=Electricity,M=Materials. (continuedonnextpage) 259 TableC6InputfactorcostsandpricesforInterfactormodel:Renewableelectricity PK PL P El PM SK SL SEl SM 1980 1981 1982 1983 0.4347 0.5530 0.6591 0.5731 0.8279 0.8910 1.0793 1.1096 PE 1.0024 1.0314 1.0961 1.2334 0.8969 0.9080 0.9192 0.9579 0.6190 0.6407 0.5465 0.5588 0.2157 0.2201 0.2831 0.2634 SE 0.0667 0.0712 0.0798 0.0747 0.0986 0.0680 0.0906 0.1031 1984 1985 1986 1987 1988 1989 1990 1991 1992 0.6020 0.7633 0.8500 0.8126 0.8201 1.0981 1.0000 0.7923 0.6037 0.9930 1.0207 1.0491 1.0796 1.0520 1.0252 1.0000 1.0184 1.0371 1.2120 1.1983 1.1547 1.1039 1.0708 1.0402 1.0000 0.9919 1.0070 0.9434 0.9507 0.9581 0.9662 0.9765 0.9869 1.0000 1.0094 1.0188 0.5996 0.6193 0.6385 0.6564 0.6998 0.7390 0.7689 0.7783 0.7868 0.2185 0.2053 0.1926 0.1810 0.1485 0.1207 0.1024 0.1024 0.1023 0.0665 0.0661 0.0655 0.0647 0.0587 0.0528 0.0474 0.0473 0.0472 0.1154 0.1094 0.1034 0.0979 0.0930 0.0875 0.0813 0.0720 0.0637 1993 1994 1995 1996 1997 1998 1999 0.5457 0.5769 0.6793 0.6508 0.5506 0.5328 0.5361 1.0567 0.9831 1.2883 1.3696 1.4617 1.4392 1.4175 0.9995 0.9729 0.9134 0.8574 0.8261 0.8536 0.8655 1.0308 0.9970 1.0752 1.0983 1.1237 1.1276 1.1331 0.7937 0.8086 0.7306 0.7272 0.7188 0.7207 0.7214 0.1019 0.0915 0.1199 0.1099 0.1009 0.0928 0.0859 0.0469 0.0452 0.0500 0.0480 0.0460 0.0473 0.0487 0.0575 0.0548 0.0996 0.1149 0.1344 0.1391 0.1439 Sources:ABS(2004d;2004i;various),(ESAAvarious). Notes: Pi=Priceoffactori,Si=Costshareoffactori; K=Capital,L=Labour,E=Primaryenergy,El=Electricity,M=Materials. TableC6InputfactorcostsandpricesforInterfactormodel:Finaldemand PE Finalconsumption PM SE Export SM PE PM SE SM 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1.2740 1.3301 1.3953 1.5570 1.5390 1.5173 1.2025 1.1023 0.9616 0.9711 0.9358 0.9508 0.9575 0.9838 0.9638 0.9691 0.9745 0.9803 0.9866 0.9929 0.0339 0.0353 0.0352 0.0371 0.0358 0.0349 0.0340 0.0331 0.0308 0.0286 0.9661 0.9647 0.9648 0.9629 0.9642 0.9651 0.9660 0.9669 0.9692 0.9714 1.3996 1.4216 1.6338 1.6241 1.4304 1.4140 1.3094 1.1541 0.9221 0.9192 0.7312 0.7840 0.8294 0.9158 0.9046 0.9303 0.9567 0.9870 0.9895 0.9925 0.1017 0.1134 0.1259 0.1551 0.1559 0.1533 0.1507 0.1482 0.1353 0.1234 0.8983 0.8866 0.8741 0.8449 0.8441 0.8467 0.8493 0.8518 0.8647 0.8766 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 1.0000 1.0752 1.0836 1.0826 1.0277 0.9607 0.9514 0.9432 0.8851 0.9387 1.0000 1.0052 1.0104 1.0166 0.9891 1.0313 1.0459 1.0616 1.0542 1.0477 0.0268 0.0268 0.0268 0.0268 0.0247 0.0220 0.0213 0.0206 0.0213 0.0220 0.9732 0.9732 0.9732 0.9732 0.9753 0.9780 0.9787 0.9794 0.9787 0.9780 1.0000 0.9798 0.9524 0.9703 0.9088 0.8134 0.8705 0.8179 0.8322 0.7838 1.0000 1.0362 1.0692 1.1174 1.0658 1.2232 1.2428 1.2621 1.2705 1.2881 0.1136 0.1230 0.1330 0.1449 0.1251 0.1237 0.1254 0.1271 0.1232 0.1194 0.8864 0.8770 0.8670 0.8551 0.8749 0.8763 0.8746 0.8729 0.8768 0.8806 Sources:ABS(2004d;2004i;various),(ESAAvarious). Notes: Pi=Priceoffactori,Si=Expenditureshareoffactori; K=Capital,L=Labour,E=Primaryenergy,El=Electricity,M=Materials. 1.0637 1.5504 1.3309 1.3209 1.3230 1.1647 0.9262 0.9199 1.0000 0.9545 0.9234 0.9427 0.8856 0.7917 0.8487 0.7898 0.8197 0.7510 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 0.9282 1.6211 1982 0.8608 0.8959 1.0356 1.0594 1.0330 1.0429 1.0794 1.0640 1.0918 1.0000 0.9845 1.0625 1.0838 1.1785 1.1876 1.1648 1.0720 0.8994 0.8353 0.8012 PGas 0.8048 0.8111 0.7903 0.7619 0.7341 0.7563 0.7653 0.7750 0.7049 0.7059 0.7411 0.7325 0.7355 0.6980 0.6557 0.6153 0.6433 0.6476 0.6292 0.6338 SCoal TableC7 0.0513 0.0363 0.0456 0.0638 0.0486 0.0512 0.0599 0.0609 0.1466 0.1176 0.0729 0.0513 0.0877 0.1268 0.2152 0.2461 0.2459 0.2623 0.2894 0.3027 SOil Steam 0.1439 0.1525 0.1641 0.1743 0.2173 0.1926 0.1748 0.1641 0.1485 0.1766 0.1860 0.2162 0.1769 0.1752 0.1291 0.1386 0.1108 0.0900 0.0814 0.0635 SGas SCoal 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 SOil SGas Internalcombustion SCoal 0.1613 0.1941 0.0867 0.0787 0.0934 0.0953 0.1099 0.0558 0.1065 0.0737 0.1060 0.0926 0.1449 0.1177 0.1626 0.1023 0.1765 0.1361 0.0669 0.2953 SOil Gasturbine 0.8387 0.8059 0.9133 0.9213 0.9066 0.9047 0.8901 0.9442 0.8935 0.9263 0.8940 0.9074 0.8551 0.8823 0.8374 0.8977 0.8235 0.8639 0.9331 0.7047 SGas SCoal SOil 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 SGas Combinedcycle InputfactorcostsandpricesforEnergysubmodel:Electricitysector ABARE(various),ESAA(various),Tedescoetal.(2004). Pi=Priceoffactori,Si=Costshareoffactori. 1.0976 1.0672 1.0190 1.1055 1.2030 1.1991 1.1911 1.0000 0.8870 0.8137 1.0997 1.2626 2.0665 2.1122 2.1410 1.9332 1.8878 1.3545 1.7791 1.3536 POil 1981 P Coal 1980 Sources: Note: SCoal SOil Renewable SGas 260 0.8197 0.7510 1998 1999 1.0637 0.9282 1.0976 1.0672 1.0190 1.1055 1.2030 1.1991 1.1911 1.0000 0.8870 0.8137 1.0997 1.2626 2.0665 2.1122 2.1410 1.9332 1.8878 1.7791 POil 0.8655 0.8536 0.8261 0.8574 0.9134 0.9729 0.9995 1.0070 0.9919 1.0000 1.0402 1.0708 1.1039 1.1547 1.1983 1.2120 1.2334 1.0961 1.0314 1.0024 PElectricity TableC7 0.8608 0.8959 1.0356 1.0594 1.0330 1.0429 1.0794 1.0640 1.0918 1.0000 0.9845 1.0625 1.0838 1.1785 1.1876 1.1648 1.0720 0.8994 0.8353 0.8012 P Gas 0.0371 0.0452 0.0541 0.0501 0.0465 0.0653 0.0153 0.0097 0.0072 0.0053 0.0061 0.0076 0.0095 0.0081 0.0072 0.0063 0.0071 0.0079 0.0099 0.0050 SCoal 0.3305 0.3126 0.2932 0.3082 0.3241 0.3384 0.3618 0.3810 0.3988 0.4166 0.4370 0.4600 0.4830 0.4892 0.4950 0.5009 0.5233 0.5416 0.5525 0.5553 SOil 0.5357 0.5751 0.6012 0.5923 0.5821 0.5378 0.5178 0.5122 0.5038 0.4945 0.4779 0.4582 0.4381 0.4356 0.4327 0.4298 0.4013 0.3795 0.3736 0.3722 SElectricity Finalconsumption 0.0966 0.0671 0.0515 0.0494 0.0473 0.0586 0.1051 0.0971 0.0902 0.0836 0.0790 0.0741 0.0694 0.0671 0.0651 0.0630 0.0683 0.0710 0.0640 0.0675 SGas 0.9241 0.9072 0.8803 0.9096 0.9266 0.9100 0.9071 0.8929 0.8795 0.8647 0.8699 0.8754 0.8807 0.8566 0.8249 0.7880 0.7622 0.7387 0.7260 0.7277 SCoal InputfactorcostsandpricesforEnergysubmodel:Finaldemand ABARE(various),ABS(various),ESAA(various),Tedescoetal.(2004). Pi=Priceoffactori,Si=Expenditureshareoffactori. 0.8487 0.7917 0.7898 0.8856 1994 1995 1997 0.9427 1993 1996 0.9545 0.9234 1991 1990 1992 0.9199 1.0000 1989 1.1647 0.9262 1987 1988 1.3209 1.3230 1986 1.3309 1984 1985 1.6211 1.5504 1982 1.3545 1981 1983 1.3536 PCoal 1980 Sources: Note: Export 0.0735 0.0903 0.1171 0.0878 0.0708 0.0879 0.0909 0.1045 0.1170 0.1307 0.1262 0.1212 0.1164 0.1404 0.1719 0.2087 0.2324 0.2547 0.2695 0.2681 SOil 0.0023 0.0024 0.0025 0.0026 0.0026 0.0021 0.0020 0.0026 0.0035 0.0046 0.0039 0.0033 0.0028 0.0030 0.0032 0.0033 0.0054 0.0066 0.0045 0.0042 SElectricity 0.0001 0.0001 0.0001 SGas 261 0.6508 0.7167 0.7671 0.9743 0.7935 0.8532 0.9174 0.9944 0.9963 0.9981 1.0000 1.0893 1.1865 1.3071 1.2529 1.6276 1.5309 1.4452 1.4573 1.4695 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 P M1 1980 1.1347 1.1257 1.1300 1.1215 1.0934 1.0702 1.0690 1.0505 1.0418 1.0000 0.9526 0.9209 0.8936 0.8749 0.8567 0.8388 0.8213 0.8041 0.7873 0.7709 P M2 1.2901 1.3106 1.3318 1.2891 1.2490 1.0697 1.1441 1.0918 1.0449 1.0000 0.9993 0.9986 0.9979 0.9525 0.9118 0.8728 0.8268 0.7796 0.7213 0.6804 PM3 P M4 1.2194 1.2883 1.3658 1.2475 1.1476 0.8663 0.9189 0.9444 0.9718 1.0000 0.9093 0.8359 0.7684 0.7720 0.7756 0.7792 0.8003 0.6766 0.6649 0.5914 P M5 1.2269 1.2333 1.2397 1.1561 1.0829 0.9705 1.0631 1.0412 1.0204 1.0000 0.9797 0.9604 0.9415 0.9310 0.9209 0.9109 0.9249 0.7815 0.7747 0.7384 1.2149 1.2172 1.2195 1.2012 1.1835 0.9939 1.0171 1.0113 1.0056 1.0000 0.9895 0.9792 0.9691 0.9603 0.9517 0.9432 0.9721 0.8245 0.8036 0.7580 P M6 1.6601 1.6677 1.6753 1.5022 1.3607 1.1474 1.2407 1.1490 1.0719 1.0000 1.0603 1.1313 1.2069 1.1649 1.1263 1.0889 1.0396 0.8294 0.7996 0.7442 P M7 TableC8 2.1823 2.0121 1.8659 1.6919 1.5468 1.6863 1.8325 1.4446 1.2019 1.0000 1.0288 1.0598 1.0918 1.0192 0.9572 0.8989 1.0035 0.6790 0.6154 0.5883 P M8 2.0930 2.0225 1.9566 1.9034 1.8529 1.5166 1.6833 1.3773 1.1736 1.0000 1.0781 1.1750 1.2806 1.2935 1.3067 1.3201 1.4932 1.3105 0.9776 0.7868 P M9 1.7737 1.6718 1.5807 1.4642 1.3634 1.1792 1.2502 1.1544 1.0744 1.0000 1.0128 1.0261 1.0395 1.0026 0.9688 0.9361 0.8620 0.6745 0.6659 0.6448 PM10 1.1145 1.1174 1.1203 1.1204 1.1206 1.0332 1.1021 1.0658 1.0324 1.0000 1.0014 1.0028 1.0041 1.0020 0.9999 0.9978 0.9639 0.9013 0.8995 0.8977 PM11 0.7158 0.7017 0.6882 0.8312 1.0604 0.8534 1.2270 1.1410 1.0682 1.0000 0.9066 0.8315 0.7626 0.7707 0.7790 0.7875 0.8050 0.6986 0.7162 0.6424 PM12 (continuedonnextpage) 2.2818 2.1940 2.1126 1.8309 1.6134 1.0814 1.1284 1.0822 1.0403 1.0000 0.8016 0.6740 0.5667 0.5625 0.5583 0.5541 0.7762 0.8406 0.7382 0.8842 PM13 1.5390 1.5108 1.4836 1.4561 1.4296 1.2903 1.3210 1.1942 1.0928 1.0000 0.9753 0.9521 0.9295 0.9137 0.8986 0.8837 0.9042 0.8291 0.8419 0.8263 PM14 InputfactorpricesforMaterialsubmodel Source: ABS(2004k). Notes: Pi=Priceoffactori; M1toM20correspondstosector9to28.SeeTableC1pp.234237fordescriptionofsector9to28. 1.7042 1.5570 1.4328 1.4091 1.3862 1.2654 1.0361 1.0238 1.0118 1.0000 0.9051 0.8291 0.7594 0.7535 0.7478 0.7421 0.5704 0.6321 0.8150 0.6997 PM15 1.4661 1.3928 1.3264 1.2549 1.1906 0.8027 0.8824 0.9184 0.9583 1.0000 0.9714 0.9447 0.9187 0.8716 0.8300 0.7904 0.7322 0.6588 0.5780 0.5158 PM16 1.3048 0.8596 0.6303 0.5971 0.5673 0.4790 0.4892 0.5802 0.7617 1.0000 0.8861 0.7985 0.7196 0.5949 0.5104 0.4379 0.2390 0.1982 0.1772 0.1700 PM17 0.9343 1.0766 1.2746 1.2217 1.1729 0.9048 0.9204 0.9455 0.9723 1.0000 1.0177 1.0363 1.0551 1.0293 1.0050 0.9813 0.8313 0.7353 0.8423 0.7905 PM18 0.8043 0.8252 0.8472 0.8301 0.8137 0.7241 0.9227 0.9471 0.9732 1.0000 1.0120 1.0243 1.0367 1.0127 0.9900 0.9678 1.7411 1.7398 1.6842 1.5547 PM19 0.9880 0.9931 0.9982 0.9886 0.9792 0.9863 0.9989 0.9992 0.9996 1.0000 0.9985 0.9971 0.9956 0.9975 0.9994 1.0013 1.0206 1.0165 1.0138 1.0166 PM20 262 0.0005 1992 0.0003 0.0003 0.0003 1997 1998 1999 0.0003 0.0003 1995 1996 0.0005 0.0013 1991 0.0003 0.0032 1990 1993 0.0029 1989 1994 0.0024 0.0026 0.0024 1987 0.0024 1985 1986 1988 0.0023 0.0024 0.0021 1982 1983 0.0020 1981 1984 0.0015 SM1 1980 SM2 0.0006 0.0006 0.0007 0.0008 0.0009 0.0008 0.0011 0.0006 0.0026 0.0112 0.0106 0.0100 0.0094 0.0102 0.0111 0.0120 0.0072 0.0065 0.0060 0.0029 SM3 0.0020 0.0024 0.0030 0.0019 0.0014 0.0011 0.0011 0.0014 0.0020 0.0029 0.0031 0.0034 0.0037 0.0033 0.0030 0.0027 0.0021 0.0022 0.0022 0.0011 SM4 0.0119 0.0117 0.0111 0.0117 0.0117 0.0047 0.0071 0.0091 0.0147 0.0228 0.0237 0.0244 0.0251 0.0251 0.0250 0.0247 0.0220 0.0188 0.0172 0.0083 SM5 TableC8 0.0461 0.0512 0.0558 0.0556 0.0527 0.0591 0.0434 0.0290 0.0207 0.0143 0.0128 0.0116 0.0105 0.0110 0.0114 0.0119 0.0090 0.0098 0.0094 0.0043 SM6 0.0394 0.0416 0.0427 0.0413 0.0380 0.0539 0.0452 0.0339 0.0258 0.0188 0.0134 0.0104 0.0081 0.0079 0.0077 0.0074 0.0057 0.0061 0.0060 0.0032 SM7 0.0048 0.0047 0.0045 0.0053 0.0060 0.0060 0.0090 0.0076 0.0062 0.0048 0.0050 0.0050 0.0051 0.0055 0.0059 0.0064 0.0145 0.0241 0.0233 0.0082 SM8 0.0000 0.0000 0.0000 0.0000 0.0001 0.0001 0.0000 0.0000 0.0001 0.0004 0.0005 0.0007 0.0010 0.0010 0.0010 0.0010 0.0009 0.0008 0.0010 0.0006 SM9 0.0183 0.0190 0.0192 0.0129 0.0092 0.0136 0.0121 0.0130 0.0126 0.0118 0.0126 0.0133 0.0141 0.0144 0.0146 0.0148 0.0117 0.0129 0.0123 0.0068 SM10 0.1249 0.1380 0.1495 0.1817 0.2188 0.2163 0.1377 0.1276 0.1102 0.0915 0.1014 0.1132 0.1260 0.1232 0.1196 0.1158 0.1093 0.1007 0.1011 0.0503 SM11 0.0008 0.0010 0.0012 0.0010 0.0008 0.0003 0.0008 0.0010 0.0019 0.0035 0.0038 0.0040 0.0043 0.0045 0.0046 0.0046 0.0037 0.0033 0.0038 0.0020 SM12 (continuedonnextpage) SM14 0.0071 0.0079 0.0307 0.0062 0.0070 0.0075 0.0125 0.0334 0.0156 0.0096 0.0057 0.0058 0.0058 0.0058 0.0065 0.0074 0.0085 0.0185 0.0164 0.0175 0.0086 0.0347 0.0386 0.0499 0.0672 0.0536 0.0787 0.0528 0.0379 0.0261 0.0261 0.0259 0.0255 0.0260 0.0264 0.0266 0.0174 0.0143 0.0149 0.0079 SM13 0.0149 0.0148 0.0143 0.0146 0.0142 0.0324 0.0313 0.0374 0.0414 0.0441 0.0439 0.0432 0.0424 0.0393 0.0364 0.0336 0.0507 0.0602 0.0673 0.0328 SM15 0.0484 0.0499 0.0499 0.0636 0.0835 0.1848 0.1767 0.1773 0.1626 0.1435 0.1451 0.1452 0.1448 0.1281 0.1145 0.1021 0.1012 0.1262 0.1722 0.0744 SM16 InputfactorcostsforMaterialsubmodel:Coalfiredelectricity Source: ABS(various). Notes: Si=Costshareoffactori; M1toM20correspondstosector9to28.SeeTableC1pp.234237fordescriptionofsector9to28. SM17 0.0030 0.0035 0.0042 0.0012 0.0006 0.0039 0.0046 0.0042 0.0036 0.0029 0.0030 0.0031 0.0031 0.0033 0.0035 0.0038 0.0320 0.0406 0.0410 0.0217 SM18 0.0139 0.0151 0.0160 0.0166 0.0164 0.0067 0.0108 0.0135 0.0164 0.0192 0.0160 0.0136 0.0116 0.0128 0.0141 0.0156 0.0103 0.0086 0.0080 0.0039 SM19 0.1058 0.0645 0.0443 0.0410 0.0364 0.0395 0.0497 0.0408 0.0325 0.0250 0.0285 0.0336 0.0393 0.0368 0.0343 0.0320 0.0209 0.0179 0.0165 0.0081 0.5261 0.5399 0.5385 0.4935 0.4344 0.3104 0.3568 0.4348 0.4978 0.5483 0.5420 0.5308 0.5178 0.5388 0.5570 0.5740 0.5606 0.5287 0.4782 0.7535 SM20 263 0.0002 1992 0.0001 0.0001 0.0001 1997 1998 1999 0.0001 0.0001 1995 1996 0.0002 0.0005 1991 0.0001 0.0010 1990 1993 0.0010 1989 1994 0.0010 0.0010 0.0011 1987 0.0012 1985 1986 1988 0.0011 0.0014 0.0011 1982 1983 0.0009 1981 1984 0.0006 SM1 1980 SM2 0.0002 0.0002 0.0002 0.0002 0.0003 0.0003 0.0004 0.0003 0.0010 0.0036 0.0037 0.0038 0.0039 0.0045 0.0056 0.0069 0.0036 0.0034 0.0029 0.0013 SM3 0.0008 0.0008 0.0009 0.0007 0.0005 0.0005 0.0004 0.0005 0.0007 0.0009 0.0011 0.0013 0.0015 0.0016 0.0016 0.0016 0.0011 0.0011 0.0010 0.0005 SM4 0.0047 0.0039 0.0033 0.0038 0.0043 0.0019 0.0027 0.0035 0.0051 0.0073 0.0081 0.0092 0.0103 0.0114 0.0128 0.0143 0.0110 0.0098 0.0082 0.0037 SM5 TableC8 0.0534 0.0581 0.0627 0.0634 0.0614 0.0722 0.0554 0.0355 0.0250 0.0171 0.0152 0.0137 0.0122 0.0123 0.0124 0.0125 0.0090 0.0097 0.0098 0.0044 SM6 0.0456 0.0471 0.0480 0.0471 0.0443 0.0658 0.0576 0.0416 0.0311 0.0226 0.0158 0.0122 0.0094 0.0089 0.0083 0.0078 0.0057 0.0060 0.0063 0.0032 SM7 0.0055 0.0053 0.0051 0.0060 0.0070 0.0073 0.0115 0.0094 0.0075 0.0058 0.0059 0.0059 0.0059 0.0062 0.0065 0.0067 0.0145 0.0239 0.0242 0.0084 SM8 0.0000 0.0000 0.0000 0.0000 0.0001 0.0001 0.0001 0.0000 0.0001 0.0005 0.0006 0.0008 0.0012 0.0011 0.0011 0.0010 0.0009 0.0008 0.0010 0.0006 SM9 0.0212 0.0215 0.0215 0.0148 0.0107 0.0166 0.0154 0.0160 0.0153 0.0142 0.0150 0.0157 0.0164 0.0162 0.0159 0.0156 0.0117 0.0127 0.0128 0.0070 SM10 0.1446 0.1564 0.1679 0.2062 0.2548 0.2642 0.1757 0.1574 0.1332 0.1097 0.1208 0.1335 0.1469 0.1380 0.1299 0.1220 0.1095 0.0998 0.1051 0.0517 SM11 0.0010 0.0011 0.0014 0.0012 0.0010 0.0003 0.0010 0.0012 0.0023 0.0042 0.0045 0.0048 0.0050 0.0050 0.0050 0.0049 0.0037 0.0033 0.0039 0.0020 SM12 (continuedonnextpage) SM14 0.0084 0.0097 0.0122 0.0073 0.0084 0.0092 0.0160 0.0449 0.0200 0.0122 0.0072 0.0072 0.0072 0.0071 0.0077 0.0086 0.0095 0.0195 0.0171 0.0191 0.0093 0.0119 0.0115 0.0156 0.0246 0.0222 0.0298 0.0181 0.0125 0.0083 0.0090 0.0098 0.0105 0.0118 0.0135 0.0154 0.0087 0.0075 0.0072 0.0035 SM13 0.0426 0.0410 0.0390 0.0426 0.0447 0.0977 0.0947 0.1043 0.1052 0.1033 0.1084 0.1129 0.1171 0.1185 0.1194 0.1201 0.1578 0.1810 0.1986 0.0846 SM15 0.0095 0.0084 0.0074 0.0099 0.0152 0.0377 0.0331 0.0308 0.0268 0.0227 0.0247 0.0270 0.0294 0.0293 0.0291 0.0288 0.0246 0.0315 0.0394 0.0157 SM16 InputfactorcostsforMaterialsubmodel:Internalcombustion Source: ABS(various). Notes: Si=Costshareoffactori; M1toM20correspondstosector9to28.SeeTableC1pp.234237fordescriptionofsector9to28. SM17 0.0031 0.0035 0.0040 0.0013 0.0007 0.0043 0.0051 0.0042 0.0034 0.0027 0.0029 0.0032 0.0034 0.0040 0.0048 0.0058 0.0440 0.0563 0.0537 0.0252 SM18 0.0055 0.0051 0.0048 0.0054 0.0060 0.0028 0.0041 0.0049 0.0055 0.0061 0.0056 0.0052 0.0048 0.0056 0.0071 0.0090 0.0051 0.0045 0.0038 0.0017 SM19 0.0311 0.0161 0.0103 0.0099 0.0092 0.0107 0.0129 0.0095 0.0072 0.0053 0.0063 0.0081 0.0103 0.0108 0.0114 0.0120 0.0068 0.0061 0.0054 0.0024 0.6091 0.6110 0.6047 0.5634 0.5059 0.3790 0.4551 0.5423 0.6054 0.6576 0.6441 0.6249 0.6037 0.6060 0.6059 0.6046 0.5615 0.5243 0.4967 0.7742 SM20 264 0.0002 1992 0.0002 0.0002 0.0001 1997 1998 1999 0.0002 0.0002 1995 1996 0.0003 0.0007 1991 0.0001 0.0028 1990 1993 0.0019 1989 1994 0.0011 0.0014 0.0013 1987 0.0019 1985 1986 1988 0.0027 0.0026 0.0035 1982 1983 0.0035 1981 1984 0.0018 SM1 1980 SM2 0.0003 0.0003 0.0004 0.0005 0.0006 0.0004 0.0006 0.0000 0.0007 0.0099 0.0071 0.0055 0.0042 0.0052 0.0084 0.0131 0.0085 0.0109 0.0109 0.0037 SM3 SM4 0.0009 0.0013 0.0019 0.0013 0.0010 0.0006 0.0006 0.0007 0.0014 0.0025 0.0022 0.0019 0.0016 0.0020 0.0025 0.0030 0.0025 0.0037 0.0039 0.0014 0.0056 0.0064 0.0071 0.0080 0.0086 0.0025 0.0039 0.0045 0.0097 0.0203 0.0165 0.0136 0.0112 0.0140 0.0197 0.0270 0.0258 0.0315 0.0310 0.0105 SM5 0.0397 0.0460 0.0519 0.0535 0.0523 0.0698 0.0491 0.0313 0.0219 0.0147 0.0142 0.0134 0.0125 0.0123 0.0115 0.0106 0.0082 0.0075 0.0066 0.0041 SM6 TableC8 0.0339 0.0374 0.0397 0.0397 0.0377 0.0636 0.0511 0.0367 0.0272 0.0193 0.0150 0.0121 0.0097 0.0087 0.0077 0.0066 0.0052 0.0046 0.0042 0.0030 SM7 0.0041 0.0043 0.0042 0.0051 0.0059 0.0071 0.0102 0.0083 0.0066 0.0050 0.0054 0.0058 0.0061 0.0062 0.0060 0.0057 0.0132 0.0184 0.0164 0.0078 SM8 0.0000 0.0000 0.0000 0.0000 0.0001 0.0001 0.0000 0.0000 0.0001 0.0004 0.0005 0.0008 0.0012 0.0011 0.0010 0.0009 0.0008 0.0006 0.0007 0.0005 SM9 0.0157 0.0171 0.0178 0.0125 0.0091 0.0160 0.0137 0.0142 0.0134 0.0122 0.0137 0.0153 0.0169 0.0160 0.0147 0.0132 0.0107 0.0098 0.0086 0.0065 SM10 0.1075 0.1240 0.1390 0.1731 0.2173 0.2552 0.1557 0.1390 0.1169 0.0941 0.1099 0.1296 0.1511 0.1359 0.1197 0.1028 0.0997 0.0766 0.0710 0.0482 SM11 0.0007 0.0009 0.0011 0.0010 0.0008 0.0003 0.0009 0.0011 0.0020 0.0036 0.0041 0.0046 0.0052 0.0050 0.0046 0.0041 0.0034 0.0025 0.0027 0.0019 SM12 (continuedonnextpage) SM14 0.0097 0.0103 0.0145 0.0087 0.0101 0.0113 0.0222 0.0570 0.0252 0.0153 0.0089 0.0096 0.0101 0.0104 0.0112 0.0114 0.0114 0.0255 0.0188 0.0185 0.0124 0.0185 0.0246 0.0330 0.0492 0.0280 0.0436 0.0369 0.0299 0.0233 0.0179 0.0143 0.0113 0.0142 0.0206 0.0291 0.0204 0.0240 0.0269 0.0100 SM13 0.0088 0.0096 0.0102 0.0110 0.0114 0.0185 0.0192 0.0248 0.0328 0.0414 0.0338 0.0281 0.0231 0.0272 0.0319 0.0366 0.0616 0.0970 0.1117 0.0449 SM15 InputfactorcostsforMaterialsubmodel:Gasturbine Source: ABS(various). Notes: Si=Costshareoffactori; M1toM20correspondstosector9to28.SeeTableC1pp.234237fordescriptionofsector9to28. SM16 0.0115 0.0137 0.0160 0.0212 0.0307 0.0485 0.0491 0.0577 0.0622 0.0642 0.0501 0.0405 0.0324 0.0388 0.0469 0.0554 0.0589 0.1029 0.1503 0.0457 SM17 0.0010 0.0014 0.0019 0.0006 0.0003 0.0014 0.0018 0.0019 0.0019 0.0018 0.0015 0.0013 0.0010 0.0013 0.0019 0.0028 0.0266 0.0464 0.0486 0.0199 SM18 0.0066 0.0082 0.0102 0.0113 0.0120 0.0035 0.0060 0.0078 0.0118 0.0171 0.0104 0.0074 0.0052 0.0064 0.0106 0.0171 0.0121 0.0144 0.0144 0.0049 SM19 0.2858 0.2146 0.1642 0.1424 0.1200 0.0960 0.1337 0.1275 0.1124 0.0947 0.0894 0.0823 0.0750 0.0919 0.1183 0.1484 0.1029 0.1246 0.1343 0.0516 0.4528 0.4866 0.5008 0.4755 0.4314 0.3661 0.4035 0.4821 0.5330 0.5638 0.5967 0.6120 0.6209 0.6013 0.5606 0.5097 0.5113 0.4024 0.3357 0.7211 SM20 265 1984 1985 1986 1987 0.0006 0.0005 0.0003 1999 1996 1997 0.0007 1995 1998 0.0006 0.0007 1994 0.0008 0.0009 1992 1993 0.0071 0.0025 1990 1991 0.0111 1983 1989 1982 0.0163 1981 1988 SM1 1980 SM2 0.0007 0.0009 0.0013 0.0016 0.0019 0.0016 0.0020 0.0006 0.0041 0.0251 0.0429 0.0695 SM3 0.0024 0.0034 0.0059 0.0042 0.0030 0.0024 0.0019 0.0025 0.0042 0.0064 0.0084 0.0103 SM4 0.0145 0.0181 0.0221 0.0248 0.0259 0.0098 0.0127 0.0163 0.0300 0.0513 0.0693 0.0889 SM5 TableC8 0.0189 0.0229 0.0268 0.0276 0.0262 0.0270 0.0180 0.0140 0.0107 0.0076 0.0050 0.0031 SM6 0.0161 0.0187 0.0205 0.0205 0.0189 0.0246 0.0188 0.0163 0.0133 0.0101 0.0073 0.0051 SM7 0.0020 0.0021 0.0022 0.0026 0.0030 0.0027 0.0037 0.0036 0.0032 0.0026 0.0021 0.0016 SM8 0.0000 0.0000 0.0000 0.0000 0.0001 0.0001 0.0000 0.0000 0.0000 0.0002 0.0004 0.0006 SM9 0.0075 0.0086 0.0092 0.0064 0.0046 0.0062 0.0050 0.0060 0.0064 0.0063 0.0063 0.0059 SM10 0.0511 0.0619 0.0717 0.0896 0.1089 0.0988 0.0572 0.0600 0.0562 0.0489 0.0428 0.0355 SM11 0.0003 0.0004 0.0006 0.0005 0.0004 0.0001 0.0003 0.0004 0.0009 0.0019 0.0027 0.0038 SM12 (continuedonnextpage) 0.0064 0.0064 0.0374 0.0059 0.0068 0.0074 0.0113 0.0275 0.0152 0.0099 0.0061 0.0028 0.0012 SM14 0.0510 0.0766 0.1033 0.1488 0.1120 0.1419 0.1092 0.0831 0.0589 0.0384 0.0237 SM13 0.0159 0.0200 0.0248 0.0272 0.0277 0.0591 0.0492 0.0627 0.0747 0.0828 0.0897 0.0921 SM15 InputfactorcostsforMaterialsubmodel:Combinedcycle Source: ABS(various). Notes: Si=Costshareoffactori; M1toM20correspondstosector9to28.SeeTableC1pp.234237fordescriptionofsector9to28. 0.0291 0.0375 0.0487 0.0651 0.0913 0.1905 0.1567 0.1749 0.1732 0.1595 0.1480 0.1303 SM16 0.0022 0.0031 0.0051 0.0016 0.0008 0.0050 0.0051 0.0052 0.0047 0.0040 0.0034 0.0028 SM17 0.0170 0.0226 0.0317 0.0352 0.0363 0.0140 0.0194 0.0258 0.0346 0.0432 0.0505 0.0560 SM18 0.5627 0.4780 0.3883 0.3373 0.2778 0.2924 0.3317 0.2926 0.2410 0.1847 0.1370 0.0965 SM19 0.2154 0.2438 0.2582 0.2449 0.2163 0.1418 0.1481 0.1939 0.2473 0.2932 0.3320 0.3567 SM20 266 0.0006 1992 0.0003 0.0003 0.0003 1997 1998 1999 0.0003 0.0003 1995 1996 0.0006 0.0014 1991 0.0003 0.0033 1990 1993 0.0031 1989 1994 0.0028 0.0030 0.0028 1987 0.0028 1985 1986 1988 0.0028 0.0028 0.0029 1982 1983 0.0028 1981 1984 0.0018 SM1 1980 SM2 0.0006 0.0006 0.0007 0.0008 0.0009 0.0009 0.0012 0.0007 0.0029 0.0117 0.0116 0.0114 0.0111 0.0120 0.0131 0.0143 0.0087 0.0090 0.0085 0.0036 SM3 0.0020 0.0024 0.0031 0.0020 0.0014 0.0013 0.0011 0.0015 0.0022 0.0030 0.0034 0.0038 0.0044 0.0040 0.0036 0.0033 0.0026 0.0030 0.0030 0.0014 SM4 0.0118 0.0118 0.0116 0.0121 0.0121 0.0053 0.0076 0.0102 0.0159 0.0238 0.0257 0.0276 0.0296 0.0297 0.0297 0.0295 0.0267 0.0262 0.0243 0.0104 SM5 TableC8 0.0502 0.0545 0.0585 0.0586 0.0561 0.0667 0.0468 0.0329 0.0236 0.0161 0.0144 0.0129 0.0116 0.0119 0.0122 0.0125 0.0094 0.0102 0.0101 0.0045 SM6 0.0429 0.0442 0.0448 0.0435 0.0404 0.0608 0.0487 0.0385 0.0293 0.0213 0.0150 0.0116 0.0089 0.0086 0.0082 0.0078 0.0059 0.0064 0.0065 0.0033 SM7 0.0052 0.0050 0.0048 0.0056 0.0063 0.0068 0.0097 0.0086 0.0070 0.0055 0.0056 0.0056 0.0056 0.0060 0.0064 0.0068 0.0152 0.0252 0.0250 0.0085 SM8 0.0000 0.0000 0.0000 0.0000 0.0001 0.0001 0.0000 0.0000 0.0001 0.0005 0.0006 0.0008 0.0011 0.0011 0.0011 0.0011 0.0009 0.0008 0.0010 0.0006 SM9 0.0199 0.0202 0.0201 0.0136 0.0098 0.0153 0.0130 0.0146 0.0143 0.0134 0.0142 0.0149 0.0156 0.0157 0.0157 0.0156 0.0123 0.0135 0.0132 0.0071 SM10 0.1360 0.1469 0.1567 0.1911 0.2328 0.2440 0.1483 0.1442 0.1251 0.1035 0.1141 0.1265 0.1397 0.1339 0.1280 0.1221 0.1148 0.1054 0.1084 0.0524 SM11 0.0009 0.0011 0.0013 0.0011 0.0009 0.0003 0.0008 0.0010 0.0021 0.0039 0.0042 0.0045 0.0048 0.0049 0.0049 0.0049 0.0039 0.0035 0.0040 0.0021 SM12 (continuedonnextpage) SM14 0.0224 0.0258 0.0304 0.0194 0.0219 0.0239 0.0419 0.1073 0.0529 0.0327 0.0193 0.0194 0.0192 0.0190 0.0211 0.0238 0.0268 0.0579 0.0511 0.0558 0.0266 0.0349 0.0403 0.0517 0.0693 0.0602 0.0849 0.0576 0.0406 0.0273 0.0284 0.0293 0.0301 0.0308 0.0313 0.0318 0.0211 0.0199 0.0211 0.0099 SM13 0.0072 0.0073 0.0072 0.0074 0.0072 0.0176 0.0163 0.0199 0.0216 0.0223 0.0231 0.0237 0.0242 0.0226 0.0210 0.0196 0.0299 0.0400 0.0452 0.0194 SM15 0.0225 0.0236 0.0244 0.0309 0.0404 0.0972 0.0890 0.0908 0.0817 0.0702 0.0738 0.0769 0.0799 0.0705 0.0631 0.0563 0.0564 0.0790 0.1092 0.0419 SM16 InputfactorcostsforMaterialsubmodel:Renewableelectricity Source: ABS(various). Notes: Si=Costshareoffactori; M1toM20correspondstosector9to28.SeeTableC1pp.234237fordescriptionofsector9to28. SM17 0.0014 0.0017 0.0021 0.0006 0.0003 0.0021 0.0023 0.0022 0.0018 0.0014 0.0015 0.0016 0.0017 0.0019 0.0020 0.0021 0.0183 0.0261 0.0266 0.0124 SM18 0.0138 0.0152 0.0167 0.0172 0.0169 0.0075 0.0116 0.0149 0.0177 0.0200 0.0176 0.0156 0.0137 0.0151 0.0168 0.0186 0.0125 0.0119 0.0113 0.0049 SM19 0.0562 0.0341 0.0236 0.0214 0.0188 0.0218 0.0264 0.0220 0.0173 0.0130 0.0151 0.0183 0.0221 0.0209 0.0198 0.0187 0.0124 0.0125 0.0117 0.0049 0.5729 0.5737 0.5645 0.5203 0.4621 0.3501 0.3843 0.4867 0.5625 0.6204 0.6093 0.5926 0.5739 0.5866 0.5965 0.6053 0.5884 0.5534 0.5123 0.7844 SM20 267 0.0158 0.0150 0.0152 0.0145 0.0135 0.0137 0.0140 0.0143 0.0139 0.0134 0.0130 0.0133 0.0136 0.0137 0.0130 0.0130 0.0130 0.0130 0.0126 0.0122 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 SM1 1980 SM2 0.0003 0.0003 0.0003 0.0003 0.0003 0.0003 0.0003 0.0002 0.0002 0.0002 0.0002 0.0002 0.0002 0.0002 0.0002 0.0002 0.0004 0.0004 0.0003 0.0003 0.0632 0.0687 0.0741 0.0701 0.0666 0.0762 0.0795 0.0797 0.0793 0.0785 0.0797 0.0808 0.0817 0.0847 0.0876 0.0905 0.1032 0.1031 0.1099 0.1117 SM3 0.0195 0.0199 0.0202 0.0222 0.0244 0.0247 0.0236 0.0259 0.0284 0.0309 0.0322 0.0334 0.0346 0.0352 0.0358 0.0363 0.0328 0.0367 0.0387 0.0397 SM4 0.0164 0.0157 0.0151 0.0157 0.0163 0.0184 0.0139 0.0153 0.0168 0.0185 0.0182 0.0179 0.0176 0.0171 0.0167 0.0163 0.0161 0.0176 0.0171 0.0170 SM5 TableC8 0.0190 0.0191 0.0191 0.0189 0.0187 0.0150 0.0144 0.0142 0.0138 0.0134 0.0134 0.0133 0.0132 0.0131 0.0131 0.0130 0.0135 0.0146 0.0149 0.0160 SM6 0.0004 0.0005 0.0008 0.0008 0.0008 0.0009 0.0006 0.0007 0.0008 0.0009 0.0010 0.0010 0.0011 0.0011 0.0011 0.0011 0.0011 0.0013 0.0014 0.0014 SM7 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0001 0.0001 0.0001 SM8 0.0000 0.0000 0.0003 0.0002 0.0002 0.0002 0.0002 0.0002 0.0002 0.0003 0.0003 0.0002 0.0002 0.0002 0.0002 0.0002 0.0002 0.0002 0.0002 0.0002 SM9 0.0012 0.0015 0.0020 0.0017 0.0015 0.0015 0.0009 0.0012 0.0019 0.0031 0.0030 0.0030 0.0029 0.0026 0.0024 0.0022 0.0025 0.0029 0.0030 0.0030 SM10 0.0396 0.0336 0.0293 0.0303 0.0313 0.0228 0.0245 0.0274 0.0308 0.0345 0.0337 0.0329 0.0321 0.0349 0.0380 0.0413 0.0391 0.0438 0.0447 0.0470 SM11 0.0043 0.0042 0.0041 0.0046 0.0051 0.0047 0.0034 0.0036 0.0038 0.0039 0.0042 0.0044 0.0047 0.0044 0.0041 0.0039 0.0046 0.0049 0.0055 0.0060 SM12 (continuedonnextpage) 0.0082 0.0081 0.0081 0.0088 0.0095 0.0017 0.0006 0.0006 0.0006 0.0005 0.0007 0.0010 0.0016 0.0015 0.0015 0.0014 0.0014 0.0014 0.0018 0.0015 SM13 0.0065 0.0071 0.0077 0.0071 0.0065 0.0054 0.0054 0.0067 0.0099 0.0147 0.0162 0.0179 0.0197 0.0200 0.0204 0.0207 0.0203 0.0180 0.0000 0.0000 SM14 0.0124 0.0120 0.0116 0.0117 0.0117 0.0140 0.0149 0.0152 0.0155 0.0157 0.0155 0.0153 0.0151 0.0151 0.0150 0.0150 0.0181 0.0181 0.0209 0.0207 SM15 InputfactorcostsforMaterialsubmodel:Finalconsumption Source: ABS(various). Notes: Si=Expenditureshareoffactori; M1toM20correspondstosector9to28.SeeTableC1pp.234237fordescriptionofsector9to28. SM16 0.0040 0.0053 0.0078 0.0068 0.0061 0.0064 0.0061 0.0063 0.0065 0.0066 0.0069 0.0072 0.0076 0.0080 0.0085 0.0090 0.0099 0.0090 0.0076 0.0074 SM17 0.0030 0.0030 0.0030 0.0029 0.0028 0.0035 0.0034 0.0021 0.0016 0.0012 0.0011 0.0010 0.0010 0.0011 0.0013 0.0015 0.0022 0.0022 0.0019 0.0021 SM18 0.0111 0.0113 0.0115 0.0110 0.0106 0.0113 0.0122 0.0127 0.0132 0.0135 0.0139 0.0142 0.0146 0.0141 0.0137 0.0134 0.0157 0.0158 0.0164 0.0165 SM19 0.0289 0.0311 0.0331 0.0336 0.0341 0.0353 0.0372 0.0295 0.0246 0.0204 0.0207 0.0209 0.0211 0.0217 0.0222 0.0227 0.0179 0.0177 0.0187 0.0199 0.7498 0.7460 0.7391 0.7403 0.7404 0.7449 0.7450 0.7449 0.7388 0.7299 0.7258 0.7215 0.7167 0.7107 0.7045 0.6979 0.6866 0.6769 0.6821 0.6738 SM20 268 0.2068 0.1892 0.1869 0.1532 0.1814 0.1743 0.1672 0.1583 0.1442 0.1307 0.1169 0.1065 0.0964 0.0865 0.0872 0.0738 0.0834 0.0963 0.0936 0.0900 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 SM1 1980 SM2 0.1491 0.1474 0.1444 0.1352 0.1269 0.1563 0.1532 0.1550 0.1546 0.1531 0.1426 0.1331 0.1237 0.1229 0.1215 0.1198 0.1257 0.1015 0.0896 0.0892 0.1228 0.1239 0.1238 0.1343 0.1440 0.1513 0.1493 0.1446 0.1388 0.1324 0.1373 0.1400 0.1420 0.1438 0.1444 0.1447 0.1673 0.1675 0.1941 0.1864 SM3 SM4 0.0250 0.0284 0.0320 0.0323 0.0322 0.0287 0.0262 0.0273 0.0279 0.0284 0.0309 0.0329 0.0350 0.0315 0.0290 0.0266 0.0291 0.0265 0.0257 0.0227 0.0168 0.0166 0.0162 0.0161 0.0159 0.0161 0.0158 0.0153 0.0146 0.0140 0.0145 0.0149 0.0152 0.0148 0.0144 0.0140 0.0135 0.0137 0.0154 0.0132 SM5 0.0361 0.0352 0.0341 0.0332 0.0323 0.0342 0.0299 0.0267 0.0241 0.0217 0.0203 0.0190 0.0177 0.0184 0.0189 0.0195 0.0203 0.0190 0.0182 0.0167 SM6 TableC8 0.0029 0.0033 0.0038 0.0036 0.0034 0.0035 0.0034 0.0029 0.0025 0.0022 0.0022 0.0022 0.0022 0.0022 0.0022 0.0021 0.0019 0.0021 0.0022 0.0019 SM7 0.0170 0.0182 0.0193 0.0207 0.0219 0.0231 0.0214 0.0234 0.0253 0.0270 0.0228 0.0199 0.0172 0.0175 0.0176 0.0176 0.0232 0.0225 0.0255 0.0302 SM8 0.0928 0.0904 0.0875 0.0947 0.1013 0.0993 0.1195 0.1257 0.1301 0.1338 0.1262 0.1189 0.1114 0.1169 0.1212 0.1254 0.1169 0.1109 0.1131 0.1288 SM9 0.0046 0.0056 0.0070 0.0074 0.0078 0.0082 0.0078 0.0098 0.0153 0.0235 0.0159 0.0123 0.0094 0.0078 0.0068 0.0060 0.0065 0.0079 0.0062 0.0066 SM10 0.0749 0.0823 0.0897 0.0845 0.0797 0.0797 0.0771 0.0677 0.0604 0.0535 0.0540 0.0537 0.0531 0.0523 0.0513 0.0503 0.0461 0.0506 0.0450 0.0385 SM11 0.0116 0.0086 0.0068 0.0069 0.0070 0.0072 0.0071 0.0056 0.0046 0.0038 0.0039 0.0039 0.0039 0.0042 0.0044 0.0046 0.0035 0.0040 0.0038 0.0031 SM12 0.0001 0.0001 0.0001 0.0001 0.0001 0.0002 0.0002 0.0002 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0002 0.0002 0.0002 SM13 0.0006 0.0008 0.0012 0.0014 0.0018 0.0005 0.0012 0.0012 0.0011 0.0011 0.0010 0.0009 0.0009 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 SM14 InputfactorcostsforMaterialsubmodel:Export Source: ABS(various). Notes: Si=Expenditureshareoffactori; M1toM20correspondstosector9to28.SeeTableC1pp.234237fordescriptionofsector9to28. SM15 0.0250 0.0234 0.0219 0.0216 0.0211 0.0241 0.0264 0.0259 0.0251 0.0242 0.0237 0.0230 0.0222 0.0222 0.0220 0.0218 0.0262 0.0242 0.0234 0.0215 SM16 0.0239 0.0176 0.0139 0.0145 0.0150 0.0288 0.0330 0.0331 0.0328 0.0322 0.0354 0.0383 0.0412 0.0421 0.0425 0.0429 0.0359 0.0339 0.0336 0.0304 SM17 0.0113 0.0122 0.0132 0.0139 0.0145 0.0209 0.0179 0.0183 0.0183 0.0183 0.0213 0.0248 0.0288 0.0323 0.0360 0.0400 0.0840 0.0863 0.0852 0.0810 SM18 0.0595 0.0518 0.0457 0.0505 0.0553 0.0674 0.0639 0.0555 0.0492 0.0432 0.0466 0.0494 0.0521 0.0457 0.0412 0.0372 0.0436 0.0416 0.0394 0.0352 SM19 0.0255 0.0234 0.0216 0.0218 0.0218 0.0297 0.0308 0.0334 0.0358 0.0380 0.0389 0.0392 0.0393 0.0405 0.0413 0.0420 0.0002 0.0002 0.0005 0.0005 0.2106 0.2172 0.2217 0.2240 0.2243 0.1337 0.1292 0.1320 0.1328 0.1327 0.1318 0.1292 0.1262 0.1177 0.1108 0.1042 0.1029 0.1005 0.0897 0.0869 SM20 269 270 APPENDIXD CO2EmissionsforPPPandSRP This appendix presents the result of CO2 emissions and percentage responsibility of theseemissionsbasedonPPPandSRP.ItcontainsthefollowingTables: Table Title Page D1 CO2emissions:PPP 271 D2 CO2responsibility:PPP 272 D3 CO2emissions:SRP 273 D4 CO2responsibility:SRP 274 Note: 1980 4,337 6,969 1,383 82,697 677 910 na 2,919 2,365 2,842 525 2,538 7,774 5,242 21,855 10,392 336 544 6 108 2,647 12,720 1,966 6,764 5,583 171 2,702 186,974 1981 3,868 6,652 1,327 85,153 818 1,584 na 3,019 1,764 2,624 478 2,406 7,312 5,487 22,925 10,261 337 511 7 82 2,599 12,958 1,951 6,705 5,565 175 2,503 189,070 1982 3,779 6,701 1,380 91,781 817 1,804 na 3,316 1,545 2,465 446 2,451 7,170 5,581 20,613 9,452 321 491 6 58 2,696 13,503 1,935 5,096 5,947 196 2,496 192,046 1983 3,491 6,259 1,368 92,921 873 1,049 na 3,012 1,389 2,280 396 2,349 6,909 5,021 15,937 8,748 286 430 4 48 2,411 13,436 1,760 5,162 5,763 225 2,374 183,903 1984 4,093 6,460 1,369 95,465 957 1,037 na 3,444 1,226 2,359 415 2,307 7,561 4,628 16,274 9,788 271 432 5 47 2,296 14,070 1,891 4,802 5,754 255 2,329 189,534 1987 4,737 6,292 1,229 110,358 583 368 na 3,422 1,693 2,501 489 2,357 7,752 4,844 17,529 11,070 300 425 7 44 2,408 15,162 1,981 4,077 6,716 249 2,538 209,132 1990 5,463 6,587 1,022 126,105 671 1,076 294 3,384 3,341 2,580 462 2,113 8,636 5,372 18,337 12,127 337 485 13 55 2,832 16,868 1,733 3,926 7,525 281 2,808 234,437 TableD1 CO2emissions:PPP 1993 6,112 7,063 844 132,824 486 779 317 3,580 3,721 2,671 459 1,955 9,269 4,822 17,635 13,255 313 463 12 54 2,875 17,234 1,630 3,193 9,652 313 3,011 244,544 ThisTableshowstheresultsobtainedbytheapplicationofEquation53,asdetailedinSection5.2.1,p.101. 