The In ationary Impacts of Fossil Fuel Price Reform in Vietnam

THE INFLATIONARY IMPACTS OF FOSSIL FUEL
AND ELECTRICITY PRICE REFORM IN VIET NAM
Center for Analysis and Forecasting
Draft paper
December 2013
Phase II: Developing a Roadmap for Fossil Fuel Fiscal Policy Reform
Please note: This report is a draft only and has not been edited. Please send any
comments to: koos.neefjes@undp.org and michaela.prokop@undp.org.
The opinions, analyses and recommendations contained in this document do not
necessarily reflect the opinions of the United Nations Development Programme in
Vietnam. The Report is an independent publication commissioned by UNDP.
THE INFLATIONARY IMPACTS OF FOSSIL FUEL
AND ELECTRICITY PRICE REFORM IN VIET NAM
– A Static Analysis1
December 2013
1
This study is conducted by La Hai Anh (haianhla2011@gmail.com), Nguyen Thang, and Nguyen Thi Thu
Phuong (Center for Analysis and Forecasting under the Vietnam Academy of Social Sciences) under Phase 2 of
the UNDP Project on “Developing A Roadmap for Fossil Fuel Fiscal Policy Reform”. Valuable comments are
provided by research components, especially Michaela Prokop, Koos Neefjes and Pham Thi Lien Phuong from
UNDP, Peter Wooders, Andrea Bassi and Nguyen Tu Chi from IISD-GSI. We also would like to thank peer
reviewers and experts - Le Thi Thuy Van, Nguyen Duc Thanh, Vo Tri Thanh, Vu Thanh Tu Anh, Pham Thi Lan
Huong and Pham Chi Lan - for their useful comments. We are grateful to Bui Trinh for his data support.
2
TABLE OF CONTENT
TABLE OF CONTENT ........................................................................................................... i
LIST OF TABLES.................................................................................................................. iii
LIST OF FIGURES .............................................................................................................. iv
ABBREVIATIONS ................................................................................................................. v
SUMMARY .......................................................................................................................... vi
I. CONTEXT .......................................................................................................................... 1
II. ENERGY SECTOR IN BRIEF – DEMAND, SUPPLY AND PRICING ................................ 2
1. Energy Demand and Supply.......................................................................................... 2
2. Energy pricing and consumption subsidy ...................................................................... 6
III. LITERATURE REVIEWS ............................................................................................... 13
IV. METHODOLOGY .......................................................................................................... 18
4.1. The price impact on other sectors – An IO model application ................................... 18
4.2. The inflationary impact ............................................................................................. 23
4.3 Building Scenarios..................................................................................................... 25
V. DATA SOURCES ........................................................................................................... 30
5.1. The 2007 Input-Output Table ................................................................................... 30
5.2. The 2010 Viet Nam Household Living Standard Survey ........................................... 32
VI. ENERGY-INTENSIVE SECTORS AND CONSUMPTION PATTERNS .......................... 33
6.1. Energy-intensive sectors .......................................................................................... 33
6.3. Expenditure patterns ................................................................................................ 38
VII. INFLATIONARY IMPACT ............................................................................................. 57
7.1. The fossil fuel price impact on other industries – The PPI......................................... 57
7.2. Inflationary Impact .................................................................................................... 60
7.3. The inflation structure ............................................................................................... 64
7.4. Possible mitigation measures ................................................................................... 67
7.5. Limitation of Results ................................................................................................. 75
VIII. CONCLUSION ............................................................................................................. 77
APPENDIX A ...................................................................................................................... 84
APPENDIX B ...................................................................................................................... 87
i
APPENDIC C ...................................................................................................................... 92
APPENDIX D ...................................................................................................................... 93
ii
LIST OF TABLES
Table 1 - Oil supply and consumption in Viet Nam, 2011
3
Table 2 – Electricity supply and consumption in Viet Nam, 2011
4
Table 3 – Fossil fuel consumption subsidies of Viet Nam during 2007-2011
6
Table 4 - Price composition for one litre of refined petroleum products
7
Table 5 - IBTs for Vietnam’s Power Sector from 1999 to Present
9
Table 6 – A comparison on the inflationary impact of 20 percent increases in electricity and
petroleum prices
18
Table 7 – Summary table: Quantitative approaches to impact assessment
20
Table 8 - Average retail prices of electricity
25
Table 9 - Percent changes in petroleum prices
29
Table 10 – IO Link with CPC and ISIC codes
31
Table 11 – Alternative IBTs scenarios (Unit: VND/kWh)
54
Table 12 – Increase in coverage and cross-subsidy amount among alternative IBT scenarios
55
Table 13 – The inflationary impact – Robustness check
62
Table 14 – Expenditure shares on the most consumed food
71
Table 15 – The magnitude of inflationary mitigation resulting from a potential VAT exemption
71
Table 16 - Indicators for Assessing Existing Mitigation Mechanisms
74
Table 17 - Indicators for Assessing Existing Mitigation Mechanisms (cont.)
74
iii
LIST OF FIGURES
Figure 1 – Petroleum price comparison among different countries during 1998-2012
8
Figure 2 – Fuel used in production, transmission and distribution of electricity
28
Figure 3 – The history of petroleum prices
29
Figure 4 – Industries intensive in electricity and petroleum products
34
Figure 5 – Share of energy consumption
35
Figure 6 – Energy-intensive sectors among household businesses
36
Figure 7 – Business income as percent of total household income
38
Figure 8 – Expenditure patterns by urban/rural areas
39
Figure 9 – Expenditure share for energy in rural/urban
42
Figure 10 – Fossil fuel use by urban/rural households
43
Figure 11 – Energy Ladder
44
Figure 12 – Per capita income/expenditure by decile and urban/rural areas
44
Figure 13 – Durable ownership by expenditure deciles
45
Figure 14 – Household expenditure on energy in urban/rural areas
47
Figure 15 – Benefit shares from lifeline tariff in rural/urban areas in 2013
48
Figure 16 – Cross subsidy among different household groups
49
Figure 17 – Changes in unit cost and EVN’s profit/loss
50
Figure 18 – Distribution of electricity consumption by urban/rural deciles
51
Figure 19 – Percentage changes in HH electricity expenditure among alternative IBT
scenarios
56
Figure 20 – Energy price impact on other industry prices
58
Figure 21 - Iterations of the electricity price impact on other industries
59
Figure 22 - Inflation vs. refined petroleum product prices
60
Figure 23 - Iterations of the energy price impact on the inflation rate
60
Figure 24 – Inflationary impact of energy price on rural/urban households
61
Figure 25 – Indirect impact as percent of total impact in rural areas
63
Figure 26 - Inflation and expenditure categories in Urban Viet Nam
64
Figure 27 - Inflation and expenditure categories in Rural Viet Nam
66
Figure 28 - Inflation and household deciles in Viet Nam
67
Figure 29 – Crude Oil Index and Food & Foodstuff Index
69
Figure 30 – Share of rice subsidy in rural/urban areas
72
iv
ABBREVIATIONS
ADB
Asian Development Bank
CGE
Computable General Equilibrium
CIEM
Central Institute for Economic Management
CPI
Consumer Price Index
EVN
Viet Nam Electricity Company
FPSF
Fuel Price Stabilization Fund
GDP
Gross Domestic Product
GSI
Global Subsidies Initiative
HB
Household Business
IBT
Incremental Block Tariff
IEA
International Energy Agency
IISD
International Institute for Sustainable Development
IMF
International Monetary Fund
IO
Input-Output
kWh
Kilowatt hours
LDU
Local Distribution Utilities
LEAP
The Long-range Energy Alternatives Planning System
LPG
Liquefied Petroleum Gas
LRMC
Long Run Marginal Cost
MOIT
Ministry of Industry and Trade
MOLISA
Ministry of Labour - Invalids and Social Affairs
MTOE
Million Tons of Oil Equivalent
OPEC
Organization of the Petroleum Exporting Countries
PDP
Power Development Plans
PM
Prime Minister
SAM
Social Accounting Matrix
TWh
Terawatt hours
UNDP
United Nations Development Programme
USD
United States Dollar
VHLSS
Viet Nam Household Living Standard Survey
VND
Vietnamese Dong
VOV
Radio The Voice of Vietnam
v
SUMMARY
Our analysis based on detailed Vietnamese data sets shows that the magnitude of the fossil-fuel price
impact can be substantial in Viet Nam, with a 20 percent increase in both petroleum and electricity
prices raising Consumer Price Index by maximum 4.0 percent. Higher inflation rate is found in urban
areas compared to rural ones (4.3 percent vs. 3.8 percent). More than half of this comes from the
indirect effect of fossil-fuel price changes on prices of other goods and services consumed by
households, especially in rural areas and in case electricity prices rise. We employ a static inputoutput model to estimate inflation. Although the poorer face a smaller impact in absolute term than the
richer do, they are more affected indirectly in both absolute and relative terms because of their higher
price pass-through from fuel and electricity particularly to food and foodstuff. Particularly, about threequarters of the inflationary impact faced by the rural poorest 10 percent come indirectly. This analysis
was also conducted to determine which households would be most affected by higher energy tariffs
and to what extent mitigation measures, such as lifeline tariffs or direct cash transfers, might lessen
the impact for poor and vulnerable households.
vi
I. CONTEXT
Viet Nam has achieved high economic growth rates for over two decades. The economic
growth in Viet Nam in the last decade is arguably characterized as investment-led, heavily
relying on extensive mobilization of resources. In particular, rising intensity of energy usage
has been a key feature of Viet Nam’s recent growth. However, it has become increasingly
clear that such a resource-based model cannot help Viet Nam sustain its past impressive
development records. Indeed, in recent years, economic growth slows down, with the
average annual growth rate declining from 7.5 percent in the 2001-2005 period to 7.02
percent during the 2006-2010 period and well below 6 percent in the first half of the 20112015 period. The average rate of inflation rose from 5.04 percent during the 2001-2005
period to 11.5 percent during the 2006-2010, and increased further to 18.1 percent in 2011
before declining to 6.81 percent in 2012. As a consequence, the country has recently
changed the course, embarking on a long-term and large-scale structural reform program,
which consists of (i) a stabilization package, widely known as Resolution 11 effective as of
February 2011, to keep down inflation and macro imbalances to manageable levels by
implementing more prudent demand management, notably in the form of tighter monetary
and fiscal policies; and (ii) a restructuring program, officially announced in October 2011,
with a view to rooting out inherent structural weaknesses on the supply side, with a special
focus on raising efficiency of public investment, state-owned-enterprises and the banking
system. These reforms aim to bring the economy back on a path of stable, sustainable and
rapid growth, through a shift from the current resource-based growth model to one that will
be largely based on efficiency.
Earlier, Viet Nam embarked a long run reform agenda for the energy sector, with the aim of
restructuring the sector to improve internal operations, efficiency, and the quality of services.
The launch of this program was part of the Government’s efforts to complete the transition
towards a market economy, which effectively means the removal of or substantial reduction
in subsidies that still prevail in a few markets, including the energy one. To this effect, an
energy subsidy phase-out plan was initiated in the late 2000’s, with the introduction of new
incremental block tariff (IBT) structure for residential consumers under the Government’s
Decision 21 in March 2009, which narrowed the band of consumption under a preferential
rate (known as the “lifeline tariff”) from 100 KWh to 50 kWh per month and increased the
1
retail price of electricity to all users. Despite growth slowdown and macroeconomic
instability, causing huge challenges to businesses and households, the Government of Viet
Nam shows its determination to consistently implement the energy price reforms by making
the energy subsidy phase out part of the above mentioned stabilization package.