1.Coalsector 2.Petroleumsector 3.Gassector 4.Renewableelectricity 5.Coalfiredelectricity 6.Internalcombustionelectricity 7.Gasturbineelectricity 8.Combinedcycleelectricity 9.Agriculture,forestryandfishing 10.RawmaterialsMining 11.Food,beveragesandtobacco 12.Textile,clothing,footwearandleather 13.Wood,paperandprintingproducts 14.Basicchemicals 15.Nonmetallicmineralproducts 16.Basicironandsteel 17.Basicnonferrousmetals 18.Fabricatedmetalproducts 19.Machineryandequipment 20.Miscellenousmanufacturing 21.Water,sewerageanddrainage 22.Construction 23.Roadtransport 24.Railwaytransport 25.Watertransport 26.Airtransport 27.Othertransport,servicesandstorage 28.Commercialservices Total 1994 5,620 7,287 783 135,018 490 712 315 3,696 4,615 2,839 467 2,100 9,510 5,086 18,108 13,559 322 472 15 56 2,971 17,740 1,595 3,261 10,010 371 3,036 250,054 1995 7,657 7,452 771 140,143 553 1,224 334 3,812 3,510 2,935 493 2,112 9,890 5,210 18,049 13,697 358 507 15 58 3,058 18,249 1,545 4,357 11,238 414 3,181 260,820 1997 9,178 6,912 737 151,026 457 1,669 546 3,974 3,911 2,900 478 2,308 8,949 4,869 17,635 13,797 351 521 15 63 3,142 19,145 1,555 4,288 12,630 453 3,305 274,817 1999 9,341 7,216 690 168,101 399 1,811 2,358 4,151 3,913 2,859 450 2,171 9,448 5,070 17,013 13,899 372 542 15 69 3,365 19,848 1,733 3,577 12,415 550 3,542 294,918 2002 9,174 7,958 931 178,187 607 3,374 4,868 5,465 4,644 2,458 410 1,826 8,898 6,182 14,894 14,406 131 322 16 84 1,905 20,524 1,554 3,779 11,961 1,018 3,748 309,323 (‘000tonnes) 271 Note: 1980 2.32 3.73 0.74 44.23 0.36 0.49 na 1.56 1.27 1.52 0.28 1.36 4.16 2.80 11.69 5.56 0.18 0.29 0.00 0.06 1.42 6.80 1.05 3.62 2.99 0.09 1.44 1981 2.05 3.52 0.70 45.04 0.43 0.84 na 1.60 0.93 1.39 0.25 1.27 3.87 2.90 12.13 5.43 0.18 0.27 0.00 0.04 1.37 6.85 1.03 3.55 2.94 0.09 1.32 1982 1.97 3.49 0.72 47.79 0.43 0.94 na 1.73 0.80 1.28 0.23 1.28 3.73 2.91 10.73 4.92 0.17 0.26 0.00 0.03 1.40 7.03 1.01 2.65 3.10 0.10 1.30 1984 2.16 3.41 0.72 50.37 0.50 0.55 na 1.82 0.65 1.24 0.22 1.22 3.99 2.44 8.59 5.16 0.14 0.23 0.00 0.02 1.21 7.42 1.00 2.53 3.04 0.13 1.23 1987 2.27 3.01 0.59 52.77 0.28 0.18 na 1.64 0.81 1.20 0.23 1.13 3.71 2.32 8.38 5.29 0.14 0.20 0.00 0.02 1.15 7.25 0.95 1.95 3.21 0.12 1.21 1990 2.33 2.81 0.44 53.79 0.29 0.46 0.13 1.44 1.43 1.10 0.20 0.90 3.68 2.29 7.82 5.17 0.14 0.21 0.01 0.02 1.21 7.20 0.74 1.67 3.21 0.12 1.20 CO2responsibility:PPP 1983 1.90 3.40 0.74 50.53 0.47 0.57 na 1.64 0.76 1.24 0.22 1.28 3.76 2.73 8.67 4.76 0.16 0.23 0.00 0.03 1.31 7.31 0.96 2.81 3.13 0.12 1.29 TableD2 ThisTableshowsthepercentageofsectoralCO2emissions,calculatedfromTableD1. 1.Coalsector 2.Petroleumsector 3.Gassector 4.Renewableelectricity 5.Coalfiredelectricity 6.Internalcombustionelectricity 7.Gasturbineelectricity 8.Combinedcycleelectricity 9.Agriculture,forestryandfishing 10.RawmaterialsMining 11.Food,beveragesandtobacco 12.Textile,clothing,footwearandleather 13.Wood,paperandprintingproducts 14.Basicchemicals 15.Nonmetallicmineralproducts 16.Basicironandsteel 17.Basicnonferrousmetals 18.Fabricatedmetalproducts 19.Machineryandequipment 20.Miscellenousmanufacturing 21.Water,sewerageanddrainage 22.Construction 23.Roadtransport 24.Railwaytransport 25.Watertransport 26.Airtransport 27.Othertransport,servicesandstorage 28.Commercialservices 1993 2.50 2.89 0.35 54.31 0.20 0.32 0.13 1.46 1.52 1.09 0.19 0.80 3.79 1.97 7.21 5.42 0.13 0.19 0.00 0.02 1.18 7.05 0.67 1.31 3.95 0.13 1.23 1994 2.25 2.91 0.31 54.00 0.20 0.28 0.13 1.48 1.85 1.14 0.19 0.84 3.80 2.03 7.24 5.42 0.13 0.19 0.01 0.02 1.19 7.09 0.64 1.30 4.00 0.15 1.21 1995 2.94 2.86 0.30 53.73 0.21 0.47 0.13 1.46 1.35 1.13 0.19 0.81 3.79 2.00 6.92 5.25 0.14 0.19 0.01 0.02 1.17 7.00 0.59 1.67 4.31 0.16 1.22 1997 3.34 2.51 0.27 54.96 0.17 0.61 0.20 1.45 1.42 1.06 0.17 0.84 3.26 1.77 6.42 5.02 0.13 0.19 0.01 0.02 1.14 6.97 0.57 1.56 4.60 0.16 1.20 1999 3.17 2.45 0.23 57.00 0.14 0.61 0.80 1.41 1.33 0.97 0.15 0.74 3.20 1.72 5.77 4.71 0.13 0.18 0.01 0.02 1.14 6.73 0.59 1.21 4.21 0.19 1.20 2002 2.97 2.57 0.30 57.61 0.20 1.09 1.57 1.77 1.50 0.79 0.13 0.59 2.88 2.00 4.81 4.66 0.04 0.10 0.01 0.03 0.62 6.64 0.50 1.22 3.87 0.33 1.21 (percent) 272 Note: 1980 3,416 5,094 886 300 31,004 256 358 na 6,465 3,884 20,863 3,088 2,377 3,862 650 6,645 11,641 1,353 5,669 571 215 7,354 2,821 6,859 6,319 1,932 53,095 186,974 1981 3,220 4,417 856 343 32,267 311 642 na 5,597 3,855 21,551 3,770 2,632 3,805 630 5,105 10,071 1,416 5,351 561 308 7,374 2,991 6,592 6,357 1,856 57,193 189,070 1982 3,477 4,788 970 352 35,000 316 734 na 6,606 4,204 19,567 2,828 2,594 3,336 733 2,875 10,175 1,356 5,265 416 253 2,994 6,494 3,604 5,376 6,341 1,808 59,585 192,046 1984 4,523 4,533 693 285 35,117 357 395 na 7,302 3,442 18,148 2,560 2,395 3,323 365 2,673 10,960 858 3,346 385 156 2,904 6,580 4,308 3,653 5,382 2,875 62,018 189,534 1987 6,322 5,245 684 254 38,723 209 132 na 6,588 4,581 17,615 3,048 2,681 3,209 462 2,779 12,362 1,330 3,279 380 188 2,963 6,520 4,426 2,979 7,029 3,155 71,987 209,132 1990 5,401 5,075 668 180 42,057 171 351 249 7,688 6,962 17,059 2,846 3,046 3,847 611 4,243 14,891 1,948 4,816 427 131 2,401 7,982 4,199 2,644 6,859 3,249 84,437 234,437 CO2emissions:SRP 1983 4,135 4,745 835 324 35,412 337 426 na 5,564 4,189 19,814 2,651 2,321 3,121 466 790 9,395 724 3,455 350 248 3,215 6,146 3,670 5,257 6,095 1,806 58,412 183,903 TableD3 1993 7,349 4,488 780 175 49,715 150 360 270 6,158 9,426 18,852 2,363 2,554 4,823 457 3,293 16,145 787 4,047 677 137 785 8,412 3,091 2,376 8,605 5,981 82,288 244,544 ThisTableshowstheresultsobtainedbytheapplicationofEquation58,asdetailedinSection5.2.2,p.104. 1.Coalsector 2.Petroleumsector 3.Gassector 4.Renewableelectricity 5.Coalfiredelectricity 6.Internalcombustionelectricity 7.Gasturbineelectricity 8.Combinedcycleelectricity 9.Agriculture,forestryandfishing 10.RawmaterialsMining 11.Food,beveragesandtobacco 12.Textile,clothing,footwearandleather 13.Wood,paperandprintingproducts 14.Basicchemicals 15.Nonmetallicmineralproducts 16.Basicironandsteel 17.Basicnonferrousmetals 18.Fabricatedmetalproducts 19.Machineryandequipment 20.Miscellenousmanufacturing 21.Water,sewerageanddrainage 22.Construction 23.Roadtransport 24.Railwaytransport 25.Watertransport 26.Airtransport 27.Othertransport,servicesandstorage 28.Commercialservices Total 1994 6,111 3,961 306 166 49,417 136 336 253 5,989 9,017 19,668 2,409 2,999 5,037 629 4,265 15,319 700 3,739 512 394 786 8,840 3,102 2,624 9,482 4,441 89,418 250,054 1995 7,329 5,096 292 185 53,257 174 439 273 5,450 7,087 19,049 3,126 3,074 6,606 714 3,994 19,930 1,008 5,638 659 1,556 1,051 6,984 3,199 3,003 9,290 4,661 87,696 260,820 1997 9,333 5,190 329 198 55,900 162 590 414 7,006 8,281 21,790 3,093 2,926 6,391 832 3,555 19,830 1,265 6,333 535 1,915 1,259 7,616 3,920 3,610 10,241 4,813 87,492 274,817 1999 9,850 6,247 585 193 58,481 142 630 831 6,798 10,204 20,622 2,924 3,831 6,581 905 4,257 19,693 805 6,693 422 2,026 1,067 9,885 3,450 3,366 10,428 6,262 97,742 294,918 2002 9,995 6,650 670 195 61,890 212 1,153 1,674 7,553 11,025 21,582 3,055 3,882 6,565 1,019 4,001 20,748 790 6,710 437 2,141 1,065 10,246 3,467 3,549 10,260 6,718 102,073 309,323 (‘000tonnes) 273 Note: 1980 1.83 2.72 0.47 0.16 16.58 0.14 0.19 na 3.46 2.08 11.16 1.65 1.27 2.07 0.35 3.55 6.23 0.72 3.03 0.31 0.11 3.93 1.51 3.67 3.38 1.03 28.40 1981 1.70 2.34 0.45 0.18 17.07 0.16 0.34 na 2.96 2.04 11.40 1.99 1.39 2.01 0.33 2.70 5.33 0.75 2.83 0.30 0.16 3.90 1.58 3.49 3.36 0.98 30.25 1982 1.81 2.49 0.51 0.18 18.22 0.16 0.38 na 3.44 2.19 10.19 1.47 1.35 1.74 0.38 1.50 5.30 0.71 2.74 0.22 0.13 1.56 3.38 1.88 2.80 3.30 0.94 31.03 1984 2.39 2.39 0.37 0.15 18.53 0.19 0.21 na 3.85 1.82 9.58 1.35 1.26 1.75 0.19 1.41 5.78 0.45 1.77 0.20 0.08 1.53 3.47 2.27 1.93 2.84 1.52 32.72 1987 3.02 2.51 0.33 0.12 18.52 0.10 0.06 na 3.15 2.19 8.42 1.46 1.28 1.53 0.22 1.33 5.91 0.64 1.57 0.18 0.09 1.42 3.12 2.12 1.42 3.36 1.51 34.42 1990 2.30 2.16 0.28 0.08 17.94 0.07 0.15 0.11 3.28 2.97 7.28 1.21 1.30 1.64 0.26 1.81 6.35 0.83 2.05 0.18 0.06 1.02 3.40 1.79 1.13 2.93 1.39 36.02 CO2responsibility:SRP 1983 2.25 2.58 0.45 0.18 19.26 0.18 0.23 na 3.03 2.28 10.77 1.44 1.26 1.70 0.25 0.43 5.11 0.39 1.88 0.19 0.13 1.75 3.34 2.00 2.86 3.31 0.98 31.76 TableD4 ThisTableshowsthepercentageofsectoralCO2emissions,calculatedfromTableD3. 1.Coalsector 2.Petroleumsector 3.Gassector 4.Renewableelectricity 5.Coalfiredelectricity 6.Internalcombustionelectricity 7.Gasturbineelectricity 8.Combinedcycleelectricity 9.Agriculture,forestryandfishing 10.RawmaterialsMining 11.Food,beveragesandtobacco 12.Textile,clothing,footwearandleather 13.Wood,paperandprintingproducts 14.Basicchemicals 15.Nonmetallicmineralproducts 16.Basicironandsteel 17.Basicnonferrousmetals 18.Fabricatedmetalproducts 19.Machineryandequipment 20.Miscellenousmanufacturing 21.Water,sewerageanddrainage 22.Construction 23.Roadtransport 24.Railwaytransport 25.Watertransport 26.Airtransport 27.Othertransport,servicesandstorage 28.Commercialservices 1993 3.00 1.84 0.32 0.07 20.33 0.06 0.15 0.11 2.52 3.85 7.71 0.97 1.04 1.97 0.19 1.35 6.60 0.32 1.66 0.28 0.06 0.32 3.44 1.26 0.97 3.52 2.45 33.65 1994 2.44 1.58 0.12 0.07 19.76 0.05 0.13 0.10 2.40 3.61 7.87 0.96 1.20 2.01 0.25 1.71 6.13 0.28 1.50 0.20 0.16 0.31 3.54 1.24 1.05 3.79 1.78 35.76 1995 2.81 1.95 0.11 0.07 20.42 0.07 0.17 0.10 2.09 2.72 7.30 1.20 1.18 2.53 0.27 1.53 7.64 0.39 2.16 0.25 0.60 0.40 2.68 1.23 1.15 3.56 1.79 33.62 1997 3.40 1.89 0.12 0.07 20.34 0.06 0.21 0.15 2.55 3.01 7.93 1.13 1.06 2.33 0.30 1.29 7.22 0.46 2.30 0.19 0.70 0.46 2.77 1.43 1.31 3.73 1.75 31.84 1999 3.34 2.12 0.20 0.07 19.83 0.05 0.21 0.28 2.30 3.46 6.99 0.99 1.30 2.23 0.31 1.44 6.68 0.27 2.27 0.14 0.69 0.36 3.35 1.17 1.14 3.54 2.12 33.14 2002 3.23 2.15 0.22 0.06 20.01 0.07 0.37 0.54 2.44 3.56 6.98 0.99 1.26 2.12 0.33 1.29 6.71 0.26 2.17 0.14 0.69 0.34 3.31 1.12 1.15 3.32 2.17 33.00 (percent) 274 275 APPENDIXE ComputerProgramOutputforProductionFunctionModel ThisappendixpresentstheoutputofEviewsprogramfortheapplicationTranslogcost function for five electricity generation technologies – coalfired, internal combustion, gasturbine,combinedcycle,andrenewable–andtwofinaldemandcategories–final consumptionandexport.ItcontainsthefollowingTables: Table Title Page E1 ResultsforInterFactorModel 276 E2 ResultsforEnergysubModel 283 276 TableE1Interfactormodel:Coalfiredelectricitygeneration System: ST_KLEM Estimation Method: Three-Stage Least Squares Date: 05/10/05 Time: 16:51 Sample: 1980 1999 Included observations: 20 Total system (balanced) observations 100 Linear estimation after one-step weighting matrix Coefficient Std. Error t-Statistic C(1) 0.341274 0.022098 15.443940 C(6) 0.002371 0.041725 0.056823 C(7) 0.026931 0.021534 1.250598 C(8) -0.062110 0.021807 -2.848145 C(9) -0.008275 0.004756 -1.739860 C(2) 0.213863 0.011443 18.689290 C(11) -0.097195 0.032152 -3.023023 C(12) 0.028219 0.014294 1.974128 C(13) 0.043551 0.009346 4.659846 C(3) 0.202706 0.012089 16.767580 C(15) 0.156924 0.021127 7.427672 C(16) -0.033098 0.007946 -4.165156 C(4) 0.069920 0.002425 28.829910 C(18) 0.067566 0.013123 5.148619 Determinant residual covariance 3.81E-24 Equation: SK = C(1) + C(6)*LOG(PK) + C(7)*LOG(PL) + C(8)*LOG(PE) + C(9)*LOG(PEL) + (-(C(6)+C(7)+C(8)+C(9)))*LOG(PM) Instruments: LOG(PK) LOG(PL) LOG(PE) LOG(PEL) LOG(PM) C Observations: 20 R-squared 0.848170 Mean dependent var Adjusted R-squared 0.829016 S.D. dependent var S.E. of regression 0.065431 Sum squared resid Durbin-W atson stat 1.335308 Equation: SL = C(2) + C(7)*LOG(PK) + C(11)*LOG(PL) + C(12)*LOG(PE) + C(13)*LOG(PEL) + (-(C(7)+C(11)+C(12)+C(13)))*LOG(PM) Instruments: LOG(PK) LOG(PL) LOG(PE) LOG(PEL) LOG(PM) C Observations: 20 R-squared 0.910381 Mean dependent var Adjusted R-squared 0.879816 S.D. dependent var S.E. of regression 0.031690 Sum squared resid Durbin-W atson stat 1.562673 Equation: SE = C(3) + C(8)*LOG(PK) + C(12)*LOG(PL) + C(15)*LOG(PE) + C(16)*LOG(PEL) + (-(C(8)+C(12)+C(15)+C(16)))*LOG(PM) Instruments: LOG(PK) LOG(PL) LOG(PE) LOG(PEL) LOG(PM) C Observations: 20 R-squared 0.868023 Mean dependent var Adjusted R-squared 0.806163 S.D. dependent var S.E. of regression 0.024739 Sum squared resid Durbin-W atson stat 1.611085 Equation: SEL = C(4) + C(9)*LOG(PK) + C(13)*LOG(PL) + C(16)*LOG(PE) + C(18)*LOG(PEL) + (-(C(9)+C(13)+C(16)+C(18)))*LOG(PM) Instruments: LOG(PK) LOG(PL) LOG(PE) LOG(PEL) LOG(PM) C Observations: 20 R-squared 0.784782 Mean dependent var Adjusted R-squared 0.768057 S.D. dependent var S.E. of regression 0.004366 Sum squared resid Durbin-W atson stat 1.814149 Equation: SM = (1 - (C(1)+C(2)+C(3)+C(4))) + (-(C(6)+C(7)+C(8)+C(9)))*LOG(PK) + (-(C(7)+C(11)+C(12)+C(13)))*LOG(PL) + (-(C(8)+C(12)+C(15)+C(16)))*LOG(PE) + (-(C(9)+C(13)+C(16)+C(18)))*LOG(PEL) + (-((-(C(6)+C(7)+C(8)+C(9))) +(-(C(7)+C(11)+C(12) +C(13)))+(-(C(8)+C(12)+C(15)+C(16)))+(-(C(9)+C(13)+C(16)+C(18)))))*LOG(PM) Instruments: LOG(PK) LOG(PL) LOG(PE) LOG(PEL) LOG(PM) C Observations: 20 R-squared 0.827909 Mean dependent var Adjusted R-squared 0.808288 S.D. dependent var S.E. of regression 0.061870 Sum squared resid Durbin-W atson stat 1.287121 Prob. 0.0000 0.9548 0.2145 0.0055 0.0855 0.0000 0.0033 0.0516 0.0000 0.0000 0.0000 0.0001 0.0000 0.0000 0.336620 0.070929 0.064219 0.197330 0.040240 0.015063 0.241605 0.045638 0.009180 0.076510 0.003579 0.000286 0.147940 0.039066 0.022968 277 TableE1Interfactormodel:Internalcombustionelectricitygeneration System: IC_KLEM Estimation Method: Three-Stage Least Squares Date: 05/10/05 Time: 17:47 Sample: 1980 1999 Included observations: 20 Total system (balanced) observations 100 Linear estimation after one-step weighting matrix Coefficient Std. Error t-Statistic C(1) 0.274725 0.014247 19.282880 C(6) 0.103652 0.022054 4.699826 C(7) -0.008415 0.014363 -0.585858 C(8) -0.137018 0.017750 -7.719166 C(9) 0.008393 0.008851 0.948238 C(2) 0.038132 0.008035 4.745692 C(11) -0.060663 0.018200 -3.333131 C(12) 0.018685 0.011781 1.585988 C(13) 0.031825 0.012165 2.616200 C(3) 0.587325 0.015119 38.845680 C(15) 0.120893 0.023985 5.040244 C(16) -0.006641 0.007673 -0.865393 C(4) 0.016725 0.003541 4.722773 C(18) 0.034174 0.015091 2.264541 Determinant residual covariance 3.53E-25 Equation: SK = C(1) + C(6)*LOG(PK) + C(7)*LOG(PL) + C(8)*LOG(PE) + C(9)*LOG(PEL) + (-(C(6)+C(7)+C(8)+C(9)))*LOG(PM) Instruments: LOG(PK) LOG(PL) LOG(PE) LOG(PEL) LOG(PM) C Observations: 20 R-squared 0.809896 Mean dependent var Adjusted R-squared 0.732534 S.D. dependent var S.E. of regression 0.039762 Sum squared resid Durbin-W atson stat 1.849748 Equation: SL = C(2) + C(7)*LOG(PK) + C(11)*LOG(PL) + C(12)*LOG(PE) + C(13)*LOG(PEL) + (-(C(7)+C(11)+C(12)+C(13)))*LOG(PM) Instruments: LOG(PK) LOG(PL) LOG(PE) LOG(PEL) LOG(PM) C Observations: 20 R-squared 0.905126 Mean dependent var Adjusted R-squared 0.846493 S.D. dependent var S.E. of regression 0.016035 Sum squared resid Durbin-W atson stat 1.627766 Equation: SE = C(3) + C(8)*LOG(PK) + C(12)*LOG(PL) + C(15)*LOG(PE) + C(16)*LOG(PEL) + (-(C(8)+C(12)+C(15)+C(16)))*LOG(PM) Instruments: LOG(PK) LOG(PL) LOG(PE) LOG(PEL) LOG(PM) C Observations: 20 R-squared 0.965889 Mean dependent var Adjusted R-squared 0.876792 S.D. dependent var S.E. of regression 0.052200 Sum squared resid Durbin-W atson stat 1.676302 Equation: SEL = C(4) + C(9)*LOG(PK) + C(13)*LOG(PL) + C(16)*LOG(PE) + C(18)*LOG(PEL) + (-(C(9)+C(13)+C(16)+C(18)))*LOG(PM) Instruments: LOG(PK) LOG(PL) LOG(PE) LOG(PEL) LOG(PM) C Observations: 20 R-squared 0.896719 Mean dependent var Adjusted R-squared 0.862511 S.D. dependent var S.E. of regression 0.003762 Sum squared resid Durbin-W atson stat 1.020955 Equation: SM = (1 - (C(1)+C(2)+C(3)+C(4))) + (-(C(6)+C(7)+C(8)+C(9)))*LOG(PK) + (-(C(7)+C(11)+C(12)+C(13)))*LOG(PL) + (-(C(8)+C(12)+C(15)+C(16)))*LOG(PE) + (-(C(9)+C(13)+C(16)+C(18)))*LOG(PEL) + (-((-(C(6)+C(7)+C(8)+C(9))) +(-(C(7)+C(11)+C(12) +C(13)))+(-(C(8)+C(12)+C(15)+C(16)))+(-(C(9)+C(13)+C(16)+C(18)))))*LOG(PM) Instruments: LOG(PK) LOG(PL) LOG(PE) LOG(PEL) LOG(PM) C Observations: 20 R-squared 0.807753 Mean dependent var Adjusted R-squared 0.788781 S.D. dependent var S.E. of regression 0.035590 Sum squared resid Durbin-W atson stat 1.409083 Prob. 0.0000 0.0000 0.5595 0.0000 0.3457 0.0000 0.0013 0.1164 0.0105 0.0000 0.0000 0.3892 0.0000 0.0261 0.197755 0.065594 0.023716 0.041100 0.018473 0.003857 0.674215 0.080241 0.040873 0.015335 0.004711 0.000212 0.071590 0.022470 0.007600 278 TableE1Interfactormodel:Gasturbineelectricitygeneration System: GT_KLEM Estimation Method: Three-Stage Least Squares Date: 05/11/05 Time: 14:33 Sample: 1980 1999 Included observations: 20 Total system (balanced) observations 100 Linear estimation after one-step weighting matrix Coefficient Std. Error t-Statistic C(1) 0.458010 0.057537 7.960307 C(6) 0.145719 0.108343 1.344971 C(7) -0.056441 0.054153 -1.042246 C(8) -0.091127 0.052867 -1.723705 C(9) -0.006290 0.013148 -0.478419 C(2) 0.119654 0.028927 4.136385 C(11) -0.253854 0.046172 -5.497960 C(12) 0.134530 0.036259 3.710238 C(13) -0.077934 0.011584 -6.727491 C(3) 0.277487 0.027973 9.919891 C(15) 0.000131 0.045034 0.002915 C(16) 0.030061 0.010108 2.974029 C(4) 0.049438 0.007030 7.032161 C(18) -0.040218 0.007217 -5.572764 Determinant residual covariance 7.71E-24 Equation: SK = C(1) + C(6)*LOG(PK) + C(7)*LOG(PL) + C(8)*LOG(PE) + C(9)*LOG(PEL) + (-(C(6)+C(7)+C(8)+C(9)))*LOG(PM) Instruments: LOG(PK) LOG(PL) LOG(PE) LOG(PEL) LOG(PM) C Observations: 20 R-squared 0.870281 Mean dependent var Adjusted R-squared 0.857644 S.D. dependent var S.E. of regression 0.134278 Sum squared resid Durbin-W atson stat 1.395485 Equation: SL = C(2) + C(7)*LOG(PK) + C(11)*LOG(PL) + C(12)*LOG(PE) + C(13)*LOG(PEL) + (-(C(7)+C(11)+C(12)+C(13)))*LOG(PM) Instruments: LOG(PK) LOG(PL) LOG(PE) LOG(PEL) LOG(PM) C Observations: 20 R-squared 0.887505 Mean dependent var Adjusted R-squared 0.829160 S.D. dependent var S.E. of regression 0.068256 Sum squared resid Durbin-W atson stat 1.439771 Equation: SE = C(3) + C(8)*LOG(PK) + C(12)*LOG(PL) + C(15)*LOG(PE) + C(16)*LOG(PEL) + (-(C(8)+C(12)+C(15)+C(16)))*LOG(PM) Instruments: LOG(PK) LOG(PL) LOG(PE) LOG(PEL) LOG(PM) C Observations: 20 R-squared 0.947993 Mean dependent var Adjusted R-squared 0.879209 S.D. dependent var S.E. of regression 0.063485 Sum squared resid Durbin-W atson stat 1.538049 Equation: SEL = C(4) + C(9)*LOG(PK) + C(13)*LOG(PL) + C(16)*LOG(PE) + C(18)*LOG(PEL) + (-(C(9)+C(13)+C(16)+C(18)))*LOG(PM) Instruments: LOG(PK) LOG(PL) LOG(PE) LOG(PEL) LOG(PM) C Observations: 20 R-squared 0.890397 Mean dependent var Adjusted R-squared 0.852163 S.D. dependent var S.E. of regression 0.016490 Sum squared resid Durbin-W atson stat 1.499896 Equation: SM = (1 - (C(1)+C(2)+C(3)+C(4))) + (-(C(6)+C(7)+C(8)+C(9)))*LOG(PK) + (-(C(7)+C(11)+C(12)+C(13)))*LOG(PL) + (-(C(8)+C(12)+C(15)+C(16)))*LOG(PE) + (-(C(9)+C(13)+C(16)+C(18)))*LOG(PEL) + (-((-(C(6)+C(7)+C(8)+C(9))) +(-(C(7)+C(11)+C(12) +C(13)))+(-(C(8)+C(12)+C(15)+C(16)))+(-(C(9)+C(13)+C(16)+C(18)))))*LOG(PM) Instruments: LOG(PK) LOG(PL) LOG(PE) LOG(PEL) LOG(PM) C Observations: 20 R-squared 0.857954 Mean dependent var Adjusted R-squared 0.841478 S.D. dependent var S.E. of regression 0.038914 Sum squared resid Durbin-W atson stat 1.756093 Prob. 0.0000 0.1822 0.3002 0.0884 0.6336 0.0001 0.0000 0.0004 0.0000 0.0000 0.9977 0.0038 0.0000 0.0000 0.388745 0.123737 0.270460 0.124940 0.067282 0.069883 0.327595 0.061111 0.060456 0.045810 0.015363 0.004079 0.112910 0.034925 0.009086 279 TableE1Interfactormodel:Combinedcycleelectricitygeneration System: CC_KLEM Estimation Method: Three-Stage Least Squares Date: 05/11/05 Time: 14:47 Sample: 1988 1999 Included observations: 12 Total system (balanced) observations 60 Linear estimation after one-step weighting matrix Coefficient Std. Error t-Statistic C(1) 0.220200 0.009089 24.226140 C(6) 0.045698 0.016425 2.782258 C(7) -0.005053 0.016177 -0.312376 C(8) -0.092215 0.026179 -3.522459 C(9) 0.015730 0.002881 5.459862 C(2) 0.206960 0.009931 20.840380 C(11) -0.273499 0.028134 -9.721330 C(12) 0.148319 0.026875 5.518749 C(13) -0.031467 0.006952 -4.526143 C(3) 0.401449 0.013309 30.164640 C(15) 0.144785 0.060750 2.383303 C(16) 0.014494 0.007501 1.932279 C(4) 0.093999 0.001546 60.790880 C(18) 0.007851 0.003795 2.068732 Determinant residual covariance 5.67E-28 Equation: SK = C(1) + C(6)*LOG(PK) + C(7)*LOG(PL) + C(8)*LOG(PE) + C(9)*LOG(PEL) + (-(C(6)+C(7)+C(8)+C(9)))*LOG(PM) Instruments: LOG(PK) LOG(PL) LOG(PE) LOG(PEL) LOG(PM) C Observations: 12 R-squared 0.903423 Mean dependent var Adjusted R-squared 0.833950 S.D. dependent var S.E. of regression 0.029889 Sum squared resid Durbin-W atson stat 1.809763 Equation: SL = C(2) + C(7)*LOG(PK) + C(11)*LOG(PL) + C(12)*LOG(PE) + C(13)*LOG(PEL) + (-(C(7)+C(11)+C(12)+C(13)))*LOG(PM) Instruments: LOG(PK) LOG(PL) LOG(PE) LOG(PEL) LOG(PM) C Observations: 12 R-squared 0.908620 Mean dependent var Adjusted R-squared 0.827832 S.D. dependent var S.E. of regression 0.026198 Sum squared resid Durbin-W atson stat 1.547499 Equation: SE = C(3) + C(8)*LOG(PK) + C(12)*LOG(PL) + C(15)*LOG(PE) + C(16)*LOG(PEL) + (-(C(8)+C(12)+C(15)+C(16)))*LOG(PM) Instruments: LOG(PK) LOG(PL) LOG(PE) LOG(PEL) LOG(PM) C Observations: 12 R-squared 0.886778 Mean dependent var Adjusted R-squared 0.863509 S.D. dependent var S.E. of regression 0.035206 Sum squared resid Durbin-W atson stat 1.941757 Equation: SEL = C(4) + C(9)*LOG(PK) + C(13)*LOG(PL) + C(16)*LOG(PE) + C(18)*LOG(PEL) + (-(C(9)+C(13)+C(16)+C(18)))*LOG(PM) Instruments: LOG(PK) LOG(PL) LOG(PE) LOG(PEL) LOG(PM) C Observations: 12 R-squared 0.915463 Mean dependent var Adjusted R-squared 0.867156 S.D. dependent var S.E. of regression 0.004071 Sum squared resid Durbin-W atson stat 1.376993 Equation: SM = (1 - (C(1)+C(2)+C(3)+C(4))) + (-(C(6)+C(7)+C(8)+C(9)))*LOG(PK) + (-(C(7)+C(11)+C(12)+C(13)))*LOG(PL) + (-(C(8)+C(12)+C(15)+C(16)))*LOG(PE) + (-(C(9)+C(13)+C(16)+C(18)))*LOG(PEL) + (-((-(C(6)+C(7)+C(8)+C(9))) +(-(C(7)+C(11)+C(12) +C(13)))+(-(C(8)+C(12)+C(15)+C(16)))+(-(C(9)+C(13)+C(16)+C(18)))))*LOG(PM) Instruments: LOG(PK) LOG(PL) LOG(PE) LOG(PEL) LOG(PM) C Observations: 12 R-squared 0.740004 Mean dependent var S.D. dependent var 0.030764 Sum squared resid Durbin-W atson stat 1.277807 Prob. 0.0000 0.0078 0.7562 0.0010 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0213 0.0595 0.0000 0.0442 0.203192 0.022698 0.006253 0.176983 0.029813 0.004804 0.450075 0.039202 0.008676 0.082767 0.011169 0.000116 0.086992 0.002707 280 TableE1Interfactormodel:Renewableelectricitygeneration System: RE_KLEM Estimation Method: Three-Stage Least Squares Date: 05/11/05 Time: 16:42 Sample: 1980 1999 Included observations: 20 Total system (balanced) observations 80 Linear estimation after one-step weighting matrix Coefficient Std. Error t-Statistic Prob. C(1) 0.696047 0.029709 23.428720 0.0000 C(6) 0.004691 0.054898 0.085447 0.9321 C(7) -0.009330 0.036465 -0.255852 0.7988 C(9) -0.032514 0.024044 -1.352280 0.1806 C(2) 0.155272 0.020058 7.741284 0.0000 C(11) -0.080099 0.037929 -2.111804 0.0382 C(13) 0.094229 0.020799 4.530461 0.0000 C(4) 0.033256 0.012339 2.695307 0.0088 C(18) 0.101763 0.034530 2.947095 0.0043 Determinant residual covariance 1.00E-19 Equation: SK = C(1) + C(6)*LOG(PK) + C(7)*LOG(PL) + C(9)*LOG(PEL) + (-(C(6)+C(7)+C(9)))*LOG(PM) Instruments: LOG(PK) LOG(PL) LOG(PEL) LOG(PM) C Observations: 20 R-squared 0.892588 Mean dependent var 0.693630 Adjusted R-squared 0.877552 S.D. dependent var 0.078962 S.E. of regression 0.081967 Sum squared resid 0.107496 Durbin-W atson stat 1.210336 Equation: SL = C(2) + C(7)*LOG(PK) + C(11)*LOG(PL) + C(13)*LOG(PEL) + (-(C(7)+C(11)+C(13)))*LOG(PM) Instruments: LOG(PK) LOG(PL) LOG(PEL) LOG(PM) C Observations: 20 R-squared 0.844972 Mean dependent var 0.152940 Adjusted R-squared 0.822155 S.D. dependent var 0.063191 S.E. of regression 0.055731 Sum squared resid 0.049695 Durbin-W atson stat 1.301576 Equation: SEL = C(4) + C(9)*LOG(PK) + C(13)*LOG(PL) + C(18)*LOG(PEL) + (-(C(9)+C(13)+C(18)))*LOG(PM) Instruments: LOG(PK) LOG(PL) LOG(PEL) LOG(PM) C Observations: 20 R-squared 0.936649 Mean dependent var 0.057035 Adjusted R-squared 0.909770 S.D. dependent var 0.011219 S.E. of regression 0.008322 Sum squared resid 0.001108 Durbin-W atson stat 1.759978 Equation: SM = (1 - (C(1)+C(2)+C(4))) + (-(C(6)+C(7)+C(9)))*LOG(PK) + (-(C(7)+C(11)+C(13)))*LOG(PL) + (-(C(9)+C(13)+C(18)))*LOG(PEL) + (-((-(C(6)+C(7)+C(9)))+(-(C(7)+C(11)+C(13)))+(-(C(9) +C(13)+C(18)))))*LOG(PM) Instruments: LOG(PK) LOG(PL) LOG(PEL) LOG(PM) C Observations: 20 R-squared 0.876104 Mean dependent var 0.096405 Adjusted R-squared 0.847816 S.D. dependent var 0.025726 S.E. of regression 0.040658 Sum squared resid 0.018184 Durbin-W atson stat 1.300820 281 TableE1Interfactormodel:Finalconsumption System: EM_CONSUMPTION Estimation Method: Three-Stage Least Squares Date: 02/25/07 Time: 03:53 Sample: 1980 1999 Included observations: 20 Total system (balanced) observations 40 Linear estimation after one-step weighting matrix Coefficient Std. Error t-Statistic C(2) C(7) Determinant residual covariance 0.000408 0.001718 0.000000 63.774988 14.370906 Equation: SE = C(2) + C(7)*LOG(PE) + Instruments: LOG(PE) LOG(PM) C Observations: 20 R-squared Adjusted R-squared S.E. of regression Durbin-Watson stat 0.025993 0.024696 (-(C(7)))*LOG(PM) 0.837743 0.828729 0.002362 1.533159 Mean dependent var S.D. dependent var Sum squared resid Equation: SM = (1-(C(2))) + (-(C(7)))*LOG(PE) + (C(7))*LOG(PM) Instruments: LOG(PE) LOG(PM) C Observations: 20 R-squared 0.837743 Mean dependent var Adjusted R-squared 0.828729 S.D. dependent var S.E. of regression 0.002362 Sum squared resid Durbin-Watson stat 1.533159 Prob. 0.000000 0.000000 0.028890 0.005707 0.000100 0.971110 0.005707 0.000100 282 TableE1Interfactormodel:Export System: EM_EXPORT Estimation Method: Three-Stage Least Squares Date: 02/25/07 Time: 05:22 Sample: 1980 1999 Included observations: 20 Total system (balanced) observations 40 Linear estimation after one-step weighting matrix Coefficient Std. Error t-Statistic C(2) C(7) Determinant residual covariance 0.002349 0.006015 0.000000 55.585228 1.423244 Equation: SE = C(2) + C(7)*LOG(PE) + Instruments: LOG(PE) LOG(PM) C Observations: 20 R-squared Adjusted R-squared S.E. of regression Durbin-Watson stat 0.130592 0.008560 Prob. 0.000000 0.032824 (-(C(7)))*LOG(PM) 0.848200 0.804678 0.015505 1.542990 Mean dependent var S.D. dependent var Sum squared resid Equation: SM = (1-(C(2))) + (-(C(7)))*LOG(PE) + (C(7))*LOG(PM) Instruments: LOG(PE) LOG(PM) C Observations: 20 R-squared 0.848200 Mean dependent var Adjusted R-squared 0.804678 S.D. dependent var S.E. of regression 0.015505 Sum squared resid Durbin-Watson stat 1.542990 0.131065 0.015469 0.004327 0.868935 0.015469 0.004327 283 TableE2Energysubmodel:Coalfiredelectricitygeneration System: ST_ENERGY Estimation Method: Three-Stage Least Squares Date: 05/06/05 Time: 13:57 Sample: 1980 1999 Included observations: 20 Total system (balanced) observations 60 Linear estimation after one-step weighting matrix Coefficient Std. Error t-Statistic C(1) 0.717991 0.002246 319.697700 C(4) -0.199790 0.024618 -8.115529 C(5) 0.034164 0.021953 1.556223 C(2) 0.076284 0.002230 34.208880 C(7) 0.221408 0.014854 14.906050 Determinant residual covariance 2.26E-15 Equation: E1 = C(1) + C(4)*LOG(P1) + C(5)*LOG(P2) + (-(C(4)+C(5)))*LOG(P3) Instruments: LOG(P1) LOG(P2) LOG(P3) C Observations: 20 R-squared 0.888702 Mean dependent var Adjusted R-squared 0.862667 S.D. dependent var S.E. of regression 0.040783 Sum squared resid Durbin-W atson stat 1.961381 Equation: E2 = C(2) + C(5)*LOG(P1) + C(7)*LOG(P2) + (-(C(5)+C(7)))*LOG(P3) Instruments: LOG(P1) LOG(P2) LOG(P3) C Observations: 20 R-squared 0.868327 Mean dependent var Adjusted R-squared 0.852836 S.D. dependent var S.E. of regression 0.036027 Sum squared resid Durbin-W atson stat 1.693205 Equation: E3 = (1-(C(1)+C(2))) + (-(C(4)+C(5)))*LOG(P1) + (-(C(5)+C(7)))*LOG(P2) + (-((-(C(4)+C(5)))+(-(C(5)+C(7)))))*LOG(P3) Instruments: LOG(P1) LOG(P2) LOG(P3) C Observations: 20 R-squared 0.789991 Mean dependent var Adjusted R-squared 0.777989 S.D. dependent var S.E. of regression 0.035593 Sum squared resid Durbin-W atson stat 1.007455 Prob. 0.0000 0.0000 0.1254 0.0000 0.0000 0.717080 0.061670 0.028275 0.129105 0.093914 0.022066 0.153820 0.041888 0.019003 284 TableE2Energysubmodel:Gasturbineelectricitygeneration System: GT_ENERGY Estimation Method: Three-Stage Least Squares Date: 05/11/05 Time: 14:13 Sample: 1980 1999 Included observations: 20 Total system (balanced) observations 40 Linear estimation after one-step weighting matrix Coefficient Std. Error C(2) 0.106130 0.013279 C(7) 0.072482 0.033198 Determinant residual covariance 0 Equation: E2 = C(2) + C(7)*LOG(P2) + (-(C(7)))*LOG(P3) Instruments: LOG(P2) LOG(P3) C Observations: 20 R-squared 0.892473 Mean dependent var Adjusted R-squared 0.847610 S.D. dependent var S.E. of regression 0.051195 Sum squared resid Durbin-W atson stat 1.976739 Equation: E3 = (1-(C(2))) + (-(C(7)))*LOG(P2) + (C(7))*LOG(P3) Instruments: LOG(P2) LOG(P3) C Observations: 20 R-squared 0.892473 Mean dependent var Adjusted R-squared 0.847610 S.D. dependent var S.E. of regression 0.051195 Sum squared resid Durbin-W atson stat 1.976739 t-Statistic 7.992205 2.183339 Prob. 0.0000 0.0353 0.122815 0.055451 0.047177 0.877185 0.055451 0.047177 285 TableE2Energysubmodel:Finalconsumption System: FINAL_CONSUMPTION Estimation Method: Three-Stage Least Squares Date: 02/25/07 Time: 02:05 Sample: 1980 1999 Included observations: 20 Total system (balanced) observations 80 Linear estimation after one-step weighting matrix Coefficient Std. Error t-Statistic Prob. C(1) 0.012923 0.005198 2.486259 0.015264 C(5) -0.021889 0.037623 -0.581808 0.562539 C(6) 0.035129 0.020567 1.708062 0.091994 C(7) -0.139821 0.053228 -2.626817 0.010552 C(2) 0.389976 0.016045 24.305824 0.000000 C(9) 0.148386 0.042307 3.507396 0.000789 C(10) 0.040564 0.032217 1.259116 0.212113 C(3) 0.477390 0.009072 52.622505 0.000000 C(12) -0.345279 0.101119 -3.414566 0.001060 Determinant residual covariance 6.09E-17 Equation: S1 = C(1) + C(5)*LOG(P1) + C(6)*LOG(P2) + C(7)*LOG(P3) + (-(C(5)+C(6)+C(7)))*LOG(P4) Instruments: LOG(P1) LOG(P2) LOG(P3) LOG(P4) C Observations: 20 R-squared 0.713738 Mean dependent var 0.020450 Adjusted R-squared 0.703813 S.D. dependent var 0.020226 S.E. of regression 0.016876 Sum squared resid 0.004557 Durbin-W atson stat 1.127280 Equation: S2 = C(2) + C(6)*LOG(P1) + C(9)*LOG(P2) + C(10)*LOG(P3) + (-(C(6)+C(9)+C(10)))*LOG(P4) Instruments: LOG(P1) LOG(P2) LOG(P3) LOG(P4) C Observations: 20 R-squared 0.866219 Mean dependent var 0.425200 Adjusted R-squared 0.884885 S.D. dependent var 0.089733 S.E. of regression 0.064403 Sum squared resid 0.066364 Durbin-W atson stat 2.075819 Equation: S3 = C(3) + C(7)*LOG(P1) + C(10)*LOG(P2) + C(12) *LOG(P3) + (-(C(7)+C(10)+C(12)))*LOG(P4) Instruments: LOG(P1) LOG(P2) LOG(P3) LOG(P4) C Observations: 20 R-squared 0.855803 Mean dependent var 0.482650 Adjusted R-squared 0.828766 S.D. dependent var 0.074084 S.E. of regression 0.030656 Sum squared resid 0.015037 Durbin-W atson stat 1.846605 Equation: S4 = (1 - (S1+S2+S3)) Observations: 20 R-squared 0.998370 Mean dependent var 0.071700 Adjusted R-squared 0.998452 S.D. dependent var 0.016073 S.E. of regression 0.000632 Sum squared resid 0.000008 Durbin-W atson stat 1.375000 286 TableE2Energysubmodel:Export System: EXPORT Estimation Method: Three-Stage Least Squares Date: 02/25/07 Time: 02:36 Sample: 1980 1999 Included observations: 20 Total system (balanced) observations 80 Linear estimation after one-step weighting matrix Coefficient Std. Error t-Statistic Prob. C(1) 0.859332 0.006954 123.567943 0.000000 C(5) -0.245345 0.033311 -7.365364 0.000000 C(6) 0.004316 0.025337 0.170358 0.865365 C(7) 0.005070 0.001985 2.553837 0.013510 C(2) 0.104191 0.008660 12.031253 0.000000 C(9) 0.172348 0.026570 6.486448 0.000000 C(10) -0.001146 0.000944 -2.215023 0.029643 C(3) 0.003474 0.000233 14.897789 0.000000 C(12) -0.000553 0.003138 -0.176200 0.860796 Determinant residual covariance 4.75E-46 Equation: S1 = C(1) + C(5)*LOG(P1) + C(6)*LOG(P2) + C(7)*LOG(P3) + (-(C(5)+C(6)+C(7)))*LOG(P4) Instruments: LOG(P1) LOG(P2) LOG(P3) LOG(P4) C Observations: 20 R-squared 0.890951 Mean dependent var 0.852605 Adjusted R-squared 0.870505 S.D. dependent var 0.067154 S.E. of regression 0.024166 Sum squared resid 0.009344 Durbin-W atson stat 1.799922 Equation: S2 = C(2) + C(6)*LOG(P1) + C(9)*LOG(P2) + C(10)*LOG(P3) + (-(C(6)+C(9)+C(10)))*LOG(P4) Instruments: LOG(P1) LOG(P2) LOG(P3) LOG(P4) C Observations: 20 R-squared 0.791911 Mean dependent var 0.144000 Adjusted R-squared 0.752894 S.D. dependent var 0.066223 S.E. of regression 0.032919 Sum squared resid 0.017339 Durbin-W atson stat 1.708313 Equation: S3 = C(3) + C(7)*LOG(P1) + C(10)*LOG(P2) + C(12) *LOG(P3) + (-(C(7)+C(10)+C(12)))*LOG(P4) Instruments: LOG(P1) LOG(P2) LOG(P3) LOG(P4) C Observations: 20 R-squared 0.867510 Mean dependent var 0.003370 Adjusted R-squared 0.805168 S.D. dependent var 0.001191 S.E. of regression 0.000748 Sum squared resid 0.000009 Durbin-W atson stat 1.863667 Equation: S4 = (1 - (S1+S2+S3)) Observations: 20 R-squared 0.997740 Mean dependent var 0.082400 Adjusted R-squared 0.997442 S.D. dependent var 0.017177 S.E. of regression 0.000432 Sum squared resid 0.000008 Durbin-W atson stat 1.680000 287 APPENDIXF ResultsfromEconomywideImpactofCarbonTax ThisappendixpresentstheresultfromtheapplicationofcarbontaxbasedonPPPand SRPforvariouscasesdiscussedinChapter6.ItcontainsthefollowingTables: Table Title Page F1 Sectoraloutputsforfinalconsumption 288 F2 Sectoraloutputsfor(net)exports 297 F3 Sectoralsupplyofinvestmentgoods 306 F4 Sectoraldemandforinvestment 315 F5 Sectoraloutputsforintermediateconsumption 324 F6 Changeinsectoralpricesandinflation 333 F7 Carbontaxrevenue 335 F8 Shareofelectricitygeneration 343 F9 Costofelectricity 345 F10 Primaryenergyconsumption 346 F11 CO2emissions 351 F12 Employment 353 F13 Neteconomicimpacts 355 Notes: 2010 2011 450 4,002 1,169 661 5,462 16 111 236 6,557 140 34,041 10,519 8,830 10,254 205 25 644 21,347 2,296 4,401 3,495 6,694 2,129 1,612 5,961 15,575 403,830 550,663 2014 460 4,094 1,196 676 5,587 17 114 242 6,708 144 34,824 10,761 9,033 10,490 210 26 659 21,838 2,348 4,503 3,575 6,848 2,178 1,649 6,098 15,933 413,118 563,328 2015 471 4,188 1,223 691 5,716 17 116 247 6,862 147 35,625 11,008 9,241 10,731 214 26 674 22,341 2,402 4,606 3,657 7,006 2,229 1,687 6,238 16,299 422,620 576,284 2016 2018 481 492 4,284 4,383 1,252 1,280 707 724 5,847 5,982 17 18 119 122 253 259 7,020 7,181 150 154 36,444 37,282 11,261 11,520 9,454 9,671 10,978 11,230 219 224 27 27 690 706 22,854 23,380 2,458 2,514 4,712 4,820 3,741 3,827 7,167 7,332 2,280 2,332 1,726 1,766 6,382 6,529 16,674 17,058 432,340 442,284 589,539 603,098 2017 2020 288 504 515 4,484 4,587 1,310 1,340 740 757 6,119 6,260 18 19 124 127 265 271 7,347 7,516 157 161 38,140 39,017 11,785 12,056 9,893 10,121 11,489 11,753 229 235 28 29 722 739 23,918 24,468 2,572 2,631 4,931 5,045 3,915 4,005 7,501 7,673 2,386 2,441 1,806 1,848 6,679 6,832 17,450 17,851 452,457 462,863 616,970 631,160 2019 ThisTableshowstheresultscalculatedusingtheassumptionofeconomicgrowthgiveninSection6.2,pp.138139; Theshareofeachsectorintotalfinalconsumptionisassumedconstant,accordingtofixedLeontiefcoefficientspresentedinquadrantBofFigureB1,p.217; TheshareofelectricitymixinfinalconsumptionreflectschangesduetoMRETscheme. 2009 440 3,912 1,143 646 5,339 16 109 231 6,410 137 33,275 10,282 8,632 10,023 200 24 630 20,867 2,244 4,302 3,416 6,544 2,082 1,576 5,827 15,224 394,751 538,282 2008 352 363 375 386 398 411 420 430 3,137 3,234 3,334 3,437 3,544 3,654 3,738 3,824 916 945 974 1,004 1,035 1,067 1,092 1,117 437 467 499 532 567 603 617 631 4,362 4,480 4,602 4,727 4,855 4,987 5,102 5,219 13 13 13 14 14 15 15 15 87 90 92 95 98 101 104 106 185 191 197 203 209 216 221 226 5,139 5,299 5,463 5,632 5,807 5,987 6,125 6,266 110 113 117 121 124 128 131 134 26,681 27,508 28,361 29,240 30,146 31,081 31,796 32,527 8,245 8,500 8,764 9,035 9,315 9,604 9,825 10,051 6,921 7,136 7,357 7,585 7,820 8,062 8,248 8,438 8,037 8,286 8,543 8,808 9,081 9,363 9,578 9,798 161 166 171 176 181 187 191 196 20 20 21 21 22 23 23 24 505 521 537 554 571 588 602 616 16,732 17,251 17,785 18,337 18,905 19,491 19,940 20,398 1,799 1,855 1,913 1,972 2,033 2,096 2,144 2,194 3,450 3,557 3,667 3,781 3,898 4,019 4,111 4,206 2,739 2,824 2,912 3,002 3,095 3,191 3,264 3,339 5,247 5,410 5,577 5,750 5,929 6,112 6,253 6,397 1,669 1,721 1,774 1,829 1,886 1,944 1,989 2,035 1,264 1,303 1,343 1,385 1,428 1,472 1,506 1,541 4,672 4,817 4,966 5,120 5,279 5,443 5,568 5,696 12,207 12,586 12,976 13,378 13,793 14,221 14,548 14,882 316,521 326,333 336,450 346,880 357,633 368,720 377,200 385,876 431,608 444,988 458,783 473,005 487,668 502,786 514,350 526,180 2007 2013 2006 Sectoraloutputsforfinalconsumption:BCscenario($million) 2012 2005 TableF1 Present value 4,034 Coalsector 35,902 Petroleumsector 10,488 Gassector 5,624 RenewableElectricity 49,306 CoalfiredElectricity 145 InternalcombustionElectricity 996 GasturbineElectricity 2,119 CombinedcycleElectricity 58,828 Agriculture,forestryandfishing 1,259 Mining 305,403 Food,beveragesandtobacco Textile,clothing,footwearandleather 94,372 79,222 Wood,paperandprintingproducts 91,996 Basicchemicals 1,838 Nonmetallicmineralproducts Basicironandsteel 224 Basicnonferrousmetals 5,782 Fabricatedmetalproducts 191,523 Machineryandequipment 20,596 Miscellenousmanufacturing 39,488 Water,sewerageanddrainage 31,353 Construction 60,061 Roadtransport 19,105 Railwaytransport 14,465 Watertransport 53,480 Airtransport Othertransport,servicesandstorage 139,731 3,623,056 Commercialservices Total 4,940,397 Notes: 2007 302 260 3,146 3,157 774 656 466 495 4,461 4,563 13 13 89 92 190 195 5,285 5,434 113 116 27,434 28,209 8,477 8,717 7,116 7,318 8,264 8,497 165 170 20 21 519 534 17,204 17,690 1,850 1,902 3,547 3,647 2,816 2,896 5,396 5,550 1,716 1,765 1,299 1,336 4,805 4,941 12,553 12,909 325,992 335,748 444,015 456,833 2006 225 3,170 557 526 4,668 14 94 200 5,587 120 29,007 8,963 7,524 8,738 175 21 549 18,191 1,956 3,751 2,978 5,708 1,815 1,374 5,082 13,275 345,799 470,066 2008 2010 194 169 3,183 3,198 475 406 558 591 4,775 4,884 14 14 97 99 206 211 5,746 5,908 123 126 29,828 30,673 9,217 9,478 7,737 7,957 8,985 9,240 179 185 22 23 565 581 18,706 19,236 2,012 2,069 3,857 3,966 3,062 3,149 5,871 6,038 1,866 1,919 1,413 1,453 5,227 5,375 13,652 14,041 356,153 366,821 483,722 497,809 2009 2012 146 126 3,189 3,180 345 294 602 613 4,976 5,070 15 15 101 103 215 219 6,029 6,152 129 132 31,298 31,937 9,671 9,869 8,119 8,284 9,428 9,620 188 192 23 23 593 605 19,628 20,028 2,111 2,154 4,047 4,129 3,213 3,279 6,163 6,290 1,959 1,999 1,483 1,513 5,486 5,599 14,328 14,622 374,879 383,117 508,362 519,163 2011 109 3,173 251 625 5,166 15 105 223 6,277 134 32,589 10,070 8,454 9,817 196 24 617 20,437 2,198 4,214 3,346 6,420 2,040 1,544 5,714 14,922 391,538 530,215 2013 2015 95 82 3,166 3,160 214 184 637 649 5,263 5,363 16 16 107 109 228 232 6,406 6,537 137 140 33,255 33,935 10,276 10,486 8,626 8,803 10,017 10,222 200 204 24 25 630 642 20,855 21,281 2,243 2,289 4,300 4,388 3,414 3,484 6,552 6,687 2,081 2,124 1,576 1,608 5,831 5,951 15,228 15,541 400,147 408,947 541,523 553,090 2014 Sectoraloutputsforfinalconsumption:PPP1 ($million) 2017 72 62 3,155 3,151 158 136 661 674 5,465 5,397 16 16 111 113 236 413 6,671 6,807 143 146 34,630 35,340 10,701 10,920 8,983 9,167 10,432 10,645 208 213 25 26 656 669 21,717 22,162 2,335 2,383 4,478 4,569 3,555 3,628 6,826 6,967 2,168 2,212 1,641 1,674 6,074 6,200 15,860 16,187 417,944 427,141 564,921 577,019 2016 55 3,148 117 686 5,324 17 115 596 6,947 149 36,066 11,145 9,355 10,864 217 26 683 22,617 2,432 4,663 3,702 7,111 2,258 1,709 6,328 16,521 436,545 589,397 2018 2020 289 48 42 3,147 3,148 102 88 700 713 5,247 5,165 17 17 118 120 786 983 7,090 7,236 152 155 36,807 37,566 11,374 11,608 9,548 9,745 11,087 11,316 221 226 27 28 697 711 23,082 23,558 2,482 2,533 4,759 4,857 3,779 3,856 7,259 7,410 2,304 2,352 1,744 1,780 6,459 6,593 16,862 17,210 446,160 455,991 602,058 615,008 2019 ThisTableshowstheresultscalculatedusingtheassumptionofeconomicgrowthgiveninSection6.2,pp.138139; Theshareofeachsectorintotalfinalconsumptionisassumedtovaryaccordingtoinputssubstitution,calculatedfromEquation520,p.110; TheshareofelectricitymixinfinalconsumptionreflectchangesduetoMRETschemeaswellasinputssubstitution,calculatedfromEquation520,p.110. 352 3,137 916 437 4,362 13 87 185 5,139 110 26,681 8,245 6,921 8,037 161 20 505 16,732 1,799 3,450 2,739 5,247 1,669 1,264 4,672 12,207 316,521 431,608 2005 TableF1 Present value 1,922 Coalsector 31,044 Petroleumsector 4,783 Gassector 5,484 RenewableElectricity 47,583 CoalfiredElectricity 142 InternalcombustionElectricity 972 GasturbineElectricity 2,633 CombinedcycleElectricity 57,945 Agriculture,forestryandfishing 1,240 Mining 300,819 Food,beveragesandtobacco Textile,clothing,footwearandleather 92,955 78,033 Wood,paperandprintingproducts 90,615 Basicchemicals 1,810 Nonmetallicmineralproducts Basicironandsteel 221 Basicnonferrousmetals 5,695 Fabricatedmetalproducts 188,648 Machineryandequipment 20,286 Miscellenousmanufacturing 38,895 Water,sewerageanddrainage 30,882 Construction 59,230 Roadtransport 18,824 Railwaytransport 14,251 Watertransport 52,724 Airtransport Othertransport,servicesandstorage 137,708 3,601,547 Commercialservices Total 4,886,891 Notes: 2007 272 212 3,100 3,066 687 520 463 489 4,434 4,508 13 13 89 91 189 193 5,253 5,371 112 115 27,272 27,881 8,427 8,615 7,075 7,232 8,215 8,398 164 168 20 20 516 528 17,103 17,484 1,839 1,880 3,526 3,605 2,800 2,862 5,365 5,487 1,706 1,745 1,292 1,321 4,777 4,885 12,482 12,764 325,616 334,982 442,809 454,434 2006 166 3,035 396 516 4,585 13 92 197 5,491 118 28,506 8,809 7,395 8,587 172 21 540 17,877 1,922 3,686 2,926 5,611 1,784 1,350 4,995 13,055 344,626 466,470 2008 2010 131 104 3,007 2,982 304 235 544 574 4,662 4,742 14 14 94 96 201 205 5,615 5,742 120 123 29,149 29,810 9,007 9,212 7,561 7,733 8,781 8,980 175 179 21 22 552 564 18,280 18,694 1,966 2,010 3,769 3,854 2,992 3,060 5,740 5,872 1,825 1,866 1,381 1,412 5,109 5,226 13,353 13,660 354,557 364,784 478,912 491,757 2009 2012 82 66 2,936 2,893 181 140 581 589 4,804 4,868 14 14 98 99 208 210 5,828 5,915 125 127 30,253 30,706 9,348 9,488 7,848 7,965 9,113 9,249 182 185 22 23 573 581 18,972 19,256 2,040 2,071 3,912 3,970 3,106 3,152 5,961 6,052 1,894 1,923 1,433 1,455 5,305 5,386 13,867 14,079 372,403 380,189 501,090 510,650 2011 52 2,852 110 597 4,780 15 100 366 6,004 128 31,168 9,631 8,085 9,389 188 23 590 19,546 2,102 4,030 3,200 6,145 1,952 1,477 5,468 14,295 388,146 520,436 2013 2015 42 34 2,816 2,783 86 69 605 613 4,690 4,598 15 15 102 103 525 688 6,095 6,189 130 132 31,642 32,128 9,778 9,928 8,208 8,334 9,531 9,678 190 193 23 24 599 608 19,843 20,148 2,134 2,167 4,091 4,154 3,248 3,298 6,240 6,338 1,982 2,013 1,499 1,523 5,552 5,639 14,516 14,744 396,282 404,603 530,467 540,744 2014 Sectoraloutputsforfinalconsumption:SRP1($million) 2017 28 23 2,753 2,727 55 45 621 630 4,503 4,405 15 15 104 106 857 1,029 6,285 6,383 135 137 32,627 33,138 10,082 10,240 8,463 8,596 9,828 9,982 196 199 24 24 618 627 20,461 20,781 2,200 2,235 4,219 4,285 3,349 3,402 6,438 6,541 2,044 2,076 1,546 1,571 5,728 5,819 14,976 15,215 413,111 421,810 551,268 562,043 2016 20 2,704 36 639 4,303 16 107 1,207 6,484 139 33,662 10,402 8,732 10,140 203 25 637 21,110 2,270 4,352 3,456 6,646 2,109 1,596 5,912 15,459 430,705 573,071 2018 2020 290 16 14 2,684 2,666 30 25 648 825 4,199 4,091 16 16 109 110 1,389 1,409 6,587 6,693 141 143 34,198 34,747 10,567 10,737 8,871 9,013 10,301 10,467 206 209 25 25 647 658 21,446 21,790 2,306 2,343 4,422 4,493 3,511 3,567 6,754 6,865 2,143 2,178 1,621 1,647 6,007 6,105 15,710 15,966 439,800 449,099 584,357 595,904 2019 ThisTableshowstheresultscalculatedusingtheassumptionofeconomicgrowthgiveninSection6.2,pp.138139; Theshareofeachsectorintotalfinalconsumptionisassumedtovaryaccordingtoinputssubstitution,calculatedfromEquation520,p.110; TheshareofelectricitymixinfinalconsumptionreflectchangesduetoMRETschemeaswellasinputssubstitution,calculatedfromEquation520,p.110. 352 3,137 916 437 4,362 13 87 185 5,139 110 26,681 8,245 6,921 8,037 161 20 505 16,732 1,799 3,450 2,739 5,247 1,669 1,264 4,672 12,207 316,521 431,608 2005 TableF1 Present value 1,526 Coalsector 29,036 Petroleumsector 3,758 Gassector 5,350 RenewableElectricity 44,556 CoalfiredElectricity 137 InternalcombustionElectricity 941 GasturbineElectricity 4,012 CombinedcycleElectricity 56,144 Agriculture,forestryandfishing 1,202 Mining 291,468 Food,beveragesandtobacco Textile,clothing,footwearandleather 90,066 75,607 Wood,paperandprintingproducts 87,799 Basicchemicals 1,754 Nonmetallicmineralproducts Basicironandsteel 214 Basicnonferrousmetals 5,518 Fabricatedmetalproducts 182,784 Machineryandequipment 19,656 Miscellenousmanufacturing 37,686 Water,sewerageanddrainage 29,922 Construction 57,423 Roadtransport 18,248 Railwaytransport 13,810 Watertransport 51,107 Airtransport Othertransport,servicesandstorage 133,583 3,579,125 Commercialservices Total 4,822,431 Notes: 2007 242 167 3,059 2,986 603 401 464 491 4,442 4,525 13 13 89 91 189 193 5,270 5,405 113 116 27,360 28,058 8,454 8,670 7,097 7,278 8,242 8,452 165 169 20 21 518 531 17,158 17,596 1,845 1,892 3,538 3,628 2,809 2,880 5,383 5,523 1,712 1,756 1,296 1,329 4,793 4,916 12,521 12,843 325,650 335,048 443,042 454,978 2006 117 2,918 269 519 4,609 14 93 198 5,543 119 28,777 8,892 7,465 8,668 173 21 545 18,046 1,941 3,721 2,954 5,666 1,801 1,363 5,044 13,174 344,723 467,372 2008 2010 82 58 2,855 2,796 183 125 548 579 4,695 4,783 14 14 95 97 202 207 5,685 5,832 122 125 29,515 30,274 9,120 9,355 7,656 7,853 8,891 9,119 178 182 22 22 559 573 18,509 18,985 1,990 2,042 3,816 3,914 3,030 3,108 5,814 5,966 1,847 1,895 1,398 1,434 5,175 5,309 13,514 13,864 354,684 364,940 480,200 493,453 2009 2012 42 30 2,719 2,646 86 59 587 596 4,854 4,773 14 15 99 100 210 365 5,936 6,042 127 129 30,814 31,365 9,522 9,692 7,993 8,136 9,282 9,448 185 189 23 23 583 594 19,324 19,669 2,078 2,115 3,984 4,055 3,163 3,220 6,075 6,186 1,929 1,964 1,460 1,486 5,406 5,504 14,114 14,369 372,585 380,396 503,193 513,166 2011 22 2,579 41 605 4,690 15 102 525 6,150 132 31,928 9,866 8,282 9,618 192 23 604 20,023 2,153 4,128 3,278 6,300 1,999 1,513 5,605 14,630 388,380 523,381 2013 2015 16 12 2,517 2,462 29 21 770 941 4,604 4,514 15 15 103 105 533 541 6,261 6,375 134 136 32,504 33,095 10,044 10,227 8,432 8,585 9,791 9,969 196 199 24 24 615 627 20,384 20,754 2,192 2,232 4,203 4,279 3,337 3,398 6,416 6,535 2,035 2,072 1,540 1,569 5,707 5,813 14,896 15,169 396,539 404,883 533,838 544,551 2014 Sectoraloutputsforfinalconsumption:PPP2($million) 2017 9 7 2,413 2,370 16 12 1,117 1,298 4,422 4,326 15 16 106 108 549 557 6,492 6,611 139 141 33,700 34,321 10,414 10,606 8,742 8,903 10,152 10,339 203 207 25 25 638 650 21,134 21,523 2,273 2,315 4,357 4,438 3,460 3,523 6,657 6,782 2,111 2,150 1,597 1,627 5,921 6,032 15,449 15,736 413,414 422,137 555,523 566,758 2016 5 2,332 9 1,484 4,226 16 110 566 6,734 144 34,957 10,802 9,068 10,530 210 26 662 21,922 2,357 4,520 3,589 6,911 2,190 1,657 6,145 16,030 431,057 578,260 2018 2020 291 4 3 2,300 2,272 7 5 1,677 1,875 4,123 4,016 16 16 111 113 575 584 6,859 6,988 147 150 35,609 36,278 11,004 11,210 9,237 9,410 10,727 10,928 214 218 26 27 674 687 22,331 22,750 2,401 2,446 4,604 4,691 3,656 3,724 7,042 7,177 2,231 2,273 1,688 1,720 6,262 6,381 16,331 16,640 440,177 449,502 590,034 602,084 2019 ThisTableshowstheresultscalculatedusingtheassumptionofeconomicgrowthgiveninSection6.2,pp.138139; Theshareofeachsectorintotalfinalconsumptionisassumedtovaryaccordingtoinputssubstitution,calculatedfromEquation520,p.110; TheshareofelectricitymixinfinalconsumptionreflectchangesduetoMRETschemeaswellasinputssubstitution,calculatedfromEquation520,p.110. 352 3,137 916 437 4,362 13 87 185 5,139 110 26,681 8,245 6,921 8,037 161 20 505 16,732 1,799 3,450 2,739 5,247 1,669 1,264 4,672 12,207 316,521 431,608 2005 TableF1 Present value 1,260 Coalsector 27,329 Petroleumsector 3,117 Gassector 6,949 RenewableElectricity 44,365 CoalfiredElectricity 138 InternalcombustionElectricity 950 GasturbineElectricity 3,108 CombinedcycleElectricity 57,113 Agriculture,forestryandfishing 1,222 Mining 296,496 Food,beveragesandtobacco Textile,clothing,footwearandleather 91,620 76,912 Wood,paperandprintingproducts 89,313 Basicchemicals 1,784 Nonmetallicmineralproducts Basicironandsteel 218 Basicnonferrousmetals 5,613 Fabricatedmetalproducts 185,937 Machineryandequipment 19,995 Miscellenousmanufacturing 38,336 Water,sewerageanddrainage 30,438 Construction 58,447 Roadtransport 18,559 Railwaytransport 14,048 Watertransport 52,011 Airtransport Othertransport,servicesandstorage 135,797 3,580,632 Commercialservices Total 4,841,708 Notes: 2007 181 96 2,965 2,812 430 210 458 479 4,388 4,416 13 13 88 89 187 189 5,208 5,280 111 113 27,037 27,408 8,355 8,469 7,013 7,110 8,144 8,256 163 165 20 20 512 519 16,955 17,188 1,823 1,848 3,496 3,544 2,776 2,814 5,321 5,397 1,692 1,716 1,281 1,298 4,737 4,804 12,378 12,556 324,899 333,525 440,631 450,335 2006 53 2,673 106 501 4,447 13 90 191 5,354 115 27,795 8,589 7,210 8,373 167 20 526 17,431 1,874 3,594 2,853 5,477 1,740 1,317 4,874 12,741 342,407 460,531 2008 2010 30 17 2,549 2,436 55 30 523 546 4,478 4,390 13 13 91 92 193 317 5,431 5,512 116 118 28,197 28,615 8,713 8,842 7,314 7,423 8,494 8,620 170 172 21 21 534 542 17,683 17,945 1,902 1,930 3,646 3,700 2,895 2,938 5,560 5,645 1,766 1,793 1,336 1,356 4,947 5,023 12,933 13,133 351,551 360,964 471,140 482,131 2009 2012 10 6 2,318 2,213 16 9 548 550 4,267 4,144 13 13 92 92 458 601 5,553 5,596 119 120 28,827 29,051 8,908 8,977 7,478 7,536 8,683 8,751 173 175 21 21 546 550 18,078 18,218 1,944 1,959 3,727 3,756 2,959 2,982 5,691 5,739 1,806 1,821 1,366 1,377 5,062 5,104 13,237 13,348 367,788 374,771 489,689 497,483 2011 4 2,119 6 553 4,022 14 93 745 5,642 121 29,289 9,050 7,598 8,823 176 21 555 18,367 1,975 3,787 3,007 5,789 1,836 1,389 5,148 13,464 381,916 505,506 2013 2015 3 2 2,035 1,961 3 2 697 844 3,900 3,779 14 14 93 94 748 752 5,690 5,741 122 123 29,538 29,804 9,128 9,210 7,662 7,731 8,898 8,978 178 179 22 22 559 564 18,524 18,691 1,992 2,010 3,819 3,854 3,032 3,060 5,842 5,898 1,852 1,869 1,401 1,413 5,194 5,243 13,586 13,715 389,225 396,713 513,756 522,265 2014 Sectoraloutputsforfinalconsumption:SRP2($million) 2017 1 1 1,896 1,839 1 1 992 1,142 3,658 3,537 14 14 94 95 757 762 5,795 5,853 124 125 30,087 30,385 9,297 9,389 7,805 7,882 9,063 9,153 181 183 22 22 570 575 18,868 19,055 2,029 2,049 3,890 3,929 3,089 3,119 5,957 6,020 1,888 1,907 1,427 1,441 5,295 5,350 13,851 13,995 404,383 412,238 531,033 540,061 2016 1 1,790 1 1,295 3,415 14 96 767 5,913 127 30,699 9,486 7,963 9,248 185 23 581 19,252 2,070 3,969 3,152 6,085 1,927 1,456 5,407 14,146 420,282 549,350 2018 2020 292 0 0 1,747 1,709 0 0 1,451 1,609 3,293 3,170 14 14 96 97 772 778 5,977 6,043 128 129 31,029 31,374 9,588 9,695 8,049 8,139 9,347 9,451 187 189 23 23 587 594 19,459 19,675 2,093 2,116 4,012 4,057 3,185 3,221 6,154 6,226 1,948 1,970 1,472 1,489 5,468 5,531 14,304 14,469 428,518 436,948 558,901 568,716 2019 ThisTableshowstheresultscalculatedusingtheassumptionofeconomicgrowthgiveninSection6.2,pp.138139; Theshareofeachsectorintotalfinalconsumptionisassumedtovaryaccordingtoinputssubstitution,calculatedfromEquation520,p.110; TheshareofelectricitymixinfinalconsumptionreflectchangesduetoMRETschemeaswellasinputssubstitution,calculatedfromEquation520,p.110. 352 3,137 916 437 4,362 13 87 185 5,139 110 26,681 8,245 6,921 8,037 161 20 505 16,732 1,799 3,450 2,739 5,247 1,669 1,264 4,672 12,207 316,521 431,608 2005 TableF1 Present value 984 Coalsector 24,435 Petroleumsector 2,428 Gassector 6,415 RenewableElectricity 40,682 CoalfiredElectricity 130 InternalcombustionElectricity 893 GasturbineElectricity 4,079 CombinedcycleElectricity 53,804 Agriculture,forestryandfishing 1,151 Mining 279,317 Food,beveragesandtobacco Textile,clothing,footwearandleather 86,311 72,455 Wood,paperandprintingproducts 84,138 Basicchemicals 1,681 Nonmetallicmineralproducts Basicironandsteel 205 Basicnonferrousmetals 5,288 Fabricatedmetalproducts 175,164 Machineryandequipment 18,836 Miscellenousmanufacturing 36,115 Water,sewerageanddrainage 28,675 Construction 55,121 Roadtransport 17,499 Railwaytransport 13,238 Watertransport 49,037 Airtransport Othertransport,servicesandstorage 128,207 3,538,242 Commercialservices Total 4,724,530 Notes: 2005 2007 211 128 3,014 2,901 516 296 463 489 4,433 4,505 13 13 89 91 189 193 5,263 5,390 113 115 27,322 27,982 8,443 8,647 7,088 7,259 8,230 8,429 164 168 20 21 517 530 17,134 17,548 1,843 1,887 3,533 3,618 2,805 2,873 5,376 5,509 1,709 1,751 1,294 1,326 4,786 4,904 12,504 12,809 325,476 334,692 442,547 454,071 2006 79 2,797 172 516 4,579 13 92 197 5,521 118 28,660 8,856 7,434 8,633 172 21 543 17,973 1,933 3,706 2,942 5,645 1,794 1,358 5,025 13,122 344,178 466,079 2008 2010 49 31 2,700 2,610 102 61 544 573 4,655 4,733 14 14 94 96 201 205 5,655 5,793 121 124 29,357 30,074 9,072 9,293 7,615 7,801 8,843 9,059 177 181 22 22 556 569 18,410 18,860 1,980 2,028 3,796 3,888 3,014 3,087 5,785 5,930 1,838 1,883 1,391 1,425 5,149 5,276 13,445 13,776 353,941 363,990 478,524 491,383 2009 2012 20 13 2,507 2,412 37 23 580 587 4,645 4,554 14 14 97 99 355 510 5,889 5,987 126 128 30,572 31,081 9,447 9,604 7,930 8,063 9,209 9,363 184 187 22 23 579 588 19,172 19,492 2,062 2,096 3,953 4,019 3,138 3,191 6,031 6,135 1,914 1,946 1,449 1,473 5,366 5,457 14,007 14,244 371,428 379,030 500,733 510,318 2011 8 2,326 14 747 4,461 15 100 516 6,087 130 31,603 9,765 8,198 9,520 190 23 598 19,819 2,131 4,086 3,244 6,241 1,979 1,498 5,551 14,486 386,798 520,134 2013 2015 6 4 2,249 2,180 9 6 910 1,078 4,366 4,268 15 15 101 103 523 530 6,191 6,297 132 135 32,138 32,688 9,931 10,101 8,337 8,479 9,681 9,847 193 197 24 24 608 619 20,154 20,499 2,167 2,204 4,155 4,226 3,299 3,356 6,350 6,461 2,013 2,047 1,523 1,550 5,647 5,746 14,734 14,989 394,741 402,862 530,198 540,510 2014 2017 3 2 2,120 2,066 4 3 1,250 1,427 4,167 4,063 15 15 104 105 537 544 6,405 6,517 137 139 33,252 33,831 10,275 10,454 8,626 8,776 10,017 10,191 200 204 24 25 630 641 20,853 21,216 2,242 2,281 4,299 4,374 3,414 3,473 6,576 6,694 2,083 2,120 1,576 1,604 5,847 5,951 15,251 15,519 411,166 419,657 551,074 561,894 2016 Sectoraloutputsforfinalconsumption:PPPforEarlyaction($million) 2 2,019 2 1,609 3,957 16 107 552 6,631 142 34,425 10,638 8,930 10,370 207 25 652 21,589 2,322 4,451 3,534 6,815 2,157 1,632 6,058 15,794 428,338 572,973 2018 2020 293 1 1 1,978 1,941 2 1 1,796 1,988 3,847 3,734 16 16 108 110 559 567 6,749 6,869 144 147 35,035 35,660 10,826 11,019 9,088 9,250 10,554 10,742 211 215 26 26 663 675 21,971 22,363 2,363 2,405 4,530 4,611 3,597 3,661 6,939 7,066 2,195 2,235 1,661 1,691 6,167 6,279 16,077 16,366 437,214 446,289 584,315 595,926 2019 ThisTableshowstheresultscalculatedusingtheassumptionofeconomicgrowthgiveninSection6.2,pp.138139; Theshareofeachsectorintotalfinalconsumptionisassumedtovaryaccordingtoinputssubstitution,calculatedfromEquation520,p.110; TheshareofelectricitymixinfinalconsumptionreflectchangesduetoMRETschemeaswellasinputssubstitution,calculatedfromEquation520,p.110. 