However, the current context of Viet Nam requires that the energy price reform should be
implemented carefully. Although long-term gains of the reform efforts in the form of improved
economic efficiency and environmental sustainability are without doubt, short-term pains in
the form of higher inflation should not be overlooked, as cost-push inflation driven by rising
energy prices does not only raise already high inflationary expectations, but also results in
rising production costs on the supply side and increasing costs of consumption baskets with
perceived negative impacts on livelihoods and the living of many poor and low income
people.
In short, the inflationary impact of energy price reform on the economy in general, and
various population groups in particular, has become a key concern, and mitigating this
impact to minimize short-term pain is key to achieving long-term gain. This is also the main
question that this paper attempts to address. This question be further elaborated into subquestions, including (i) to what extent do energy price increases affect prices of other goods
and services? (ii) how do the expenditure patterns change across different household
groups and influence prices of their consumption baskets (i.e. individual household-specific
CPI), and (iii) what are possible mitigation measures, their advantages and disadvantages?
To answer the above questions, the study first makes an overview of the energy sector
presented in Section II, followed by a review of the literature in Section III. Sections IV and V
present the methodology and data used in this research, respectively. Section VI describes
energy-intensive industries and consumption patterns across different household groups.
Results and possible mitigation measures are shown in Section VII and the conclusion
follows in Section VIII.
II. ENERGY SECTOR IN BRIEF – DEMAND, SUPPLY AND PRICING
1. Energy Demand and Supply
2
Recently, Vietnamese people increased their primary energy consumption2 at an average
rate of 7.15 percent per annum, from 28.74 million tons of oil equivalent (MTOE) in 2000 to
61.21 MTOE in 2011 according to IEA statistics 3 . Out of the latter figure, fossil fuels
accounted for 71.77 percent of total energy consumption, of which 33.50 percent was from
crude oil and oil products, 25.38 percent from coal and peat, and 12.16 percent from natural
gas (IEA).
The demand for crude oil and refined petroleum products keeps rising while Viet Nam’s
domestic supply is limited. Over the past two decades, this country has been an important oil
and natural gas producer in the Southeast Asian region. Viet Nam has boosted exploration
activities, allowed for more foreign investment and cooperation in the oil and gas sectors,
and introduced market reforms to support the energy industry. However, since 2004 after
several years of steady increases, Viet Nam's oil production has slowly declined and
become a net oil importer (by volume) since 2010 when consumption surpassed supply,
according to IEA statistics.
Table 1 gives more details on fossil fuel supply and consumption by volume in Viet Nam. In
2011, crude oil was mainly exported (57.3 percent of total production and stock changes).
36.1 percent of total supply, a significant increase from 9.3 percent in 2009, was used to
produce refined petroleum products thanks to the operation of Viet Nam’s first refinery Dung
Quat since July 2009. Specifically, the percentage of domestically produced motor gasoline
increased significantly from 16.7 percent in 2009 to 51.8 percent in 2011. Meanwhile, 36.2
percent of the liquefied petroleum gas (LPG) and diesel demand was supplied domestically
in 2011 while 55.7 percent was imported. However, kerosene and fuel oil were almost
completely imported (99.9 percent of domestic demand and international marine/aviation
bankers) in 2011. Along with Nghi Son refinery started its construction in 2011 and another
refinery planned to build in Long Son, it is forecasted that until 2025 the domestic supply of
petroleum products could serve two thirds of the expected domestic demand (UNDP, 2012).
Table 1 - Oil supply and consumption in Viet Nam, 2011
2
Primary energy consists of coal and peat, crude oil, imported oil products, natural gas, hydropower, imported
electricity, biofuels and waste.
3
http://www.iea.org/statistics/
3
In thousand tons of oil Crude LPG Motor
Jet
Other
Gas/ Fuel Oil Coal Natural Electri Biofuels Hydro
equivalent (ktoe)
Oil
Gasoline Kerosene Kerosene Diesel
&Peat Gas -city &Waste
Production
16956 382 2557
46
2874 162 24916 8079 8529 14706 2565
Imports
770 2160
988
28
5288 1951 644
536
Exports
10086
270
59
23
1044 227 10023
92
Domestic Supply*
7694 1152 4941
195
77
7850 1919 15537 8079 8973 14706 2565
- Transformation
6352
273
895
+ Electricity Plants
273
5140 7627
2565
+ Oil Refineries
6240
Final Consumption**
517 1415 4942
195
78
7579 921 10397 451 7819 13811
- Industry
212
12
1241 798 8716 451 4140 2581
- Transport
4807
195
5617
88
- Residential
798
53
43
5
1275
2868 11228
- Commercial & Public Ser.
405
13
280
22
385
726
- Agriculture/Forestry
135
398
8
21
86
Notes:
* Covering international marine/aviation bunkers and stock changes
** Covering energy industry own use and non-energy use
Source: IEA Energy Statistics (http://data.iea.org)
Fossil fuels have been increasingly important for power generation in Viet Nam (see Table
2). While hydropower explained 28.58 percent of the domestic electricity supply in 2011,
41.74 percent and 20.05 percent were generated by gas turbine and coal fired thermal
plants, respectively. In addition, 4.6 percent of power came from oil products. However, the
electricity loss rate was still high with 9.64 percent of the total domestic supply. The VIth and
VIIth Power Development Plans (PDPs for 2005-2025 and 2010-2030 periods, respectively)
envisage rapidly increasing electric power demand. This demand is estimated to grow at an
average annual rate of between 9.9 - 11.2 percent for the 2005-2025 period. Electricity
generation might increase from 97.4 TWh in 2009 to 227-305 TWh in 2020, and to 695-834
TWh in 2030, of which 54.6 percent could be covered by coal-fired thermal plants and
therefore 25 percent is expected to rely on about 80 million tons of imported coal per year,
which reflects the more dependence of electricity tariff on the international base (UNDP,
2012).
Table 2 – Electricity supply and consumption in Viet Nam, 2011
GWh
Percent
- Coal and peat
20920
20.05
- Oil
4749
4.55
- Gas
43548
41.74
4
- Hydro
29820
28.58
- Imports
6231
5.97
- Export
-1073
-1.03
Domestic Supply*
104337
100
Losses
10060
9.64
Final Consumption**
90922
100
Note:
* Cover power generated by biofuels and wind
** Cover energy industry own use
Source: IEA Energy Statistics (http://data.iea.org)
Looking back to Table 1, fossil fuel plays the most important role (71.3 percent of total fuel
demand) while 28.7 percent comes from non-fossil fuel (biofuels and waste). Fuel is most
widely used in industries (37.7 percent of total fuel demand), followed by households (33.8
percent), and transport sector 4 (22.2 percent). However, while households consume
substantially non-fossil fuel (69 percent of total fuel demand in the residential sector) and
industry sector utilizes 14.2 percent of their need on non-fossil fuel, 100 percent of the fuel
demand in the transport sector comes from fossil fuel. Out of total fossil fuel consumption,
44.1 percent is from refined petroleum production, 30.3 percent from coal and peat, and 22.8
percent from electricity. The transportation sector uses 70.8 percent of refined petroleum
products while more than 80 percent of coal and peat and 52.3 percent of electricity are
utilized in the industry sector. This sector consumes 15 percent of oil products. Meanwhile,
households rank the second with their consumption of 12.3 percent of coal and 36.7 percent
of electricity.
In terms of refined petroleum products (see Table 1), diesel was the most consumed fuel
(48.5 percent), followed by gasoline (31.6 percent), LPG (9.0 percent), fuel oil (5.9 percent)
and kerosene (1.7 percent). Among final consumers, 97.3 percent of gasoline and above 70
percent of diesel and kerosene were consumed in the transport sector while a majority of
fuel oil (86.6 percent) was used in industries. Meanwhile, LPG is mostly utilized in residential
sector (56.4 percent), followed by commercial and public services (28.6 percent) and
industry sector (15.0 percent).
4
Note that the transport sector covers the usage of motorbikes/cars by households.
5
2. Energy pricing and consumption subsidy
Since Viet Nam is greatly dependent on imported refined products, the domestic petroleum
prices fluctuate with the international prices. According to Decree 84/2009/ND-CP, the
energy reform allows Vietnamese retailers to increase domestic petroleum prices by 7
percent when international prices upsurge by the same rate within a 30-day period. Beyond
this percentage, the government attempts to lower the rising price level through a number of
mitigation measures such as import tariff reduction 5 and/or the usage of Fuel Price
Stabilization Fund (FPSF)6, which comes from a surcharge on petroleum products paid by
consumers at different points of time. Although the government’s purpose is to sustain a
growing economy, keep down the inflationary impact, and protect consumers, these
measures sometimes deplete the FPSF, forcing the government to roll back fuel subsidies
and apply market-based pricing in order to alleviate state budget constraints. For instance,
when international oil prices escalated in 2010, the FPSF was used and tariffs on refined
petroleum products were cut several times. However, this resulted in a substantial amount of
petroleum subsidies in 2011 (1.02 billion USD, equivalent to 25 percent of the total energy
subsidies in Viet Nam, compared to 0 percent in two previous years – see Table 3)7 although
fuel prices finally increased by 34 percent in 2011, and an additional 12 percent by March
20128.
Table 3 – Fossil fuel consumption subsidies of Viet Nam during 2007-2011
2007
2008
2009
2010
2011
Total fossil fuel consumption subsidy (billion $), of which:
2.10
3.56
2.15
2.93
4.12
- Oil
0.32
1.09
0
0
1.02
- Natural gas
0.09
0.21
0.13
0.23
0.16
- Coal
0.01
0.01
0.01
0.01
0.02
5
When international fuel prices increase by more than 12 percent.
6
In case that international fuel prices increase by an amount between 7 and 12 percent, retailers are allowed to
raise the domestic fuel prices by 60 percent of this amount while the remaining is subsidized from FPSF.
7
IEA data
8
Note that this is denominated in VND. In terms of USD, the corresponding rates are 20.5 percent in 2011 and a
further 8.6 percent in March 2012.
6
- Electricity
1.68
2.25
2.1
2.69
2.92
- % of GDP
2.95
3.94
1.24
2.83
3.4
- % of state budget expenditure(*)
8.7
11.9
3.5
8.6
9.1
Total fossil fuel consumption subsidy as:
Source: CIEM (2013) – Phase 2 of the UNDP Project on “Developing A Roadmap for Fossil Fuel Fiscal Policy
Reform”.
Table 4 shows the composition of basic price on 6th November 2013 for one litre of different
kinds of refined petroleum products. The CIF price accounts for 62.2 percent of the basic
price for gasoline and 73 percent for other kinds of petroleum products, which reflect the
heavy dependence of domestic prices of petroleum products on international prices.
Table 4 - Price composition for one litre of refined petroleum products
as of 06/11/2013
No.
Cost items
Unit
Refined petroleum products
Gasoline 92 DO 0.05S
Kerosene
FO 3.5S
*
World price on 06/11/2013
USD/barrel, tons
108.39
121.80
120.87
605.47
1
30-day average world price (FOB)
USD/barrel, tons
111.41
123.92
123.12
615.43
USD/barrel, tons
2.50
2.50
3.00
30.00
2
3
Insurance and Transportation cost from
overseas port to domestic port
30-day average exchange rate
VND/USD
21,125
Inter-bank exchange rate
VND/USD
21,036
CIF Price (4=1+2)
4
CIF Price (to calculate basic price)
CIF Price (to calculate import and
excise taxes)
USD/barrel, tons
113.91
126.42
126.12
645.43
VND/litre, kg
14,902
16,613
16,530
13,635
VND/litre, kg
14,839
16,542
16,460
13,577
Rate (%)
18%
14%
16%
15%
VND/litre, kg
2,671
2,316
2,634
2,037
Rate (%)
10%
VND/litre, kg
1,751
5
Import tax
6
Excise tax
7
Cost norm
VND/litre, kg
860
860
860
500
8
Profit norm
VND/litre, kg
300
100
100
300
9
Price stabilization fund contribution
VND/litre, kg
300
300
300
300
10 Environment tax
VND/litre, kg
1.000
500
300
300
11 Value added tax
VND/litre, kg
2,178
2,069
2,072
1,707
12 Basic price (12=4+5+6+7+8+9+10+11)
VND/litre, kg
23,962
22,757
22,795
18,779
13 Current retail price
VND/litre, kg
23,880
22,310
22,020
18,510
%
-0.34%
-1.97%
-3.40%
-1.43%
14 Gap between current retail price and
7
basic price
VND/litre, kg
-82
-447
-775
-269
Source: http://hiephoixangdau.org/gia-co-so/gia-co-so-hang-ngay/newest-content/default.aspx.