352 3,137 916 437 4,362 13 87 185 5,139 110 26,681 8,245 6,921 8,037 161 20 505 16,732 1,799 3,450 2,739 5,247 1,669 1,264 4,672 12,207 316,521 431,608 TableF1 Present value 1,091 Coalsector 25,756 Petroleumsector 2,702 Gassector 7,336 RenewableElectricity 43,232 CoalfiredElectricity 137 InternalcombustionElectricity 939 GasturbineElectricity 3,229 CombinedcycleElectricity 56,705 Agriculture,forestryandfishing 1,214 Mining 294,383 Food,beveragesandtobacco Textile,clothing,footwearandleather 90,966 76,363 Wood,paperandprintingproducts 88,677 Basicchemicals 1,771 Nonmetallicmineralproducts Basicironandsteel 216 Basicnonferrousmetals 5,573 Fabricatedmetalproducts 184,611 Machineryandequipment 19,852 Miscellenousmanufacturing 38,063 Water,sewerageanddrainage 30,221 Construction 58,064 Roadtransport 18,429 Railwaytransport 13,950 Watertransport 51,662 Airtransport Othertransport,servicesandstorage 134,861 3,570,188 Commercialservices Total 4,820,193 Notes: 2005 2007 228 150 3,034 2,940 562 351 460 484 4,412 4,463 13 13 88 90 188 191 5,231 5,326 112 114 27,158 27,649 8,392 8,544 7,045 7,172 8,181 8,329 163 166 20 20 514 523 17,031 17,339 1,831 1,865 3,511 3,575 2,788 2,838 5,343 5,443 1,699 1,730 1,286 1,310 4,757 4,845 12,431 12,663 325,267 334,271 441,747 452,405 2006 100 2,854 223 509 4,517 13 91 194 5,424 116 28,157 8,701 7,304 8,482 169 21 533 17,657 1,899 3,641 2,891 5,545 1,763 1,334 4,936 12,901 343,540 463,512 2008 2010 68 46 2,775 2,702 144 94 534 560 4,572 4,628 13 14 93 94 197 200 5,524 5,628 118 120 28,680 29,219 8,862 9,029 7,440 7,579 8,639 8,802 173 176 21 21 543 553 17,985 18,323 1,934 1,970 3,708 3,778 2,944 3,000 5,651 5,760 1,796 1,830 1,359 1,385 5,029 5,126 13,146 13,399 353,084 362,909 475,031 486,945 2009 2012 32 23 2,614 2,535 62 42 565 570 4,523 4,418 14 14 95 96 346 494 5,691 5,756 122 123 29,543 29,879 9,129 9,233 7,664 7,751 8,899 9,001 178 180 22 22 559 566 18,527 18,738 1,992 2,015 3,820 3,863 3,033 3,067 5,826 5,895 1,850 1,872 1,400 1,416 5,184 5,245 13,554 13,714 370,129 377,515 495,373 504,041 2011 16 2,464 29 575 4,311 14 97 645 5,823 125 30,227 9,341 7,841 9,105 182 22 572 18,956 2,038 3,908 3,103 5,967 1,894 1,433 5,308 13,879 385,070 512,945 2013 2015 12 9 2,399 2,340 20 14 580 586 4,203 4,093 14 14 97 98 800 957 5,892 5,963 126 128 30,587 30,959 9,452 9,566 7,934 8,031 9,214 9,326 184 186 22 23 579 586 19,182 19,415 2,063 2,088 3,955 4,003 3,140 3,178 6,041 6,117 1,917 1,941 1,450 1,468 5,373 5,440 14,050 14,226 392,796 400,697 522,081 531,451 2014 2017 6 5 2,287 2,240 10 8 742 902 3,982 3,870 14 15 99 100 966 976 6,037 6,114 129 131 31,342 31,740 9,685 9,808 8,130 8,233 9,441 9,561 189 191 23 23 593 601 19,655 19,905 2,114 2,140 4,052 4,104 3,218 3,258 6,195 6,276 1,965 1,990 1,486 1,505 5,509 5,581 14,408 14,596 408,776 417,046 541,054 550,919 2016 Sectoraloutputsforfinalconsumption:SRPforearlyaction($million) 4 2,199 6 1,065 3,756 15 101 986 6,194 133 32,153 9,936 8,341 9,685 193 24 609 20,164 2,168 4,157 3,301 6,361 2,016 1,525 5,655 14,791 425,511 561,048 2018 2020 294 3 2 2,164 2,134 4 3 1,232 1,403 3,640 3,523 15 15 102 104 996 1,007 6,276 6,362 134 136 32,582 33,025 10,068 10,205 8,452 8,567 9,815 9,948 196 199 24 24 617 625 20,432 20,711 2,197 2,227 4,213 4,270 3,345 3,390 6,448 6,539 2,044 2,072 1,545 1,566 5,732 5,812 14,993 15,202 434,175 443,041 571,445 582,113 2019 ThisTableshowstheresultscalculatedusingtheassumptionofeconomicgrowthgiveninSection6.2,pp.138139; Theshareofeachsectorintotalfinalconsumptionisassumedtovaryaccordingtoinputssubstitution,calculatedfromEquation520,p.110; TheshareofelectricitymixinfinalconsumptionreflectchangesduetoMRETschemeaswellasinputssubstitution,calculatedfromEquation520,p.110. 352 3,137 916 437 4,362 13 87 185 5,139 110 26,681 8,245 6,921 8,037 161 20 505 16,732 1,799 3,450 2,739 5,247 1,669 1,264 4,672 12,207 316,521 431,608 TableF1 Present value 1,187 Coalsector 26,598 Petroleumsector 2,919 Gassector 5,914 RenewableElectricity 42,302 CoalfiredElectricity 133 InternalcombustionElectricity 917 GasturbineElectricity 4,325 CombinedcycleElectricity 54,969 Agriculture,forestryandfishing 1,176 Mining 285,366 Food,beveragesandtobacco Textile,clothing,footwearandleather 88,180 74,024 Wood,paperandprintingproducts 85,960 Basicchemicals 1,717 Nonmetallicmineralproducts Basicironandsteel 209 Basicnonferrousmetals 5,403 Fabricatedmetalproducts 178,957 Machineryandequipment 19,244 Miscellenousmanufacturing 36,897 Water,sewerageanddrainage 29,296 Construction 56,267 Roadtransport 17,872 Railwaytransport 13,523 Watertransport 50,068 Airtransport Othertransport,servicesandstorage 130,885 3,558,893 Commercialservices Total 4,773,201 Notes: 2005 2007 363 375 3,234 3,334 945 974 467 499 4,480 4,602 13 13 90 92 191 197 5,299 5,463 113 117 27,508 28,361 8,500 8,764 7,136 7,357 8,286 8,543 166 171 20 21 521 537 17,251 17,785 1,855 1,913 3,557 3,667 2,824 2,912 5,410 5,577 1,721 1,774 1,303 1,343 4,817 4,966 12,586 12,976 326,333 336,450 444,988 458,783 2006 386 3,437 1,004 532 4,727 14 95 203 5,632 121 29,240 9,035 7,585 8,808 176 21 554 18,337 1,972 3,781 3,002 5,750 1,829 1,385 5,120 13,378 346,880 473,005 2008 2010 398 411 3,544 3,654 1,035 1,067 567 603 4,855 4,987 14 15 98 101 209 216 5,807 5,987 124 128 30,146 31,081 9,315 9,604 7,820 8,062 9,081 9,363 181 187 22 23 571 588 18,905 19,491 2,033 2,096 3,898 4,019 3,095 3,191 5,929 6,112 1,886 1,944 1,428 1,472 5,279 5,443 13,793 14,221 357,633 368,720 487,668 502,786 2009 2012 77 16 3,245 2,894 129 19 604 605 4,995 5,004 15 15 102 102 216 216 6,044 6,102 129 131 31,375 31,680 9,695 9,789 8,139 8,218 9,451 9,543 189 191 23 23 594 600 19,676 19,867 2,116 2,136 4,057 4,096 3,221 3,252 6,177 6,243 1,963 1,983 1,486 1,501 5,498 5,556 14,362 14,508 375,246 381,911 508,823 516,203 2011 4 2,593 3 607 5,015 15 102 217 6,163 132 31,995 9,887 8,300 9,638 193 23 606 20,064 2,158 4,137 3,285 6,312 2,003 1,516 5,616 14,659 388,718 523,958 2013 2015 1 0 2,332 2,109 1 0 608 765 4,872 4,729 15 15 102 102 373 374 6,226 6,291 133 135 32,320 32,659 9,987 10,092 8,384 8,472 9,736 9,838 194 197 24 24 612 618 20,268 20,481 2,180 2,202 4,179 4,223 3,318 3,353 6,383 6,456 2,024 2,046 1,532 1,548 5,677 5,741 14,815 14,976 395,670 402,775 531,963 540,218 2014 2017 0 0 1,921 1,763 0 0 924 1,084 4,588 4,447 15 15 103 103 375 376 6,359 6,431 136 138 33,014 33,385 10,201 10,316 8,564 8,660 9,945 10,057 199 201 24 24 625 632 20,703 20,937 2,226 2,251 4,269 4,317 3,389 3,427 6,533 6,613 2,068 2,092 1,565 1,583 5,808 5,877 15,145 15,322 410,046 417,486 548,745 557,538 2016 Sectoraloutputsforfinalconsumption:PPPforDelayaction($million) 0 1,629 0 1,245 4,306 15 103 377 6,506 139 33,774 10,436 8,761 10,174 203 25 639 21,180 2,278 4,367 3,467 6,696 2,117 1,602 5,950 15,506 425,098 566,594 2018 2020 295 0 0 1,515 1,417 0 0 1,408 1,573 4,166 4,027 15 15 104 104 379 381 6,584 6,665 141 143 34,178 34,599 10,561 10,691 8,866 8,975 10,295 10,422 206 208 25 25 647 655 21,434 21,697 2,305 2,333 4,419 4,474 3,509 3,552 6,783 6,873 2,143 2,170 1,621 1,641 6,026 6,104 15,697 15,896 432,884 440,847 575,910 585,486 2019 ThisTableshowstheresultscalculatedusingtheassumptionofeconomicgrowthgiveninSection6.2,pp.138139; Theshareofeachsectorintotalfinalconsumptionisassumedtovaryaccordingtoinputssubstitution,calculatedfromEquation520,p.110; TheshareofelectricitymixinfinalconsumptionreflectchangesduetoMRETschemeaswellasinputssubstitution,calculatedfromEquation520,p.110. 352 3,137 916 437 4,362 13 87 185 5,139 110 26,681 8,245 6,921 8,037 161 20 505 16,732 1,799 3,450 2,739 5,247 1,669 1,264 4,672 12,207 316,521 431,608 TableF1 Present value 2,147 Coalsector 28,202 Petroleumsector 5,523 Gassector 6,453 RenewableElectricity 45,523 CoalfiredElectricity 138 InternalcombustionElectricity 950 GasturbineElectricity 2,429 CombinedcycleElectricity 57,102 Agriculture,forestryandfishing 1,222 Mining 296,440 Food,beveragesandtobacco Textile,clothing,footwearandleather 91,602 76,897 Wood,paperandprintingproducts 89,296 Basicchemicals 1,784 Nonmetallicmineralproducts Basicironandsteel 218 Basicnonferrousmetals 5,612 Fabricatedmetalproducts 185,902 Machineryandequipment 19,991 Miscellenousmanufacturing 38,329 Water,sewerageanddrainage 30,433 Construction 58,437 Roadtransport 18,555 Railwaytransport 14,046 Watertransport 52,002 Airtransport Othertransport,servicesandstorage 135,769 3,579,637 Commercialservices Total 4,844,637 Notes: 2007 386 3,437 1,004 532 4,727 14 95 203 5,632 121 29,240 9,035 7,585 8,808 176 21 554 18,337 1,972 3,781 3,002 5,750 1,829 1,385 5,120 13,378 346,880 473,005 2008 2010 398 411 3,544 3,654 1,035 1,067 567 603 4,855 4,987 14 15 98 101 209 216 5,807 5,987 124 128 30,146 31,081 9,315 9,604 7,820 8,062 9,081 9,363 181 187 22 23 571 588 18,905 19,491 2,033 2,096 3,898 4,019 3,095 3,191 5,929 6,112 1,886 1,944 1,428 1,472 5,279 5,443 13,793 14,221 357,633 368,720 487,668 502,786 2009 2012 159 65 3,353 3,089 354 126 601 600 4,970 4,956 15 15 101 101 215 214 5,993 6,003 128 128 31,114 31,164 9,615 9,630 8,071 8,084 9,373 9,387 187 188 23 23 589 590 19,512 19,543 2,098 2,102 4,023 4,029 3,194 3,199 6,124 6,139 1,947 1,951 1,474 1,476 5,452 5,464 14,247 14,281 375,119 381,669 508,051 514,215 2011 28 2,856 47 598 4,944 15 100 214 6,015 129 31,228 9,650 8,101 9,407 188 23 591 19,584 2,106 4,038 3,206 6,157 1,956 1,480 5,478 14,322 388,373 520,833 2013 2015 13 6 2,650 2,471 19 8 597 596 4,782 4,623 15 15 100 100 366 517 6,031 6,050 129 129 31,308 31,407 9,674 9,705 8,121 8,147 9,431 9,461 188 189 23 23 593 595 19,634 19,696 2,111 2,118 4,048 4,061 3,214 3,224 6,177 6,202 1,961 1,968 1,484 1,489 5,496 5,516 14,369 14,425 395,232 402,264 527,765 535,005 2014 2017 3 2 2,316 2,179 4 2 596 747 4,468 4,314 15 15 100 100 669 669 6,072 6,098 130 131 31,525 31,659 9,741 9,783 8,178 8,212 9,496 9,537 190 191 23 23 597 599 19,769 19,854 2,126 2,135 4,076 4,093 3,236 3,250 6,230 6,261 1,976 1,985 1,495 1,501 5,540 5,567 14,489 14,561 409,468 416,846 542,526 550,315 2016 1 2,062 1 900 4,164 15 100 669 6,129 131 31,817 9,832 8,253 9,584 191 23 602 19,953 2,146 4,114 3,266 6,297 1,996 1,509 5,598 14,643 424,417 558,411 2018 2020 296 1 0 1,960 1,872 1 0 1,053 1,207 4,016 3,870 15 15 100 100 670 671 6,163 6,202 132 133 31,996 32,196 9,887 9,949 8,300 8,352 9,638 9,698 193 194 23 24 606 610 20,065 20,191 2,158 2,171 4,137 4,163 3,285 3,305 6,337 6,381 2,008 2,021 1,518 1,527 5,632 5,671 14,734 14,835 432,182 440,144 566,808 575,501 2019 ThisTableshowstheresultscalculatedusingtheassumptionofeconomicgrowthgiveninSection6.2,pp.138139; Theshareofeachsectorintotalfinalconsumptionisassumedtovaryaccordingtoinputssubstitution,calculatedfromEquation520,p.110; TheshareofelectricitymixinfinalconsumptionreflectchangesduetoMRETschemeaswellasinputssubstitution,calculatedfromEquation520,p.110. 363 375 3,234 3,334 945 974 467 499 4,480 4,602 13 13 90 92 191 197 5,299 5,463 113 117 27,508 28,361 8,500 8,764 7,136 7,357 8,286 8,543 166 171 20 21 521 537 17,251 17,785 1,855 1,913 3,557 3,667 2,824 2,912 5,410 5,577 1,721 1,774 1,303 1,343 4,817 4,966 12,586 12,976 326,333 336,450 444,988 458,783 2006 Sectoraloutputsforfinalconsumption:SRPforDelayaction($million) 2005 352 3,137 916 437 4,362 13 87 185 5,139 110 26,681 8,245 6,921 8,037 161 20 505 16,732 1,799 3,450 2,739 5,247 1,669 1,264 4,672 12,207 316,521 431,608 TableF1 Present value 2,243 Coalsector 29,534 Petroleumsector 5,749 Gassector 5,776 RenewableElectricity 45,122 CoalfiredElectricity 137 InternalcombustionElectricity 941 GasturbineElectricity 2,984 CombinedcycleElectricity 56,119 Agriculture,forestryandfishing 1,201 Mining 291,338 Food,beveragesandtobacco Textile,clothing,footwearandleather 90,026 75,574 Wood,paperandprintingproducts 87,760 Basicchemicals 1,753 Nonmetallicmineralproducts Basicironandsteel 214 Basicnonferrousmetals 5,516 Fabricatedmetalproducts 182,702 Machineryandequipment 19,647 Miscellenousmanufacturing 37,669 Water,sewerageanddrainage 29,909 Construction 57,398 Roadtransport 18,239 Railwaytransport 13,804 Watertransport 51,085 Airtransport Othertransport,servicesandstorage 133,520 3,577,714 Commercialservices Total 4,823,672 Notes: 7,324 825 197 5,017 9,221 547 3,869 1,600 3,185 15 905 5,732 76 9,589 1,019 635 425 1,005 971 255 869 401 35,689 25,495 7,104 804 191 4,864 8,944 524 3,757 1,558 3,096 11 876 5,560 73 9,301 987 616 412 975 942 248 843 389 34,616 24,765 7,551 847 203 5,176 9,506 570 3,985 1,643 3,276 19 936 5,910 80 9,885 1,052 655 438 1,036 1,001 263 896 413 36,795 26,248 2007 7,784 869 209 5,339 9,801 594 4,104 1,688 3,370 23 967 6,093 83 10,191 1,086 675 451 1,068 1,033 271 924 426 37,935 27,024 2008 8,025 892 215 5,507 10,104 619 4,227 1,734 3,468 27 1,000 6,281 87 10,506 1,121 696 465 1,102 1,065 280 953 439 39,110 27,824 2009 8,274 915 222 5,681 10,417 645 4,353 1,782 3,568 32 1,033 6,476 91 10,831 1,157 717 480 1,136 1,098 289 982 453 40,322 28,649 2010 8,464 933 227 5,813 10,656 664 4,450 1,819 3,645 35 1,058 6,625 94 11,079 1,185 734 491 1,162 1,123 295 1,005 463 41,249 29,279 2011 8,659 952 232 5,949 10,901 684 4,549 1,856 3,723 39 1,085 6,777 97 11,333 1,213 751 502 1,189 1,149 302 1,028 474 42,197 29,924 2012 8,857 971 238 6,088 11,152 705 4,650 1,894 3,803 42 1,111 6,933 100 11,593 1,242 768 513 1,216 1,176 309 1,051 485 43,166 30,584 2013 9,061 990 243 6,230 11,408 726 4,754 1,933 3,886 46 1,139 7,092 103 11,859 1,272 786 525 1,244 1,203 316 1,076 496 44,158 31,259 2014 9,269 1,010 249 6,375 11,670 748 4,860 1,973 3,970 50 1,166 7,255 106 12,131 1,302 804 537 1,273 1,231 323 1,100 507 45,173 31,949 2015 Sectoraloutputsfor(net)exports:BCscenario($million) 9,482 1,030 255 6,524 11,938 770 4,968 2,014 4,055 54 1,195 7,422 110 12,410 1,333 822 549 1,302 1,259 331 1,126 519 46,212 32,655 2016 9,700 1,050 260 6,676 12,213 792 5,079 2,056 4,143 58 1,224 7,592 113 12,694 1,365 841 562 1,332 1,288 338 1,151 531 47,274 33,378 2017 9,923 1,072 266 6,832 12,493 815 5,193 2,098 4,233 62 1,254 7,767 117 12,986 1,398 861 575 1,363 1,318 346 1,178 543 48,360 34,117 2018 10,151 1,093 273 6,991 12,780 839 5,309 2,142 4,325 66 1,285 7,945 120 13,284 1,431 880 588 1,394 1,348 354 1,205 556 49,472 34,873 2019 ThisTableshowstheresultscalculatedusingtheassumptionofeconomicgrowthgiveninSection6.2,pp.138139; Theshareofeachsectorintotal(net)exportsisassumedconstant,accordingtofixedLeontiefcoefficientspresentedinquadrantBofFigureB1,p.217. 2006 2005 TableF2 Present value 81,301 Coalsector 8,997 Petroleumsector 2,183 Gassector RenewableElectricity CoalfiredElectricity InternalcombustionElectricity GasturbineElectricity CombinedcycleElectricity 55,815 Agriculture,forestryandfishing 102,358 Mining 6,331 Food,beveragesandtobacco 42,777 Textile,clothing,footwearandleather 17,516 Wood,paperandprintingproducts 35,065 Basicchemicals 310 Nonmetallicmineralproducts 10,147 Basicironandsteel 63,634 Basicnonferrousmetals 892 Fabricatedmetalproducts 106,423 Machineryandequipment 11,371 Miscellenousmanufacturing 7,049 Water,sewerageanddrainage 4,714 Construction 11,160 Roadtransport 10,788 Railwaytransport 2,836 Watertransport 9,650 Airtransport 4,450 Othertransport,servicesandstorage 396,199 Commercialservices Total 281,524 10,384 1,115 279 7,154 13,074 863 5,427 2,187 4,419 70 1,316 8,128 124 13,589 1,465 901 601 1,426 1,379 362 1,233 569 50,609 35,647 2020 297 Notes: 2006 7,253 797 161 5,004 9,197 546 3,859 1,596 3,176 14 903 5,718 76 9,563 1,016 633 424 1,003 969 255 869 399 35,666 25,483 2005 7,104 804 191 4,864 8,944 524 3,757 1,558 3,096 11 876 5,560 73 9,301 987 616 412 975 942 248 843 389 34,616 24,765 TableF2 7,403 790 136 5,149 9,458 569 3,964 1,635 3,259 18 931 5,880 79 9,832 1,046 651 436 1,032 997 263 895 410 36,749 26,233 2007 7,554 783 116 5,298 9,726 593 4,072 1,676 3,345 22 959 6,047 82 10,109 1,077 669 448 1,062 1,026 271 922 421 37,864 27,015 2008 7,707 776 98 5,451 10,002 617 4,183 1,717 3,432 26 989 6,219 86 10,393 1,109 688 460 1,093 1,056 279 950 433 39,013 27,829 2009 7,861 770 84 5,609 10,287 641 4,297 1,760 3,523 30 1,019 6,396 89 10,687 1,141 707 473 1,124 1,087 287 978 445 40,198 28,676 2010 7,956 758 71 5,725 10,497 660 4,381 1,792 3,589 33 1,042 6,527 92 10,904 1,166 722 483 1,148 1,109 294 1,000 453 41,098 29,333 2011 8,051 747 61 5,845 10,712 679 4,467 1,824 3,658 36 1,065 6,661 95 11,125 1,190 736 493 1,172 1,133 300 1,022 462 42,017 30,010 2012 8,147 736 52 5,966 10,931 698 4,555 1,857 3,727 39 1,088 6,798 97 11,351 1,215 751 503 1,197 1,156 307 1,045 471 42,958 30,706 2013 8,243 726 44 6,091 11,156 718 4,645 1,891 3,799 43 1,112 6,938 100 11,582 1,241 767 513 1,222 1,181 313 1,068 480 43,920 31,422 2014 2015 8,341 715 38 6,218 11,385 739 4,737 1,925 3,871 46 1,136 7,080 103 11,818 1,268 782 523 1,248 1,206 320 1,092 490 44,904 32,157 Sectoraloutputsfor(net)exports:PPP1 ($million) 8,440 704 32 6,348 11,618 759 4,831 1,960 3,945 49 1,161 7,226 106 12,059 1,294 798 534 1,274 1,231 328 1,116 499 45,909 32,911 2016 8,541 694 28 6,481 11,859 784 4,926 1,996 4,021 53 1,187 7,377 109 12,304 1,322 814 544 1,301 1,257 335 1,141 508 46,916 33,645 2017 ThisTableshowstheresultscalculatedusingtheassumptionofeconomicgrowthgiveninSection6.2,pp.138139; Theshareofeachsectorintotal(net)exportsisassumedtovaryaccordingtoinputssubstitution,calculatedfromEquation520,p.110. Present value 76,555 Coalsector 7,460 Petroleumsector 992 Gassector RenewableElectricity CoalfiredElectricity InternalcombustionElectricity GasturbineElectricity CombinedcycleElectricity 55,005 Agriculture,forestryandfishing 100,891 Mining 6,298 Food,beveragesandtobacco 42,143 Textile,clothing,footwearandleather 17,267 Wood,paperandprintingproducts 34,554 Basicchemicals 290 Nonmetallicmineralproducts 9,993 Basicironandsteel 62,741 Basicnonferrousmetals 875 Fabricatedmetalproducts 104,803 Machineryandequipment 11,191 Miscellenousmanufacturing 6,935 Water,sewerageanddrainage 4,641 Construction 11,033 Roadtransport 10,661 Railwaytransport 2,821 Watertransport 9,609 Airtransport 4,352 Othertransport,servicesandstorage 394,733 Commercialservices Total 282,299 8,644 683 24 6,617 12,105 809 5,024 2,032 4,097 57 1,214 7,532 112 12,555 1,350 830 555 1,329 1,285 342 1,167 516 47,945 34,398 2018 8,748 674 20 6,756 12,356 835 5,123 2,069 4,176 60 1,241 7,690 116 12,811 1,378 846 566 1,358 1,312 350 1,193 525 48,997 35,170 2019 8,855 664 18 6,899 12,613 861 5,225 2,106 4,256 64 1,268 7,851 119 13,073 1,408 863 578 1,387 1,341 358 1,220 533 50,073 35,960 2020 298 Notes: 2006 7,132 787 143 4,992 9,169 565 3,834 1,585 3,155 14 900 5,701 76 9,500 1,009 629 421 1,003 968 256 873 391 35,636 25,443 2005 7,104 804 191 4,864 8,944 524 3,757 1,558 3,096 11 876 5,560 73 9,301 987 616 412 975 942 248 843 389 34,616 24,765 TableF2 7,157 770 108 5,124 9,401 607 3,913 1,612 3,215 17 925 5,845 79 9,705 1,032 643 430 1,031 995 264 903 394 36,688 26,162 2007 7,179 755 82 5,259 9,639 651 3,995 1,641 3,277 21 950 5,994 83 9,915 1,055 657 440 1,061 1,023 273 934 397 37,771 26,918 2008 7,201 740 63 5,398 9,884 695 4,079 1,670 3,341 25 976 6,146 86 10,131 1,079 672 449 1,091 1,052 282 966 400 38,887 27,709 2009 7,223 726 48 5,542 10,135 741 4,165 1,701 3,407 29 1,003 6,303 90 10,354 1,104 687 459 1,122 1,081 291 999 403 40,038 28,532 2010 7,189 709 37 5,644 10,313 780 4,221 1,720 3,450 31 1,022 6,415 93 10,500 1,120 697 466 1,145 1,103 298 1,025 403 40,903 29,166 2011 7,156 692 29 5,749 10,495 820 4,279 1,739 3,493 34 1,042 6,528 96 10,650 1,136 707 472 1,169 1,125 305 1,052 403 41,787 29,818 2012 7,125 676 22 5,856 10,682 863 4,338 1,759 3,537 37 1,062 6,646 99 10,802 1,153 717 479 1,193 1,148 313 1,079 402 42,674 30,456 2013 7,096 661 17 5,965 10,873 907 4,398 1,779 3,582 40 1,082 6,766 102 10,959 1,171 727 486 1,218 1,172 321 1,107 401 43,582 31,112 2014 2015 7,071 648 14 6,078 11,069 952 4,460 1,800 3,628 43 1,103 6,889 105 11,119 1,189 738 493 1,243 1,196 328 1,136 400 44,510 31,785 Sectoraloutputsfor(net)exports:SRP1($million) 7,048 635 11 6,192 11,269 997 4,523 1,821 3,676 46 1,125 7,015 108 11,284 1,207 749 501 1,269 1,220 336 1,165 399 45,460 32,474 2016 7,028 624 9 6,309 11,473 1,043 4,588 1,843 3,725 50 1,147 7,144 111 11,453 1,226 760 508 1,295 1,245 344 1,194 398 46,432 33,181 2017 ThisTableshowstheresultscalculatedusingtheassumptionofeconomicgrowthgiveninSection6.2,pp.138139; Theshareofeachsectorintotal(net)exportsisassumedtovaryaccordingtoinputssubstitution,calculatedfromEquation520,p.110. Present value 69,952 Coalsector 7,096 Petroleumsector 779 Gassector RenewableElectricity CoalfiredElectricity InternalcombustionElectricity GasturbineElectricity CombinedcycleElectricity 54,276 Agriculture,forestryandfishing 99,250 Mining 7,383 Food,beveragesandtobacco 40,709 Textile,clothing,footwearandleather 16,620 Wood,paperandprintingproducts 33,301 Basicchemicals 275 Nonmetallicmineralproducts 9,820 Basicironandsteel 61,741 Basicnonferrousmetals 883 Fabricatedmetalproducts 101,192 Machineryandequipment 10,782 Miscellenousmanufacturing 6,709 Water,sewerageanddrainage 4,487 Construction 11,007 Roadtransport 10,607 Railwaytransport 2,861 Watertransport 9,834 Airtransport 3,896 Othertransport,servicesandstorage 392,825 Commercialservices Total 280,507 7,011 613 7 6,429 11,682 1,089 4,655 1,865 3,775 53 1,169 7,275 114 11,626 1,245 771 516 1,322 1,271 353 1,224 398 47,425 33,904 2018 6,997 604 6 6,551 11,895 1,136 4,723 1,888 3,826 56 1,192 7,409 118 11,804 1,265 783 524 1,350 1,297 361 1,255 397 48,442 34,645 2019 6,984 596 5 6,674 12,111 1,180 4,794 1,913 3,880 60 1,215 7,544 121 11,987 1,285 796 532 1,377 1,323 370 1,286 399 49,506 35,447 2020 299 Notes: 2006 7,183 769 125 4,991 9,174 546 3,849 1,592 3,168 14 900 5,704 75 9,537 1,013 631 423 1,001 967 255 868 398 35,644 25,470 2005 7,104 804 191 4,864 8,944 524 3,757 1,558 3,096 11 876 5,560 73 9,301 987 616 412 975 942 248 843 389 34,616 24,765 TableF2 7,251 735 83 5,122 9,410 568 3,943 1,627 3,242 17 926 5,851 78 9,778 1,040 647 433 1,028 993 262 894 407 36,703 26,239 2007 7,314 703 56 5,257 9,653 591 4,040 1,663 3,319 21 952 6,002 82 10,027 1,068 664 444 1,056 1,020 270 920 416 37,794 27,059 2008 7,373 673 38 5,396 9,902 614 4,139 1,700 3,398 25 978 6,158 85 10,283 1,096 680 455 1,084 1,047 278 947 426 38,919 27,923 2009 7,431 644 25 5,538 10,158 637 4,242 1,739 3,479 28 1,006 6,318 88 10,546 1,126 698 467 1,113 1,075 286 975 437 40,077 28,826 2010 7,430 612 17 5,639 10,341 654 4,315 1,766 3,536 31 1,025 6,432 90 10,733 1,147 710 475 1,134 1,096 292 995 444 40,950 29,545 2011 7,431 582 12 5,743 10,528 675 4,388 1,793 3,594 34 1,045 6,550 93 10,923 1,168 722 483 1,156 1,117 298 1,017 449 41,823 30,249 2012 7,432 554 8 5,849 10,720 696 4,464 1,821 3,653 37 1,066 6,671 95 11,117 1,189 734 492 1,179 1,139 305 1,039 455 42,715 30,974 2013 7,434 527 6 5,957 10,914 713 4,541 1,850 3,715 40 1,087 6,792 98 11,316 1,212 747 501 1,201 1,160 311 1,061 464 43,653 31,765 2014 2015 7,439 504 4 6,067 11,112 730 4,621 1,880 3,778 42 1,108 6,915 100 11,522 1,235 761 510 1,224 1,182 317 1,083 472 44,613 32,579 Sectoraloutputsfor(net)exports:PPP2($million) 7,447 482 3 6,179 11,314 747 4,703 1,911 3,843 45 1,129 7,041 103 11,732 1,258 775 519 1,247 1,204 324 1,106 481 45,595 33,415 2016 7,459 463 2 6,293 11,521 763 4,787 1,942 3,910 48 1,151 7,170 105 11,948 1,282 789 528 1,271 1,227 331 1,129 490 46,600 34,273 2017 ThisTableshowstheresultscalculatedusingtheassumptionofeconomicgrowthgiveninSection6.2,pp.138139; Theshareofeachsectorintotal(net)exportsisassumedtovaryaccordingtoinputssubstitution,calculatedfromEquation520,p.110. Present value 71,959 Coalsector 6,331 Petroleumsector 645 Gassector RenewableElectricity CoalfiredElectricity InternalcombustionElectricity GasturbineElectricity CombinedcycleElectricity 54,220 Agriculture,forestryandfishing 99,475 Mining 6,229 Food,beveragesandtobacco 41,551 Textile,clothing,footwearandleather 17,038 Wood,paperandprintingproducts 34,081 Basicchemicals 270 Nonmetallicmineralproducts 9,844 Basicironandsteel 61,873 Basicnonferrousmetals 859 Fabricatedmetalproducts 103,285 Machineryandequipment 11,022 Miscellenousmanufacturing 6,830 Water,sewerageanddrainage 4,573 Construction 10,906 Roadtransport 10,535 Railwaytransport 2,804 Watertransport 9,561 Airtransport 4,272 Othertransport,servicesandstorage 393,385 Commercialservices Total 284,477 7,473 445 1 6,410 11,732 780 4,874 1,975 3,978 51 1,174 7,302 108 12,169 1,307 804 538 1,295 1,250 338 1,153 499 47,629 35,154 2018 7,491 429 1 6,529 11,948 796 4,962 2,008 4,048 55 1,197 7,436 110 12,396 1,332 819 548 1,320 1,274 345 1,176 509 48,682 36,059 2019 7,511 415 1 6,651 12,169 812 5,053 2,043 4,121 58 1,221 7,573 113 12,629 1,358 834 558 1,345 1,298 352 1,201 520 49,759 36,986 2020 300 Notes: 2006 6,940 749 89 4,966 9,117 584 3,799 1,569 3,125 13 894 5,669 76 9,412 999 624 417 1,000 965 256 876 382 35,584 25,390 2005 7,104 804 191 4,864 8,944 524 3,757 1,558 3,096 11 876 5,560 73 9,301 987 616 412 975 942 248 843 389 34,616 24,765 TableF2 6,763 699 43 5,072 9,296 643 3,843 1,582 3,155 16 914 5,781 79 9,527 1,012 632 423 1,026 989 265 910 375 36,582 26,118 2007 6,585 654 22 5,181 9,480 704 3,890 1,596 3,188 19 933 5,897 82 9,649 1,025 640 428 1,053 1,014 274 944 369 37,612 26,904 2008 6,413 614 11 5,293 9,670 764 3,938 1,610 3,221 22 954 6,015 86 9,775 1,039 649 434 1,080 1,039 283 979 363 38,672 27,728 2009 6,250 578 6 5,408 9,866 828 3,988 1,624 3,256 26 975 6,139 89 9,906 1,053 658 440 1,108 1,065 293 1,014 356 39,751 28,555 2010 6,051 543 3 5,483 9,990 884 4,010 1,629 3,270 28 988 6,218 92 9,966 1,060 662 443 1,129 1,084 300 1,043 347 40,545 29,187 2011 5,865 512 2 5,560 10,118 939 4,034 1,634 3,285 30 1,002 6,299 94 10,031 1,067 666 446 1,149 1,103 308 1,072 338 41,357 29,832 2012 5,691 485 1 5,639 10,250 994 4,060 1,639 3,301 32 1,016 6,383 97 10,100 1,074 671 449 1,170 1,122 316 1,101 330 42,189 30,489 2013 5,527 462 0 5,719 10,383 1,045 4,088 1,647 3,320 35 1,031 6,466 100 10,175 1,083 677 452 1,191 1,140 323 1,129 323 43,063 31,199 2014 2015 5,376 441 0 5,802 10,521 1,096 4,119 1,655 3,340 37 1,045 6,552 102 10,256 1,091 683 456 1,212 1,160 331 1,158 317 43,958 31,925 Sectoraloutputsfor(net)exports:SRP2($million) 5,237 424 0 5,886 10,663 1,145 4,152 1,664 3,363 39 1,060 6,641 105 10,343 1,101 689 460 1,234 1,179 338 1,188 311 44,876 32,667 2016 5,109 409 0 5,973 10,809 1,195 4,187 1,674 3,387 42 1,076 6,732 108 10,435 1,111 696 464 1,255 1,199 346 1,217 305 45,817 33,425 2017 ThisTableshowstheresultscalculatedusingtheassumptionofeconomicgrowthgiveninSection6.2,pp.138139; Theshareofeachsectorintotal(net)exportsisassumedtovaryaccordingtoinputssubstitution,calculatedfromEquation520,p.110. Present value 60,933 Coalsector 5,913 Petroleumsector 502 Gassector RenewableElectricity CoalfiredElectricity InternalcombustionElectricity GasturbineElectricity CombinedcycleElectricity 52,843 Agriculture,forestryandfishing 96,400 Mining 8,147 Food,beveragesandtobacco 38,927 Textile,clothing,footwearandleather 15,862 Wood,paperandprintingproducts 31,792 Basicchemicals 242 Nonmetallicmineralproducts 9,518 Basicironandsteel 59,986 Basicnonferrousmetals 870 Fabricatedmetalproducts 96,674 Machineryandequipment 10,274 Miscellenousmanufacturing 6,421 Water,sewerageanddrainage 4,292 Construction 10,847 Roadtransport 10,421 Railwaytransport 2,874 Watertransport 9,956 Airtransport 3,458 Othertransport,servicesandstorage 389,987 Commercialservices Total 281,065 4,990 396 0 6,062 10,960 1,243 4,225 1,685 3,413 44 1,092 6,826 110 10,534 1,122 703 469 1,278 1,220 354 1,247 301 46,780 34,202 2018 4,880 385 0 6,153 11,114 1,292 4,265 1,697 3,441 46 1,109 6,922 113 10,638 1,133 710 474 1,301 1,240 362 1,277 296 47,767 34,996 2019 4,779 376 0 6,247 11,274 1,340 4,307 1,710 3,471 49 1,126 7,021 116 10,748 1,145 718 479 1,324 1,261 370 1,308 292 48,777 35,809 2020 301 Notes: 7,147 755 107 4,985 9,162 546 3,844 1,590 3,164 14 899 5,696 75 9,523 1,012 630 422 1,000 966 255 868 397 35,632 25,464 7,104 804 191 4,864 8,944 524 3,757 1,558 3,096 11 876 5,560 73 9,301 987 616 412 975 942 248 843 389 34,616 24,765 7,172 708 61 5,109 9,385 567 3,932 1,623 3,234 17 923 5,836 78 9,751 1,037 645 432 1,026 991 262 893 405 36,680 26,249 2007 7,189 665 35 5,237 9,615 589 4,024 1,657 3,306 20 948 5,979 81 9,986 1,063 661 442 1,052 1,017 270 919 414 37,759 27,097 2008 7,201 624 21 5,367 9,851 612 4,118 1,692 3,380 24 973 6,127 84 10,227 1,090 677 453 1,080 1,043 277 945 423 38,871 27,992 2009 7,212 586 12 5,502 10,093 635 4,214 1,728 3,456 27 999 6,278 87 10,476 1,118 693 464 1,107 1,070 285 973 433 40,016 28,929 2010 7,168 547 7 5,596 10,264 654 4,281 1,752 3,509 30 1,017 6,386 89 10,647 1,137 704 471 1,128 1,089 291 993 438 40,857 29,643 2011 7,126 511 4 5,693 10,438 674 4,349 1,777 3,562 33 1,036 6,496 92 10,822 1,157 715 479 1,148 1,109 297 1,014 443 41,716 30,378 2012 7,085 478 2 5,790 10,613 690 4,419 1,804 3,618 35 1,055 6,605 94 11,003 1,177 726 487 1,169 1,129 303 1,035 450 42,619 31,180 2013 7,049 449 1 5,889 10,792 705 4,492 1,831 3,675 38 1,074 6,717 96 11,189 1,198 739 495 1,190 1,149 309 1,057 457 43,544 32,004 2014 7,017 422 1 5,991 10,976 720 4,566 1,859 3,734 40 1,093 6,831 98 11,380 1,219 751 503 1,211 1,169 316 1,078 465 44,491 32,851 2015 6,989 399 0 6,094 11,163 735 4,642 1,888 3,795 43 1,113 6,948 101 11,576 1,241 764 512 1,233 1,190 322 1,100 474 45,460 33,719 2016 6,965 378 0 6,200 11,355 749 4,721 1,917 3,857 46 1,134 7,067 103 11,778 1,263 777 521 1,255 1,211 329 1,122 483 46,452 34,610 2017 ThisTableshowstheresultscalculatedusingtheassumptionofeconomicgrowthgiveninSection6.2,pp.138139; Theshareofeachsectorintotal(net)exportsisassumedtovaryaccordingtoinputssubstitution,calculatedfromEquation520,p.110. 2006 Sectoraloutputsfor(net)exports:PPPforEarlyaction($million) 2005 TableF2 Present value 69,773 Coalsector 5,868 Petroleumsector 558 Gassector RenewableElectricity CoalfiredElectricity InternalcombustionElectricity GasturbineElectricity CombinedcycleElectricity 53,829 Agriculture,forestryandfishing 98,772 Mining 6,185 Food,beveragesandtobacco 41,262 Textile,clothing,footwearandleather 16,927 Wood,paperandprintingproducts 33,851 Basicchemicals 261 Nonmetallicmineralproducts 9,770 Basicironandsteel 61,442 Basicnonferrousmetals 851 Fabricatedmetalproducts 102,546 Machineryandequipment 10,940 Miscellenousmanufacturing 6,779 Water,sewerageanddrainage 4,540 Construction 10,842 Roadtransport 10,471 Railwaytransport 2,796 Watertransport 9,535 Airtransport 4,235 Othertransport,servicesandstorage 392,722 Commercialservices Total 285,704 6,945 359 0 6,308 11,550 763 4,802 1,948 3,921 49 1,155 7,189 105 11,985 1,286 791 530 1,278 1,233 335 1,145 492 47,467 35,524 2018 6,928 342 0 6,419 11,751 777 4,885 1,979 3,987 52 1,176 7,314 108 12,197 1,310 805 539 1,301 1,255 342 1,168 501 48,505 36,462 2019 6,915 327 0 6,532 11,955 790 4,970 2,012 4,055 55 1,198 7,441 110 12,416 1,334 819 549 1,324 1,277 349 1,191 511 49,567 37,422 2020 302 Notes: 7,039 768 117 4,980 9,144 574 3,817 1,577 3,140 14 897 5,685 76 9,457 1,004 626 419 1,001 967 256 874 387 35,610 25,415 7,104 804 191 4,864 8,944 524 3,757 1,558 3,096 11 876 5,560 73 9,301 987 616 412 975 942 248 843 389 34,616 24,765 6,965 735 73 5,099 9,350 625 3,879 1,598 3,186 17 919 5,814 79 9,618 1,022 637 426 1,029 993 265 906 385 36,635 26,132 2007 6,888 704 46 5,221 9,561 677 3,943 1,619 3,233 20 942 5,946 83 9,784 1,040 649 434 1,057 1,019 274 939 383 37,690 26,898 2008 6,811 676 29 5,347 9,779 730 4,009 1,640 3,282 24 965 6,082 86 9,955 1,059 660 442 1,086 1,046 283 973 381 38,778 27,702 2009 6,736 650 19 5,476 10,002 784 4,077 1,663 3,333 27 989 6,222 90 10,132 1,079 673 450 1,115 1,074 292 1,007 380 39,899 28,539 2010 6,613 621 12 5,565 10,154 834 4,116 1,674 3,360 30 1,006 6,319 92 10,234 1,090 679 454 1,137 1,094 299 1,035 374 40,717 29,153 2011 6,497 596 8 5,656 10,310 884 4,156 1,686 3,388 32 1,022 6,417 95 10,339 1,102 686 459 1,160 1,115 307 1,063 369 41,553 29,782 2012 6,388 573 6 5,750 10,470 935 4,198 1,698 3,418 35 1,040 6,518 98 10,449 1,114 693 464 1,182 1,136 315 1,091 363 42,408 30,426 2013 6,284 552 4 5,845 10,633 986 4,241 1,711 3,449 38 1,057 6,622 101 10,563 1,126 701 469 1,205 1,158 322 1,120 358 43,282 31,085 2014 6,187 533 3 5,943 10,801 1,037 4,286 1,724 3,481 40 1,075 6,728 104 10,681 1,139 709 474 1,229 1,180 330 1,149 353 44,176 31,757 2015 6,094 517 2 6,042 10,970 1,084 4,334 1,739 3,515 43 1,093 6,834 107 10,804 1,153 717 480 1,253 1,201 338 1,178 350 45,118 32,492 2016 6,009 502 1 6,143 11,143 1,131 4,383 1,755 3,551 46 1,112 6,942 110 10,933 1,167 726 486 1,277 1,224 346 1,208 347 46,083 33,245 2017 ThisTableshowstheresultscalculatedusingtheassumptionofeconomicgrowthgiveninSection6.2,pp.138139; Theshareofeachsectorintotal(net)exportsisassumedtovaryaccordingtoinputssubstitution,calculatedfromEquation520,p.110. 2006 Sectoraloutputsfor(net)exports:SRPforearlyaction($million) 2005 TableF2 Present value 65,291 Coalsector 6,458 Petroleumsector 604 Gassector RenewableElectricity CoalfiredElectricity InternalcombustionElectricity GasturbineElectricity CombinedcycleElectricity 53,571 Agriculture,forestryandfishing 97,843 Mining 7,802 Food,beveragesandtobacco 39,809 Textile,clothing,footwearandleather 16,233 Wood,paperandprintingproducts 32,536 Basicchemicals 259 Nonmetallicmineralproducts 9,672 Basicironandsteel 60,883 Basicnonferrousmetals 878 Fabricatedmetalproducts 98,913 Machineryandequipment 10,526 Miscellenousmanufacturing 6,561 Water,sewerageanddrainage 4,388 Construction 10,931 Roadtransport 10,520 Railwaytransport 2,870 Watertransport 9,902 Airtransport 3,663 Othertransport,servicesandstorage 391,277 Commercialservices Total 280,549 5,931 490 1 6,246 11,322 1,177 4,435 1,772 3,589 49 1,131 7,053 113 11,067 1,182 736 492 1,301 1,246 354 1,238 345 47,071 34,017 2018 5,859 479 1 6,353 11,504 1,224 4,488 1,789 3,628 52 1,150 7,167 116 11,207 1,197 745 498 1,326 1,269 362 1,268 343 48,083 34,808 2019 5,794 470 0 6,461 11,691 1,271 4,544 1,808 3,669 54 1,170 7,284 119 11,352 1,213 755 505 1,352 1,293 371 1,299 342 49,119 35,618 2020 303 Notes: 7,324 825 197 5,017 9,221 547 3,869 1,600 3,185 15 905 5,732 76 9,589 1,019 635 425 1,005 971 255 869 401 35,689 25,495 7,104 804 191 4,864 8,944 524 3,757 1,558 3,096 11 876 5,560 73 9,301 987 616 412 975 942 248 843 389 34,616 24,765 7,551 847 203 5,176 9,506 570 3,985 1,643 3,276 19 936 5,910 80 9,885 1,052 655 438 1,036 1,001 263 896 413 36,795 26,248 2007 7,784 869 209 5,339 9,801 594 4,104 1,688 3,370 23 967 6,093 83 10,191 1,086 675 451 1,068 1,033 271 924 426 37,935 27,024 2008 8,025 892 215 5,507 10,104 619 4,227 1,734 3,468 27 1,000 6,281 87 10,506 1,121 696 465 1,102 1,065 280 953 439 39,110 27,824 2009 8,274 915 222 5,681 10,417 645 4,353 1,782 3,568 32 1,033 6,476 91 10,831 1,157 717 480 1,136 1,098 289 982 453 40,322 28,649 2010 8,060 775 26 5,739 10,522 661 4,392 1,796 3,598 33 1,044 6,543 92 10,931 1,169 724 484 1,150 1,112 294 1,001 455 41,121 29,217 2011 7,773 656 3 5,799 10,629 676 4,432 1,810 3,629 35 1,056 6,611 94 11,034 1,180 730 489 1,165 1,125 299 1,020 457 41,940 30,078 2012 7,489 556 0 5,860 10,739 691 4,474 1,825 3,662 37 1,068 6,680 95 11,142 1,192 737 493 1,180 1,139 305 1,039 460 42,778 30,997 2013 7,219 470 0 5,923 10,853 708 4,517 1,840 3,695 39 1,080 6,754 97 11,253 1,205 743 498 1,195 1,154 310 1,059 461 43,613 31,902 2014 6,966 398 0 5,987 10,968 721 4,562 1,857 3,731 40 1,092 6,826 98 11,369 1,218 751 503 1,211 1,169 316 1,078 465 44,495 32,876 2015 6,732 339 0 6,052 11,086 731 4,610 1,875 3,769 42 1,105 6,900 100 11,492 1,231 759 508 1,226 1,183 321 1,098 470 45,399 33,873 2016 6,516 290 0 6,120 11,208 741 4,660 1,894 3,809 44 1,118 6,977 101 11,622 1,246 767 514 1,242 1,198 327 1,117 475 46,324 34,892 2017 ThisTableshowstheresultscalculatedusingtheassumptionofeconomicgrowthgiveninSection6.2,pp.138139; Theshareofeachsectorintotal(net)exportsisassumedtovaryaccordingtoinputssubstitution,calculatedfromEquation520,p.110. 2006 Sectoraloutputsfor(net)exports:PPPforDelayaction($million) 2005 TableF2 Present value 72,010 Coalsector 6,654 Petroleumsector 1,147 Gassector RenewableElectricity CoalfiredElectricity InternalcombustionElectricity GasturbineElectricity CombinedcycleElectricity 54,186 Agriculture,forestryandfishing 99,419 Mining 6,185 Food,beveragesandtobacco 41,549 Textile,clothing,footwearandleather 17,042 Wood,paperandprintingproducts 34,083 Basicchemicals 269 Nonmetallicmineralproducts 9,837 Basicironandsteel 61,833 Basicnonferrousmetals 857 Fabricatedmetalproducts 103,278 Machineryandequipment 11,021 Miscellenousmanufacturing 6,831 Water,sewerageanddrainage 4,573 Construction 10,897 Roadtransport 10,525 Railwaytransport 2,802 Watertransport 9,550 Airtransport 4,285 Othertransport,servicesandstorage 393,417 Commercialservices Total 285,509 6,315 250 0 6,188 11,334 748 4,713 1,914 3,851 46 1,132 7,056 103 11,757 1,261 776 520 1,258 1,213 332 1,137 481 47,272 35,932 2018 6,129 216 0 6,259 11,463 755 4,768 1,935 3,895 48 1,146 7,137 104 11,899 1,277 785 526 1,274 1,228 338 1,156 488 48,242 36,994 2019 5,956 189 0 6,332 11,596 761 4,826 1,957 3,941 49 1,160 7,220 106 12,047 1,293 794 532 1,291 1,244 344 1,176 496 49,236 38,077 2020 304 Notes: 7,324 825 197 5,017 9,221 547 3,869 1,600 3,185 15 905 5,732 76 9,589 1,019 635 425 1,005 971 255 869 401 35,689 25,495 7,104 804 191 4,864 8,944 524 3,757 1,558 3,096 11 876 5,560 73 9,301 987 616 412 975 942 248 843 389 34,616 24,765 7,551 847 203 5,176 9,506 570 3,985 1,643 3,276 19 936 5,910 80 9,885 1,052 655 438 1,036 1,001 263 896 413 36,795 26,248 2007 7,784 869 209 5,339 9,801 594 4,104 1,688 3,370 23 967 6,093 83 10,191 1,086 675 451 1,068 1,033 271 924 426 37,935 27,024 2008 8,025 892 215 5,507 10,104 619 4,227 1,734 3,468 27 1,000 6,281 87 10,506 1,121 696 465 1,102 1,065 280 953 439 39,110 27,824 2009 8,274 915 222 5,681 10,417 645 4,353 1,782 3,568 32 1,033 6,476 91 10,831 1,157 717 480 1,136 1,098 289 982 453 40,322 28,649 2010 7,907 824 73 5,740 10,507 717 4,349 1,775 3,558 34 1,043 6,533 93 10,823 1,156 717 480 1,155 1,115 297 1,014 436 41,096 29,131 2011 7,524 744 26 5,800 10,600 788 4,346 1,768 3,550 35 1,053 6,593 96 10,821 1,156 718 480 1,174 1,132 305 1,047 420 41,890 29,773 2012 7,154 676 9 5,863 10,696 858 4,347 1,763 3,545 37 1,063 6,654 99 10,825 1,156 719 480 1,194 1,149 313 1,079 405 42,703 30,469 2013 6,808 616 3 5,928 10,797 930 4,349 1,758 3,540 39 1,074 6,719 101 10,834 1,157 719 481 1,214 1,167 321 1,112 389 43,516 31,150 2014 6,489 565 1 5,995 10,903 1,001 4,353 1,754 3,538 41 1,086 6,788 104 10,850 1,158 721 482 1,234 1,185 329 1,144 373 44,348 31,844 2015 6,195 521 0 6,064 11,013 1,070 4,361 1,751 3,538 44 1,098 6,858 107 10,873 1,161 722 483 1,255 1,204 338 1,177 358 45,201 32,548 2016 5,923 484 0 6,134 11,125 1,133 4,372 1,751 3,542 46 1,110 6,929 109 10,904 1,164 725 484 1,276 1,222 346 1,209 346 46,102 33,311 2017 ThisTableshowstheresultscalculatedusingtheassumptionofeconomicgrowthgiveninSection6.2,pp.138139; Theshareofeachsectorintotal(net)exportsisassumedtovaryaccordingtoinputssubstitution,calculatedfromEquation520,p.110. 2006 Sectoraloutputsfor(net)exports:SRPforDelayaction($million) 2005 TableF2 Present value 70,153 Coalsector 7,272 Petroleumsector 1,195 Gassector RenewableElectricity CoalfiredElectricity InternalcombustionElectricity GasturbineElectricity CombinedcycleElectricity 54,226 Agriculture,forestryandfishing 99,166 Mining 7,334 Food,beveragesandtobacco 40,698 Textile,clothing,footwearandleather 16,620 Wood,paperandprintingproducts 33,296 Basicchemicals 274 Nonmetallicmineralproducts 9,811 Basicironandsteel 61,683 Basicnonferrousmetals 881 Fabricatedmetalproducts 101,160 Machineryandequipment 10,779 Miscellenousmanufacturing 6,709 Water,sewerageanddrainage 4,486 Construction 10,995 Roadtransport 10,594 Railwaytransport 2,858 Watertransport 9,821 Airtransport 3,907 Othertransport,servicesandstorage 392,819 Commercialservices Total 281,144 5,676 453 0 6,207 11,242 1,195 4,386 1,752 3,548 48 1,122 7,002 112 10,943 1,168 728 486 1,297 1,241 354 1,241 335 47,028 34,090 2018 5,451 428 0 6,282 11,364 1,255 4,403 1,754 3,557 50 1,135 7,078 115 10,991 1,173 732 489 1,318 1,260 363 1,274 324 47,977 34,885 2019 5,244 406 0 6,360 11,490 1,314 4,424 1,757 3,568 52 1,149 7,158 117 11,046 1,179 737 491 1,339 1,279 371 1,306 315 48,952 35,696 2020 305 Note: 579 978 386 2,563 241 89 35 35 3,043 37,905 99 85,023 775 151 76 121 250 17,784 150,133 562 949 374 2,487 233 86 34 34 2,952 36,769 96 82,466 752 146 74 117 243 17,252 145,626 597 1,008 398 2,642 248 91 37 36 3,137 39,077 102 87,659 799 156 79 125 258 18,332 154,780 2007 2009 615 634 1,039 1,071 410 423 2,724 2,808 256 263 94 97 38 39 37 38 3,233 3,333 40,286 41,532 105 108 90,377 93,180 824 849 160 165 81 84 129 133 266 274 18,898 19,481 159,572 164,513 2008 2011 654 669 1,104 1,129 436 446 2,895 2,961 272 278 100 102 40 41 39 40 3,436 3,515 42,817 43,796 112 114 96,070 98,269 876 896 170 174 86 88 137 140 282 289 20,082 20,542 169,608 173,489 2010 ThisTableshowstheresultsobtainedbytheapplicationofEquation534,p.124. 2006 684 1,155 456 3,029 284 105 42 41 3,595 44,799 117 100,519 916 178 90 143 296 21,012 177,461 2012 700 1,182 466 3,098 291 107 43 42 3,677 45,824 119 102,820 937 182 92 146 302 21,493 181,523 2013 716 1,209 477 3,169 297 110 44 43 3,762 46,873 122 105,175 959 187 95 150 309 21,985 185,679 2014 732 1,236 488 3,242 304 112 45 44 3,848 47,946 125 107,583 981 191 97 153 316 22,488 189,931 2015 2016 749 1,265 499 3,316 311 115 46 45 3,936 49,044 128 110,047 1,003 195 99 156 324 23,003 194,280 Sectoralsupplyofinvestmentgoods:BCscenario($million) 2005 TableF3 Present value Coalsector Petroleumsector Gassector RenewableElectricity CoalfiredElectricity InternalcombustionElectricity GasturbineElectricity CombinedcycleElectricity 6,423 Agriculture,forestryandfishing 10,850 Mining Food,beveragesandtobacco Textile,clothing,footwearandleather 4,282 28,443 Wood,paperandprintingproducts 2,669 Basicchemicals 983 Nonmetallicmineralproducts 394 Basicironandsteel 387 Basicnonferrousmetals 33,762 Fabricatedmetalproducts 420,660 Machineryandequipment 1,096 Miscellenousmanufacturing Water,sewerageanddrainage 943,745 Construction 8,603 Roadtransport 1,675 Railwaytransport 848 Watertransport 1,342 Airtransport Othertransport,servicesandstorage 2,776 197,323 Commercialservices Total 1,666,260 2018 766 783 1,294 1,323 511 522 3,392 3,469 318 325 117 120 47 48 46 47 4,026 4,118 50,167 51,316 131 134 112,568 115,146 1,026 1,049 200 204 101 103 160 164 331 339 23,529 24,068 198,729 203,281 2017 2020 801 820 1,354 1,385 534 547 3,549 3,630 333 341 123 125 49 50 48 49 4,212 4,309 52,492 53,694 137 140 117,784 120,482 1,073 1,098 209 214 106 108 168 171 346 354 24,620 25,183 207,938 212,701 2019 306 Note: 562 949 374 2,487 233 86 34 34 2,952 36,769 96 82,466 752 146 74 117 243 17,252 145,626 2005 2007 615 1,039 410 2,723 256 94 38 37 3,233 40,275 105 90,352 824 160 81 129 266 18,893 159,527 2008 2010 634 653 1,071 1,104 423 436 2,807 2,893 263 271 97 100 39 40 38 39 3,332 3,435 41,517 42,797 108 111 93,146 96,027 849 875 165 170 84 86 132 137 274 282 19,474 20,073 164,453 169,531 2009 2012 668 684 1,129 1,155 446 456 2,959 3,027 278 284 102 105 41 42 40 41 3,513 3,593 43,773 44,771 114 117 98,217 100,457 895 916 174 178 88 90 140 143 289 295 20,531 20,999 173,397 177,352 2011 699 1,181 466 3,096 290 107 43 42 3,675 45,792 119 102,749 937 182 92 146 302 21,478 181,397 2013 2015 715 731 1,208 1,235 477 488 3,167 3,239 297 304 109 112 44 45 43 44 3,759 3,844 46,837 47,906 122 125 105,093 107,491 958 980 186 191 94 97 149 153 309 316 21,968 22,470 185,536 189,770 2014 Sectoralsupplyofinvestmentgoods:PPP1 ($million) 579 597 978 1,008 386 398 2,563 2,642 241 248 89 91 35 37 35 36 3,043 3,136 37,902 39,070 99 102 85,015 87,642 775 799 151 156 76 79 121 125 250 258 17,782 18,329 150,119 154,751 2006 TableF3 ThisTableshowstheresultsobtainedbytheapplicationofEquation534,p.124. Present value Coalsector Petroleumsector Gassector RenewableElectricity CoalfiredElectricity InternalcombustionElectricity GasturbineElectricity CombinedcycleElectricity 6,420 Agriculture,forestryandfishing 10,844 Mining Food,beveragesandtobacco Textile,clothing,footwearandleather 4,280 28,428 Wood,paperandprintingproducts 2,667 Basicchemicals 983 Nonmetallicmineralproducts 393 Basicironandsteel 387 Basicnonferrousmetals 33,740 Fabricatedmetalproducts 420,356 Machineryandequipment 1,095 Miscellenousmanufacturing Water,sewerageanddrainage 942,933 Construction 8,598 Roadtransport 1,674 Railwaytransport 847 Watertransport 1,341 Airtransport Othertransport,servicesandstorage 2,774 197,206 Commercialservices Total 1,664,965 2017 748 765 1,264 1,292 499 510 3,313 3,388 311 318 115 117 46 47 45 46 3,932 4,020 48,999 50,089 128 130 109,945 112,352 1,002 1,024 195 199 99 101 156 160 323 331 22,982 23,500 194,101 198,391 2016 783 1,321 522 3,465 325 120 48 47 4,111 51,204 133 114,814 1,047 204 103 163 338 24,030 202,778 2018 2020 800 819 1,351 1,382 533 545 3,544 3,624 332 340 122 125 49 50 48 49 4,203 4,297 52,344 53,511 136 140 117,332 119,906 1,071 1,095 208 213 105 108 167 171 346 353 24,572 25,126 207,265 211,853 2019 307 Note: 562 949 374 2,487 233 86 34 34 2,952 36,769 96 82,466 752 146 74 117 243 17,252 145,626 2005 2007 615 1,039 410 2,722 255 94 38 37 3,231 40,261 105 90,320 823 160 81 128 266 18,887 159,473 2008 2010 634 653 1,070 1,103 422 435 2,806 2,892 263 271 97 100 39 40 38 39 3,331 3,433 41,498 42,774 108 111 93,104 95,974 849 875 165 170 84 86 132 136 274 282 19,466 20,063 164,380 169,440 2009 2012 668 683 1,128 1,154 445 455 2,958 3,025 277 284 102 105 41 42 40 41 3,511 3,590 43,745 44,738 114 117 98,154 100,383 895 915 174 178 88 90 140 143 289 295 20,519 20,985 173,287 177,223 2011 699 1,180 466 3,093 290 107 43 42 3,670 45,729 119 102,571 935 182 92 146 302 21,455 181,121 2013 2015 714 731 1,206 1,233 476 487 3,163 3,235 297 303 109 112 44 45 43 44 3,752 3,836 46,743 47,779 122 125 104,807 107,095 956 977 186 190 94 96 149 152 309 315 21,937 22,430 185,108 189,185 2014 Sectoralsupplyofinvestmentgoods:SRP1($million) 579 597 978 1,008 386 398 2,563 2,641 240 248 89 91 35 37 35 36 3,042 3,135 37,897 39,061 99 102 85,004 87,621 775 799 151 156 76 79 121 125 250 258 17,780 18,325 150,100 154,715 2006 TableF3 ThisTableshowstheresultsobtainedbytheapplicationofEquation534,p.124. Present value Coalsector Petroleumsector Gassector RenewableElectricity CoalfiredElectricity InternalcombustionElectricity GasturbineElectricity CombinedcycleElectricity 6,416 Agriculture,forestryandfishing 10,835 Mining Food,beveragesandtobacco Textile,clothing,footwearandleather 4,276 28,408 Wood,paperandprintingproducts 2,665 Basicchemicals 982 Nonmetallicmineralproducts 393 Basicironandsteel 387 Basicnonferrousmetals 33,707 Fabricatedmetalproducts 419,872 Machineryandequipment 1,094 Miscellenousmanufacturing Water,sewerageanddrainage 941,505 Construction 8,589 Roadtransport 1,671 Railwaytransport 846 Watertransport 1,340 Airtransport Othertransport,servicesandstorage 2,772 197,039 Commercialservices Total 1,662,798 2017 747 764 1,261 1,290 498 509 3,308 3,383 310 317 114 117 46 47 45 46 3,922 4,010 48,839 49,924 127 130 109,433 111,825 999 1,021 194 199 98 101 156 159 323 330 22,934 23,449 193,355 197,620 2016 782 1,319 520 3,459 324 119 48 47 4,100 51,033 133 114,270 1,044 203 103 163 337 23,977 201,982 2018 2020 799 817 1,349 1,379 532 545 3,538 3,619 332 339 122 125 49 50 48 49 4,192 4,288 52,167 53,396 136 139 116,771 119,593 1,068 1,092 207 212 105 108 166 170 345 353 24,517 25,081 206,442 211,356 2019 308 Note: 562 949 374 2,487 233 86 34 34 2,952 36,769 96 82,466 752 146 74 117 243 17,252 145,626 2005 2007 615 1,039 410 2,723 255 94 38 37 3,232 40,264 105 90,327 824 160 81 128 266 18,888 159,485 2008 2010 634 653 1,070 1,103 422 435 2,806 2,892 263 271 97 100 39 40 38 39 3,331 3,433 41,502 42,779 108 111 93,113 95,987 849 875 165 170 84 86 132 137 274 282 19,468 20,065 164,396 169,461 2009 2012 668 683 1,128 1,154 445 455 2,958 3,025 278 284 102 105 41 42 40 41 3,511 3,590 43,752 44,721 114 117 98,169 100,310 895 915 174 178 88 90 140 143 289 295 20,522 20,982 173,313 177,128 2011 699 1,180 466 3,093 290 107 43 42 3,670 45,713 119 102,499 935 182 92 146 302 21,453 181,030 2013 2015 715 731 1,206 1,234 476 488 3,164 3,237 297 303 109 112 44 45 43 44 3,754 3,841 46,788 47,890 122 125 104,975 107,511 957 979 186 191 94 97 149 153 309 316 21,946 22,450 185,335 189,744 2014 Sectoralsupplyofinvestmentgoods:PPP2($million) 579 597 978 1,008 386 398 2,563 2,641 240 248 89 91 35 37 35 36 3,042 3,136 37,898 39,063 99 102 85,006 87,626 775 799 151 156 76 79 121 125 250 258 17,780 18,326 150,104 154,722 2006 TableF3 ThisTableshowstheresultsobtainedbytheapplicationofEquation534,p.124. Present value Coalsector Petroleumsector Gassector RenewableElectricity CoalfiredElectricity InternalcombustionElectricity GasturbineElectricity CombinedcycleElectricity 6,417 Agriculture,forestryandfishing 10,836 Mining Food,beveragesandtobacco Textile,clothing,footwearandleather 4,280 28,420 Wood,paperandprintingproducts 2,665 Basicchemicals 982 Nonmetallicmineralproducts 393 Basicironandsteel 387 Basicnonferrousmetals 33,730 Fabricatedmetalproducts 420,452 Machineryandequipment 1,094 Miscellenousmanufacturing Water,sewerageanddrainage 943,680 Construction 8,597 Roadtransport 1,674 Railwaytransport 848 Watertransport 1,342 Airtransport Othertransport,servicesandstorage 2,772 197,151 Commercialservices Total 1,665,722 2017 747 764 1,261 1,290 499 511 3,311 3,387 310 317 114 117 46 47 45 46 3,929 4,019 49,017 50,172 127 130 110,109 112,769 1,002 1,025 195 200 99 101 156 160 323 330 22,967 23,495 194,258 198,881 2016 782 1,319 523 3,465 325 120 48 47 4,112 51,354 133 115,494 1,049 204 104 164 337 24,036 203,615 2018 2020 800 818 1,349 1,380 535 547 3,545 3,626 332 339 122 125 49 50 48 49 4,207 4,304 52,564 53,803 136 139 118,284 121,142 1,074 1,099 209 214 106 108 168 172 345 353 24,589 25,155 208,461 213,424 2019 309 Note: 562 949 374 2,487 233 86 34 34 2,952 36,769 96 82,466 752 146 74 117 243 17,252 145,626 2005 2007 614 1,038 410 2,721 255 94 38 37 3,230 40,237 105 90,268 823 160 81 128 266 18,876 159,380 2008 2010 633 653 1,070 1,102 422 435 2,804 2,889 263 271 97 100 39 40 38 39 3,328 3,429 41,467 42,715 108 111 93,035 95,812 848 874 165 170 84 86 132 136 274 282 19,452 20,041 164,259 169,184 2009 2012 667 682 1,127 1,152 445 455 2,954 3,021 277 283 102 104 41 42 40 41 3,505 3,582 43,654 44,616 114 116 97,885 100,005 893 913 174 178 88 90 139 142 288 295 20,488 20,945 172,880 176,661 2011 698 1,178 465 3,088 290 107 43 42 3,662 45,599 119 102,173 933 181 92 145 301 21,413 180,529 2013 2015 713 730 1,204 1,231 476 487 3,159 3,231 296 303 109 112 44 45 43 44 3,746 3,832 46,667 47,762 122 124 104,630 107,147 955 977 186 190 94 96 149 152 308 315 21,903 22,405 184,803 189,181 2014 Sectoralsupplyofinvestmentgoods:SRP2($million) 579 596 978 1,007 386 397 2,562 2,640 240 248 89 91 35 37 35 36 3,041 3,134 37,889 39,045 99 102 84,986 87,585 775 799 151 155 76 79 121 125 250 258 17,776 18,318 150,068 154,651 2006 TableF3 ThisTableshowstheresultsobtainedbytheapplicationofEquation534,p.124. Present value Coalsector Petroleumsector Gassector RenewableElectricity CoalfiredElectricity InternalcombustionElectricity GasturbineElectricity CombinedcycleElectricity 6,411 Agriculture,forestryandfishing 10,824 Mining Food,beveragesandtobacco Textile,clothing,footwearandleather 4,275 28,391 Wood,paperandprintingproducts 2,662 Basicchemicals 981 Nonmetallicmineralproducts 393 Basicironandsteel 386 Basicnonferrousmetals 33,686 Fabricatedmetalproducts 419,815 Machineryandequipment 1,093 Miscellenousmanufacturing Water,sewerageanddrainage 941,904 Construction 8,585 Roadtransport 1,671 Railwaytransport 846 Watertransport 1,340 Airtransport Othertransport,servicesandstorage 2,769 196,916 Commercialservices Total 1,662,949 2017 746 763 1,259 1,287 498 510 3,305 3,381 310 317 114 117 46 47 45 46 3,920 4,010 48,883 50,031 127 130 109,726 112,368 999 1,023 194 199 98 101 156 160 322 329 22,918 23,444 193,667 198,262 2016 780 1,316 521 3,459 324 119 48 47 4,102 51,207 133 115,076 1,046 204 103 163 337 23,983 202,969 2018 2020 798 816 1,346 1,377 534 546 3,538 3,619 331 339 122 125 49 50 48 49 4,197 4,293 52,411 53,644 136 139 117,850 120,691 1,071 1,096 208 213 106 108 167 171 344 352 24,534 25,099 207,790 212,728 2019 310 Note: 2007 579 596 978 1,008 386 398 2,563 2,641 240 248 89 91 35 37 35 36 3,042 3,135 37,896 39,059 99 102 85,002 87,618 775 799 151 156 76 79 121 125 250 258 17,780 18,324 150,097 154,708 2006 615 1,038 410 2,722 255 94 38 37 3,231 40,258 105 90,315 823 160 81 128 266 18,886 159,464 2008 2010 634 653 1,070 1,103 422 435 2,806 2,892 263 271 97 100 39 40 38 39 3,330 3,432 41,495 42,771 108 111 93,098 95,967 849 875 165 170 84 86 132 136 274 282 19,465 20,062 164,369 169,427 2009 2012 668 683 1,128 1,153 445 455 2,957 3,024 277 284 102 104 41 42 40 41 3,509 3,587 43,717 44,684 114 116 98,056 100,192 894 914 174 178 88 90 139 143 289 295 20,511 20,971 173,150 176,956 2011 698 1,179 466 3,093 290 107 43 42 3,670 45,734 119 102,609 935 182 92 146 302 21,452 181,159 2013 2015 714 730 1,206 1,233 477 488 3,164 3,237 297 303 109 112 44 45 43 44 3,754 3,840 46,809 47,910 122 125 105,085 107,621 957 979 186 191 94 97 149 153 308 315 21,944 22,448 185,463 189,871 2014 2017 747 764 1,261 1,289 499 511 3,311 3,387 310 317 114 117 46 47 45 46 3,929 4,019 49,037 50,192 127 130 110,219 112,879 1,002 1,025 195 200 99 101 157 160 323 330 22,964 23,492 194,385 199,007 2016 Sectoralsupplyofinvestmentgoods:PPPforEarlyaction($million) ThisTableshowstheresultsobtainedbytheapplicationofEquation534,p.124. 562 949 374 2,487 233 86 34 34 2,952 36,769 96 82,466 752 146 74 117 243 17,252 145,626 2005 TableF3 Present value Coalsector Petroleumsector Gassector RenewableElectricity CoalfiredElectricity InternalcombustionElectricity GasturbineElectricity CombinedcycleElectricity 6,415 Agriculture,forestryandfishing 10,833 Mining Food,beveragesandtobacco Textile,clothing,footwearandleather 4,280 28,417 Wood,paperandprintingproducts 2,665 Basicchemicals 982 Nonmetallicmineralproducts 393 Basicironandsteel 387 Basicnonferrousmetals 33,725 Fabricatedmetalproducts 420,457 Machineryandequipment 1,094 Miscellenousmanufacturing Water,sewerageanddrainage 943,852 Construction 8,597 Roadtransport 1,674 Railwaytransport 848 Watertransport 1,342 Airtransport Othertransport,servicesandstorage 2,771 197,123 Commercialservices Total 1,665,854 781 1,318 523 3,465 324 120 48 47 4,112 51,373 133 115,605 1,049 204 104 164 337 24,032 203,740 2018 2020 799 817 1,348 1,379 535 547 3,544 3,626 332 339 122 125 49 50 48 49 4,206 4,303 52,583 53,822 136 139 118,396 121,254 1,074 1,099 209 214 106 109 168 172 345 353 24,586 25,152 208,587 213,550 2019 311 Note: 2007 579 596 978 1,008 386 398 2,563 2,641 240 248 89 91 35 37 35 36 3,042 3,135 37,893 39,053 99 102 84,995 87,604 775 799 151 156 76 79 121 125 250 258 17,778 18,321 150,085 154,683 2006 615 1,038 410 2,722 255 94 38 37 3,231 40,249 105 90,294 823 160 81 128 266 18,881 159,427 2008 2010 633 653 1,070 1,103 422 435 2,805 2,891 263 271 97 100 39 40 38 39 3,329 3,431 41,483 42,755 108 111 93,070 95,932 848 874 165 170 84 86 132 136 274 282 19,459 20,054 164,319 169,365 2009 2012 668 683 1,127 1,153 445 455 2,956 3,022 277 283 102 104 41 42 40 41 3,507 3,586 43,698 44,663 114 116 98,014 100,142 894 914 174 178 88 90 139 142 288 295 20,503 20,961 173,075 176,870 2011 698 1,178 465 3,091 290 107 43 42 3,665 45,650 119 102,319 934 182 92 146 301 21,430 180,752 2013 2015 714 730 1,205 1,232 476 486 3,160 3,232 296 303 109 112 44 45 43 44 3,747 3,831 46,659 47,692 122 124 104,546 106,822 955 976 186 190 94 96 149 152 308 315 21,911 22,402 184,723 188,783 2014 2017 747 764 1,260 1,288 498 509 3,306 3,381 310 317 114 117 46 47 45 46 3,919 4,009 48,812 49,959 127 130 109,397 112,035 999 1,022 194 199 98 101 156 159 322 330 22,916 23,442 193,265 197,854 2016 Sectoralsupplyofinvestmentgoods:SRPforearlyaction($million) ThisTableshowstheresultsobtainedbytheapplicationofEquation534,p.124. 562 949 374 2,487 233 86 34 34 2,952 36,769 96 82,466 752 146 74 117 243 17,252 145,626 2005 TableF3 Present value Coalsector Petroleumsector Gassector RenewableElectricity CoalfiredElectricity InternalcombustionElectricity GasturbineElectricity CombinedcycleElectricity 6,413 Agriculture,forestryandfishing 10,829 Mining Food,beveragesandtobacco Textile,clothing,footwearandleather 4,275 28,399 Wood,paperandprintingproducts 2,663 Basicchemicals 981 Nonmetallicmineralproducts 393 Basicironandsteel 387 Basicnonferrousmetals 33,694 Fabricatedmetalproducts 419,788 Machineryandequipment 1,094 Miscellenousmanufacturing Water,sewerageanddrainage 941,510 Construction 8,586 Roadtransport 1,671 Railwaytransport 846 Watertransport 1,339 Airtransport Othertransport,servicesandstorage 2,770 196,963 Commercialservices Total 1,662,601 781 1,317 521 3,459 324 119 48 47 4,101 51,134 133 114,737 1,046 203 103 163 337 23,981 202,555 2018 2020 799 817 1,347 1,378 533 546 3,538 3,620 331 339 122 125 49 50 48 49 4,196 4,292 52,338 53,570 136 139 117,505 120,341 1,070 1,095 208 213 105 108 167 171 345 352 24,532 25,097 207,370 212,301 2019 312 Note: 2005 2007 579 597 978 1,008 386 398 2,563 2,642 241 248 89 91 35 37 35 36 3,043 3,137 37,905 39,077 99 102 85,023 87,659 775 799 151 156 76 79 121 125 250 258 17,784 18,332 150,133 154,780 2006 615 1,039 410 2,724 256 94 38 37 3,233 40,286 105 90,377 824 160 81 129 266 18,898 159,572 2008 2010 634 654 1,071 1,104 423 436 2,808 2,895 263 272 97 100 39 40 38 39 3,333 3,436 41,532 42,817 108 112 93,180 96,070 849 876 165 170 84 86 133 137 274 282 19,481 20,082 164,513 169,608 2009 2012 668 683 1,129 1,154 446 456 2,960 3,026 278 284 102 105 41 42 40 41 3,513 3,592 43,776 44,759 114 117 98,223 100,430 895 915 174 178 88 90 140 143 289 295 20,532 20,994 173,408 177,304 2011 699 1,180 466 3,094 290 107 43 42 3,673 45,766 119 102,690 936 182 92 146 302 21,467 181,294 2013 2015 715 731 1,207 1,234 476 487 3,164 3,236 297 303 109 112 44 45 43 44 3,754 3,840 46,770 47,862 122 125 104,907 107,422 957 979 186 191 94 96 149 153 309 316 21,944 22,444 185,247 189,618 2014 2017 747 764 1,261 1,289 499 510 3,310 3,385 310 317 114 117 46 47 45 46 3,927 4,017 48,981 50,127 127 130 110,000 112,642 1,001 1,025 195 200 99 101 156 160 323 330 22,956 23,481 194,098 198,688 2016 Sectoralsupplyofinvestmentgoods:PPPforDelayaction($million) ThisTableshowstheresultsobtainedbytheapplicationofEquation534,p.124. 