Note: * Prices of petroleum products in the Singapore market.
Figure 1 – Petroleum price comparison among different countries during 1998-2012
Source: World Bank database
All types of taxes and contribution fee to price stabilization fund (300 VND per litre) explain
33 percent of the basic price for gasoline and 23 percent for the others. Cost norms are 500
VND/litre for fuel oil 3.5S and 860 VND/litre for the others while profit norms range from 100
to 300 VND/litre. However, the domestic prices of refined petroleum products in Viet Nam
are still cheaper than those of a majority of countries in the region, except Indonesia,
Malaysia and Myanmar (e.g, gasoline and diesel prices shown in Figure 1).
The price stabilization fund for petroleum products was established in 2009 and has been
used and kept by petroleum traders to offset loses because of fluctuations in market prices.
The increasing concern is transparency toward this fund. Therefore, since July 2013, the
Ministry of Finance start publishing its first and second editions of quarterly statistics related
to the management and use of the fuel price stabilisation fund on its website.
In terms of electricity, since 2006 the Vietnamese government approved a roadmap for
phasing out the current system of state monopoly and subsidies on electricity and
8
establishing a competitive power market. The first phase, started in July 20129, comprises
the establishment of a competitive power generation market, where a single buyer
purchases electricity from the generators and sell it to distribution companies and large
consumers at regulated prices. The next phase, scheduled to start in 2017, will entail a
wholesale competitive market where sellers (power plants) and buyers (distributors and
large consumers) will competitively transact in a power pool. The final stage, planned to
begin in 2024, will be a competitive retail market, where retail consumers are allowed to
choose their suppliers. Currently, Vietnam Electricity Company (EVN) dominates the power
sector with a majority in generation capacity (over 60 percent in 2010) and has a monopoly
in electricity transmission and distribution. By end-2012, EVN had over 19.8 million
customers, a rise by 1.08 million from 2011.
Table 5 - IBTs for Vietnam’s Power Sector from 1999 to Present
10/1999 –
11/2002 –
2/2005 –
2/2007 –
3/2009 –
10/2002
1/2005
1/2007
3/2009
2/2010
PM Decision PM Decision PM Decision PM Decision PM Decision
Unit: 193/1999/QĐ- 124/2002/QĐ- 215/2004/ 276/2006/QĐ- 21/2009/QĐTTg dated QĐ-TTg dated TTg dated TTg dated
VND/kWh TTg dated
22/09/1999 20/09/2002 29/12/2004 04/12/2006 12/02/2009
<300 >300
kWh/m kWh/m
0-50
600
500
550
550 1100
550
51-100
845
101-150
704
900
900 1100
1110
1135
151-200
957
1210
1210 1100
1470
1495
201-300
1166
1340
1340 1340
1600
1620
301-400
1400
1720
1740
>400
1397
1400
1400 1500
1780
1790
3/2010 –
2/2011
Gov't Office
Document
50/2010/TBVPCP dated
12/02/2010
600
1004
1214
1594
1722
1844
1890
3/2011 –
7/2012 –
12/2012- 8/2013 to
6/2012
12/2012
7/2013
date
PM Decision PM Decision Circular No. Circular No.
24/2011/QĐ- 268/2011/QĐ- 38/2012/TT- 19/2012/TTTTg dated TTg dated BCT dated BCT dated
15/04/2011 23/02/2011 20/12/2012 31/7/2013
1242*
1284*
1350*
1418*
1369
1734
1877
2008
2060
1457
1843
1997
2137
2192
1545
1947
2105
2249
2307
1622
2044
2210
2361
2420
Note: * Poor and low Income households using less than 50kWh have paid only 993 VND/kWh
Source: Prime Minister Decisions and Circulars
The incremental block tariffs10 (IBTs) for electricity has been applied in Viet Nam for a long
time (as shown in Table 5). Before 2009, the lowest 100 kWh block was designated as Viet
9
Tuan Hoang, “Vận hành thị trường bán lẻ điện cạnh tranh từ năm 2020”, http://icon.com.vn/vn-s83-110452-
634/Van-hanh-thi-truong-ban-le-dien-canh-tranh-tu-nam-2020.aspx, 8th Nov 2012.
10
The incremental block tariffs (IBTs) are often used by electricity retailers to provide cross subsidies to users
who consume less than a subsistence threshold considered adequate for meeting basic needs; hence the use of
the term “lifeline” rate. Lifeline subsidies entail low administrative costs, and they often enjoy widespread political
support. One of the major drawbacks of lifeline tariffs is that they may not be well-targeted – a household’s level
of electricity consumption may not be a good indicator of poverty – and leakages to the non-poor are often high.
In lieu of lifelines, many countries compensate poorer households for high electricity tariffs through income
transfers and related social protection measures.
9
Nam’s lifeline band and priced at less than half of the economic cost of electricity supply in
2005, leading to a substantial leakage to the non-poor. Despite inflation and rising costs, the
lifeline tariff was kept constant in nominal terms until the adjustments approved by the Prime
Minister in February 2009 (Decision 21). From March 2009 to February 2011, the first block
was narrowed down from 100 kWh to 50 kWh to all users and set the new lifeline tariff at
around 40 percent of the economic cost of supply. However, although the new lifeline tariff
increased in nominal terms, this inflation-adjusted tariff was still lower than those set in 2002.
The next block (51-100 kWh) was priced at the economic cost without profits. Profits were
covered by residential tariffs in higher blocks as well as cross subsidies from other tariff
categories, mainly industrial and commercial users. Since March 2011, only poor and lowincome households whose monthly consumption was fewer than 50 kWh for three
consecutive months are beneficiaries from the lifeline tariff.
With the aim of ensuring fair treatment of all households in Viet Nam, the PM’s Decision 21
also put all residential consumers under a single, unified tariff structure, regardless of
whether they were supplied by local distribuition utilities (LDUs) or EVN. The new tariffs went
into effect in March 2009 for all EVN customers. The LDUs were grandfathered under the
old tariff structure through September 2009, with the aim of giving them time to transition to
the new cost structure (Valerie Kozel and Nguyen Viet Cuong, 2010).11 Although the tariffs in
IBTs continue raising since 2009, the cross-subsidy mechanism are kept unchanged,
contributing to large subsidies on electricity consumption in Viet Nam, which reached the
peak of 2.92 billion USD in 2011 (see Table 3). Besides that, as an excuse of EVN for lifeline
tariff increases from 600 to 993 VND/kWh, a cash transfer of 30,000 VND per month has
been sent to poor households since March 2011 (according to Decision No. 268/QD-TTg),
resulting in total direct subsidy of 930 billion VND in 2011. This budget shrinks in 2012
11
More than 5,600 LDUs were operating in rural communes as of June, 2008. Many LDUs were very small,
operated on a narrow profit margin and struggled with issues of capacity, quality of supply, and safety. The
government required LDUs to operate according to a new set of performance criteria in the future, including
obtaining an electricity distribution and retail supply license, developing a reliable and transparent system of
accounts, entering into a supply contract with each customer, issuing monthly bills and ensuring all customers
have a certified power meter. They had to adhere to the unified tariff. However, many of them were not able to
meet the standards and operate profitably under the unified IBT system. The Decision 21 allowed the takeover of
financially weak LDUs by the PCs, resulting in a strong reduction in distribution utilities by LDUs from 56 percent
before 2009 to 20 percent after 2009.
10
thanks to a fall in the MOLISA list of poor households12 from approximate 2.6 million in 2011
to 2.15 million in 201213. At the beginning, EVN committed to support poor households.
Later, however, due to its losses, this social task was shifted to MOLISA.
As also seen in Table 5, although electricity tariffs were adjusted every year, the price
increases have not been much in real terms due to the devaluation VND. The price was 4.48
US cents/kWh in 1999, increased to 5.1 US cents/kWh in 2005, and nearly 6.00 US
cents/kWh in 2011. This price level was lower than the 7.00 US cents/kWh, which was
committed by EVN in 2001 to international financial organizations14. Before 2012, the prices
that customers paid could not cover actual electricity production costs. However, in 2012,
with the price reaching 6.9 US cent/kWh, EVN claimed it made a profit15 (with approximately
2,500 billion VND16 after off-setting a part of the accumulated loss from previous years). The
price continues rising and touches 7.15 US cent/kWh since 1st August 2013. 17 This
increment aims to achieve the profit targets and pay back gradually the accumulated loss of
the exchange rate differences of 15,000 billion VND and another 8,000 billion VND debt due
to high-cost electricity purchases since 2011.18
12 Note
that the beneficiaries consist of poor households with monthly income per capita below 400,000 VND in
rural areas and 500,000 VND in urban areas, according to the definition of the Ministry of Labour - Invalids and
Social Affairs (MOLISA).
13 Decision
14
No. 749/QD-LDTBXH dated 13rd May 2013 by MOLISA
According to ADB (2003), "EVN was in default of ADB covenants requiring retail tariffs to be at 7 cents per
kWh by March 2001... At the end of fiscal year 2000, the average tariff was only at 728.0 VND or 5.1 US cents,
which was also inadequate to achieve the World Bank’s self-financing ratio covenant". And then "ADB and the
World Bank agreed with the government on a staggered tariff increase to reach the level of 7.0 cents by July
2005".
15
According to EVN, the 2012 profit resulted from favorable weather and rising electricity prices twice during this
year. Source: Hữu Tùng, “Đằng sau câu chuyện ‘lãi - lỗ’ của EVN”, http://petrotimes.net/ news/vn/kinh-te/dangsau-cau-chuyen-lai-lo-cua-evn.html, 27th Feb 2013.
16
However, the 2012 profit calculated by EVN did not cover EVN’s debt to PVN as well as its future investment,
leading to no reflection of the long-run marginal cost of power generation.
17 The
applied exchange rate is 21,115 VND/USD.
18 Việt
Hà/VOV (2013), “EVN xử lý 8.000 tỷ đồng lỗ do phát điện giá cao”, http://vov.vn/Kinh-te/EVN-xu-ly-8000-
ty-dong-lo-do-phat-dien-gia-cao/280607.vov, 14th Sept 2013.
11
The average power price in Viet Nam is currently still lower than that of most countries in the
region (e.g., the price in Thailand was 10.6 US cents/kWh in 2011) and it is therefore not
attractive for local and foreign enterprises to invest in new generating capacity in Viet Nam19.
Nevertheless, it is difficult to get the public’s support for any increase in electricity prices by
EVN due to its mismanagement and lack of transparency. There are a number of issues that
involve EVN’s mismanagement on non-core investments and over-budget salary payment.
For example, since 2006, EVN has branched out an investment of 121,000 billion VND into
non-score sectors, including telecommunication, securities, banking, finance and real estate
and this investment only brought losses, with the total estimated at VND 2,190 billion (USD
103.3 million), which is eventually paid for by the government, hence taxpayers. It is
noteworthy that this huge investment is equivalent to 28.5 percent of total investment capital
demanded to develop 42 power projects. Lack of capital led to 20 out of these projects under
slow progress, causing electricity shortage of 84 billion kWh, equivalent to 80-90 percent of
annual power consumption.20 As reported by the Ministry of Industry and Trade, currently
126 communes in Viet Nam with approximately 580,000 rural households mainly in
mountainous areas and on islands, are still without access to electricity. Kerosene and
candles are normally used for light in these communes.