562 949 374 2,487 233 86 34 34 2,952 36,769 96 82,466 752 146 74 117 243 17,252 145,626 TableF3 Present value Coalsector Petroleumsector Gassector RenewableElectricity CoalfiredElectricity InternalcombustionElectricity GasturbineElectricity CombinedcycleElectricity 6,417 Agriculture,forestryandfishing 10,838 Mining Food,beveragesandtobacco Textile,clothing,footwearandleather 4,280 28,422 Wood,paperandprintingproducts 2,666 Basicchemicals 982 Nonmetallicmineralproducts 393 Basicironandsteel 387 Basicnonferrousmetals 33,735 Fabricatedmetalproducts 420,484 Machineryandequipment 1,095 Miscellenousmanufacturing Water,sewerageanddrainage 943,736 Construction 8,598 Roadtransport 1,674 Railwaytransport 848 Watertransport 1,342 Airtransport Othertransport,servicesandstorage 2,773 197,173 Commercialservices Total 1,665,845 781 1,318 522 3,462 324 120 48 47 4,109 51,301 133 115,349 1,048 204 103 164 337 24,018 203,391 2018 2020 799 817 1,348 1,379 534 547 3,542 3,623 332 339 122 125 49 50 48 49 4,204 4,300 52,504 53,736 136 139 118,124 120,967 1,073 1,097 209 214 106 108 168 172 345 353 24,568 25,132 208,210 213,146 2019 313 Note: 2005 2007 579 597 978 1,008 386 398 2,563 2,642 241 248 89 91 35 37 35 36 3,043 3,137 37,905 39,077 99 102 85,023 87,659 775 799 151 156 76 79 121 125 250 258 17,784 18,332 150,133 154,780 2006 615 1,039 410 2,724 256 94 38 37 3,233 40,286 105 90,377 824 160 81 129 266 18,898 159,572 2008 2010 634 654 1,071 1,104 423 436 2,808 2,895 263 272 97 100 39 40 38 39 3,333 3,436 41,532 42,817 108 112 93,180 96,070 849 876 165 170 84 86 133 137 274 282 19,481 20,082 164,513 169,608 2009 2012 668 683 1,129 1,154 446 456 2,959 3,026 278 284 102 105 41 42 40 41 3,513 3,591 43,773 44,753 114 117 98,216 100,415 895 915 174 178 88 90 140 143 289 295 20,531 20,991 173,396 177,279 2011 699 1,180 466 3,094 290 107 43 42 3,672 45,756 119 102,667 936 182 92 146 302 21,462 181,255 2013 2015 714 730 1,206 1,233 476 487 3,163 3,234 297 303 109 112 44 45 43 44 3,753 3,836 46,757 47,782 122 125 104,877 107,138 956 977 186 190 94 96 149 152 309 315 21,938 22,426 185,195 189,227 2014 2017 747 764 1,261 1,289 498 509 3,306 3,382 310 317 114 117 46 47 45 46 3,921 4,010 48,831 49,972 127 130 109,451 112,075 999 1,022 194 199 98 101 156 159 322 330 22,925 23,448 193,352 197,915 2016 Sectoralsupplyofinvestmentgoods:SRPforDelayaction($million) ThisTableshowstheresultsobtainedbytheapplicationofEquation534,p.124. 562 949 374 2,487 233 86 34 34 2,952 36,769 96 82,466 752 146 74 117 243 17,252 145,626 TableF3 Present value Coalsector Petroleumsector Gassector RenewableElectricity CoalfiredElectricity InternalcombustionElectricity GasturbineElectricity CombinedcycleElectricity 6,416 Agriculture,forestryandfishing 10,837 Mining Food,beveragesandtobacco Textile,clothing,footwearandleather 4,278 28,414 Wood,paperandprintingproducts 2,665 Basicchemicals 982 Nonmetallicmineralproducts 393 Basicironandsteel 387 Basicnonferrousmetals 33,720 Fabricatedmetalproducts 420,160 Machineryandequipment 1,094 Miscellenousmanufacturing Water,sewerageanddrainage 942,581 Construction 8,593 Roadtransport 1,673 Railwaytransport 847 Watertransport 1,341 Airtransport Othertransport,servicesandstorage 2,772 197,098 Commercialservices Total 1,664,252 781 1,318 521 3,459 324 119 48 47 4,102 51,140 133 114,764 1,046 203 103 163 337 23,983 202,592 2018 2020 799 817 1,347 1,378 533 545 3,538 3,619 331 339 122 125 49 50 48 49 4,196 4,292 52,338 53,565 136 139 117,521 120,346 1,070 1,095 208 213 105 108 167 171 345 352 24,532 25,094 207,385 212,297 2019 314 Note: 6,386 248 826 1,463 7,204 25 185 211 7,622 4,901 2,200 305 1,641 1,611 731 568 1,276 762 2,523 147 1,529 3,538 1,780 3,300 346 3,423 9,174 86,208 150,133 6,200 241 801 1,369 7,018 24 180 205 7,398 4,754 2,135 296 1,593 1,564 710 552 1,238 739 2,447 143 1,483 3,432 1,726 3,202 335 3,320 8,900 83,622 145,626 6,578 255 851 1,561 7,395 26 191 218 7,854 5,052 2,267 314 1,691 1,660 753 586 1,316 785 2,601 152 1,576 3,648 1,834 3,401 356 3,529 9,457 88,875 154,780 2007 2009 6,775 6,979 263 270 876 903 1,663 1,771 7,591 7,793 26 27 196 202 224 231 8,092 8,338 5,209 5,370 2,336 2,408 324 333 1,742 1,795 1,711 1,763 776 799 603 622 1,356 1,398 809 834 2,681 2,764 156 161 1,625 1,675 3,761 3,877 1,891 1,949 3,505 3,613 367 379 3,638 3,751 9,749 10,050 91,624 94,458 159,572 164,513 2008 2011 7,189 7,353 279 285 930 951 1,883 1,926 7,999 8,182 28 29 209 213 238 243 8,592 8,786 5,536 5,663 2,481 2,537 344 351 1,850 1,892 1,816 1,857 823 841 640 655 1,442 1,475 860 879 2,850 2,915 166 170 1,727 1,766 3,998 4,089 2,009 2,055 3,723 3,809 390 399 3,867 3,956 10,360 10,597 97,380 99,614 169,608 173,489 2010 7,520 291 973 1,970 8,370 29 218 249 8,984 5,793 2,595 359 1,934 1,899 860 669 1,509 899 2,982 174 1,807 4,183 2,102 3,896 408 4,047 10,840 101,900 177,461 2012 7,691 298 995 2,015 8,561 30 223 255 9,187 5,925 2,654 367 1,978 1,942 879 685 1,543 920 3,050 178 1,848 4,279 2,150 3,985 418 4,139 11,088 104,239 181,523 2013 7,866 304 1,018 2,062 8,757 31 228 260 9,395 6,061 2,714 376 2,023 1,986 898 700 1,579 941 3,120 183 1,891 4,376 2,199 4,076 427 4,235 11,342 106,631 185,679 2014 8,046 311 1,041 2,109 8,958 31 234 266 9,607 6,201 2,776 384 2,069 2,031 918 716 1,615 962 3,191 187 1,934 4,477 2,249 4,169 437 4,332 11,602 109,079 189,931 2015 Sectoraldemandforinvestment:BCscenario($million) ThisTableshowstheresultsobtainedbytheapplicationofEquation533,p.124. 2006 2005 TableF4 Present value 70,708 Coalsector 2,738 Petroleumsector 9,148 Gassector 17,565 RenewableElectricity 79,151 CoalfiredElectricity 275 InternalcombustionElectricity 2,051 GasturbineElectricity 2,340 CombinedcycleElectricity 84,426 Agriculture,forestryandfishing 54,394 Mining 24,381 Food,beveragesandtobacco Textile,clothing,footwearandleather 3,376 18,177 Wood,paperandprintingproducts 17,849 Basicchemicals 8,085 Nonmetallicmineralproducts 6,292 Basicironandsteel 14,164 Basicnonferrousmetals 8,448 Fabricatedmetalproducts 27,999 Machineryandequipment 1,636 Miscellenousmanufacturing 16,967 Water,sewerageanddrainage 39,272 Construction 19,740 Roadtransport 36,596 Railwaytransport 3,836 Watertransport 37,997 Airtransport Othertransport,servicesandstorage 101,799 956,851 Commercialservices Total 1,666,260 8,229 318 1,065 2,157 9,163 32 239 273 9,824 6,343 2,839 393 2,115 2,077 939 732 1,652 984 3,265 191 1,978 4,579 2,301 4,264 447 4,431 11,868 111,582 194,280 2016 2018 8,417 8,608 325 332 1,089 1,114 2,207 2,257 9,373 9,587 33 34 244 250 279 285 10,046 10,274 6,489 6,637 2,903 2,969 402 411 2,163 2,212 2,124 2,172 960 981 748 765 1,690 1,729 1,006 1,029 3,339 3,416 196 200 2,024 2,070 4,684 4,791 2,353 2,407 4,362 4,461 457 468 4,533 4,637 12,140 12,418 114,144 116,764 198,729 203,281 2017 2020 8,805 9,006 340 347 1,140 1,166 2,309 2,362 9,807 10,032 34 35 256 262 292 298 10,506 10,744 6,790 6,946 3,036 3,105 420 430 2,262 2,313 2,222 2,272 1,003 1,025 782 800 1,768 1,809 1,053 1,077 3,494 3,574 205 209 2,118 2,166 4,901 5,013 2,462 2,518 4,563 4,668 479 490 4,744 4,853 12,703 12,994 119,444 122,186 207,938 212,701 2019 315 Note: 6,200 241 801 1,369 7,018 24 180 205 7,398 4,754 2,135 296 1,593 1,564 710 552 1,238 739 2,447 143 1,483 3,432 1,726 3,202 335 3,320 8,900 83,622 145,626 2005 2007 6,761 263 872 1,663 7,589 26 196 224 8,092 5,208 2,336 324 1,742 1,710 775 603 1,356 809 2,681 156 1,624 3,760 1,890 3,503 367 3,638 9,745 91,612 159,527 2008 2010 6,960 7,165 270 278 897 923 1,770 1,882 7,790 7,996 27 28 202 208 231 238 8,338 8,591 5,369 5,534 2,408 2,481 333 344 1,795 1,849 1,762 1,816 799 822 621 640 1,398 1,441 834 859 2,763 2,848 161 166 1,674 1,726 3,876 3,996 1,949 2,008 3,610 3,720 379 390 3,750 3,866 10,045 10,354 94,442 97,360 164,453 169,531 2009 2012 7,323 7,485 285 291 942 963 1,925 1,969 8,178 8,365 29 29 213 218 243 249 8,785 8,983 5,661 5,791 2,537 2,595 351 359 1,891 1,934 1,857 1,899 840 859 654 669 1,474 1,508 879 899 2,913 2,980 170 174 1,765 1,805 4,087 4,180 2,054 2,101 3,804 3,890 399 408 3,955 4,046 10,590 10,832 99,590 101,872 173,397 177,352 2011 7,651 297 983 2,014 8,555 30 223 254 9,186 5,923 2,654 367 1,977 1,941 878 684 1,543 919 3,048 178 1,847 4,276 2,149 3,978 418 4,138 11,079 104,206 181,397 2013 2015 7,820 7,993 304 311 1,004 1,026 2,060 2,107 8,751 8,950 31 31 228 233 260 266 9,394 9,606 6,059 6,198 2,714 2,775 376 384 2,022 2,068 1,985 2,030 897 917 699 715 1,578 1,615 940 961 3,118 3,189 182 187 1,889 1,932 4,373 4,473 2,198 2,248 4,068 4,160 427 437 4,233 4,330 11,332 11,590 106,594 109,037 185,536 189,770 2014 Sectoraldemandforinvestment:PPP1 ($million) 6,381 6,568 248 255 824 848 1,463 1,561 7,203 7,394 25 26 185 191 211 217 7,622 7,854 4,901 5,052 2,200 2,267 305 314 1,641 1,691 1,611 1,660 731 753 568 585 1,276 1,315 762 785 2,523 2,600 147 152 1,529 1,576 3,538 3,647 1,779 1,834 3,299 3,400 346 356 3,423 3,529 9,173 9,455 86,204 88,867 150,119 154,751 2006 TableF4 ThisTableshowstheresultsobtainedbytheapplicationofEquation533,p.124. Present value 70,326 Coalsector 2,735 Petroleumsector 9,278 Gassector 17,507 RenewableElectricity 77,968 CoalfiredElectricity 275 InternalcombustionElectricity 2,044 GasturbineElectricity 2,976 CombinedcycleElectricity 84,420 Agriculture,forestryandfishing 54,374 Mining 24,380 Food,beveragesandtobacco Textile,clothing,footwearandleather 3,376 18,172 Wood,paperandprintingproducts 17,841 Basicchemicals 8,076 Nonmetallicmineralproducts 6,288 Basicironandsteel 14,162 Basicnonferrousmetals 8,441 Fabricatedmetalproducts 27,981 Machineryandequipment 1,635 Miscellenousmanufacturing 16,958 Water,sewerageanddrainage 39,239 Construction 19,734 Roadtransport 36,547 Railwaytransport 3,835 Watertransport 37,990 Airtransport Othertransport,servicesandstorage 101,769 956,638 Commercialservices Total 1,664,965 2017 8,170 8,317 318 324 1,047 1,135 2,155 2,189 9,155 9,013 32 33 239 242 272 474 9,823 10,045 6,340 6,483 2,838 2,903 393 402 2,114 2,162 2,076 2,123 938 957 731 747 1,652 1,689 983 1,005 3,262 3,335 191 195 1,976 2,022 4,575 4,675 2,299 2,352 4,255 4,350 447 457 4,430 4,531 11,855 12,135 111,536 114,094 194,101 198,391 2016 8,467 332 1,225 2,224 8,864 33 246 682 10,272 6,630 2,969 411 2,210 2,170 978 764 1,728 1,027 3,410 200 2,068 4,778 2,405 4,447 468 4,636 12,422 116,711 202,778 2018 2020 8,621 8,778 339 346 1,318 1,413 2,260 2,296 8,709 8,547 34 34 250 254 897 1,118 10,505 10,743 6,780 6,934 3,036 3,105 420 430 2,260 2,311 2,219 2,269 999 1,020 781 798 1,767 1,808 1,050 1,074 3,487 3,565 205 209 2,116 2,165 4,883 4,991 2,460 2,515 4,546 4,647 478 489 4,742 4,851 12,716 13,016 119,387 122,126 207,265 211,853 2019 316 Note: 6,200 241 801 1,369 7,018 24 180 205 7,398 4,754 2,135 296 1,593 1,564 710 552 1,238 739 2,447 143 1,483 3,432 1,726 3,202 335 3,320 8,900 83,622 145,626 2005 2007 6,742 262 868 1,662 7,586 26 196 224 8,092 5,207 2,336 324 1,742 1,710 775 603 1,356 809 2,680 156 1,623 3,758 1,890 3,500 367 3,637 9,742 91,598 159,473 2008 2010 6,935 7,133 270 278 892 916 1,769 1,881 7,786 7,991 27 28 202 208 231 238 8,337 8,591 5,367 5,532 2,408 2,481 333 343 1,794 1,849 1,762 1,815 798 822 621 640 1,398 1,441 833 859 2,762 2,847 161 166 1,673 1,724 3,874 3,994 1,948 2,008 3,605 3,714 379 390 3,750 3,865 10,040 10,348 94,424 97,337 164,380 169,440 2009 2012 7,284 7,439 284 291 935 953 1,924 1,968 8,172 8,358 29 29 213 218 243 249 8,784 8,983 5,659 5,788 2,537 2,595 351 359 1,890 1,933 1,856 1,897 840 858 654 669 1,474 1,508 878 898 2,911 2,978 170 174 1,763 1,803 4,084 4,177 2,053 2,100 3,797 3,882 399 408 3,954 4,044 10,583 10,823 99,563 101,841 173,287 177,223 2011 7,568 297 1,032 1,998 8,226 30 221 433 9,185 5,919 2,653 367 1,976 1,940 876 683 1,542 918 3,044 178 1,845 4,268 2,148 3,968 418 4,137 11,078 104,172 181,121 2013 2015 7,700 7,835 303 310 1,113 1,197 2,029 2,061 8,088 7,944 30 31 225 228 623 818 9,392 9,605 6,053 6,189 2,714 2,775 376 384 2,021 2,066 1,984 2,028 895 913 698 714 1,578 1,614 938 959 3,112 3,182 182 187 1,887 1,931 4,362 4,457 2,196 2,246 4,055 4,145 427 437 4,232 4,329 11,338 11,605 106,557 108,997 185,108 189,185 2014 Sectoraldemandforinvestment:SRP1($million) 6,375 6,556 248 255 823 845 1,462 1,560 7,202 7,392 25 26 185 191 211 217 7,622 7,853 4,900 5,051 2,200 2,267 305 314 1,641 1,690 1,611 1,660 731 753 568 585 1,276 1,315 762 785 2,522 2,600 147 152 1,528 1,575 3,537 3,646 1,779 1,834 3,298 3,397 346 356 3,423 3,528 9,172 9,452 86,200 88,858 150,100 154,715 2006 TableF4 ThisTableshowstheresultsobtainedbytheapplicationofEquation533,p.124. Present value 69,697 Coalsector 2,732 Petroleumsector 9,785 Gassector 17,518 RenewableElectricity 74,673 CoalfiredElectricity 272 InternalcombustionElectricity 2,027 GasturbineElectricity 4,710 CombinedcycleElectricity 84,414 Agriculture,forestryandfishing 54,341 Mining 24,379 Food,beveragesandtobacco Textile,clothing,footwearandleather 3,375 18,164 Wood,paperandprintingproducts 17,832 Basicchemicals 8,062 Nonmetallicmineralproducts 6,282 Basicironandsteel 14,158 Basicnonferrousmetals 8,432 Fabricatedmetalproducts 27,954 Machineryandequipment 1,635 Miscellenousmanufacturing 16,949 Water,sewerageanddrainage 39,182 Construction 19,724 Roadtransport 36,475 Railwaytransport 3,834 Watertransport 37,982 Airtransport Othertransport,servicesandstorage 101,785 956,421 Commercialservices Total 1,662,798 2017 7,974 8,116 317 324 1,282 1,370 2,093 2,126 7,793 7,636 31 32 232 235 1,020 1,227 9,822 10,044 6,329 6,473 2,838 2,902 393 402 2,112 2,160 2,074 2,120 933 953 729 745 1,650 1,688 980 1,002 3,253 3,326 191 195 1,975 2,021 4,555 4,655 2,297 2,349 4,237 4,331 447 457 4,428 4,530 11,877 12,156 111,493 114,046 193,355 197,620 2016 8,263 331 1,460 2,159 7,472 32 239 1,441 10,271 6,619 2,968 411 2,208 2,168 973 762 1,727 1,024 3,401 200 2,067 4,757 2,402 4,427 467 4,634 12,441 116,659 201,982 2018 2020 8,412 8,563 338 345 1,553 1,581 2,193 2,804 7,300 7,146 33 33 243 247 1,662 1,693 10,503 10,741 6,769 6,924 3,036 3,105 420 430 2,258 2,309 2,217 2,267 994 1,017 778 796 1,766 1,807 1,047 1,071 3,477 3,558 205 209 2,115 2,162 4,861 4,978 2,457 2,513 4,525 4,623 478 489 4,740 4,849 12,732 13,021 119,331 122,074 206,442 211,356 2019 317 Note: 6,200 241 801 1,369 7,018 24 180 205 7,398 4,754 2,135 296 1,593 1,564 710 552 1,238 739 2,447 143 1,483 3,432 1,726 3,202 335 3,320 8,900 83,622 145,626 2005 2007 6,748 262 868 1,663 7,587 26 196 224 8,092 5,207 2,336 324 1,742 1,710 775 603 1,356 809 2,680 156 1,624 3,759 1,890 3,501 367 3,637 9,742 91,601 159,485 2008 2010 6,942 7,141 270 278 892 916 1,770 1,882 7,787 7,992 27 28 202 208 231 238 8,337 8,591 5,368 5,533 2,408 2,481 333 344 1,795 1,849 1,762 1,815 798 822 621 640 1,398 1,441 834 859 2,762 2,847 161 166 1,673 1,725 3,875 3,994 1,948 2,008 3,607 3,716 379 390 3,750 3,866 10,041 10,349 94,427 97,342 164,396 169,461 2009 2012 7,295 7,421 284 291 934 1,011 1,924 1,955 8,174 8,047 29 29 213 216 243 423 8,785 8,983 5,659 5,787 2,537 2,595 351 359 1,891 1,933 1,856 1,898 840 858 654 668 1,474 1,508 878 898 2,912 2,977 170 174 1,764 1,805 4,085 4,174 2,054 2,100 3,799 3,883 399 408 3,954 4,045 10,584 10,834 99,569 101,849 173,313 177,128 2011 7,551 297 1,089 1,985 7,913 30 220 609 9,185 5,918 2,653 367 1,976 1,940 876 683 1,542 918 3,044 178 1,846 4,266 2,148 3,969 418 4,138 11,089 104,181 181,030 2013 2015 7,681 7,814 303 310 1,108 1,128 2,540 3,114 7,798 7,676 30 31 224 228 621 633 9,393 9,605 6,053 6,191 2,714 2,775 376 384 2,021 2,067 1,984 2,029 896 917 699 715 1,578 1,614 939 961 3,114 3,187 182 187 1,888 1,931 4,368 4,473 2,197 2,247 4,054 4,142 427 437 4,232 4,329 11,341 11,598 106,574 109,022 185,335 189,744 2014 Sectoraldemandforinvestment:PPP2($million) 6,377 6,559 248 255 823 845 1,463 1,560 7,203 7,392 25 26 185 191 211 217 7,622 7,853 4,900 5,051 2,200 2,267 305 314 1,641 1,691 1,611 1,660 731 753 568 585 1,276 1,315 762 785 2,522 2,600 147 152 1,529 1,575 3,537 3,646 1,779 1,834 3,299 3,398 346 356 3,423 3,529 9,172 9,453 86,200 88,859 150,104 154,722 2006 TableF4 ThisTableshowstheresultsobtainedbytheapplicationofEquation533,p.124. Present value 69,635 Coalsector 2,732 Petroleumsector 9,385 Gassector 22,710 RenewableElectricity 73,738 CoalfiredElectricity 273 InternalcombustionElectricity 2,029 GasturbineElectricity 3,591 CombinedcycleElectricity 84,418 Agriculture,forestryandfishing 54,351 Mining 24,379 Food,beveragesandtobacco Textile,clothing,footwearandleather 3,376 18,171 Wood,paperandprintingproducts 17,837 Basicchemicals 8,078 Nonmetallicmineralproducts 6,287 Basicironandsteel 14,162 Basicnonferrousmetals 8,441 Fabricatedmetalproducts 27,978 Machineryandequipment 1,635 Miscellenousmanufacturing 16,948 Water,sewerageanddrainage 39,265 Construction 19,730 Roadtransport 36,462 Railwaytransport 3,834 Watertransport 37,984 Airtransport Othertransport,servicesandstorage 101,745 956,549 Commercialservices Total 1,665,722 2017 7,950 8,090 317 324 1,148 1,169 3,710 4,327 7,547 7,411 31 32 233 237 645 657 9,823 10,045 6,332 6,477 2,838 2,903 393 402 2,114 2,162 2,075 2,122 938 959 731 748 1,651 1,690 983 1,005 3,261 3,336 191 195 1,974 2,019 4,581 4,691 2,298 2,351 4,231 4,322 447 457 4,429 4,530 11,861 12,131 111,527 114,090 194,258 198,881 2016 8,232 331 1,190 4,967 7,266 32 242 669 10,272 6,625 2,969 411 2,211 2,170 981 765 1,728 1,029 3,414 200 2,065 4,803 2,405 4,416 467 4,634 12,407 116,713 203,615 2018 2020 8,378 8,528 338 345 1,212 1,235 5,630 6,316 7,113 6,953 33 34 246 251 682 695 10,505 10,743 6,776 6,931 3,036 3,105 420 430 2,262 2,313 2,219 2,270 1,004 1,027 782 800 1,768 1,809 1,053 1,077 3,493 3,574 205 209 2,111 2,159 4,919 5,037 2,460 2,516 4,512 4,610 478 489 4,740 4,849 12,689 12,978 119,396 122,141 208,461 213,424 2019 318 Note: 6,200 241 801 1,369 7,018 24 180 205 7,398 4,754 2,135 296 1,593 1,564 710 552 1,238 739 2,447 143 1,483 3,432 1,726 3,202 335 3,320 8,900 83,622 145,626 2005 2007 6,711 262 860 1,661 7,582 26 196 224 8,091 5,205 2,336 323 1,741 1,709 774 603 1,356 808 2,678 156 1,622 3,756 1,889 3,495 367 3,636 9,735 91,575 159,380 2008 2010 6,893 7,056 270 278 882 953 1,768 1,868 7,780 7,719 27 28 202 207 231 384 8,337 8,590 5,365 5,528 2,407 2,481 333 343 1,794 1,848 1,761 1,814 797 820 621 639 1,398 1,441 833 858 2,760 2,843 161 166 1,671 1,723 3,871 3,987 1,947 2,007 3,598 3,704 378 390 3,748 3,864 10,032 10,345 94,394 97,302 164,259 169,184 2009 2012 7,170 7,289 284 290 1,026 1,101 1,896 1,925 7,588 7,451 28 29 210 213 561 743 8,783 8,981 5,653 5,780 2,537 2,594 351 359 1,889 1,931 1,854 1,896 837 854 653 667 1,474 1,507 876 896 2,907 2,971 170 174 1,762 1,802 4,074 4,162 2,052 2,098 3,785 3,867 399 408 3,952 4,043 10,586 10,833 99,523 101,796 172,880 176,661 2011 7,411 296 1,178 1,954 7,308 29 216 931 9,184 5,911 2,653 367 1,974 1,938 872 682 1,541 915 3,037 178 1,843 4,253 2,145 3,951 417 4,135 11,085 104,121 180,529 2013 2015 7,534 7,662 303 309 1,197 1,218 2,499 3,064 7,184 7,053 30 30 220 225 948 966 9,391 9,603 6,045 6,183 2,713 2,775 376 384 2,019 2,065 1,982 2,026 892 913 697 713 1,577 1,613 936 958 3,108 3,179 182 187 1,885 1,927 4,354 4,459 2,194 2,244 4,035 4,122 427 437 4,230 4,327 11,335 11,591 106,508 108,950 184,803 189,181 2014 Sectoraldemandforinvestment:SRP2($million) 6,364 6,535 248 255 820 840 1,462 1,559 7,201 7,389 25 26 185 190 211 217 7,622 7,853 4,900 5,050 2,200 2,267 305 314 1,641 1,690 1,611 1,659 731 752 568 585 1,276 1,315 762 785 2,522 2,599 147 152 1,528 1,574 3,537 3,645 1,779 1,833 3,296 3,394 346 356 3,423 3,528 9,169 9,448 86,191 88,842 150,068 154,651 2006 TableF4 ThisTableshowstheresultsobtainedbytheapplicationofEquation533,p.124. Present value 68,863 Coalsector 2,728 Petroleumsector 9,775 Gassector 22,470 RenewableElectricity 70,922 CoalfiredElectricity 270 InternalcombustionElectricity 2,013 GasturbineElectricity 5,098 CombinedcycleElectricity 84,407 Agriculture,forestryandfishing 54,309 Mining 24,377 Food,beveragesandtobacco Textile,clothing,footwearandleather 3,375 18,159 Wood,paperandprintingproducts 17,823 Basicchemicals 8,058 Nonmetallicmineralproducts 6,279 Basicironandsteel 14,157 Basicnonferrousmetals 8,428 Fabricatedmetalproducts 27,940 Machineryandequipment 1,635 Miscellenousmanufacturing 16,928 Water,sewerageanddrainage 39,194 Construction 19,716 Roadtransport 36,357 Railwaytransport 3,832 Watertransport 37,969 Airtransport Othertransport,servicesandstorage 101,701 956,165 Commercialservices Total 1,662,949 2017 7,793 7,928 316 323 1,239 1,261 3,649 4,255 6,915 6,769 31 31 229 233 984 1,003 9,820 10,043 6,324 6,468 2,838 2,902 393 402 2,112 2,160 2,072 2,119 933 955 729 746 1,650 1,688 980 1,003 3,253 3,328 191 195 1,970 2,015 4,565 4,675 2,295 2,348 4,210 4,300 446 457 4,426 4,527 11,854 12,122 111,450 114,007 193,667 198,262 2016 8,068 330 1,284 4,884 6,616 32 238 1,022 10,270 6,616 2,968 411 2,209 2,167 977 763 1,727 1,026 3,405 200 2,060 4,787 2,401 4,393 467 4,631 12,396 116,624 202,969 2018 2020 8,211 8,359 337 344 1,307 1,332 5,534 6,208 6,455 6,285 33 33 242 247 1,041 1,061 10,503 10,740 6,767 6,921 3,035 3,104 420 430 2,259 2,310 2,216 2,266 999 1,022 780 798 1,767 1,808 1,049 1,074 3,484 3,564 205 209 2,107 2,154 4,901 5,019 2,456 2,513 4,488 4,586 478 489 4,737 4,845 12,678 12,965 119,302 122,041 207,790 212,728 2019 319 Note: 2007 6,375 6,555 248 255 822 844 1,462 1,560 7,202 7,392 25 26 185 191 211 217 7,622 7,853 4,900 5,051 2,200 2,267 305 314 1,641 1,690 1,611 1,660 731 753 568 585 1,276 1,315 762 785 2,522 2,600 147 152 1,528 1,575 3,537 3,646 1,779 1,834 3,298 3,397 346 356 3,423 3,528 9,171 9,452 86,198 88,855 150,097 154,708 2006 6,741 262 866 1,662 7,586 26 196 224 8,092 5,207 2,336 324 1,742 1,710 775 603 1,356 809 2,679 156 1,623 3,758 1,890 3,500 367 3,637 9,741 91,595 159,464 2008 2010 6,932 7,130 270 278 889 912 1,769 1,881 7,786 7,991 27 28 202 208 231 238 8,337 8,591 5,367 5,532 2,407 2,481 333 343 1,794 1,849 1,762 1,815 798 822 621 640 1,398 1,441 833 859 2,762 2,847 161 166 1,673 1,724 3,874 3,993 1,948 2,008 3,605 3,714 379 390 3,750 3,865 10,039 10,347 94,420 97,334 164,369 169,427 2009 2012 7,251 7,376 284 290 987 1,063 1,911 1,941 7,866 7,735 28 29 212 215 414 595 8,784 8,982 5,657 5,785 2,537 2,595 351 359 1,890 1,932 1,856 1,897 839 857 654 668 1,474 1,508 878 897 2,910 2,975 170 174 1,764 1,805 4,081 4,170 2,053 2,100 3,796 3,879 399 408 3,954 4,045 10,590 10,839 99,560 101,838 173,150 176,956 2011 7,501 297 1,081 2,482 7,622 29 219 607 9,185 5,917 2,653 367 1,976 1,940 876 683 1,542 918 3,044 178 1,845 4,270 2,148 3,962 418 4,137 11,085 104,176 181,159 2013 2015 7,629 7,761 303 310 1,099 1,118 3,044 3,626 7,503 7,376 30 31 223 227 618 630 9,393 9,605 6,052 6,190 2,714 2,775 376 384 2,021 2,067 1,984 2,029 896 917 699 715 1,578 1,614 939 961 3,115 3,187 182 187 1,887 1,930 4,372 4,477 2,197 2,247 4,047 4,134 427 437 4,232 4,329 11,336 11,593 106,568 109,016 185,463 189,871 2014 2016 2017 7,895 8,034 316 323 1,138 1,159 4,229 4,854 7,242 7,101 31 32 232 236 642 654 9,822 10,045 6,331 6,475 2,838 2,903 393 402 2,114 2,162 2,075 2,122 938 960 731 748 1,651 1,690 983 1,006 3,261 3,336 191 195 1,973 2,018 4,585 4,695 2,298 2,351 4,224 4,315 447 457 4,428 4,529 11,856 12,126 111,520 114,082 194,385 199,007 Sectoraldemandforinvestment:PPPforEarlyaction($million) ThisTableshowstheresultsobtainedbytheapplicationofEquation533,p.124. 6,200 241 801 1,369 7,018 24 180 205 7,398 4,754 2,135 296 1,593 1,564 710 552 1,238 739 2,447 143 1,483 3,432 1,726 3,202 335 3,320 8,900 83,622 145,626 2005 TableF4 Present value 69,391 Coalsector 2,731 Petroleumsector 9,406 Gassector 24,308 RenewableElectricity 72,437 CoalfiredElectricity 272 InternalcombustionElectricity 2,025 GasturbineElectricity 3,775 CombinedcycleElectricity 84,416 Agriculture,forestryandfishing 54,343 Mining 24,379 Food,beveragesandtobacco Textile,clothing,footwearandleather 3,375 18,170 Wood,paperandprintingproducts 17,835 Basicchemicals 8,077 Nonmetallicmineralproducts 6,287 Basicironandsteel 14,161 Basicnonferrousmetals 8,440 Fabricatedmetalproducts 27,975 Machineryandequipment 1,635 Miscellenousmanufacturing 16,943 Water,sewerageanddrainage 39,271 Construction 19,728 Roadtransport 36,431 Railwaytransport 3,834 Watertransport 37,981 Airtransport Othertransport,servicesandstorage 101,730 956,496 Commercialservices Total 1,665,854 8,175 330 1,180 5,501 6,951 32 241 667 10,272 6,623 2,968 411 2,211 2,170 982 765 1,728 1,029 3,414 200 2,063 4,807 2,404 4,408 467 4,633 12,402 116,703 203,740 2018 2020 8,320 8,469 338 345 1,201 1,224 6,172 6,866 6,794 6,628 33 34 245 250 679 692 10,505 10,743 6,775 6,929 3,036 3,105 420 430 2,262 2,313 2,219 2,269 1,005 1,028 782 800 1,768 1,809 1,053 1,077 3,493 3,574 205 209 2,110 2,158 4,923 5,041 2,459 2,516 4,504 4,601 478 489 4,740 4,848 12,684 12,972 119,386 122,130 208,587 213,550 2019 320 Note: 2007 6,370 6,546 248 255 822 843 1,462 1,560 7,201 7,390 25 26 185 191 211 217 7,622 7,853 4,900 5,051 2,200 2,267 305 314 1,641 1,690 1,611 1,659 731 752 568 585 1,276 1,315 762 785 2,522 2,599 147 152 1,528 1,575 3,537 3,645 1,779 1,834 3,297 3,396 346 356 3,423 3,528 9,171 9,450 86,196 88,850 150,085 154,683 2006 6,727 262 864 1,662 7,584 26 196 224 8,091 5,206 2,336 324 1,741 1,709 775 603 1,356 809 2,679 156 1,623 3,757 1,890 3,497 367 3,637 9,738 91,587 159,427 2008 2010 6,914 7,107 270 278 887 910 1,769 1,880 7,783 7,987 27 28 202 208 231 238 8,337 8,590 5,366 5,531 2,407 2,481 333 343 1,794 1,848 1,761 1,814 797 821 621 639 1,398 1,441 833 858 2,761 2,846 161 166 1,672 1,723 3,873 3,992 1,948 2,007 3,602 3,710 379 390 3,749 3,865 10,036 10,343 94,409 97,319 164,319 169,365 2009 2012 7,225 7,346 284 290 984 1,060 1,909 1,939 7,860 7,727 28 29 211 215 414 595 8,784 8,982 5,656 5,783 2,537 2,594 351 359 1,890 1,932 1,855 1,896 838 856 653 668 1,474 1,507 877 897 2,909 2,974 170 174 1,763 1,803 4,079 4,168 2,053 2,099 3,791 3,874 399 408 3,953 4,044 10,585 10,833 99,543 101,819 173,075 176,870 2011 7,471 296 1,138 1,969 7,588 29 218 782 9,184 5,914 2,653 367 1,975 1,939 874 682 1,542 916 3,040 178 1,844 4,259 2,146 3,959 417 4,136 11,087 104,147 180,752 2013 2015 7,600 7,733 303 309 1,219 1,301 1,999 2,030 7,443 7,291 30 30 221 225 974 1,172 9,392 9,604 6,047 6,184 2,713 2,775 376 384 2,019 2,065 1,982 2,027 892 911 697 712 1,577 1,613 937 957 3,108 3,178 182 187 1,887 1,930 4,352 4,447 2,195 2,245 4,046 4,135 427 437 4,231 4,328 11,346 11,611 106,529 108,966 184,723 188,783 2014 2016 2017 7,866 8,003 316 323 1,324 1,347 2,596 3,183 7,157 7,016 31 31 229 233 1,194 1,217 9,821 10,043 6,325 6,469 2,838 2,902 393 402 2,111 2,159 2,073 2,119 932 953 729 745 1,650 1,688 979 1,002 3,251 3,326 191 195 1,973 2,018 4,553 4,662 2,296 2,348 4,223 4,314 447 457 4,427 4,528 11,873 12,142 111,467 114,025 193,265 197,854 Sectoraldemandforinvestment:SRPforearlyaction($million) ThisTableshowstheresultsobtainedbytheapplicationofEquation533,p.124. 6,200 241 801 1,369 7,018 24 180 205 7,398 4,754 2,135 296 1,593 1,564 710 552 1,238 739 2,447 143 1,483 3,432 1,726 3,202 335 3,320 8,900 83,622 145,626 2005 TableF4 Present value 69,218 Coalsector 2,730 Petroleumsector 9,888 Gassector 19,959 RenewableElectricity 72,197 CoalfiredElectricity 271 InternalcombustionElectricity 2,017 GasturbineElectricity 5,238 CombinedcycleElectricity 84,410 Agriculture,forestryandfishing 54,322 Mining 24,378 Food,beveragesandtobacco Textile,clothing,footwearandleather 3,375 18,161 Wood,paperandprintingproducts 17,827 Basicchemicals 8,058 Nonmetallicmineralproducts 6,280 Basicironandsteel 14,157 Basicnonferrousmetals 8,429 Fabricatedmetalproducts 27,945 Machineryandequipment 1,635 Miscellenousmanufacturing 16,939 Water,sewerageanddrainage 39,181 Construction 19,719 Roadtransport 36,412 Railwaytransport 3,833 Watertransport 37,976 Airtransport Othertransport,servicesandstorage 101,756 956,290 Commercialservices Total 1,662,601 8,144 330 1,372 3,791 6,867 32 238 1,240 10,270 6,617 2,968 411 2,209 2,167 975 762 1,727 1,025 3,403 200 2,063 4,774 2,402 4,407 467 4,632 12,417 116,644 202,555 2018 2020 8,288 8,437 337 345 1,397 1,422 4,421 5,074 6,711 6,546 33 33 242 247 1,263 1,287 10,503 10,741 6,768 6,923 3,036 3,105 420 430 2,259 2,310 2,217 2,267 998 1,021 780 797 1,767 1,808 1,049 1,073 3,482 3,563 205 209 2,110 2,158 4,889 5,006 2,457 2,513 4,503 4,600 478 489 4,738 4,847 12,699 12,987 119,323 122,064 207,370 212,301 2019 321 Note: 2007 6,386 6,578 248 255 826 851 1,463 1,561 7,204 7,395 25 26 185 191 211 218 7,622 7,854 4,901 5,052 2,200 2,267 305 314 1,641 1,691 1,611 1,660 731 753 568 586 1,276 1,316 762 785 2,523 2,601 147 152 1,529 1,576 3,538 3,648 1,780 1,834 3,300 3,401 346 356 3,423 3,529 9,174 9,457 86,208 88,875 150,133 154,780 2006 6,775 263 876 1,663 7,591 26 196 224 8,092 5,209 2,336 324 1,742 1,711 776 603 1,356 809 2,681 156 1,625 3,761 1,891 3,505 367 3,638 9,749 91,624 159,572 2008 2010 6,979 7,189 270 279 903 930 1,771 1,883 7,793 7,999 27 28 202 209 231 238 8,338 8,592 5,370 5,536 2,408 2,481 333 344 1,795 1,850 1,763 1,816 799 823 622 640 1,398 1,442 834 860 2,764 2,850 161 166 1,675 1,727 3,877 3,998 1,949 2,009 3,613 3,723 379 390 3,751 3,867 10,050 10,360 94,458 97,380 164,513 169,608 2009 2012 7,328 7,470 285 291 944 958 1,925 1,969 8,179 8,362 29 29 213 218 243 249 8,785 8,983 5,661 5,790 2,537 2,595 351 359 1,891 1,933 1,857 1,898 841 859 654 669 1,474 1,508 879 898 2,914 2,979 170 174 1,765 1,805 4,087 4,179 2,054 2,101 3,804 3,887 399 408 3,955 4,045 10,590 10,828 99,592 101,860 173,408 177,304 2011 7,616 297 973 2,013 8,551 30 223 254 9,186 5,921 2,653 367 1,977 1,940 877 684 1,543 918 3,046 178 1,845 4,273 2,148 3,973 418 4,137 11,072 104,181 181,294 2013 2015 7,734 7,855 303 310 1,049 1,063 2,044 2,614 8,415 8,300 30 31 226 231 443 451 9,393 9,605 6,054 6,192 2,714 2,775 376 384 2,021 2,067 1,984 2,028 895 916 699 714 1,578 1,614 939 960 3,114 3,185 182 187 1,887 1,930 4,366 4,470 2,197 2,247 4,058 4,144 427 437 4,232 4,329 11,330 11,586 106,557 108,996 185,247 189,618 2014 2016 2017 7,979 8,108 317 323 1,079 1,095 3,205 3,817 8,178 8,048 32 32 235 239 459 468 9,822 10,044 6,333 6,477 2,838 2,902 393 402 2,113 2,161 2,074 2,121 937 958 730 747 1,651 1,689 982 1,005 3,259 3,334 191 195 1,973 2,017 4,576 4,686 2,298 2,350 4,231 4,321 447 457 4,428 4,529 11,847 12,114 111,493 114,048 194,098 198,688 Sectoraldemandforinvestment:PPPforDelayaction($million) ThisTableshowstheresultsobtainedbytheapplicationofEquation533,p.124. 6,200 241 801 1,369 7,018 24 180 205 7,398 4,754 2,135 296 1,593 1,564 710 552 1,238 739 2,447 143 1,483 3,432 1,726 3,202 335 3,320 8,900 83,622 145,626 2005 TableF4 Present value 69,871 Coalsector 2,733 Petroleumsector 9,147 Gassector 21,409 RenewableElectricity 75,901 CoalfiredElectricity 274 InternalcombustionElectricity 2,038 GasturbineElectricity 2,831 CombinedcycleElectricity 84,418 Agriculture,forestryandfishing 54,360 Mining 24,379 Food,beveragesandtobacco Textile,clothing,footwearandleather 3,376 18,171 Wood,paperandprintingproducts 17,838 Basicchemicals 8,079 Nonmetallicmineralproducts 6,288 Basicironandsteel 14,162 Basicnonferrousmetals 8,442 Fabricatedmetalproducts 27,981 Machineryandequipment 1,635 Miscellenousmanufacturing 16,947 Water,sewerageanddrainage 39,268 Construction 19,731 Roadtransport 36,482 Railwaytransport 3,834 Watertransport 37,984 Airtransport Othertransport,servicesandstorage 101,719 956,546 Commercialservices Total 1,665,845 8,241 331 1,113 4,451 7,912 33 244 477 10,271 6,624 2,968 411 2,210 2,169 980 764 1,728 1,028 3,411 200 2,062 4,798 2,404 4,413 467 4,632 12,388 116,662 203,391 2018 2020 8,378 8,520 338 345 1,131 1,151 5,108 5,789 7,767 7,615 33 34 249 253 486 495 10,504 10,742 6,775 6,929 3,036 3,105 420 430 2,261 2,312 2,218 2,268 1,003 1,026 781 799 1,768 1,809 1,051 1,076 3,490 3,570 205 209 2,109 2,156 4,913 5,030 2,459 2,515 4,507 4,603 478 489 4,738 4,847 12,669 12,956 119,338 122,075 208,210 213,146 2019 322 Note: 2007 6,386 6,578 248 255 826 851 1,463 1,561 7,204 7,395 25 26 185 191 211 218 7,622 7,854 4,901 5,052 2,200 2,267 305 314 1,641 1,691 1,611 1,660 731 753 568 586 1,276 1,316 762 785 2,523 2,601 147 152 1,529 1,576 3,538 3,648 1,780 1,834 3,300 3,401 346 356 3,423 3,529 9,174 9,457 86,208 88,875 150,133 154,780 2006 6,775 263 876 1,663 7,591 26 196 224 8,092 5,209 2,336 324 1,742 1,711 776 603 1,356 809 2,681 156 1,625 3,761 1,891 3,505 367 3,638 9,749 91,624 159,572 2008 2010 6,979 7,189 270 279 903 930 1,771 1,883 7,793 7,999 27 28 202 209 231 238 8,338 8,592 5,370 5,536 2,408 2,481 333 344 1,795 1,850 1,763 1,816 799 823 622 640 1,398 1,442 834 860 2,764 2,850 161 166 1,675 1,727 3,877 3,998 1,949 2,009 3,613 3,723 379 390 3,751 3,867 10,050 10,360 94,458 97,380 164,513 169,608 2009 2012 7,322 7,459 285 291 944 958 1,925 1,968 8,178 8,361 29 29 213 218 243 249 8,785 8,983 5,661 5,789 2,537 2,595 351 359 1,891 1,933 1,857 1,898 840 858 654 669 1,474 1,508 879 898 2,913 2,979 170 174 1,765 1,804 4,087 4,178 2,054 2,101 3,803 3,885 399 408 3,955 4,045 10,590 10,827 99,590 101,854 173,396 177,279 2011 7,601 297 973 2,012 8,548 30 223 254 9,185 5,921 2,653 367 1,976 1,940 877 683 1,543 918 3,045 178 1,844 4,272 2,148 3,970 418 4,137 11,069 104,172 181,255 2013 2015 7,716 7,835 303 310 1,049 1,128 2,043 2,074 8,410 8,266 30 31 226 230 442 636 9,392 9,604 6,053 6,189 2,713 2,775 376 384 2,020 2,066 1,983 2,027 895 914 698 713 1,578 1,614 938 959 3,113 3,182 182 187 1,886 1,929 4,364 4,459 2,196 2,246 4,054 4,141 427 437 4,231 4,328 11,327 11,590 106,545 108,974 185,195 189,227 2014 2016 2017 7,960 8,087 316 323 1,209 1,228 2,105 2,692 8,114 7,984 31 32 233 237 836 851 9,821 10,043 6,329 6,472 2,838 2,902 393 402 2,112 2,159 2,073 2,119 933 954 729 745 1,650 1,688 980 1,002 3,252 3,327 191 195 1,973 2,017 4,555 4,664 2,296 2,348 4,231 4,320 447 457 4,427 4,528 11,859 12,126 111,460 114,011 193,352 197,915 Sectoraldemandforinvestment:SRPforDelayaction($million) ThisTableshowstheresultsobtainedbytheapplicationofEquation533,p.124. 6,200 241 801 1,369 7,018 24 180 205 7,398 4,754 2,135 296 1,593 1,564 710 552 1,238 739 2,447 143 1,483 3,432 1,726 3,202 335 3,320 8,900 83,622 145,626 2005 TableF4 Present value 69,801 Coalsector 2,733 Petroleumsector 9,405 Gassector 19,210 RenewableElectricity 75,771 CoalfiredElectricity 273 InternalcombustionElectricity 2,034 GasturbineElectricity 3,577 CombinedcycleElectricity 84,415 Agriculture,forestryandfishing 54,350 Mining 24,379 Food,beveragesandtobacco Textile,clothing,footwearandleather 3,375 18,167 Wood,paperandprintingproducts 17,834 Basicchemicals 8,070 Nonmetallicmineralproducts 6,285 Basicironandsteel 14,160 Basicnonferrousmetals 8,436 Fabricatedmetalproducts 27,966 Machineryandequipment 1,635 Miscellenousmanufacturing 16,945 Water,sewerageanddrainage 39,223 Construction 19,727 Roadtransport 36,474 Railwaytransport 3,834 Watertransport 37,982 Airtransport Othertransport,servicesandstorage 101,735 956,456 Commercialservices Total 1,664,252 8,218 330 1,247 3,300 7,847 32 242 867 10,270 6,620 2,968 411 2,208 2,167 975 762 1,727 1,025 3,404 200 2,062 4,775 2,402 4,411 467 4,631 12,399 116,623 202,592 2018 2020 8,354 8,495 338 345 1,268 1,290 3,929 4,582 7,702 7,550 33 34 246 251 884 900 10,502 10,740 6,770 6,924 3,035 3,104 420 429 2,258 2,310 2,216 2,266 998 1,021 780 797 1,767 1,808 1,049 1,073 3,482 3,563 205 209 2,108 2,156 4,889 5,006 2,457 2,513 4,505 4,601 478 489 4,737 4,846 12,678 12,965 119,295 122,030 207,385 212,297 2019 323 Note: 12,519 6,350 2,536 1,958 18,765 55 376 799 21,595 11,718 18,444 6,801 28,870 28,960 12,248 12,184 5,298 16,373 41,828 1,236 2,881 5,752 12,001 3,432 1,701 6,754 42,841 240,762 565,036 12,166 6,161 2,462 1,833 18,280 53 365 776 20,956 11,369 17,894 6,600 28,008 28,100 11,882 11,821 5,140 15,883 40,575 1,199 2,795 5,580 11,645 3,331 1,650 6,552 41,561 233,556 548,194 12,884 6,544 2,612 2,089 19,264 56 387 824 22,254 12,078 19,010 7,009 29,758 29,846 12,625 12,557 5,461 16,877 43,119 1,274 2,969 5,929 12,369 3,536 1,753 6,962 44,160 248,192 582,399 2007 2009 13,259 13,645 6,745 6,951 2,691 2,771 2,227 2,370 19,775 20,299 58 60 399 411 849 874 22,933 23,634 12,449 12,832 19,593 20,195 7,223 7,444 30,673 31,617 30,760 31,702 13,014 13,414 12,942 13,340 5,630 5,803 17,398 17,934 44,451 45,824 1,314 1,354 3,060 3,154 6,112 6,301 12,748 13,139 3,643 3,754 1,807 1,862 7,177 7,399 45,519 46,921 255,852 263,749 600,299 618,754 2008 2011 14,043 14,359 7,164 7,328 2,855 2,920 2,521 2,579 20,838 21,314 62 63 423 433 901 922 24,356 24,908 13,226 13,528 20,815 21,290 7,672 7,846 32,590 33,334 32,673 33,416 13,828 14,143 13,749 14,062 5,982 6,119 18,487 18,910 47,239 48,321 1,396 1,428 3,251 3,325 6,495 6,644 13,542 13,850 3,868 3,956 1,919 1,963 7,627 7,802 48,367 49,473 271,892 278,116 637,781 652,349 2010 14,682 7,495 2,986 2,638 21,802 64 443 943 25,473 13,837 21,775 8,024 34,095 34,175 14,465 14,381 6,258 19,341 49,428 1,461 3,401 6,796 14,165 4,046 2,008 7,980 50,604 284,484 667,252 2012 15,013 7,666 3,054 2,698 22,301 66 453 964 26,050 14,154 22,272 8,207 34,873 34,952 14,794 14,709 6,402 19,783 50,560 1,494 3,479 6,952 14,488 4,138 2,054 8,163 51,762 290,998 682,498 2013 15,352 7,841 3,123 2,760 22,812 67 464 986 26,642 14,477 22,780 8,393 35,670 35,747 15,131 15,043 6,548 20,235 51,718 1,528 3,559 7,111 14,818 4,232 2,101 8,350 52,946 297,662 698,095 2014 15,698 8,020 3,194 2,823 23,334 69 474 1,009 27,246 14,808 23,300 8,584 36,484 36,560 15,476 15,386 6,698 20,698 52,903 1,563 3,640 7,274 15,155 4,328 2,149 8,541 54,158 304,479 714,051 2015 16,052 8,203 3,267 2,888 23,869 71 485 1,032 27,865 15,146 23,831 8,779 37,318 37,392 15,829 15,736 6,851 21,171 54,115 1,599 3,723 7,441 15,501 4,427 2,198 8,737 55,397 311,453 730,373 2016 2018 16,414 16,784 8,390 8,581 3,341 3,417 2,954 3,021 24,415 24,974 72 74 496 508 1,056 1,080 28,498 29,145 15,492 15,846 24,375 24,931 8,979 9,183 38,170 39,042 38,243 39,114 16,189 16,558 16,094 16,461 7,007 7,168 21,655 22,150 55,355 56,623 1,636 1,673 3,808 3,895 7,611 7,786 15,854 16,215 4,528 4,631 2,248 2,299 8,937 9,142 56,665 57,962 318,587 325,886 747,071 764,153 2017 ThisTableshowstheresultsobtainedbymultiplyingfixedtechnicalcoefficientmatrix(TableC3,AppendixC)withEquation532,p.124. 2006 Sectoraloutputsforintermediateconsumption:BCscenario($million) 2005 TableF5 Present value 138,252 Coalsector 70,407 Petroleumsector 28,078 Gassector 23,513 RenewableElectricity 206,181 CoalfiredElectricity 606 InternalcombustionElectricity 4,164 GasturbineElectricity 8,860 CombinedcycleElectricity 239,326 Agriculture,forestryandfishing 129,970 Mining 204,536 Food,beveragesandtobacco Textile,clothing,footwearandleather 75,387 320,225 Wood,paperandprintingproducts 321,048 Basicchemicals 135,846 Nonmetallicmineralproducts 135,090 Basicironandsteel 58,777 Basicnonferrousmetals 181,641 Fabricatedmetalproducts 464,159 Machineryandequipment 13,716 Miscellenousmanufacturing 31,950 Water,sewerageanddrainage 63,823 Construction 133,066 Roadtransport 38,024 Railwaytransport 18,860 Watertransport 74,944 Airtransport Othertransport,servicesandstorage 475,272 2,671,564 Commercialservices Total 6,267,285 2020 17,163 17,551 8,777 8,978 3,495 3,575 3,090 3,161 25,546 26,132 76 77 519 531 1,105 1,130 29,808 30,485 16,209 16,579 25,501 26,083 9,392 9,606 39,934 40,847 40,005 40,916 16,936 17,322 16,836 17,220 7,332 7,499 22,656 23,174 57,921 59,248 1,712 1,751 3,985 4,076 7,964 8,147 16,585 16,963 4,737 4,845 2,352 2,405 9,352 9,566 59,289 60,646 333,352 340,990 781,627 799,504 2019 324 Note: 2007 12,392 12,628 6,326 6,497 2,507 2,554 1,951 2,075 18,702 19,135 54 56 374 385 797 818 21,544 22,149 11,675 11,991 18,405 18,931 6,784 6,975 28,805 29,628 28,873 29,672 12,212 12,553 12,148 12,485 5,283 5,432 16,324 16,779 41,709 42,880 1,233 1,269 2,872 2,951 5,735 5,895 11,970 12,305 3,407 3,486 1,694 1,739 6,739 6,931 42,725 43,927 240,178 247,020 563,419 579,148 2006 12,875 6,673 2,605 2,205 19,579 57 395 840 22,773 12,317 19,474 7,172 30,476 30,496 12,904 12,833 5,584 17,249 44,088 1,306 3,034 6,061 12,651 3,569 1,786 7,130 45,169 254,085 595,386 2008 2010 13,131 13,397 6,854 7,041 2,658 2,715 2,340 2,480 20,035 20,502 59 61 406 417 863 887 23,415 24,076 12,653 13,000 20,032 20,608 7,374 7,583 31,351 32,253 31,347 32,224 13,267 13,642 13,191 13,562 5,742 5,904 17,735 18,235 45,335 46,620 1,343 1,382 3,119 3,207 6,231 6,408 13,008 13,376 3,655 3,744 1,834 1,884 7,336 7,547 46,451 47,774 261,376 268,897 612,143 629,427 2009 2012 13,584 13,777 7,179 7,320 2,754 2,795 2,529 2,579 20,908 21,322 62 63 425 433 904 922 24,567 25,069 13,255 13,515 21,038 21,477 7,738 7,897 32,926 33,615 32,873 33,538 13,919 14,203 13,836 14,116 6,024 6,147 18,606 18,986 47,574 48,550 1,412 1,441 3,272 3,339 6,538 6,672 13,649 13,929 3,808 3,874 1,921 1,958 7,705 7,867 48,760 49,769 274,511 280,258 642,278 655,432 2011 13,975 7,465 2,838 2,631 21,746 64 442 940 25,582 13,782 21,926 8,059 34,319 34,219 14,493 14,403 6,273 19,374 49,548 1,472 3,408 6,809 14,214 3,942 1,996 8,032 50,801 286,138 668,891 2013 2015 14,180 14,390 7,612 7,763 2,882 2,927 2,683 2,737 22,179 22,621 66 67 451 460 959 978 26,106 26,641 14,055 14,333 22,385 22,854 8,225 8,394 35,040 35,776 34,915 35,626 14,789 15,093 14,696 14,996 6,402 6,533 19,771 20,178 50,569 51,613 1,503 1,535 3,478 3,550 6,949 7,092 14,507 14,805 4,012 4,084 2,035 2,075 8,202 8,375 51,858 52,939 292,154 298,307 682,660 696,744 2014 2016 2017 14,605 14,697 7,918 8,070 2,974 3,250 2,791 2,828 23,074 22,653 68 69 469 475 998 1,732 27,188 27,747 14,618 14,900 23,334 23,824 8,567 8,744 36,529 37,293 36,354 37,093 15,404 15,706 15,303 15,609 6,667 6,802 20,593 21,007 52,680 53,748 1,568 1,601 3,624 3,700 7,238 7,385 15,111 15,420 4,157 4,228 2,116 2,157 8,552 8,733 54,044 55,230 304,601 311,027 711,146 725,730 Sectoraloutputsforintermediateconsumption:PPP1 ($million) 14,793 8,225 3,528 2,865 22,219 70 481 2,486 28,318 15,189 24,324 8,925 38,073 37,850 16,015 15,921 6,941 21,430 54,839 1,635 3,779 7,535 15,736 4,300 2,200 8,919 56,442 317,598 740,637 2018 2020 325 14,893 14,996 8,384 8,547 3,808 4,090 2,903 2,941 21,772 21,309 71 72 488 494 3,260 4,054 28,901 29,497 15,484 15,785 24,836 25,359 9,110 9,299 38,871 39,686 38,623 39,413 16,331 16,654 16,241 16,568 7,082 7,227 21,862 22,305 55,955 57,096 1,669 1,705 3,860 3,942 7,689 7,846 16,058 16,389 4,374 4,450 2,243 2,287 9,109 9,303 57,681 58,947 324,316 331,183 755,873 771,443 2019 ThisTableshowstheresultsobtainedbymultiplyinganupdatedtechnicalcoefficientmatrix(calculatedfromEquation520,p.110)withEquation532,p.124. 12,166 6,161 2,462 1,833 18,280 53 365 776 20,956 11,369 17,894 6,600 28,008 28,100 11,882 11,821 5,140 15,883 40,575 1,199 2,795 5,580 11,645 3,331 1,650 6,552 41,561 233,556 548,194 2005 TableF5 Present value 130,990 Coalsector 69,054 Petroleumsector 27,380 Gassector 23,006 RenewableElectricity 199,616 CoalfiredElectricity 594 InternalcombustionElectricity 4,079 GasturbineElectricity 11,018 CombinedcycleElectricity 236,195 Agriculture,forestryandfishing 127,474 Mining 202,229 Food,beveragesandtobacco Textile,clothing,footwearandleather 74,401 316,520 Wood,paperandprintingproducts 316,163 Basicchemicals 133,798 Nonmetallicmineralproducts 133,034 Basicironandsteel 57,915 Basicnonferrousmetals 178,889 Fabricatedmetalproducts 457,360 Machineryandequipment 13,568 Miscellenousmanufacturing 31,483 Water,sewerageanddrainage 62,865 Construction 131,235 Roadtransport 36,721 Railwaytransport 18,477 Watertransport 74,078 Airtransport Othertransport,servicesandstorage 469,078 2,639,283 Commercialservices Total 6,176,503 Note: 2007 12,282 12,414 6,299 6,443 2,492 2,527 1,943 2,057 18,618 18,967 54 55 373 381 793 811 21,457 21,974 11,624 11,890 18,348 18,815 6,758 6,923 28,724 29,465 28,762 29,450 12,169 12,466 12,102 12,394 5,265 5,394 16,264 16,660 41,558 42,579 1,230 1,263 2,861 2,931 5,716 5,857 11,927 12,219 3,381 3,436 1,686 1,724 6,720 6,895 42,586 43,653 239,508 245,690 561,502 575,333 2006 12,559 6,593 2,568 2,176 19,327 57 390 829 22,505 12,165 19,297 7,092 30,231 30,163 12,775 12,696 5,528 17,071 43,636 1,296 3,003 6,003 12,521 3,495 1,763 7,075 44,759 252,095 589,669 2008 2010 12,716 12,883 6,747 6,907 2,612 2,660 2,300 2,429 19,697 20,078 58 59 399 408 849 868 23,052 23,616 12,450 12,744 19,794 20,306 7,267 7,447 31,022 31,838 30,900 31,662 13,095 13,426 13,009 13,332 5,666 5,809 17,496 17,936 44,728 45,857 1,331 1,367 3,078 3,155 6,154 6,310 12,833 13,155 3,558 3,625 1,803 1,845 7,262 7,454 45,903 47,086 258,718 265,559 604,499 619,820 2009 2012 12,976 13,075 7,018 7,132 2,692 2,725 2,467 2,507 20,396 20,723 60 61 415 421 882 896 24,010 24,414 12,948 13,156 20,672 21,047 7,574 7,704 32,427 33,030 32,198 32,748 13,660 13,900 13,560 13,794 5,909 6,012 18,247 18,566 46,657 47,477 1,393 1,419 3,211 3,267 6,421 6,535 13,384 13,617 3,667 3,711 1,873 1,902 7,594 7,737 47,934 48,804 270,507 275,577 630,752 641,958 2011 13,073 7,244 2,999 2,530 20,265 62 425 1,550 24,825 13,363 21,430 7,837 33,642 33,310 14,133 14,027 6,116 18,884 48,298 1,446 3,328 6,650 13,854 3,754 1,932 7,884 49,747 280,782 653,389 2013 2015 13,079 13,093 7,360 7,479 3,277 3,561 2,553 2,577 19,800 19,327 62 63 429 433 2,216 2,894 25,247 25,679 13,575 13,794 21,823 22,224 7,973 8,113 34,269 34,912 33,887 34,479 14,373 14,619 14,266 14,512 6,222 6,332 19,211 19,546 49,141 50,006 1,474 1,502 3,389 3,453 6,768 6,889 14,097 14,346 3,800 3,847 1,963 1,994 8,034 8,189 50,713 51,702 286,118 291,586 665,120 677,150 2014 2016 2017 13,114 13,143 7,601 7,727 3,851 4,147 2,601 2,626 18,846 18,356 64 64 437 441 3,585 4,290 26,122 26,575 14,018 14,248 22,636 23,057 8,256 8,403 35,570 36,244 35,086 35,708 14,871 15,130 14,764 15,022 6,443 6,558 19,890 20,243 50,893 51,802 1,531 1,561 3,517 3,584 7,013 7,141 14,601 14,862 3,897 3,948 2,027 2,060 8,347 8,509 52,715 53,751 297,186 302,920 689,482 702,117 Sectoraloutputsforintermediateconsumption:SRP1($million) 13,178 7,856 4,448 2,652 17,857 65 445 5,008 27,038 14,484 23,488 8,553 36,933 36,345 15,395 15,286 6,675 20,604 52,733 1,591 3,652 7,271 15,130 4,001 2,094 8,674 54,810 308,790 715,058 2018 2020 326 13,220 13,255 7,989 8,127 4,756 4,813 2,678 3,406 17,349 16,888 65 66 450 456 5,740 5,817 27,513 28,000 14,725 14,979 23,928 24,380 8,706 8,864 37,639 38,375 36,998 37,674 15,666 15,973 15,557 15,848 6,795 6,921 20,974 21,373 53,687 54,697 1,623 1,655 3,722 3,790 7,405 7,543 15,404 15,688 4,056 4,107 2,130 2,165 8,844 9,016 55,894 56,948 314,797 320,985 728,308 741,809 2019 ThisTableshowstheresultsobtainedbymultiplyinganupdatedtechnicalcoefficientmatrix(calculatedfromEquation520,p.110)withEquation532,p.124. 12,166 6,161 2,462 1,833 18,280 53 365 776 20,956 11,369 17,894 6,600 28,008 28,100 11,882 11,821 5,140 15,883 40,575 1,199 2,795 5,580 11,645 3,331 1,650 6,552 41,561 233,556 548,194 2005 TableF5 Present value 124,886 Coalsector 67,602 Petroleumsector 29,216 Gassector 22,491 RenewableElectricity 187,423 CoalfiredElectricity 576 InternalcombustionElectricity 3,957 GasturbineElectricity 16,785 CombinedcycleElectricity 231,216 Agriculture,forestryandfishing 124,709 Mining 198,965 Food,beveragesandtobacco Textile,clothing,footwearandleather 72,942 312,056 Wood,paperandprintingproducts 310,200 Basicchemicals 131,410 Nonmetallicmineralproducts 130,552 Basicironandsteel 56,879 Basicnonferrousmetals 175,655 Fabricatedmetalproducts 449,117 Machineryandequipment 13,399 Miscellenousmanufacturing 30,961 Water,sewerageanddrainage 61,821 Construction 128,862 Roadtransport 35,490 Railwaytransport 18,058 Watertransport 73,103 Airtransport Othertransport,servicesandstorage 462,267 2,604,152 Commercialservices Total 6,074,750 Note: 2007 12,264 12,386 6,303 6,451 2,477 2,501 1,945 2,062 18,638 19,009 54 56 373 382 794 813 21,493 22,046 11,632 11,907 18,367 18,855 6,768 6,942 28,741 29,503 28,787 29,505 12,176 12,483 12,112 12,415 5,269 5,403 16,275 16,685 41,590 42,650 1,231 1,264 2,863 2,935 5,718 5,863 11,938 12,244 3,382 3,440 1,687 1,726 6,723 6,902 42,609 43,707 239,595 245,905 561,803 576,037 2006 12,525 6,605 2,533 2,183 19,391 57 391 832 22,616 12,193 19,358 7,122 30,291 30,251 12,804 12,730 5,541 17,113 43,750 1,298 3,010 6,013 12,560 3,504 1,767 7,087 44,849 252,463 590,836 2008 2010 12,679 12,845 6,765 6,931 2,569 2,610 2,310 2,442 19,785 20,189 58 60 401 410 852 873 23,202 23,806 12,489 12,795 19,877 20,411 7,308 7,499 31,106 31,946 31,023 31,822 13,136 13,479 13,057 13,394 5,685 5,832 17,555 18,013 44,888 46,064 1,334 1,370 3,088 3,169 6,168 6,329 12,886 13,223 3,572 3,644 1,809 1,852 7,278 7,475 46,032 47,256 259,253 266,268 606,165 622,009 2009 2012 12,938 12,925 7,047 7,162 2,634 2,857 2,484 2,509 20,532 20,098 61 61 417 421 888 1,537 24,240 24,683 13,009 13,221 20,800 21,197 7,637 7,779 32,559 33,180 32,395 32,977 13,725 13,964 13,636 13,877 5,938 6,044 18,342 18,669 46,911 47,756 1,397 1,424 3,228 3,289 6,445 6,561 13,466 13,712 3,692 3,738 1,882 1,913 7,620 7,768 48,145 49,104 271,389 276,622 633,458 645,049 2011 12,919 7,280 3,075 2,534 19,656 62 426 2,199 25,136 13,439 21,603 7,923 33,815 33,574 14,209 14,123 6,153 19,004 48,622 1,452 3,352 6,680 13,964 3,785 1,945 7,919 50,084 281,976 656,909 2013 2015 12,914 12,918 7,403 7,529 3,091 3,109 3,224 3,933 19,267 18,867 63 64 432 437 2,229 2,260 25,601 26,076 13,668 13,904 22,019 22,445 8,071 8,223 34,480 35,161 34,195 34,832 14,488 14,775 14,389 14,662 6,268 6,386 19,368 19,741 49,544 50,490 1,481 1,510 3,414 3,478 6,803 6,930 14,225 14,493 3,830 3,877 1,978 2,011 8,074 8,232 51,036 52,011 287,519 293,198 669,072 681,553 2014 2016 2017 12,929 12,948 7,660 7,794 3,130 3,154 4,661 5,410 18,454 18,029 65 65 444 450 2,291 2,323 26,564 27,063 14,146 14,394 22,882 23,328 8,379 8,539 35,859 36,573 35,485 36,155 15,069 15,371 14,942 15,229 6,506 6,629 20,124 20,516 51,459 52,453 1,540 1,571 3,543 3,609 7,060 7,193 14,768 15,050 3,925 3,976 2,046 2,081 8,394 8,560 53,012 54,036 299,016 304,974 694,352 707,474 Sectoraloutputsforintermediateconsumption:PPP2($million) 12,974 7,931 3,180 6,179 17,591 66 456 2,356 27,573 14,648 23,786 8,702 37,304 36,842 15,680 15,523 6,756 20,918 53,471 1,603 3,678 7,329 15,338 4,028 2,118 8,730 55,086 311,074 720,923 2018 2020 327 13,006 13,045 8,073 8,218 3,208 3,239 6,970 7,783 17,140 16,673 67 68 463 469 2,390 2,424 28,096 28,631 14,909 15,176 24,254 24,732 8,870 9,041 38,053 38,819 37,546 38,267 15,996 16,321 15,825 16,133 6,885 7,017 21,330 21,752 54,514 55,583 1,635 1,669 3,748 3,819 7,469 7,612 15,634 15,937 4,083 4,139 2,156 2,194 8,904 9,082 56,161 57,263 317,319 323,712 734,703 748,819 2019 ThisTableshowstheresultsobtainedbymultiplyinganupdatedtechnicalcoefficientmatrix(calculatedfromEquation520,p.110)withEquation532,p.124. 12,166 6,161 2,462 1,833 18,280 53 365 776 20,956 11,369 17,894 6,600 28,008 28,100 11,882 11,821 5,140 15,883 40,575 1,199 2,795 5,580 11,645 3,331 1,650 6,552 41,561 233,556 548,194 2005 TableF5 Present value 124,102 Coalsector 67,867 Petroleumsector 26,861 Gassector 29,097 RenewableElectricity 186,147 CoalfiredElectricity 580 InternalcombustionElectricity 3,985 GasturbineElectricity 13,017 CombinedcycleElectricity 233,281 Agriculture,forestryandfishing 125,282 Mining 200,111 Food,beveragesandtobacco Textile,clothing,footwearandleather 73,515 313,340 Wood,paperandprintingproducts 312,016 Basicchemicals 132,213 Nonmetallicmineralproducts 131,328 Basicironandsteel 57,159 Basicnonferrousmetals 176,655 Fabricatedmetalproducts 451,614 Machineryandequipment 13,439 Miscellenousmanufacturing 31,088 Water,sewerageanddrainage 62,031 Construction 129,627 Roadtransport 35,641 Railwaytransport 18,145 Watertransport 73,325 Airtransport Othertransport,servicesandstorage 463,818 2,612,347 Commercialservices Total 6,097,630 Note: 2007 12,045 11,978 6,249 6,347 2,447 2,455 1,927 2,026 18,471 18,681 54 55 370 375 787 799 21,319 21,699 11,530 11,710 18,252 18,626 6,716 6,839 28,579 29,186 28,565 29,074 12,089 12,317 12,021 12,239 5,232 5,330 16,155 16,455 41,288 42,064 1,225 1,252 2,842 2,895 5,679 5,788 11,853 12,075 3,330 3,345 1,672 1,696 6,687 6,831 42,332 43,176 238,254 243,337 557,970 568,651 2006 11,945 6,453 2,473 2,129 18,906 56 381 811 22,093 11,903 19,015 6,968 29,822 29,615 12,559 12,471 5,433 16,774 42,886 1,280 2,952 5,903 12,310 3,369 1,722 6,982 44,071 248,693 579,973 2008 2010 11,935 11,858 6,564 6,678 2,498 2,719 2,235 2,331 19,142 18,747 56 57 388 392 825 1,356 22,501 22,924 12,106 12,313 19,417 19,833 7,102 7,241 30,482 31,162 30,182 30,771 12,813 13,068 12,714 12,962 5,540 5,650 17,109 17,450 43,746 44,626 1,310 1,340 3,012 3,076 6,023 6,147 12,554 12,806 3,399 3,432 1,749 1,778 7,139 7,303 45,006 46,020 254,276 260,077 591,824 604,115 2009 2012 11,715 11,591 6,745 6,817 2,951 3,186 2,337 2,344 18,200 17,654 57 57 393 394 1,956 2,560 23,183 23,453 12,433 12,560 20,108 20,391 7,329 7,420 31,620 32,093 31,144 31,533 13,228 13,395 13,117 13,279 5,720 5,792 17,667 17,893 45,187 45,772 1,361 1,383 3,118 3,163 6,227 6,311 12,967 13,135 3,442 3,456 1,795 1,812 7,415 7,530 46,713 47,429 264,033 268,117 612,162 620,521 2011 11,484 6,893 3,424 2,352 17,111 57 395 3,168 23,732 12,693 20,684 7,515 32,581 31,937 13,568 13,448 5,866 18,128 46,379 1,405 3,208 6,398 13,308 3,473 1,831 7,649 48,165 272,326 629,180 2013 2015 11,383 11,298 6,974 7,059 3,441 3,461 2,973 3,604 16,627 16,143 58 58 398 401 3,190 3,214 24,022 24,325 12,838 12,990 20,986 21,298 7,613 7,715 33,096 33,627 32,363 32,806 13,774 13,986 13,635 13,829 5,946 6,029 18,389 18,661 47,038 47,723 1,428 1,452 3,253 3,299 6,489 6,584 13,491 13,682 3,488 3,506 1,851 1,872 7,771 7,897 48,878 49,616 276,694 281,204 638,086 647,339 2014 2016 2017 11,229 11,173 7,149 7,243 3,484 3,509 4,246 4,900 15,658 15,169 59 59 404 407 3,240 3,267 24,639 24,965 13,149 13,316 21,621 21,954 7,821 7,931 34,176 34,741 33,267 33,744 14,207 14,435 14,031 14,240 6,115 6,204 18,942 19,233 48,433 49,169 1,476 1,501 3,347 3,397 6,682 6,784 13,879 14,083 3,527 3,551 1,894 1,917 8,026 8,160 50,380 51,170 285,854 290,645 656,934 666,868 Sectoraloutputsforintermediateconsumption:SRP2($million) 11,130 7,341 3,538 5,567 14,677 60 411 3,295 25,303 13,489 22,297 8,044 35,323 34,239 14,670 14,456 6,296 19,535 49,930 1,527 3,448 6,889 14,295 3,577 1,941 8,297 51,985 295,578 677,138 2018 2020 328 11,099 11,078 7,443 7,549 3,569 3,602 6,248 6,942 14,180 13,677 60 61 415 419 3,325 3,356 25,652 26,014 13,669 13,856 22,651 23,015 8,162 8,283 35,922 36,538 34,751 35,280 14,913 15,164 14,680 14,910 6,390 6,488 19,846 20,167 50,716 51,527 1,554 1,581 3,501 3,556 6,998 7,110 14,513 14,739 3,606 3,637 1,966 1,993 8,439 8,584 52,825 53,692 300,652 305,869 687,744 698,685 2019 ThisTableshowstheresultsobtainedbymultiplyinganupdatedtechnicalcoefficientmatrix(calculatedfromEquation520,p.110)withEquation532,p.124. 