It is also hard for consumers and economists to trust EVN due to the lack of transparency in
its price calculations and business performance. According to government inspectors,
besides suffering losses due to non-core investments, many unjustified expenses has been
accounted when calculating costs. For example, nearly 600 billion VND (28.4 million USD)
for building houses, villas, tennis courts, swimming pools, and other facilities for EVN’s staff
is accounted as “administrative buildings”. Public also claims on EVN’s unreasonable salary
payment. Notably, there is a big gap between actual wage and wage norm: over 45 percent
higher in actual wage in 2009 and 51.5 percent in 2010. Additionally, by selling electricity
under prices lower than the average to steel and cement producers for which FDI accounts
for a large proportion, loss compensation covered by EVN for FDI enteprises become
considerable (more than VND 2,100 billion, equivalent to USD 0.1 billion in 2011).
19
Mai Hoa, “Năm mới vừa ‘tới cửa’, điện lại ‘đe’ tăng giá”, http://www.phapluatvn.vn/xa-hoi/doi-song/201302/
Chua-chao-nam-moi-dien-da-lai-de-tang-gia-2075068/, 7th Feb 2013.
20
Pham Huyen (2013), “Thói quen chậm tiến độ, kêu lỗ đòi tăng giá điện”, http://vietnamnet.vn/vn/kinh-
te/143888/thoi-quen-cham-tien-do--keu-lo-doi-tang-gia-dien.html.
12
Another issue of inefficiency in the electricity sector is the quality of transmission system. In
major urban cities, there was still blackouts as a result of overloading in transmission, which
was designed for only 77 percent of current generation capacity. The annual technical loss
of an average of 10 percent decreases the actual consumption amount of electricity to below
the demand level. As a result, Viet Nam imported 6,23 billion kWh of electricity in 2011,
while exporting only 1,07 billion kWh (see Table 2). In World Bank’s report 2011, Vietnam
only ranks at 88 out of 125 countries on the quality of electricity supply. Thus any effort to
increase generation would be inadequate if lack of proper maintainance and upgrade of the
transmission system.
III. LITERATURE REVIEWS
There is a vast literature on the impact of fuel subsidy removal and energy price increases
on inflation and household welfare. Studies across household groups are based on a range
of methodologies, and give mixed results. Rising energy prices increases the prices of
goods and services that use fuel products as inputs, resulting in cost-push inflation. In
Indonesia, for example, the Central Bank estimates that every 500 IDR (0.06 US$) rise in
the subsidized fuel price can lead to the inflation rate of 1.6 percent (IISD-GSI, 2012). In
Thailand, Credit Suisse finds that a 10 percent growth in the retail diesel price would
increase CPI by 0.7 percent within a year (Sriring, 2011).
Several studies conclude that high-income groups receive most fuel subsidies and therefore
become the hardest hit when fuel prices go up. The International Energy Agency (IEA)
estimates out of the 409 billion USD spent on fossil-fuel consumption subsidies in 2010, only
35 billion USD (equivalent to 8 percent of the total) reached the poorest quintile of the
population (IEA, 2011). Similarly, using data collected from the 2009 Indonesian national
household socio-economic survey, the World Bank (2011) shows that the richest 10 percent
consumed 40 percent of the subsidized gasoline but the poorest 10 percent spent less than
one percent.21 Likewise, in a study of energy subsidy reform in Poland, which resulted in an
21
Indonesian fuel prices are among the lowest in the world and the subsidies have for years led to a hike in
demand for fuel while draining state finances and undermining foreign investment. After months of haggling,
petrol and diesel prices were set to rise by an average of 33 percent amid a revised budget last year but this fuel
13
80 percent growth in energy prices, welfare declines among the richest quintile are
estimated to be greater (8.2 percent) than those among the poorest (5.9 percent) under the
assumption of a zero elasticity of demand (Freund and Wallich, 2000). When the elasticity of
demand was taken into account, decreases in welfare range from 4.6 percent to 7.6 percent.
Employing a CGE model, a study by Clements et al. (2007) demonstrates in Indonesia that
the reduction in energy subsidies raises production costs, leading to other sectors’ price rise.
They run both Keynesian and non-Keynesian models and conclude that the aggregate price
level grows by 1.1 percent as a result of a 25 percent increase in petroleum prices.
Electricity prices go up the most while agricultural goods’ prices raise the least. In the
Keynesian model, the authors find a decrease in real consumption by 2.1 to 2.7 percent. In
their non-Keynesian model, the decline in real consumption is much smaller, at 0.9 percent.
Moreover, Clements et al. prove that high-income urban and rural groups are more affected
due to their relatively higher consumption of petroleum products. This result is consistent
with other studies’ findings (IEA 2011, Freund and Wallich 2000).
In contrast, other researches demonstrate the poorer households are harder hit by fossil fuel
prices. For example, Nganou et al. (2009) apply the social accounting matrix (SAM) model
for the case of Kenya and find that for every one percent increase in oil price, the producer
price index rises by 0.38 percent. They also conclude a 25-percent increase in oil price
raises the costs of living by 9.2 percent, with the rise being faster in urban areas than in rural
areas and larger among the poorer than the richer households. Similarly, by using the CGE
model, Naranpanawa and Bandara (2011) conclude that low-income urban households in
Sri Lanka become the most affected, followed by low-income rural households. Warr (2011)
also adopts a CGE model for Laos and suggests that an increase in petroleum prices from
70 USD to 100 USD will bring about an 18-percent decrease in aggregate real consumption.
However, different from Nganou et al. (2009) and Naranpanawa and Bandara (2011), the
impact is more severe in the rural areas, where show the highest poverty incidence, and in
which the people are more vulnerable to increases in transport costs.
price reform failed to push through due to sparked violent demonstrations around the country and heated
opposition in Parliament. As a result, the government spent $20 billion on fuel subsidies in 2012 and this was
expected to rise to $23 billion this year. Source: Luke Hunt (2013), “Indonesia Finally Moves on Fuel Subsidies”,
http://thediplomat.com/asean-beat/2013/06/20/indonesia-finally-moves-on-fuel-subsidies/, 20th June 2013.
14
Meanwhile, a cross-national study of Coady et al. (2006) illustrates the mixed distribution
impact of fossil fuel subsidy reform. This study simulates both the direct and indirect effects
of fossil fuel subsidy reform in Bolivia, Ghana, Jordan, Mali and Sri Lanka. They find that the
direct effects of increasing fossil-fuel prices on aggregate real income ranged from 0.9
percent in Mali to 2.0 percent in Jordan. In some countries, the direct effects were distributed
neutrally, affecting the highest and lowest income quintiles similarly. However in Ghana,
Jordan and Sri Lanka, they were regressive, influencing the lowest income quintile more
than the highest income groups. Indirect effects of the reform on prices of other goods and
services were higher, ranging from 1.1 percent to 6.7 percent but tended to be equally
distributed across income quintiles. As a result, the combined direct and indirect effects
ranged from 2 percent for Mali to 8.5 percent for Ghana. For all countries, this total effect is
slightly regressive, affecting the lowest quintile the most.
Another cross-national research is Hope and Singh (1995)'s study on energy price reform in
other six developing countries (Columbia, Ghana, Indonesia, Malaysia, Turkey and
Zimbabwe). Although some modeling was undertaken, this study was implemented based
on actual subsidy reforms in the 1980s. In all six countries, the income loss due to subsidy
reform ranged from 1 to 3 percent with urban poor being the worst affected.
It is worth disaggregating fuel price impact according to different types of fuel. In Egypt, for
example, disaggregation shows that the income effect of the gasoline- and natural gassubsidy reform would be 0 and 0.1 percent on the poorest quintile; while reform of kerosene
and LPG face an income effect of 2.2 percent and 5.4 percent, respectively (World Bank,
2009).
Viet Nam is currently paying more attention to assessing the impact of its fossil fuel subsidy
reform. Phase I of the UNDP Project on “Developing A Roadmap for Fossil Fuel Fiscal
Policy Reform”, the report titled “Fossil Fuel Prices And Taxes: Effects On Economic
Development And Income Distribution In Viet Nam” applies a CGE model to analyze macroeconomic impact and assess the consequences of price increases on energy demand as
well as household consumption and GDP. The report mentions that the results are based on
“real” or “inflation free” price changes. It also takes into account “phased out” subsidies and
15
“phased in” tax over a three-year period, in steps, in order to minimize shocks in the
economy. This analysis assesses the impacts of the targets and guidelines, with sectoral
disaggregation but without details on the inflationary impact. Another report in Phase I of the
UNDP Project (“Value Chain and Policy Analysis of Fossil Fuel Trade, Subsidy and Tax in
Viet Nam”) applies the LEAP model to link subsidy removal to energy consumption and the
generation of air emissions, without considering other socio-economic impacts. Implemented
under Phase II of the UNDP Project, this study therefore will fill this gap.
From late 2007 to end of March 2008, the International Monetary Fund (IMF, 2008) looked
into the impact of food and fuel price increases on inflation and poverty in a number of
countries, including Viet Nam. This report finds among the countries hardest hit by inflation
was Viet Nam, with the annual inflation rise by almost 12.6 percent. The impact of food price
growth seems to be much more significant than fuel price changes for the evolution of
overall inflation.
A study by Nguyen et al. (2009) employs the Input - Output (IO) table of the year 2005 and
uses the Viet Nam Household Living Standard Survey (VHLSS) in 2006 to show that 20percent increase in electricity tariff can immediately reduce the real consumption of
households by 0.7 percent. Poor households in both urban and rural areas are found to
experience larger direct impacts. However, this paper fails to explain for the indirect impacts
of electricity price increase on other sectors’ prices and then on household consumption.
Meanwhile, CIEM (2012) applies the CGE model and uses a micro-macro simulation tool to
assess the impact of energy price changes in Viet Nam. The results show that when
electricity price grows by 5 percent and petroleum price rises by 10 percent, the largest
increase in rural CPI is found in the South Central region (2.53 percent) while the smallest is
observed in the South East (2.21 percent). For urban households, the CPI goes up most
slowly in the Red River Delta (2.15 percent) but rises most rapidly in the Central Highland
(2.38 percent). In addition, the impact is more severe for rural households in poor regions
than in richer ones. The study also concludes that the total impact is larger in the longer term
than in the short term. Likewise, using regional CGE model, Pham and Bui (2009) find the
inflationary impact of 0.47-0.51 percent in 8 regions of Viet Nam as a result of 8 percent
increase in electricity price. The impact fluctuates among regions but seems to be equal
16
between rural and urban areas. Similar to CIEM (2012), this study also shows that long-run
impact is 10-percentage point higher than the short-run impact for all regions.
Another study on Viet Nam (Nguyen, 2012) employs a static approach and uses the 2007 IO
table to examine the impact of increasing electricity tariff (6 US cents/kWh) to the Long Run
Marginal Cost (LRMC) of 9.5 US cents/kWh on prices of consumer goods and services and
the distribution impact on different quintiles. The study concludes that a rise of 58.3 percent
in the electricity tariff results in the CPI increases by 4.2 percent. This study also shows that
the lower quintile suffers less direct loss than the richer because the poorer pay smaller
expenditure shares for electricity. This result is influenced by the fact that a number of
households in rural areas are still without access to electricity. They are poor and have
relatively lower electrification rates than better-income households. The overall inflationary
impact therefore ranges from 3.65 percent for the poorest 20 percent to 4.54 percent for the
richest.