12,166 6,161 2,462 1,833 18,280 53 365 776 20,956 11,369 17,894 6,600 28,008 28,100 11,882 11,821 5,140 15,883 40,575 1,199 2,795 5,580 11,645 3,331 1,650 6,552 41,561 233,556 548,194 2005 TableF5 Present value 115,347 Coalsector 65,373 Petroleumsector 28,238 Gassector 27,335 RenewableElectricity 172,734 CoalfiredElectricity 553 InternalcombustionElectricity 3,796 GasturbineElectricity 17,395 CombinedcycleElectricity 224,130 Agriculture,forestryandfishing 120,456 Mining 194,114 Food,beveragesandtobacco Textile,clothing,footwearandleather 70,850 305,280 Wood,paperandprintingproducts 301,328 Basicchemicals 128,052 Nonmetallicmineralproducts 126,936 Basicironandsteel 55,289 Basicnonferrousmetals 170,952 Fabricatedmetalproducts 437,029 Machineryandequipment 13,133 Miscellenousmanufacturing 30,141 Water,sewerageanddrainage 60,202 Construction 125,362 Roadtransport 33,635 Railwaytransport 17,406 Watertransport 71,557 Airtransport Othertransport,servicesandstorage 451,135 2,548,992 Commercialservices Total 5,916,750 TableF5 Note: 12,166 6,161 2,462 1,833 18,280 53 365 776 20,956 11,369 17,894 6,600 28,008 28,100 11,882 11,821 5,140 15,883 40,575 1,199 2,795 5,580 11,645 3,331 1,650 6,552 41,561 233,556 548,194 2005 2007 12,200 12,268 6,291 6,428 2,462 2,477 1,941 2,055 18,605 18,946 54 55 373 381 793 810 21,467 21,994 11,610 11,865 18,347 18,816 6,759 6,925 28,708 29,441 28,743 29,422 12,158 12,450 12,093 12,381 5,261 5,388 16,250 16,639 41,530 42,536 1,230 1,261 2,859 2,927 5,710 5,847 11,922 12,213 3,369 3,418 1,684 1,720 6,716 6,887 42,550 43,599 239,298 245,359 560,981 574,507 2006 12,359 6,572 2,501 2,173 19,299 57 389 828 22,537 12,132 19,300 7,097 30,201 30,132 12,755 12,681 5,520 17,047 43,585 1,295 2,999 5,990 12,515 3,473 1,757 7,066 44,695 251,683 588,636 2008 2010 12,468 12,591 6,722 6,878 2,530 2,564 2,296 2,424 19,662 20,036 58 59 398 407 847 866 23,096 23,672 12,409 12,695 19,799 20,313 7,275 7,458 30,987 31,798 30,868 31,629 13,073 13,401 12,992 13,314 5,657 5,797 17,470 17,907 44,673 45,797 1,329 1,364 3,074 3,151 6,138 6,291 12,827 13,149 3,534 3,599 1,796 1,837 7,250 7,441 45,832 47,010 258,240 265,017 603,300 618,466 2009 2012 12,533 12,485 6,980 7,085 2,771 2,970 2,445 2,466 19,584 19,125 60 60 411 414 1,498 2,140 24,077 24,492 12,883 13,077 20,682 21,058 7,588 7,721 32,375 32,966 32,161 32,707 13,620 13,844 13,533 13,759 5,894 5,993 18,206 18,513 46,571 47,366 1,389 1,415 3,208 3,266 6,397 6,506 13,375 13,606 3,635 3,673 1,864 1,892 7,579 7,720 47,899 48,809 269,889 274,877 629,107 640,007 2011 12,441 7,195 2,976 3,133 18,720 61 419 2,166 24,918 13,282 21,445 7,858 33,586 33,276 14,102 14,003 6,098 18,848 48,215 1,442 3,323 6,620 13,847 3,710 1,921 7,864 49,691 280,048 651,210 2013 2015 12,409 12,387 7,309 7,427 2,986 2,999 3,816 4,517 18,307 17,883 62 63 424 430 2,193 2,220 25,355 25,803 13,493 13,710 21,841 22,247 7,998 8,142 34,222 34,873 33,861 34,463 14,367 14,640 14,254 14,512 6,206 6,317 19,192 19,546 49,087 49,982 1,470 1,498 3,382 3,442 6,736 6,856 14,094 14,348 3,748 3,788 1,951 1,982 8,012 8,164 50,596 51,525 285,351 290,787 662,724 674,549 2014 2017 12,374 12,370 7,549 7,674 3,014 3,033 5,236 5,973 17,449 17,004 63 64 435 441 2,249 2,277 26,261 26,731 13,933 14,162 22,663 23,088 8,289 8,440 35,540 36,224 35,080 35,713 14,919 15,205 14,777 15,048 6,430 6,546 19,909 20,280 50,900 51,842 1,527 1,557 3,504 3,567 6,979 7,105 14,608 14,875 3,831 3,875 2,014 2,047 8,319 8,478 52,478 53,455 296,357 302,063 686,686 699,138 2016 Sectoraloutputsforintermediateconsumption:PPPforEarlyaction($million) 12,374 7,803 3,054 6,729 16,547 65 447 2,307 27,213 14,398 23,524 8,595 36,924 36,362 15,499 15,326 6,664 20,662 52,807 1,587 3,632 7,234 15,149 3,921 2,082 8,641 54,456 307,906 711,909 2018 2020 329 12,386 12,405 7,936 8,073 3,077 3,103 7,505 8,302 16,078 15,595 66 67 452 459 2,338 2,369 27,706 28,211 14,640 14,888 23,970 24,427 8,753 8,916 37,641 38,374 37,028 37,710 15,800 16,109 15,611 15,904 6,786 6,911 21,053 21,454 53,797 54,812 1,619 1,650 3,699 3,767 7,366 7,502 15,429 15,716 3,969 4,019 2,117 2,153 8,808 8,978 55,482 56,533 313,890 320,017 725,002 738,422 2019 ThisTableshowstheresultsobtainedbymultiplyinganupdatedtechnicalcoefficientmatrix(calculatedfromEquation520,p.110)withEquation532,p.124. Present value 121,331 Coalsector 67,324 Petroleumsector 26,531 Gassector 30,780 RenewableElectricity 181,626 CoalfiredElectricity 574 InternalcombustionElectricity 3,944 GasturbineElectricity 13,551 CombinedcycleElectricity 231,854 Agriculture,forestryandfishing 124,250 Mining 199,076 Food,beveragesandtobacco Textile,clothing,footwearandleather 73,085 311,797 Wood,paperandprintingproducts 310,041 Basicchemicals 131,443 Nonmetallicmineralproducts 130,509 Basicironandsteel 56,791 Basicnonferrousmetals 175,584 Fabricatedmetalproducts 448,870 Machineryandequipment 13,377 Miscellenousmanufacturing 30,902 Water,sewerageanddrainage 61,639 Construction 128,855 Roadtransport 35,173 Railwaytransport 17,991 Watertransport 72,964 Airtransport Othertransport,servicesandstorage 461,299 2,599,423 Commercialservices Total 6,060,582 TableF5 Note: 12,166 6,161 2,462 1,833 18,280 53 365 776 20,956 11,369 17,894 6,600 28,008 28,100 11,882 11,821 5,140 15,883 40,575 1,199 2,795 5,580 11,645 3,331 1,650 6,552 41,561 233,556 548,194 2005 2007 12,165 12,195 6,275 6,396 2,458 2,467 1,935 2,042 18,545 18,824 54 55 371 378 790 805 21,390 21,839 11,578 11,801 18,301 18,722 6,737 6,881 28,653 29,326 28,665 29,263 12,129 12,392 12,062 12,317 5,249 5,363 16,210 16,558 41,426 42,323 1,228 1,257 2,852 2,913 5,698 5,822 11,890 12,148 3,356 3,390 1,679 1,710 6,704 6,863 42,461 43,414 238,889 244,510 559,751 571,972 2006 12,246 6,523 2,484 2,152 19,115 56 386 820 22,302 12,034 19,158 7,030 30,027 29,888 12,666 12,583 5,481 16,921 43,260 1,288 2,977 5,953 12,416 3,430 1,742 7,029 44,411 250,377 584,758 2008 2010 12,315 12,398 6,656 6,794 2,507 2,535 2,267 2,387 19,417 19,730 57 58 393 401 836 853 22,780 23,273 12,278 12,530 19,607 20,071 7,185 7,344 30,751 31,501 30,539 31,213 12,953 13,249 12,860 13,148 5,603 5,730 17,300 17,693 44,235 45,244 1,320 1,354 3,044 3,114 6,088 6,228 12,694 12,981 3,476 3,525 1,776 1,811 7,200 7,378 45,449 46,524 256,468 262,773 598,056 611,841 2009 2012 12,307 12,230 6,879 6,969 2,737 2,934 2,400 2,414 19,228 18,725 59 59 403 406 1,471 2,095 23,598 23,933 12,686 12,849 20,390 20,718 7,451 7,561 32,019 32,551 31,661 32,125 13,438 13,633 13,334 13,527 5,814 5,900 17,950 18,215 45,909 46,596 1,377 1,401 3,163 3,214 6,322 6,420 13,173 13,371 3,548 3,574 1,833 1,856 7,503 7,632 47,314 48,124 267,193 271,737 621,162 630,767 2011 12,165 7,062 3,127 2,429 18,219 59 408 2,728 24,277 13,017 21,055 7,674 33,098 32,603 13,834 13,726 5,988 18,489 47,304 1,425 3,266 6,520 13,575 3,601 1,880 7,764 48,956 276,403 640,650 2013 2015 12,110 12,066 7,158 7,258 3,316 3,501 2,444 2,460 17,709 17,196 60 60 411 413 3,369 4,019 24,631 24,995 13,191 13,370 21,400 21,754 7,790 7,909 33,658 34,233 33,095 33,601 14,041 14,254 13,931 14,141 6,080 6,173 18,770 19,059 48,033 48,782 1,450 1,476 3,319 3,374 6,623 6,729 13,784 14,000 3,631 3,663 1,905 1,931 7,899 8,038 49,808 50,681 281,188 286,095 650,805 661,231 2014 2017 12,026 11,998 7,363 7,472 3,505 3,513 3,119 3,793 16,737 16,272 61 61 417 422 4,060 4,102 25,369 25,756 13,562 13,761 22,119 22,494 8,033 8,160 34,839 35,461 34,131 34,678 14,501 14,755 14,371 14,609 6,272 6,375 19,377 19,705 49,588 50,418 1,503 1,530 3,428 3,484 6,840 6,954 14,225 14,458 3,693 3,726 1,958 1,985 8,180 8,326 51,533 52,410 291,195 296,438 672,005 683,116 2016 Sectoraloutputsforintermediateconsumption:SRPforearlyaction($million) 11,980 7,584 3,525 4,482 15,800 62 426 4,146 26,154 13,966 22,880 8,291 36,100 35,242 15,018 14,854 6,480 20,044 51,274 1,558 3,542 7,071 14,697 3,761 2,014 8,477 53,313 301,824 694,564 2018 2020 330 11,971 11,972 7,701 7,822 3,541 3,560 5,186 5,908 15,320 14,831 63 63 431 436 4,192 4,240 26,565 26,987 14,178 14,397 23,276 23,682 8,426 8,565 36,756 37,430 35,823 36,422 15,287 15,565 15,106 15,365 6,588 6,700 20,392 20,750 52,154 53,060 1,587 1,617 3,601 3,662 7,192 7,317 14,944 15,198 3,798 3,838 2,044 2,075 8,631 8,789 54,242 55,196 307,356 313,034 706,352 718,480 2019 ThisTableshowstheresultsobtainedbymultiplyinganupdatedtechnicalcoefficientmatrix(calculatedfromEquation520,p.110)withEquation532,p.124. Present value 119,585 Coalsector 66,449 Petroleumsector 27,690 Gassector 24,946 RenewableElectricity 178,470 CoalfiredElectricity 563 InternalcombustionElectricity 3,869 GasturbineElectricity 18,228 CombinedcycleElectricity 227,651 Agriculture,forestryandfishing 122,520 Mining 196,517 Food,beveragesandtobacco Textile,clothing,footwearandleather 71,880 308,577 Wood,paperandprintingproducts 305,620 Basicchemicals 129,644 Nonmetallicmineralproducts 128,677 Basicironandsteel 56,067 Basicnonferrousmetals 173,201 Fabricatedmetalproducts 442,870 Machineryandequipment 13,262 Miscellenousmanufacturing 30,532 Water,sewerageanddrainage 60,986 Construction 127,070 Roadtransport 34,484 Railwaytransport 17,723 Watertransport 72,308 Airtransport Othertransport,servicesandstorage 456,565 2,575,497 Commercialservices Total 5,991,451 TableF5 Note: 12,166 6,161 2,462 1,833 18,280 53 365 776 20,956 11,369 17,894 6,600 28,008 28,100 11,882 11,821 5,140 15,883 40,575 1,199 2,795 5,580 11,645 3,331 1,650 6,552 41,561 233,556 548,194 2005 2007 12,519 12,884 6,350 6,544 2,536 2,612 1,958 2,089 18,765 19,264 55 56 376 387 799 824 21,595 22,254 11,718 12,078 18,444 19,010 6,801 7,009 28,870 29,758 28,960 29,846 12,248 12,625 12,184 12,557 5,298 5,461 16,373 16,877 41,828 43,119 1,236 1,274 2,881 2,969 5,752 5,929 12,001 12,369 3,432 3,536 1,701 1,753 6,754 6,962 42,841 44,160 240,762 248,192 565,036 582,399 2006 13,259 6,745 2,691 2,227 19,775 58 399 849 22,933 12,449 19,593 7,223 30,673 30,760 13,014 12,942 5,630 17,398 44,451 1,314 3,060 6,112 12,748 3,643 1,807 7,177 45,519 255,852 600,299 2008 2010 13,645 14,043 6,951 7,164 2,771 2,855 2,370 2,521 20,299 20,838 60 62 411 423 874 901 23,634 24,356 12,832 13,226 20,195 20,815 7,444 7,672 31,617 32,590 31,702 32,673 13,414 13,828 13,340 13,749 5,803 5,982 17,934 18,487 45,824 47,239 1,354 1,396 3,154 3,251 6,301 6,495 13,139 13,542 3,754 3,868 1,862 1,919 7,399 7,627 46,921 48,367 263,749 271,892 618,754 637,781 2009 2012 13,640 13,389 7,194 7,245 2,753 2,718 2,535 2,554 20,957 21,115 62 62 426 429 906 913 24,615 24,894 13,283 13,377 21,071 21,348 7,751 7,842 32,968 33,410 32,924 33,267 13,937 14,091 13,857 14,003 6,035 6,100 18,632 18,835 47,646 48,175 1,413 1,433 3,276 3,313 6,548 6,619 13,671 13,827 3,814 3,803 1,925 1,936 7,714 7,819 48,816 49,416 274,798 278,474 643,170 650,407 2011 13,190 7,304 2,697 2,575 21,285 63 433 920 25,181 13,482 21,635 7,936 33,872 33,636 14,257 14,160 6,167 19,053 48,741 1,454 3,354 6,695 13,992 3,802 1,949 7,929 50,057 282,356 658,176 2013 2015 12,911 12,663 7,363 7,429 2,865 2,834 2,579 3,254 20,658 20,103 63 63 433 435 1,580 1,588 25,477 25,784 13,587 13,706 21,929 22,234 8,033 8,135 34,342 34,843 34,018 34,428 14,416 14,612 14,317 14,495 6,236 6,310 19,271 19,520 49,309 49,939 1,475 1,497 3,398 3,441 6,772 6,854 14,159 14,338 3,802 3,801 1,964 1,980 8,042 8,159 50,769 51,454 286,350 290,542 666,118 674,443 2014 2017 12,452 12,272 7,502 7,581 2,811 2,795 3,937 4,630 19,551 19,000 64 64 438 441 1,597 1,607 26,103 26,433 13,833 13,969 22,548 22,873 8,241 8,350 35,361 35,896 34,858 35,307 14,816 15,029 14,681 14,875 6,388 6,468 19,780 20,051 50,596 51,281 1,520 1,544 3,485 3,532 6,941 7,031 14,525 14,719 3,805 3,813 1,998 2,018 8,280 8,405 52,167 52,907 294,882 299,365 683,161 692,255 2016 Sectoraloutputsforintermediateconsumption:PPPforDelayaction($million) 12,119 7,665 2,785 5,334 18,450 65 443 1,617 26,775 14,112 23,207 8,463 36,448 35,774 15,249 15,077 6,552 20,332 51,992 1,568 3,580 7,125 14,920 3,825 2,039 8,534 53,673 303,988 701,713 2018 2020 331 11,988 11,879 7,754 7,848 2,780 2,780 6,049 6,776 17,898 17,344 65 65 446 450 1,628 1,640 27,128 27,493 14,262 14,420 23,552 23,906 8,581 8,702 37,016 37,601 36,260 36,762 15,476 15,712 15,286 15,502 6,638 6,727 20,624 20,925 52,730 53,492 1,593 1,619 3,630 3,682 7,223 7,324 15,129 15,344 3,841 3,859 2,061 2,085 8,667 8,804 54,465 55,282 308,752 313,655 711,523 721,680 2019 ThisTableshowstheresultsobtainedbymultiplyinganupdatedtechnicalcoefficientmatrix(calculatedfromEquation520,p.110)withEquation532,p.124. Present value 125,962 Coalsector 67,998 Petroleumsector 26,329 Gassector 27,290 RenewableElectricity 191,806 CoalfiredElectricity 583 InternalcombustionElectricity 4,004 GasturbineElectricity 10,260 CombinedcycleElectricity 233,257 Agriculture,forestryandfishing 125,442 Mining 200,109 Food,beveragesandtobacco Textile,clothing,footwearandleather 73,528 313,459 Wood,paperandprintingproducts 312,280 Basicchemicals 132,351 Nonmetallicmineralproducts 131,444 Basicironandsteel 57,179 Basicnonferrousmetals 176,830 Fabricatedmetalproducts 452,003 Machineryandequipment 13,443 Miscellenousmanufacturing 31,121 Water,sewerageanddrainage 62,095 Construction 129,697 Roadtransport 35,862 Railwaytransport 18,174 Watertransport 73,360 Airtransport Othertransport,servicesandstorage 464,014 2,614,003 Commercialservices Total 6,103,883 TableF5 Note: 12,166 6,161 2,462 1,833 18,280 53 365 776 20,956 11,369 17,894 6,600 28,008 28,100 11,882 11,821 5,140 15,883 40,575 1,199 2,795 5,580 11,645 3,331 1,650 6,552 41,561 233,556 548,194 2005 2007 12,519 12,884 6,350 6,544 2,536 2,612 1,958 2,089 18,765 19,264 55 56 376 387 799 824 21,595 22,254 11,718 12,078 18,444 19,010 6,801 7,009 28,870 29,758 28,960 29,846 12,248 12,625 12,184 12,557 5,298 5,461 16,373 16,877 41,828 43,119 1,236 1,274 2,881 2,969 5,752 5,929 12,001 12,369 3,432 3,536 1,701 1,753 6,754 6,962 42,841 44,160 240,762 248,192 565,036 582,399 2006 13,259 6,745 2,691 2,227 19,775 58 399 849 22,933 12,449 19,593 7,223 30,673 30,760 13,014 12,942 5,630 17,398 44,451 1,314 3,060 6,112 12,748 3,643 1,807 7,177 45,519 255,852 600,299 2008 2010 13,645 14,043 6,951 7,164 2,771 2,855 2,370 2,521 20,299 20,838 60 62 411 423 874 901 23,634 24,356 12,832 13,226 20,195 20,815 7,444 7,672 31,617 32,590 31,702 32,673 13,414 13,828 13,340 13,749 5,803 5,982 17,934 18,487 45,824 47,239 1,354 1,396 3,154 3,251 6,301 6,495 13,139 13,542 3,754 3,868 1,862 1,919 7,399 7,627 46,921 48,367 263,749 271,892 618,754 637,781 2009 2012 13,676 13,409 7,183 7,216 2,769 2,726 2,528 2,538 20,893 20,978 62 62 425 426 903 907 24,508 24,678 13,257 13,314 21,012 21,226 7,722 7,781 32,912 33,280 32,843 33,076 13,912 14,026 13,825 13,928 6,022 6,071 18,594 18,741 47,539 47,926 1,412 1,429 3,269 3,297 6,539 6,595 13,635 13,747 3,808 3,777 1,921 1,927 7,704 7,793 48,736 49,208 274,474 277,580 642,082 647,661 2011 13,193 7,257 2,699 2,550 21,080 62 428 912 24,860 13,386 21,453 7,846 33,673 33,343 14,156 14,046 6,124 18,908 48,361 1,447 3,328 6,658 13,870 3,759 1,935 7,888 49,731 280,948 653,901 2013 2015 12,902 12,649 7,300 7,350 2,878 3,044 2,546 2,544 20,398 19,727 62 62 428 427 1,560 2,207 25,053 25,260 13,460 13,545 21,689 21,936 7,914 7,987 34,079 34,505 33,629 33,937 14,283 14,419 14,166 14,295 6,179 6,237 19,079 19,262 48,807 49,286 1,466 1,486 3,363 3,400 6,723 6,793 13,999 14,137 3,744 3,735 1,944 1,955 7,989 8,094 50,334 50,966 284,483 288,180 660,457 667,427 2014 2017 12,426 12,227 7,405 7,468 3,200 3,169 2,542 3,202 19,066 18,482 62 62 427 429 2,855 2,865 25,479 25,712 13,639 13,749 22,195 22,465 8,065 8,147 34,948 35,424 34,266 34,624 14,564 14,746 14,433 14,593 6,299 6,367 19,457 19,685 49,795 50,369 1,507 1,529 3,439 3,478 6,868 6,948 14,283 14,440 3,731 3,727 1,967 1,981 8,204 8,317 51,623 52,263 292,025 296,090 674,769 682,557 2016 Sectoraloutputsforintermediateconsumption:SRPforDelayaction($million) 12,057 7,537 3,146 3,869 17,904 63 430 2,877 25,961 13,868 22,748 8,234 35,920 35,005 14,937 14,763 6,439 19,925 50,975 1,551 3,519 7,033 14,607 3,729 1,997 8,435 52,935 300,326 690,792 2018 2020 332 11,912 11,789 7,612 7,693 3,130 3,119 4,544 5,228 17,332 16,764 63 63 432 435 2,890 2,906 26,224 26,502 13,997 14,135 23,043 23,350 8,326 8,422 36,437 36,973 35,408 35,832 15,138 15,349 14,942 15,130 6,514 6,593 20,178 20,444 51,614 52,283 1,575 1,599 3,562 3,607 7,122 7,216 14,783 14,968 3,735 3,746 2,014 2,033 8,558 8,685 53,639 54,373 304,729 309,295 699,455 708,531 2019 ThisTableshowstheresultsobtainedbymultiplyinganupdatedtechnicalcoefficientmatrix(calculatedfromEquation520,p.110)withEquation532,p.124. Present value 125,886 Coalsector 67,676 Petroleumsector 27,064 Gassector 24,441 RenewableElectricity 190,393 CoalfiredElectricity 578 InternalcombustionElectricity 3,971 GasturbineElectricity 12,666 CombinedcycleElectricity 231,131 Agriculture,forestryandfishing 124,809 Mining 198,910 Food,beveragesandtobacco Textile,clothing,footwearandleather 72,931 312,106 Wood,paperandprintingproducts 310,304 Basicchemicals 131,582 Nonmetallicmineralproducts 130,647 Basicironandsteel 56,887 Basicnonferrousmetals 175,803 Fabricatedmetalproducts 449,399 Machineryandequipment 13,399 Miscellenousmanufacturing 30,958 Water,sewerageanddrainage 61,856 Construction 128,888 Roadtransport 35,608 Railwaytransport 18,069 Watertransport 73,102 Airtransport Othertransport,servicesandstorage 462,052 2,604,622 Commercialservices Total 6,075,737 44.3 21.7 254.7 18.1 27.2 23.9 21.9 8.0 184.6 6.3 10.6 7.6 Gassector Electricity Food,beveragesandtobacco 19.3 36.7 65.6 75.4 34.5 12.9 7.0 22.7 18.1 31.7 28.5 44.8 26.6 17.5 12.5 9.1 16.7 34.1 37.6 11.2 4.0 2.0 7.6 5.4 21.1 11.3 25.0 17.6 5.5 3.4 Basicchemicals Nonmetallicmineralproducts Basicironandsteel Basicnonferrousmetals Fabricatedmetalproducts Machineryandequipment Miscellenousmanufacturing Water,sewerageanddrainage Construction Roadtransport Railwaytransport Watertransport Airtransport Othertransport,servicesandstorage Commercialservices 6.3 10.3 35.1 49.6 21.6 41.8 10.4 14.1 3.9 7.7 21.6 73.1 66.6 32.3 17.7 11.4 7.4 14.4 20.2 12.2 336.9 15.6 43.1 23.5 23.2 32.0 51.9 87.4 52.9 61.7 34.3 41.6 13.1 24.2 65.3 142.3 125.1 69.3 36.7 33.7 22.9 44.7 50.6 34.2 450.9 41.0 85.1 45.1 SRP2 7.8 12.6 43.9 62.0 26.7 52.3 12.9 17.2 4.8 9.6 26.7 90.7 82.9 40.1 22.0 14.1 9.1 17.8 24.9 15.2 409.0 19.4 53.8 29.3 PPPEarly ThisTableshowstheresultsobtainedbytheapplicationofEquations514and515asdetailedinSection5.4,pp.106107. 12.3 18.0 3.9 6.0 Textile,clothing,footwearandleather Wood,paperandprintingproducts Mining Agriculture,forestryandfishing 23.9 12.1 Coalsector Petroleumsector PPP2 17.8 24.7 39.0 65.7 40.7 46.5 26.1 32.2 10.0 18.5 49.7 108.6 95.0 52.9 27.9 25.8 17.6 34.3 38.9 26.1 353.9 31.3 64.4 34.4 SRPEarly Changeinsectoralprices(percentagechangefromBCscenario) SRP1 TableF6 PPP1 Note: 10.6 17.2 60.5 85.5 36.6 72.1 17.6 23.5 6.6 13.1 36.7 124.6 113.9 55.1 30.2 19.3 12.5 24.4 34.1 20.9 556.1 26.7 74.0 40.2 PPPDelay 21.0 29.1 46.2 77.8 48.0 55.0 30.9 37.9 11.9 21.9 58.7 128.2 112.3 62.4 33.0 30.5 20.7 40.5 45.9 30.8 416.8 37.0 76.2 40.7 SRPDelay 333 334 TableF6 PPP1 SRP1 Changesininflation(Index) PPP2 SRP2 PPPEarly SRPEarly PPPDelay SRPDelay 2005 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 2006 1.006 1.016 1.013 1.031 1.016 1.023 1.000 1.000 2007 1.013 1.031 1.025 1.061 1.032 1.046 1.000 1.000 2008 1.019 1.046 1.038 1.090 1.047 1.068 1.000 1.000 2009 1.025 1.060 1.050 1.119 1.062 1.089 1.000 1.000 2010 1.031 1.075 1.062 1.147 1.077 1.110 1.000 1.000 2011 1.037 1.089 1.073 1.173 1.092 1.131 1.031 1.039 2012 1.043 1.103 1.085 1.199 1.106 1.151 1.062 1.076 2013 1.049 1.117 1.096 1.224 1.119 1.170 1.091 1.113 2014 1.055 1.130 1.107 1.248 1.132 1.189 1.120 1.148 2015 1.061 1.143 1.118 1.271 1.145 1.207 1.148 1.182 2016 1.066 1.156 1.128 1.294 1.157 1.224 1.174 1.215 2017 1.072 1.168 1.137 1.315 1.169 1.241 1.199 1.246 2018 1.077 1.180 1.147 1.336 1.180 1.258 1.223 1.276 2019 1.083 1.192 1.156 1.356 1.191 1.274 1.246 1.305 2020 1.088 1.203 1.165 1.375 1.202 1.289 1.268 1.332 Note: ThisTableshowstheresultsobtainedbycalculateweightedmeanofchangeinpricesfromall sectorsshowninpreviousTablewiththetotaloutput[thatis,(finalconsumption+(net) exports+investmentdemand+intermediatedemand)]ofeachsector. Note: 2006 108 76 7 1,831 5 35 55 48 47 31 5 21 117 56 157 160 4 6 0.2 1 38 224 19 43 159 9 44 3,307 2005 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 109 77 7 1,854 5 35 57 49 48 32 5 22 119 58 160 164 4 6 0.2 1 39 229 20 44 163 9 45 3,362 2007 TableF7 110 79 7 1,878 5 36 58 50 49 33 5 22 122 59 164 168 5 7 0.2 1 40 235 20 45 167 9 46 3,418 2008 112 80 7 1,903 5 37 59 51 50 34 5 23 125 60 167 172 5 7 0.2 1 40 240 20 46 171 9 47 3,476 2009 113 81 7 1,928 6 38 61 52 52 34 6 23 127 62 171 176 5 7 0.2 1 41 246 21 47 175 10 48 3,535 2010 114 81 7 1,947 6 38 61 53 52 35 6 23 129 62 174 178 5 7 0.2 1 42 249 21 48 178 10 49 3,576 2011 115 82 7 1,966 6 39 62 54 53 36 6 24 131 63 176 181 5 7 0.2 1 43 253 21 49 180 10 50 3,618 2012 115 83 7 1,985 6 39 63 55 54 36 6 24 133 64 179 184 5 7 0.2 1 43 257 22 49 183 10 50 3,661 2013 2014 116 83 7 2,005 6 40 64 55 55 37 6 25 135 65 181 187 5 7 0.2 1 44 261 22 50 186 10 51 3,705 Carbontaxrevenue:PPP1($million) 117 84 7 2,025 6 40 65 56 56 37 6 25 137 66 184 190 5 7 0.2 1 45 265 22 51 189 10 52 3,749 2015 118 85 7 2,045 6 41 66 57 56 38 6 25 139 67 187 193 5 8 0.2 1 45 269 23 52 192 11 53 3,795 2016 118 85 7 1,988 6 41 114 58 57 38 6 26 141 68 190 195 5 8 0.2 1 46 273 23 53 195 11 54 3,810 2017 ThisTableshowstheresultsobtainedbymultiplyingadvaloremtaxrate,tn(calculatedfromEquation511,p.105)withEquation532,p.124. Present value 900 Coalsector 644 Petroleumsector 56 Gassector RenewableElectricity 15,241 CoalfiredElectricity 45 InternalcombustionElectricity 302 GasturbineElectricity 640 CombinedcycleElectricity 422 Agriculture,forestryandfishing 417 Mining 279 Food,beveragesandtobacco Textile,clothing,footwearandleather 45 187 Wood,paperandprintingproducts 1,029 Basicchemicals 497 Nonmetallicmineralproducts 1,381 Basicironandsteel 1,419 Basicnonferrousmetals 38 Fabricatedmetalproducts 56 Machineryandequipment 2 Miscellenousmanufacturing 7 Water,sewerageanddrainage 334 Construction 1,985 Roadtransport 169 Railwaytransport 382 Watertransport 1,414 Airtransport Othertransport,servicesandstorage 78 388 Commercialservices Total 28,356 119 86 8 1,931 6 42 163 59 58 39 6 26 144 69 193 198 5 8 0.2 1 47 278 23 53 198 11 55 3,826 2018 119 87 8 1,874 6 42 213 60 59 40 6 27 146 70 195 202 5 8 0.2 1 47 282 24 54 201 11 56 3,843 2019 120 87 9 1,817 6 42 263 61 60 40 6 27 148 71 198 205 5 8 0.2 1 48 286 24 55 205 11 56 3,861 2020 335 Note: 2006 220 164 22 60 2,644 6 39 72 195 215 337 54 184 265 155 322 357 163 310 7 41 383 295 72 70 213 275 1,933 9,074 2005 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 219 165 21 62 2,645 6 40 73 198 218 340 55 186 268 156 327 362 165 314 7 42 387 300 72 71 217 277 1,956 9,149 2007 TableF7 218 165 20 65 2,647 6 40 74 200 220 344 55 188 272 159 332 367 167 317 7 42 393 305 73 72 221 279 1,981 9,229 2008 217 166 20 67 2,650 7 41 75 203 222 347 56 191 276 161 337 372 170 321 7 42 398 311 74 74 225 281 2,006 9,313 2009 216 167 19 69 2,654 7 41 76 205 225 351 56 193 279 163 342 378 172 325 7 42 404 316 74 75 230 284 2,032 9,402 2010 214 166 19 69 2,649 7 42 76 207 226 352 56 194 281 164 345 380 173 326 7 42 406 320 74 76 232 284 2,043 9,430 2011 212 166 19 69 2,648 7 42 77 208 227 354 57 195 284 165 348 384 174 328 7 43 410 323 75 76 235 286 2,059 9,477 2012 210 166 20 69 2,548 7 42 131 210 229 356 57 196 286 166 351 387 176 330 7 43 413 326 75 77 237 287 2,076 9,479 2013 2014 207 166 21 68 2,441 7 42 186 210 229 356 57 196 287 167 353 389 176 330 7 42 414 330 75 78 240 286 2,077 9,436 Carbontaxrevenue:SRP1($million) 204 165 23 66 2,337 7 42 240 211 229 356 57 197 288 168 355 391 177 331 7 42 415 333 75 79 243 285 2,079 9,399 2015 201 165 24 65 2,236 7 42 295 212 229 356 57 197 290 168 357 393 177 331 7 42 417 336 74 79 245 285 2,082 9,369 2016 199 165 26 64 2,138 7 42 349 213 229 356 57 197 292 169 360 395 178 332 7 42 418 340 74 80 248 284 2,086 9,346 2017 ThisTableshowstheresultsobtainedbymultiplyingadvaloremtaxrate,tn(calculatedfromEquation512,p.105)withEquation532,p.124. Present value 1,671 Coalsector 1,312 Petroleumsector 172 Gassector 523 RenewableElectricity 19,699 CoalfiredElectricity 53 InternalcombustionElectricity 326 GasturbineElectricity 1,275 CombinedcycleElectricity 1,630 Agriculture,forestryandfishing 1,778 Mining 2,773 Food,beveragesandtobacco Textile,clothing,footwearandleather 443 1,526 Wood,paperandprintingproducts 2,222 Basicchemicals 1,294 Nonmetallicmineralproducts 2,724 Basicironandsteel 3,005 Basicnonferrousmetals 1,365 Fabricatedmetalproducts 2,568 Machineryandequipment 57 Miscellenousmanufacturing 333 Water,sewerageanddrainage 3,204 Construction 2,533 Roadtransport 585 Railwaytransport 599 Watertransport 1,841 Airtransport Othertransport,servicesandstorage 2,236 16,089 Commercialservices Total 73,834 197 165 27 63 2,042 7 42 404 214 229 357 57 198 293 170 362 398 179 333 7 42 420 343 74 81 251 284 2,091 9,329 2018 195 165 29 62 1,948 7 42 458 215 230 358 57 198 295 171 365 400 180 334 7 42 422 347 75 82 254 284 2,098 9,317 2019 193 165 29 78 1,863 7 42 460 216 231 359 57 199 297 172 368 403 181 335 7 42 426 351 75 82 257 284 2,105 9,281 2020 336 Note: 2006 212 151 14 3,649 10 69 111 95 94 63 10 42 232 112 312 320 9 13 0.3 2 75 447 38 86 318 17 87 6,589 2005 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 212 152 13 3,665 10 70 113 97 96 64 10 43 237 115 318 326 9 13 0.4 2 77 456 39 88 325 18 89 6,656 2007 TableF7 212 152 12 3,683 10 71 115 99 98 65 11 44 242 117 325 333 9 13 0.4 2 78 466 40 90 332 18 91 6,728 2008 213 153 12 3,701 11 73 117 101 100 67 11 45 247 119 331 340 9 13 0.4 2 80 476 40 91 339 19 93 6,802 2009 214 154 12 3,721 11 74 119 103 102 68 11 46 252 122 338 347 9 14 0.4 2 82 486 41 93 346 19 95 6,879 2010 213 154 12 3,728 11 75 121 104 103 69 11 46 255 123 342 351 9 14 0.4 2 83 492 41 94 351 19 97 6,922 2011 212 153 13 3,596 11 75 208 106 104 70 11 47 258 125 346 356 10 14 0.4 2 84 499 42 96 356 20 98 6,910 2012 211 153 13 3,466 11 75 296 107 106 71 11 48 261 126 351 361 10 14 0.4 2 85 505 42 97 361 20 100 6,902 2013 2014 210 153 13 3,348 11 76 298 109 107 72 12 48 265 128 355 365 10 14 0.4 2 86 512 43 98 366 20 101 6,823 Carbontaxrevenue:PPP2($million) 209 154 13 3,231 11 76 301 110 108 73 12 49 268 130 360 370 10 15 0.4 2 88 519 43 99 371 20 103 6,746 2015 208 154 13 3,116 11 77 304 111 110 74 12 50 272 132 365 375 10 15 0.4 2 89 526 44 101 376 21 104 6,671 2016 207 155 13 3,002 12 78 306 113 111 75 12 50 276 133 370 380 10 15 0.4 2 90 533 44 102 381 21 106 6,598 2017 ThisTableshowstheresultsobtainedbymultiplyingadvaloremtaxrate,tn(calculatedfromEquation511,p.105)withEquation532,p.124. Present value 1,671 Coalsector 1,215 Petroleumsector 103 Gassector RenewableElectricity 27,375 CoalfiredElectricity 87 InternalcombustionElectricity 586 GasturbineElectricity 1,550 CombinedcycleElectricity 830 Agriculture,forestryandfishing 819 Mining 549 Food,beveragesandtobacco Textile,clothing,footwearandleather 88 368 Wood,paperandprintingproducts 2,026 Basicchemicals 979 Nonmetallicmineralproducts 2,720 Basicironandsteel 2,792 Basicnonferrousmetals 75 Fabricatedmetalproducts 110 Machineryandequipment 3 Miscellenousmanufacturing 14 Water,sewerageanddrainage 660 Construction 3,911 Roadtransport 329 Railwaytransport 750 Watertransport 2,790 Airtransport Othertransport,servicesandstorage 153 769 Commercialservices Total 53,320 206 155 13 2,888 12 78 309 115 113 76 12 51 279 135 375 385 10 15 0.4 2 92 541 45 103 387 21 107 6,527 2018 206 156 14 2,775 12 79 312 116 114 77 12 52 283 137 381 391 11 15 0.4 2 93 549 45 105 393 22 109 6,458 2019 205 157 14 2,663 12 79 315 118 116 78 12 53 287 139 386 396 11 16 0.4 2 94 556 46 106 398 22 111 6,391 2020 337 Note: 2006 428 323 40 119 5,246 13 78 143 388 428 669 108 367 526 307 641 709 324 616 14 82 760 586 142 139 424 546 3,851 18,014 2005 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 413 317 36 121 5,147 13 78 143 388 427 667 107 366 527 308 644 712 325 615 14 81 762 592 141 140 429 542 3,857 17,913 2007 TableF7 401 312 35 124 5,056 13 78 143 389 426 665 107 366 529 309 648 715 326 615 14 80 765 598 140 141 434 539 3,866 17,835 2008 390 308 34 126 4,971 13 78 143 390 426 665 106 367 532 311 652 719 327 616 14 80 768 604 140 143 439 537 3,878 17,777 2009 379 304 36 128 4,731 13 78 233 392 426 664 106 367 534 312 657 724 329 617 14 79 772 611 139 144 445 535 3,892 17,660 2010 364 299 38 123 4,450 13 77 331 389 421 655 104 363 532 310 656 720 326 610 13 78 767 613 137 144 447 526 3,852 17,359 2011 352 294 40 119 4,188 12 77 427 387 417 649 103 360 530 309 655 718 325 604 13 76 763 615 135 145 449 519 3,824 17,106 2012 340 290 43 115 3,942 12 76 522 385 413 643 102 358 529 308 655 717 324 600 13 75 760 617 133 145 452 512 3,800 16,882 2013 2014 330 286 42 141 3,723 12 76 520 384 410 637 101 356 528 308 656 716 323 597 13 74 760 620 132 145 454 506 3,782 16,632 Carbontaxrevenue:SRP2($million) 318 282 42 163 3,494 12 75 516 380 404 626 99 350 525 306 654 711 320 588 13 72 754 622 129 146 456 493 3,721 16,273 2015 308 278 41 182 3,278 12 75 513 377 397 616 97 345 522 305 652 707 318 581 13 70 749 625 127 146 459 481 3,663 15,937 2016 298 275 41 199 3,073 12 75 510 374 392 607 95 341 520 303 652 703 315 573 13 68 745 628 125 147 461 470 3,610 15,624 2017 ThisTableshowstheresultsobtainedbymultiplyingadvaloremtaxrate,tn(calculatedfromEquation512,p.105)withEquation532,p.124. Present value 2,856 Coalsector 2,358 Petroleumsector 306 Gassector 1,147 RenewableElectricity 33,715 CoalfiredElectricity 98 InternalcombustionElectricity 608 GasturbineElectricity 2,603 CombinedcycleElectricity 3,045 Agriculture,forestryandfishing 3,282 Mining 5,109 Food,beveragesandtobacco Textile,clothing,footwearandleather 812 2,834 Wood,paperandprintingproducts 4,175 Basicchemicals 2,438 Nonmetallicmineralproducts 5,158 Basicironandsteel 5,647 Basicnonferrousmetals 2,558 Fabricatedmetalproducts 4,761 Machineryandequipment 105 Miscellenousmanufacturing 601 Water,sewerageanddrainage 6,014 Construction 4,841 Roadtransport 1,067 Railwaytransport 1,139 Watertransport 3,532 Airtransport Othertransport,servicesandstorage 4,076 29,971 Commercialservices Total 134,857 289 273 40 215 2,879 12 75 508 371 386 598 94 336 518 302 651 700 314 567 12 66 741 631 123 147 464 459 3,559 15,330 2018 281 271 40 229 2,695 12 74 506 369 381 590 92 333 516 301 651 697 312 561 12 65 738 634 121 148 467 449 3,511 15,055 2019 274 269 39 242 2,519 12 74 504 367 377 583 91 329 515 300 651 695 310 555 12 63 735 638 119 149 470 439 3,466 14,797 2020 338 Note: 2006 264 188 17 4,570 13 86 139 119 118 79 13 53 291 141 391 401 11 16 0.4 2 94 560 48 108 398 22 109 8,250 2005 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 TableF7 263 188 16 4,571 13 88 141 121 120 80 13 54 297 143 398 408 11 16 0.4 2 96 571 49 110 406 22 111 8,308 2007 262 188 15 4,574 13 89 143 124 122 82 13 55 302 146 406 416 11 16 0.4 2 98 582 49 112 415 23 114 8,373 2008 261 188 15 4,579 13 90 146 126 124 83 13 56 308 149 413 424 11 17 0.5 2 100 594 50 114 423 23 116 8,441 2009 261 188 14 4,585 14 92 148 129 127 85 14 57 314 152 421 432 12 17 0.5 2 102 606 51 116 432 24 119 8,514 2010 258 187 15 4,405 14 92 255 130 128 86 14 58 317 153 426 437 12 17 0.5 2 103 613 51 117 437 24 121 8,476 2011 256 186 16 4,228 14 92 363 132 130 87 14 58 321 155 431 443 12 17 0.5 2 104 620 52 119 443 24 122 8,443 2012 253 186 16 4,069 14 93 365 133 131 88 14 59 325 157 436 448 12 18 0.5 2 106 628 52 120 449 25 124 8,325 2013 251 186 16 3,912 14 93 368 135 133 89 14 60 329 159 442 453 12 18 0.5 2 107 636 53 122 455 25 126 8,211 2014 2015 249 186 16 3,759 14 94 371 137 134 90 14 61 333 161 447 459 12 18 0.5 2 109 644 53 123 461 25 128 8,101 Carbontaxrevenue:PPPforEarlyaction($million) 247 186 16 3,608 14 94 374 138 136 91 15 62 337 163 453 465 13 18 0.5 2 110 653 54 125 467 26 130 7,996 2016 245 186 16 3,459 14 95 377 140 137 93 15 62 341 166 459 470 13 19 0.5 2 112 661 54 126 473 26 132 7,894 2017 ThisTableshowstheresultsobtainedbymultiplyingadvaloremtaxrate,tn(calculatedfromEquation511,p.105)withEquation532,p.124. Present value 2,027 Coalsector 1,483 Petroleumsector 125 Gassector RenewableElectricity 32,942 CoalfiredElectricity 107 InternalcombustionElectricity 725 GasturbineElectricity 2,036 CombinedcycleElectricity 1,034 Agriculture,forestryandfishing 1,018 Mining 683 Food,beveragesandtobacco Textile,clothing,footwearandleather 110 459 Wood,paperandprintingproducts 2,521 Basicchemicals 1,220 Nonmetallicmineralproducts 3,387 Basicironandsteel 3,474 Basicnonferrousmetals 94 Fabricatedmetalproducts 137 Machineryandequipment 4 Miscellenousmanufacturing 17 Water,sewerageanddrainage 822 Construction 4,871 Roadtransport 408 Railwaytransport 933 Watertransport 3,476 Airtransport Othertransport,servicesandstorage 191 960 Commercialservices Total 65,263 244 186 16 3,312 14 96 380 142 139 94 15 63 346 168 465 476 13 19 0.5 2 114 670 55 128 480 26 134 7,796 2018 242 187 16 3,167 14 96 383 143 141 95 15 64 350 170 471 482 13 19 0.5