The above studies on Viet Nam take different scenarios of energy prices. Therefore, for
comparison purpose, under the assumption that the inflationary impact has the linearity
property, all the findings are adjusted according to 20 percent increases in electricity and
petroleum prices, which is represented in Table 6. According to this table, there are some
variations where the inflation rate ranges from 0.8 percent (by Committee of the National
Financial Supervision) to 1.18-1.28 percent (Pham and Bui, 2009) or 1.44 percent (Nguyen,
2012) as electricity price goes up by 20 percent. Much large fluctuations in the inflationary
impact are found in the case of petroleum price rise by the same percentage. This impact
can be vary from very low values with 0.4-0.7 percent (Nguyen et al. 2009 and according to
Committee of the National Financial Supervision) to medium ones with 2.33 percent (in
accordance with Price Management Department - Ministry of Finance) or very large values
with 6.6 percent (under Ho Chi Minh Securities Corporation). A combination of both
electricity and petroleum price increases by 20 percent lead to CPI rise by more than 4.6-5.0
percent (CIEM, 2012). Different models and datasets give different results. None of them
explores components of inflationary impact in details and then suggestions on possible
mitigation measures.
17
Table 6 – A comparison on the inflationary impact of 20 percent increases in electricity and
petroleum prices
Sources
Inflation rate (%)
Inflation rate (%)
due to electricity
due to petroleum due to electricity and
price rises
price rise
CIEM (2012)
Inflation rate (%)
petroleum prices rise
>4.6-5.0 (long-term)
Nguyen et al. (2009)
Nguyen (2012)
0.68
1.44
Pham and Bui (2009)
1.18-1.28
Ho Chi Minh Securities Corporation*
6.6
Price Management Department**
2.33
Committee of the National Financial
Supervision***
0.8
0.4-0.6
1.2-1.4
Note: * Vietnam Economic Forum (2012), http://vef.vn/2012-03-08-tang-gia-nang-dong-va-linh-hoat-de-ung-pho.
One-percent increase in petroleum price leads to CPI rise by 0.33 percent.
** Ministry of Finance. Source: Radio The Voice of Vietnam VOV (2012), http://vov.vn/Kinh-te/CPI-se-tang0199-theo-gia-xang-dau/222955.vov. 1.71 percent increase in petroleum price leads to CPI rise by 0.20
percent.
*** Vietnam Chamber Commerce Industry VCCI (2013), http://www.vcci.com.vn/tin-tuc/2013031104133599
2/ghim-gia-de-kim-lam-phat.htm. 10 percent and 5 percent increases in electricity and petroleum prices
result in CPI rise by 0.40 percent and 0.1-0.15 percent, respectively.
IV. METHODOLOGY
The inflationary impact of energy price increases is calculated based on two indicators: price
changes in all sectors and the consumption patterns of different population groups. The
effects of increasing fuel prices on the prices of other goods and services are multiplied by
consumers’ budget shares for each category and then aggregated to measure the inflation.
The first indicator is estimated by the Input-Output (IO) model, which is presented in the subsection 4.1 while the sub-section 4.2 gives the formula to calculate inflation rates. The final
sub-section discusses different scenarios of energy price increases.
4.1. The price impact on other sectors – An IO model application
To measure the energy price impact on macro-economic indicators, two methodologies - IO
18
and CGE models - are used widely in the literature under different data requirements and
assumptions. The IO approach has the attractiveness of requiring substantially less data and
less modeling intensity than CGE models. In contrast, a CGE model captures better the
complication of the whole economy with the specification of utility and profit functions, the
implicit demand equations for both final and intermediate goods as well as the complete
specification of commodity and factor market structures. However, the robust and
comprehensive data demanded by CGE models is often difficult to generate, particularly for
developing countries in general and Viet Nam in particular, and many parameters of CGE
models normally have to be borrowed from other countries. In addition, results obtained by
CGE-based simulations are very sensitive to the specification of the functions and market
structures (see Table 7 for a summary of quantitative approaches to impact assessment and
Appendix A for further discussion). Therefore IO model is adopted in this study in order to
not only take advantage of data requirement but also supplement to CGE model which was
used in Phase I of this Project.
The IO-based simulation methodology has a number of attractive properties such as
simplicity, linearity (i.e. inflationary impact of a 20 percent increase in energy price is double
that of its 10 percent increase) and adding up (i.e. inflationary impact of a combined scenario
of 20 percent increase in electricity tariff and 20 percent increase in prices of petroleum
products is equal to the sum of price effects under individual scenarios), in addition to the
IO’s main property that allows to capture cross-sectoral inter-dependence. Furthermore, the
household survey-based micro-simulation methodology employed in this study has a
valuable property of high level of disaggregation, down to as low as household unit record,
resulting in flexibility of impact analysis for any socio-economic group of policy concern (e.g.
ethnic minorities in any region).
As a result, a combined use of these methodologies can allow researchers and policy
makers quickly produce, in a top-of-the head manner, estimates of inflationary impacts of
any scenario, based on estimates of the main scenarios, in this case 20 percent increases in
prices of electricity, and 20 percent increases in prices of petroleum products.
Thanks to numerous valuable properties, including those as mentioned above, the IO price
model (Leontief, 1951) has been widely used to analyze the nature of cost-price inter-
19
relationships within a sectoral framework. This model is simply representative for the
production side of an economy, where the set of producers of analogous goods and services
forms a homogeneous industry. Each industry requires different inputs to produce its output,
with these inputs procured from other domestic industries or imported.
Table 7 – Summary table: Quantitative approaches to impact assessment
Data
Captures impacts on…
Data availability and resource requirements
source(s)
Income and
Direct impacts only. Disaggregates energy by individual Data generally publicly available in all
expenditure
fossil fuels. Estimates static, first-order impacts on
survey
households only, can disaggregate by income group and two weeks of result of survey. Little technical
countries. Useful results achievable within
location. Useful for poverty analysis. Does not assess
expertise is required.
Input-output
impacts on informal sector, energy access or
Direct
and indirect impacts. Usually aggregate fossil
environment.
I-O tables tend to be built by national
(I-O) table
fuels into a limited number of categories, separate from statistical agencies every 5–7 years, and can
electricity. Estimates static, first-order impacts on
therefore be out of date. Experienced
households and economic sectors, with no
analysts are able to produce results within
disaggregation of households but good disaggregation of four weeks of receipt of table. Specialized
Social
Accounting
economic sectors. Does not assess impacts on informal technical expertise is required.
Direct and indirect impacts but standard SAM does not SAMs tend to be built by national statistics
sector, energy access or environment.
explicitly include data fields on electricity and fuel
agencies or international organizations such
Matrix (SAM) expenditure—this requires additional calculations.
SAM and/or
I-O table
as the World Bank every 5–7 years, and can
Estimates static, first-order impacts on households and
therefore be out of date. Experienced
economic sectors, but does not usually disaggregate
analysts able to produce results within three
households. Does not assess impacts on informal sector, months. Specialized technical expertise is
Direct and indirect impacts, and typically some but not all SAMs and I-O tables are usually used as the
energy access or environment.
required.
induced impacts. Usually aggregate fossil fuels into a
core databases underlying a CGE model,
limited number of categories, separate from electricity.
and, as these are usually built every 5–7
Estimates dynamic impacts of different orders of
years, they can be out of date. Also they
causation on households and economic sectors, with
require significant additional data, estimates
households not usually disaggregated and economic
of econometric relationships, assumptions
sectors not highly disaggregated. Different models will
and ad hoc adjustments. Can take an
allow different variables to respond to changing
experienced team up to a year to build and
economic conditions, e.g., most CGEs assume full
calibrate a CGE. Existing models are likely to
employment and require adaptation in order to estimate require adaptation to assess fossil-fuel
employment impacts. Does not assess impacts on
subsidy reform. Highly specialized technical
informal sector, energy access or environment.
expertise is required.
20
Energy
Direct and indirect impacts for energy sector only. Can
Data typically available from a number of
statistics,
fully disaggregate individual fossil fuels. Estimates
sources and fairly up to date. Building and
demand and dynamic impacts on energy consumers and energy
calibrating a new model can take an average
supply
sector, ranging from aggregated to highly disaggregated. of four months. Existing models are likely to
projects
Assumes no demand response to price changes. Does
require adaptation to assess fossil-fuel
not assess impacts on informal sector, energy access or subsidy reform. Specialized technical
be adapted
to project
changes
in for Policy-Makers
expertise is inrequired.
Source:environment.
GSI (2013), “ACan
Guidebook
to Fossil-Fuel
Subsidy
Reform
Southeast Asia”, page 51
–resource
Table 10,stocks.
drawing on inputs from Coady (2006); Markandya & Hunt (2004); World Bank (2010).
According to Leontief (1951), IO systems are based on the following assumptions:
(i)
Homogeneity of output;
(ii) No substitution between inputs;
(iii) Fixed proportions between inputs and outputs;
(iv) Absence of economies of scale;
(v) Linearity of coefficients; and
(vi) Exogeneity of primary inputs and final demand components.
In the IO price model, the price in a particular sector, Pi, depends on:
(i)
The input coefficients aij,
(ii) The prices of the required domestic intermediate inputs,
(iii) The primary components (wages, operating surplus, indirect taxes/subsidies) or
value-added per unit of output
(iv) The value (price times quantity) of imported intermediate inputs per unit of output.
The traditional Leontief price model has the following equation (Miller and Blair, 1985, p.354):
P = AT×P + v
(1)
where
P = the price index vector for n sectors
A = n×n direct coefficient matrix
AT = transpose matrix of A
v = the column vector of ratios of value added to output in n sectors
 P = (I – AT)-1v
(2)
where I = the identity matrix or unit matrix
21
Equation (2) shows that when imposing a primary input price shock on the model, prices (P)
of all sectors in the IO table are treated as endogenous variables. A shock to the IO price
model can be imposed in two ways:
(i)
A price shock to one sector through an increase in, say, indirect taxes, wages, value
added, imported values
(ii) The price of a commodity can be rendered exogenously by dropping it partially or
fully from the system.
We adopt the second approach in this study. This is because we assume that the prices of
petroleum and electricity (the column vector PE) are entirely exogenous while the other
sectors (the column vector PN) are endogenous. The exogeneity assumption is possible and
fits the fact that the electricity industry in Viet Nam is still dominated by SOEs and therefore
the government rather than the market regulates the electricity prices. Meanwhile, since a
majority of refined petroleum products are currently imported, the petroleum prices depend
much on the international prices and therefore they become independent of cost-price
interaction by other industries in Viet Nam.
To model this, equation (1) is partitioned into exogenous and endogenous components:
é P ù é AT
ê E ú = ê EE
T
êë PN úû ê AEN
ë
ù é
T
ù é
ANE
ú ´ ê PE ú + ê vE
T
ú ê PN ú ê vN
ANN
û ë
û ë
ù
ú
úû
(3)
where:
(i)
T
AEE
= the transpose matrix of the energy input coefficients for the production of one
unit of energy output
(ii)
T
ANE
= the transpose matrix of the non-energy input coefficients for the production of
one unit of energy output
(iii)
T
AEN
= the transpose matrix of the energy input coefficients for the production of one
unit of non-energy output
(iv)
T
ANN
= the transpose matrix of the non-energy input coefficients for the production of
one unit of non-energy output
(v) vE = the column vector of ratios of value added to output in energy sectors
(vi)
vN
= the column vector of ratios of value added to output in non-energy sectors
22
(vii) n = the number of exogenous and endogenous sectors
With PE excluded from the IO price system under the assumption of exogeneity, equation (3)
is then focused on the determination of PN. Accordingly, equation (3) can be written as:
PN =
T
T
AEN
PE + ANN PN + vN
 PN = (I –
T
T
T
ANN
)-1 AEN PE +(I – ANN )-1vN
(4)
It is worth noting that equation (4) provides the sum of both direct and indirect impact of an
increase in PE on PN. It should be borne in mind that when PE = 1, there is no deviation in the
prices of the petroleum and electricity sectors from its baseline values, and therefore, the
solution of the system yields a column vector of unity for PN.
 PN = (I –
T
T
ANN
)-1 AEN PE
(5)
Specific assumptions and methodological constraints need to be considered when using the
IO model results. First, on the one hand, the impact on prices of other goods and services is
linear with the scale of price reform due to the model structure. On the other hand, the
higher the change in price, the larger the policy-induced response of the system is expected
to be (e.g., lower consumption through energy substitution, energy efficiency and
conservation). Consequently, the impact may become non-linear, with the growth of inflation
progressively declining with higher policy-induced price increases. The results therefore
imply the overestimation of the negative economic impact in the short-term and the
underestimation of the positive medium to longer-term impact. Second, the IO model does
not consider both endogenous and policy-induced technological changes. A reduction in
energy intensity for fossil fuels would reduce the pressure on energy prices and inflation.
This constraint again leads to overestimate the inflationary impact, and the results hence
should be interpreted as the “maximum impact” on the inflation. In other words, this provides
an upper boundary for inflation, which is crucial information for policy formulation.
4.2. The inflationary impact
The price impact varies from one sector to another and the inflation rate is defined as a
weighted average of the sectoral price changes. These changes - so-called Production Price
23
Index (PPI) - are estimated using sectoral output shares as weights while the inflation rates
(changes in CPI) take sectoral shares of total private consumption as their weights. These
weights change among locations and across different population groups.
CPI is calculated using a Laspeyres index:
n
åp q
t
i
CPI t®0 =
0
i
n
æ pt ö
= åWi 0 ´ ç i0 ÷
è pi ø
å pi0 qi0 i=1
i=1
n
(5)
i=1
where:
(i)
CPI t 0 = the consumer price index at the period t compared to the base period 0
(ii)
pit = the price index in sector i at time t
(iii)
pi0 = the price index in sector i at time 0
(iv)
Wi 0 = weights at time 0 where Wi 0 =
pi0 qi0
n
åp q
0 0
i i
i=1
Then, inflation rate is calculated by:
I
t t 1
n
CPI t 0  CPI t 10
p t  p t 1
0
 100 
 100  Wi 
CPI t 10
p t 1
i 1
(6)
or
I t®t-1 =100W T DP
where
T

(7)

 WET WNT )
(i)
WT = the row vector of weights ( W
(ii)
 P 
P   E  (Using results from sub-section 4.1)
PN 
More specifically, inflationary impacts of energy price reform can be estimated in two steps:
Step 1: Calculating full price effects (direct plus indirect/spill-over) of energy price shock
The quantitative model used is based on the current officially Input-Output Table (IO - 2007
version), to calculate direct and spillover effects of energy price increase under each
scenario on all other prices in the economy as per the IO industry classification.
24
Step 2: Estimating average reduction (in percentage) in household welfare as measured by
household’s consumption in real terms
Changes in prices obtained from Step 1 are used to estimate changes in household real
consumption based on data of Viet Nam Household Living Standard Survey (VHLSS) in
2010. In this step, household expenditure items are mapped with IO’s classification of
industries to calculate household’s specific Consumer Price Index (CPI). To produce CPIs
that are specific to different groups of the population of policy concerns (e.g. CPI for the
urban poorest deciles or CPI for ethnic minorities in the North West etc.), individual
household-specific CPI will be aggregated accordingly, by household sampling weights
augmented by household sizes.
Such produced national CPI is different from conventional GSO’s CPI, because the former
uses shares of different expenditure items derived from the 2010 VHLSS, while GSO uses a
set of consumption shares estimated presumably from earlier years. The 2007 IO table and
the 2010 VHLSS database will be presented in more details in Section V.
4.3 Building Scenarios
To measure the impact of energy prices on other sectors in particular and the overall
economy in general, alternative scenarios are set up with the possible maximum changes in
petroleum and electricity prices based on the price history. It is reminded that the equations
(5) and (7) give linear results with respect to the size of energy price increases. Therefore,
choosing maximum growth in energy prices would result in the upper boundary for inflation.
a. Electricity
Since the Prime Minister in Decision 26 dated 01/26/2006 approved the roadmap and
conditions for the establishment and the development of the electricity market in Viet Nam,
electricity tariffs have continuously increased (see Table 8).
Table 8 - Average retail prices of electricity
25
Time
Average retail price (VND)
% increase
Sources
01/01/2007
842
7.6
45/2006/QD-BCN
01/07/2008
890
5.7
276/2006/QD-TTg
01/03/2009
948.5
6.6
05/2009/TT-BCT
01/03/2010
1,058
11.5
08/2010/TT-BCT
01/03/2011
1,242
17.4
05/2011/TT-BCT
20/12/2011
1,304
5.0
42/2011/TT-BCT
01/07/2012
1,369
5.0
17/2012/TT-BCT
22/12/2012
1,437
5.0
38/2012/TT-BCT
01/08/2013
1,509
5.0
19/2013/TT-BCT
In 2011, on Decision 24/2011/QĐ-TTg when the Prime Minister approved market-based
pricing mechanism for electricity, and allowed EVN to decide the level of price increase up to
five percent in a three-month period, this level has been selected three times for every 6
months during 2011-2012 (Table 8). After these price increases, in 2012 EVN made a profit
of about 6,000 billion VND. This figure, however, has not covered EVN’s accumulated loss
from previous years.
Based on a three-month period for each time of electricity price modification (under Decision
24/2011/QĐ-TTg), electricity prices are expected to increase by a maximum 20 percent (four
times of 5 percent) in one year.22 Therefore, a scenario of a 20 percent increase in electricity
price is taken, which may occur in 2013 due to two main reasons implied by EVN. First,
raising electricity prices will help EVN offset the losses accumulated from previous years and
exchange rate differences (with a total of 23,000 billion VND)23. Second, the coal and gas
input costs are expected to increase. In fact, from December 2012 to July 2013, the coal
price for electricity generation increased by 35.7 percent, reaching 85-87 percent of the coal
production cost24, and therefore leaving a possible minimum increase of 13-15 percent in
22
This reflects the highest possibility proposed by EVN and decided by MOIT without PM interference. This
scenario is taken before the latest changes in electricity tariff starting from 1st August 2013. However, the
scenario of a total 20 percent price rise is possible if having the PM’s decision. The findings are also easy to
modify along with different scenarios thanks to the IO model’s linearity and adding-up characteristics.
23 ___(2013).
“Từ 1-8: Tăng giá điện để bù đắp chi phí”, http://pclamdong.evnspc.vn/index.php?option=com_
content&view=article&id=7340:t-1-8-tng-gia-in--bu-p-chi-phi&catid=87:tin-tc-va-s-kin&Itemid=400, on 1st August
2013.
24
Hoàng Lan, “Tăng giá bán than cho điện”, http://kinhdoanh.vnexpress.net/tin-tuc/vi-mo/tang-gia-ban-than-cho-
dien-2741568.html
26
coal prices. Meanwhile, during this period, gas and oil (DO and FO) prices for power
production went up by 2.2 percent and 9.6 percent, respectively. Along with these increases
in electricity generation cost, shares of coal and gas thermal power rose by 19 percent and 6
percent, leading to an addition 5,198 billion VND payment on coal and another 1,593 billion
VND payment on gas, which can not be covered fully by the current electricity prices
(according to EVN).25
b. Coal
Since the second quarter of 2013, the coal price paid by the power generation plants in Viet
Nam has increased to 85-87 percent of the coal production cost. According to the 2013 plan,
the coal production cost is 1,291 thousand VND/ton (approximately 62 USD/ton)26 while the
average domestic coal price is 1,323 thousand VND/ton (63.5 USD/ton) and the export price
about 1,511 thousand VND/ton (72.5 USD/ton). Almost 100 percent of coal exports, where
new demand is expected to be imported in the near future, could be utilized to generate
electricity and produce cement.27 Meanwhile, the government requires gradual increases in
coal prices to reach the market-based levels by the end of 2013. To meet this target, the
coal price paid by the power sector might rise from 52.7 USD/ton (85 percent of the coal
production cost) to at most 72.5 USD/ton (the export price of coal) or by a maximum of 37.6
percent.
Cost structure in the power industry (Figure 2) shows that the majority of fossil fuel used for
electricity generation, transmission and distribution was coal (5.5 percent of total sector
costs), followed by refined petroleum products (2.9 percent) and natural gas (0.4 percent). 28
As a result, a rise in coal price causes electricity prices to go up. With coal prices expected
to increase by 37.6 percent to reach market prices, the price of electricity is able to increase
25 Thanh
Mai (2013), “Tăng giá điện, khó tránh tác động đến sản xuất và giá cả”, http://hanoimoi.com.vn/Tin-
tuc/Kinh-te/602915/tang-gia-dien-kho-tranh-tac-dong-den-san-xuat-va-gia-ca, 2nd August 2013.
26
1 USD = 20,833 VND in 2013
27
---, “10 lý do phải tái cơ cấu ngành Than Việt Nam”, http://nangluongvietnam.vn/news/vn/nhan-dinh-phan-bien-
kien-nghi/phan-bien-kien-nghi/10-ly-do-phai-tai-co-cau-nganh-than-viet-nam.html, 23rd Jan 2013
28
Note that these ratios reflect the percentages of total costs in values instead of by volume, which is calculated
by IEA (where 39.80 percent and 21.82 percent were generated by gas turbine and coal fired thermal plants,
respectively in the same year, 2007).
27
by 2.1 percent, which is taken into account by the scenario of a 20 percent increase in
electricity prices.
Figure 2 – Fuel used in production, transmission and distribution of electricity
Source: Calculated from the 2007 IO Table
c. Refined petroleum products
Domestic petroleum products prices are expected to continue increasing. According to the
Ministry of Finance, Viet Nam's petroleum product prices in 2012 were among the lowest in
the Southeast Asian region, leaving a sizable gap for domestic prices to increase (e.g. the
Hong Kong’s prices were double)29. Additionally, the world petroleum prices are anticipated
to go up due to scarce crude oil reserves, low OPEC spare production capacity, the political
turmoil in the Middle East and the disrupted supply from non-OPEC countries (according to
Société Générale).30
29
Particularly, the price of RON 92 in Viet Nam (23,150 VND/liter) ranked 9/10 countries in the region, just above
Indonesia (21,226 VND/liter). Gasoline prices in other countries were much higher, for example Hong Kong
46,422 VND/liter, Singapore 35,399 VND/liter, China 24,516 VND/liter, Cambodia 26,951 VND/liter and Laos
26,936 VND/liter. Similarly, RON 95 and diesel 0.05%S prices in Viet Nam also ranked 9/10 countries. (Source:
http://gafin.vn/)
30
T.H., “Những dự báo về giá dầu năm 2012 và 2013”, http://vietstock.vn/2012/03/nhung-du-bao-ve-gia-dau-
nam-2012-va-2013-34-217903.htm, 20th March 2012.
28
In Viet Nam, domestic petroleum product prices depend on the international prices. There
are four kinds of refined products shown in Figure 3, diesel, gasoline, kerosene and fuel oil.
In the period 2006-2012, diesel and kerosene experienced most price fluctuations and fuel
oil the least. Kerosene had the lowest prices over time whereas gasoline was the most
expensive. However, there was a trend that prices of different kinds of refined petroleum
products seem to move together. This supports the assumption that prices of all petroleum
products increase together at similar rates, driven by the fact that they are all derived from
crude oil.
Figure 3 – The history of petroleum prices
(a) Daily changes (VND)
(b) Annual changes (VND)
25,000
25,000
20,000
20,000
15,000
15,000
10,000
10,000
5,000
10/10/2006
Diesel 0.05S
Kerosene (liter)
22/02/2008
6/07/2009
Gasoline A92
Fuel oil 3.5S
18/11/2010
1/04/2012
14/08/2013
Diesel 0.05S
Kerosene (liter)
5,000
2006
2007
2008
2009
Gasoline A92
Fuel oil 3.5S
2010
2011
2012
2013
Sources: GSO and Decrees on energy prices
Although the Ministry of Finance tried to restrain the volatility of domestic prices, the
petroleum prices still increased, on average, by 20 percent per annum during 2006-2013
(see Table 9). A scenario of petroleum price increases is therefore built on the basis of this
growth (20 percent). This scenario is feasible because of the existing petroleum price gaps
between Viet Nam and other countries in the region.
Table 9 - Percent changes in petroleum prices
Year
Diesel 0.05S Gasoline A92 Kerosene Fuel oil 3.5S
29
2008
35.61
34.35
54.33
24.37
2009
-11.84
-5.96
-16.41
7.10
2010
19.65
15.25
14.57
13.92
2011
37.43
24.89
32.17
22.50
2012
3.31
7.33
3.64
16.05
Average
21.04
18.97
22.07
20.98
Sources: GSO and Decrees on energy prices
V. DATA SOURCES
To estimate the mutual price impact among sectors, the 2007 Input-Output (IO) table - the
best and most updated data - is used. Meanwhile, to take into account the sectoral
consumption patterns across household groups, the 2010 Viet Nam Household Living
Standard Survey (VHLSS) is selected because of its rich information on household income
and expenditure as well as its representativeness for the whole country.
5.1. The 2007 Input-Output Table
The IO table is a tool to give a comprehensive picture of a country’s economy in aspects of
production technology (represented by input coefficients), consumption (reflected by gross
capital formation, final consumption and exports) and value-added (described by
compensation of employees, depreciation, net production taxes and operating surplus).
Moreover, analysis of the IO table is an economic model useful for analysis and forecasting,
which help economic managers make decisions, give socio-economic solutions benefiting
the national development.
The IO table for the year 2007 is the fourth one (after the 1989, 1996 and 2000 IO tables)
with the dimension of 138 products (see details in Appendix B). The classification of 138
products is chosen based on their importance in the economy as well as economic analysis
and statistics. The concepts and methods applied in the 2007 IO table result from those in
SNA 1986 and 1993 and are consistent with those adopted in the previous IO tables. To
compile the IO tables, the General Statistics Office (GSO) conducted a survey of sampled
production units, which are representative for all types of ownership.
30
Industry codes classified in the 2007 IO table are compatible with CPC and ISIC codes.
According to these three types of classification (Table 10), refined petroleum products (Code
48) in the IO table are defined to contain gasoline, diesel (gas oil), kerosene, mazut (fuel oil)
and LPG (propane, butane). Electricity (Code 83) in the IO Table refers to power generation,
transmission and distribution and is produced from diesel/oil (Code 48), gas (code 19) and
coal (code 17). Fuel wood is not separated in the IO Table but among other items in logs of
wood products (Code 13). Briquettes, which are consumed by households, are classified in
coal product (Code 17) in the IO table. This product is differentiated by coke coal (Code 47),
which is used as input for the iron and steel industry only.
Table 10 – IO Link with CPC31 and ISIC32 codes
IO
CPC Ver 1.1
ISIC Rev. 3.1
13 – Logs of 03110 - Logs of coniferous wood
0200 - Forestry, logging and
wood
related service activities
03120 - Logs of non-coniferous wood
03130 - Fuel wood, in logs, in billets, in twigs, in faggots or in similar
forms;
03190 - Other wood in the rough (including split poles and pickets).
17 – Coal
11010 - Coal, not agglomerated
1010 - Mining and agglomeration
11020 - Briquettes and similar solid fuels manufactured from coal
of hard coal
11030 - Lignite, whether or not agglomerated
11040 – Peat
18 – Crude 12010 - Petroleum oils and oils obtained from bituminous minerals,
1110 - Extraction of crude
oil
petroleum and natural gas
crude
19 – Natural 12020 - Natural gas, liquefied or in the gaseous state
1110 - Extraction of crude
gas
12030 - Bituminous or oil shale and tar sands
petroleum and natural gas
47 – Coke
33100 - Coke and semi-coke of coal, of lignite or of peat; retort carbon 2310 - Manufacture of coke oven
coal and by- 33200 - Tar distilled from coal, from lignite or from peat, and other
products
products
mineral tars
48 –
33310 - Motor spirit (gasoline) including aviation spirit
2320 - Manufacture of refined
Petroleum
33320 - Spirit type (gasoline type) jet fuel
petroleum products, include:
products
33330 - Other light petroleum oils and light oils obtained from
- production of motor fuel:
bituminous minerals (other than crude); light preparations n.e.c.
gasoline, kerosene etc.
containing not less than 70 per cent by weight of petroleum oils or oils - production of fuel: light, medium
31
CPC stands for Central Product Classification
32
ISIC stands for International Standard Industrial Classification
31
obtained from bituminous minerals (other than crude)
and heavy fuel oil, refinery gases
33340 - Kerosene (including kerosene type jet fuel)
such as ethane, propane, butane
33350 - Other medium petroleum oils and medium oils obtained from etc.
bituminous minerals (not kerosene), other than crude; medium
- manufacture of oil-based
preparations n.e.c. containing not less than 70 per cent by weight of
lubricating oils or greases,
petroleum oils or oils obtained from bituminous minerals
including from waste oil
33360 - Gas oils/diesel
- manufacture of products for the
33370 - Fuel oils
petrochemical industry and for the
33380 - Lubricating petroleum oils and oils obtained from bituminous
manufacture of road coverings
minerals, other heavy petroleum oils and heavy oils obtained from
- manufacture of various products:
bituminous minerals (other than crude), and heavy preparations n.e.c. white spirit, vaseline, paraffin wax,
containing not less than 70 per cent by weight of petroleum
petroleum jelly etc.
83 –
69111 - Electricity transmission services
4010 - The production, distribution
Electricity
69112 - Electricity distribution services
and transmission of electricity
Source: 1. Ministry of Planning and Investment, General Statistics Office (2010), “The product classification in the 2007 IO
Table linked to CPC and ISIC classification”, pp. 630-637, in “The 2007 Input-Output Table of Viet Nam” (“Bảng
cân đối liên ngành của Việt Nam năm 2007”), Nhà xuất bản thống kê, 2010.
2. CPC Ver. 1.1 Code: http://unstats.un.org/unsd/cr/registry/regcst.asp?Cl=16
3. ISIC Rev 3.1 Code: http://unstats.un.org/unsd/cr/registry/regcst.asp?Cl=17
The main limitation of the 2007 IO table is that various kinds of fuels such as gasoline,
kerosene, diesel, mazut (fuel oil) and LPG are summarized under one category named
"Petroleum", so the impact cannot be separated. However, as mentioned in Sub-section 4.3
(part c), the fact supports the assumption that all refined products increase their prices
together at the same rates. In addition, because this 2007 version of IO Table is rather old,
all later findings are based on the assumption that the economic structures do not change
much over recent 5 years.
5.2. The 2010 Viet Nam Household Living Standard Survey
The Viet Nam Living Standards survey was brought to Viet Nam in the early 1990s to
provide reliable data for monitoring living standards, evidence-based policy design, and
evaluation of policies and programs. The first two rounds were conducted in 1992/1993 and
1997/1998 by the State Planning Committee and the GSO under the technical assistance of
the World Bank. Both surveys were representative at the national level, stratified along
administrative regions with probability proportional to sampling size.
32
Inheriting the technical capacity from these two surveys, the GSO carried out the series of
Viet Nam Household Living Standard Surveys (VHLSS) every two years from 2002 to 2010.
The 2010 VHLSS sample was selected based on a master sample, which was randomly
chosen from the 2009 Population Census enumeration areas. The master sample is a twostage sample of which communes were selected in the first stage and 3 enumeration areas
(EAs) per commune were chosen in the second stage. The communes were stratified along
provinces and urban/rural areas. Both communes and EAs were selected with probability
proportional to the 2009 Population Census. In the 2010 VHLSS, more than 3,000
communes were selected, accounting for nearly 30 percent of all communes in Viet Nam. In
each chosen commune, 3 households were interviewed, generating a total household
sample size of about 9,400.
The 2010 VHLSS collected information through household-level questionnaires, including
basic demography, employment, education, health, income, expenditures, housing and
asset ownership. Household income consists of farm and non-farm production income,
salary/wage, pension, scholarship, loan interest, house rental, remittances and subsidies. Of
which, farm production income comes from crop, livestock, aquaculture and forestry.
Meanwhile, household expenditures consist of food and non-food components. Non-food
component comprises expenditures on electricity, fuel, education, healthcare, housing and
durable purchases. In addition, the VHLSS gives details on different kinds of fossil fuel
(gasoline, LPG, diesel, kerosene and mazut) in terms of not only their expenditure patterns
but also the production cost structures (if any).
VI. ENERGY-INTENSIVE SECTORS AND CONSUMPTION PATTERNS
6.1. Energy-intensive sectors
a. Energy-intensive industries in Viet Nam
Energy affects other industries through their cost shares for energy and their energy demand
(see Figure 4).
33
Figure 4 – Industries intensive in electricity and petroleum products
Source: The 2007 IO table
Based on energy cost shares, electricity-intensive industries include steam and hot water
distribution, air-conditioner and ice production (with electricity accounting for 25.6 percent of
total industrial cost), water exploitation and supply (15.3 percent), gas distribution (11.9
percent), residential services (11.6 percent) and real estate services (7.5 percent). Electricity
used as input for the steel and cement industries only explains 1.4 percent of the industrial
cost in 2007, which might underestimate the current important role of electricity in these
industries. However, the 2012 financial statements of listed Viet Nam’s steel and cement
companies give a clue of very light changes in the steel industry and slightly larger variations
in the cement companies. In these statements, the purchased service category which
electricity belongs to accounts for just only 1.4 percent of total cost in some steel companies
and 4-5 percent in others but between 4 and 14 percent in cement firms. This suggests that
the majority of energy in cement and steel are non-electricity. In addition, raw materials cost
heavily in these industries (80-90 percent of total sectoral cost in the steel industry and 55-
34
75 percent in the cement industry), implying that these industries are likely to be outsourced
in Viet Nam.33
Petroleum affects many industries due to their large cost shares for petroleum products (see
Figure 4). The industries spending 40 percent of their costs on refined products include
fishery, other products extracted from gas and oil, road and pipeline transport. Among other
transport industries, waterway and airline use more than 30 percent of their cost on
petroleum while railway spends over 15 percent.
Figure 5 – Share of energy consumption
Source: The 2007 IO table
Note: Total domestic consumption = Industry consumption + Household consumption +
33
Particularly, in 2012, in Thai Nguyen Iron and Steel joint stock Corporation, raw materials explain 82.6 percent
of total cost, purchased services – 1.4 percent, for Nam Kim Steel Joint Stock Company: raw materials - 90.8
percent, general production cost - 5.2 percent; for Viet Y Steel Joint Stock Company: raw materials - 90.9
percent, general production cost – 4.5 percent; for Hoang Mai cement joint stock company: raw materials – 54.2
percent, purchased services – 4 percent; for Ha Tien 1 cement joint stock company: raw materials – 75.1 percent,
purchased services and other cost – 12 percent; for Hai Van cement joint stock company: raw materials – 69.6
percent, purchased services – 14 percent. Note that purchased services cost include electricity, water, telephone,
transportation fee and expenditure for hiring porters, consultants and auditors. General production cost is related
to material and fuel purchases, electricity, water, telephone, fixed asset depreciation, wage and insurance
contribution.
35
Government consumption + Investment
In terms of the energy consumption demand (Figure 5), electricity industry explains the
largest share of total power demand in Viet Nam (13.5 percent), followed by real estate
services (5.6 percent), and residential services (3.6 percent) while petroleum is spent the
most in fishery industry (9.2 percent), wholesale and retail sale services (9.0 percent), road,
pipeline and waterway transport (above 5.8 percent for each), railway and road construction
(4.5 percent). Although electricity is the most important input in steam and hot water
distribution, air-conditioner and ice production and water exploitation and supply, the amount
of electricity consumed in these industries is not large due to their small output share in the
economy. Besides the industry sector, the residential sector also consumes a large share of
energy: 34.3 percent of total electricity demand and 25 percent of petroleum demand.
b. Energy-intensive sectors among household businesses
There is a difference in the cost structure between household businesses (HBs) and the
industry. HBs tend to be small and are more likely to be involved in the informal sector. The
2007 IO table does not cover these informal businesses. 34 The 2010 VHLSS hence
supplements this shortage35. This survey sorts out the detailed information on revenue and
cost components of HBs by industries, which each HB belongs to. Additionally, this survey
classifies energy used by HBs in more details including electricity, gasoline, diesel, coal and
firewood.
Figure 6 – Energy-intensive sectors among household businesses
34
The IO table is built based on the enterprise survey, which only covers formal enterprises.
35
VHLSS does not cover migrants. We therefore assume that their businesses follow the similar cost share for
energy of other household businesses.
36
Source: Our calculation from the 2010 VHLSS
The list of energy-intensive sectors among HBs as well as the number of sampled HBs is
depicted in Figure 6. It is noted that HBs without using any kind of energy are excluded
because of implied missing values and one household may run more than one business. Out
of total sample of 8,474 HBs36, HBs largely work on pig husbandry sector (1,926 HBs); crop
production (1,443 HBs); wholesale and retail (except automobiles and motorbikes) with
1,177 HBs; poultry (760 HBs); and food services (422 HBs). Of those, HBs in the wholesale
and retail sector utilize the largest cost share for energy (20 percent). Other sectors (with
200-300 sampled HBs per each sector) include railways, road and pipeline transport; fish
farming; agricultural services; foodstuff production; beverage production; forestry; and
fishery. Out of these HBs, transport sector uses the largest cost share for energy (59
percent), followed by fishery (53 percent); agricultural services (36 percent); and forestry (28
percent).
Details of energy components in each sector are also shown in Figure 6 (right side).
Transport HBs spend 35 percent of their total cost on diesel and 20 percent on gasoline.
Diesel is consumed the most in Fishery sector (46 percent of total sectoral cost) and
36
This figure does not match the number of households because one household can run more than one
business.
37
Agriculture services (28 percent) while gasoline is used the most in Forestry sector (21
percent) and wholesale and retail (10 percent). Meanwhile, electricity accounts for 7-8
percent of the sectoral cost in household services and computer repairing services.37
Figure 7 – Business income as percent of total household income
Source: Our calculation from the 2010 VHLSS
Although HBs in the above listed sectors are most affected by energy price increases, this
impact is mitigated thanks to the fact that each household usually has more than one source
of income. In addition to production income from at least one business, household income is
also diversified by other sources such as wage/salary, bank interest, house rental,
remittances and subsidies. For example, in Figure 7, on average, income from wholesale
and retail businesses explains 51 percent of household income, from transport service
businesses - 47.5 percent, fishery – 42 percent, agriculture services - 15 percent, forestry –
14.6 percent. For HBs in the most popular sectors including crop production and pig
husbandry, the production income only accounts for 14-16 percent.
6.3. Expenditure patterns
37
For HBs working in crop production and pig husbandry sectors, fossil fuel explains only 1-3 percent of the
sectoral cost.
38
The impact of increasing fuel prices on inflation and therefore household welfare arises
through two channels. First, there is a direct impact on households when they directly
consume fuels for cooking, heating, lighting, and private transport. Second, an indirect
impact appears when higher fuel prices result in higher prices of other goods and services
consumed by households. The magnitude of these effects therefore depends on two factors:
(i) the fuel demand in household expenditure baskets, and (ii) the fuel intensity of other
goods and services. The distributional impact across different household groups relies on
the relative importance of these two factors among groups. For example, if the expenditure
baskets for higher-income groups are relatively more fuel intensive than those for lowerincome groups, then the impact on the former will be greater than that on the latter.
a. Expenditure structures of goods and services
Before estimating the inflationary impact of energy price increases, it is worth looking at the
expenditure patterns in Viet Nam as a whole, by urban/rural areas and across different
household groups in particular. It is shown in Figure 8 that food and foodstuff are the most
important items consumed by Vietnamese households, explaining 34.2 percent of total
expenditure. This ratio climbs to 47.6 percent if covering food services, beverages and
tobacco. Fuel - including electricity, petroleum and other fossil and non-fossil fuel - explains
10.5 percent of total expenditure. Education and health account for 11.1 percent while
housing and telecommunication composes 7.9 percent of total expenditure. Meanwhile, the
expenditure share on public transport is small (1.1 percent) as most expenditure on
individual transport (by cars or motorbikes) is covered by gasoline consumption. Other
expenditure consists of apparel, headwear and footwear (4.3 percent), recreation and
tourism services (2.5 percent), durable purchases (10.1 percent) and other goods and
services (4.8 percent).38
Figure 8 – Expenditure patterns by urban/rural areas
38
According to GSO (2011), the basket of goods and services includes food 8.18%, foodstuffs 24.35%, outside
eating 7.4%, housing, electricity, water, gas and construction materials 10%; transport 8.87% and
telecommunications 2.73%; equipment and housewares 8.65%; apparel, headwear and footwear 7.28%;
beverages and tobacco 4.03%; medicine and health 5.61%; education 5.72%; cultural, recreation and tourism
services 3.83%; other goods and services 3.34%.
39
Source: Our calculation from the 2010 VHLSS
Notes: (i) Sample weights are applied to make the data representative for the entire population
(ii) All monetary values are adjusted for regional price indexes and inflation rates according to
2013 prices.
There is a recognized difference in expenditure patterns between rural and urban areas
(Figure 8). Rural households tend to consume more food and foodstuff (38.0 percent of total
expenditure) compared to urban households (28.9 percent) but less food services (8.2
percent vs. 12.7 percent). Expenditure structures also change across household groups39
with food contributing the most to the consumption basket of poor households. For the
richest 10 percent, food makes up 26.2 percent of their budget in rural areas and 18.9
percent in urban areas. These shares become larger for poorer groups and the poorest 10
percent spend 59.1 percent of their expenditure on food in rural areas and 45.0 percent in
39
Based on the World Bank’s poverty line of 653 thousand VND per month per person, the poverty rate of Viet
Nam in 2010 is 20.7 percent, i.e. some distance into the second expenditure quintile.
40
urban areas. In contrast, food services only make up 2.2 percent of the spending in the
bottom rural decile but absorb 11.2 percent in the top rural decile. The similar trend but with
much higher expenditure shares on food services is found in urban areas, ranging from 8.7
percent at the bottom decile to 13-14 percent among the second half of the urban population.
All households in different deciles spend 9-12 percent of their expenditure on fuel (see
Figure 8). However, there is a contrast between fossil and non-fossil fuel usage across these
groups. The poorer tends to consume more non-fossil fuel and less fossil fuel than the richer
and rural households tend to use less fossil fuel but more non-fossil fuel than urban ones.
Besides that, rural households tend to spend more on beverages and tobacco but less on
education, recreation, telecommunication and housing compared to urban ones.
In absolute values (Figure 8), with budgets ranging from 425,000 VND/month among the
rural poorest to 3,028,000 VND/month among the rural richest group and from 699,000
VND/month to 5,667,000 VND/month in urban areas, the richer spend more on all items.
Remarkably, the top 10 percent of households consumes more heavily on durable
purchases and outside eating.
b. Energy expenditure patterns
Figure 9 describes energy expenditure components in Viet Nam. Generally, Vietnamese
households allocate 43.6 percent of their energy expenditure to gasoline. Following is
electricity with 27.6 percent. Additional 14.9 percent of their energy disbursement was on
LPG. Firewood and agriculture residuals, in terms of values, explain 10.8 percent of fuel
costs although in terms of volume, they are consumed much higher (69 percent of total fuel
consumption in the residental sector – see Table 2). This contradiction comes from the very
cheap, even cost-free consumption of these kinds of fuel. For the remaining fuels,
Vietnamese households only spend the overall 1.4 percent of their energy expenditure on
diesel, kerosene and mazut and another 1.4 percent on briquettes.
In spite of similar budget shares on fuel (around 10 percent), rural and urban households
follow different energy expenditure patterns (Figure 9). Compared to rural households, those
in urban areas tend to spend their fuel budgets more on gasoline (46.5 vs. 41.3 percent),
41
electricity (32.4 vs. 23.7 percent) and LPG (16.4 vs. 13.8 percent), which are more
expensive than other fuels. Rural households are more likely to use cheaper fuels, including
firewood and agricultural residuals (17.9 percent of their energy spending, compared to only
1.9 percent in urban areas). Other fuels including briquettes, diesel, kerosene and mazut are
consumed negligibly.40
Figure 9 – Expenditure share for energy in rural/urban
Source: Our calculation from the 2010 VHLSS
Notes: (i) Sample weights are applied to make the data representative for the entire population
(ii) All monetary values are adjusted for regional price indexes and inflation rates according to
2013 prices.
40
It is noticeable that the composition of fuel consumption differs across regions in the world. For example, the
relative importance of kerosene in Africa reflects the low level of household access to electricity. In contrast, like
Viet Nam, kerosene is much less important due to more extensive access to electricity. As mentioned by Dahl
(1994), Bhattacharyya and Blake (2009), for households at low-income levels, kerosene is a normal good for
cooking and lighting, since it is a substitute for cheaper fuels. For households at higher income levels, kerosene
is an inferior good compared to other commercial sources like LPG, natural gas and electricity.
42
Figure 9 also demonstrates the expenditure of all kinds of fuel consumed by households in
rural/urban areas and across groups. On average, the bottom 10 percent of rural households
spend 44,000 VND per month per person on energy while the richest decile spends six
times larger on fuel, respectively. Likewise, urban households’ payment for energy ranges
from 81,000 VND to approximately 569,000 VND per month per person. The notably higher
energy expenditure among the richest decile comparing to the others mostly come from
much higher spending on gasoline and electricity. On the contrary, the poorer tend to spend
more money on biomass. This leads to the richest 10 percent consume approximately one
forth of fossil fuel while only 2-3 percent of fuel goes to the bottom decile in both urban and
rural areas (Figure 10).
Figure 10 – Fossil fuel use by urban/rural households
Source: Our calculation from the 2010 VHLSS
Notes: (i) Sample weights are applied to make the data representative for the entire population
(ii) All monetary values are adjusted for regional price indexes and inflation rates according to
2013 prices.
Similar energy spending patterns are also found among expenditure quintiles (Figure 9). The
poorer tend to use more firewood, coal and kerosene than the better off. In contrast, the
better off are likely to spend more on expensive fuel (gasoline and LPG). This fact reflects
the concept of the “energy ladder” (Hosier and Dowd, 1987), which establishes a direct
43
relationship between income and the type of energy source, and shows that households will
transition from biomass to modern sources as a consequence of income increases. Typical
ladders have the cheapest energy sources at the bottom (preferred by the low-income
families) and the most expensive at the top (see Figure 11).
Figure 11 – Energy Ladder
Gasoline, LPG,
Electricity
Kerosene, Briquettes
Firewood, Agriculture residuals
Under these ladders, the poor seem to be the least affected by fossil fuel prices because of
their smaller expenditure shares. However, any change in the poor’s spending, though
small, may have a large impact on them. According to Von Moltke et al. (2004), the sudden
removal of subsidies for cooking fuels could lead to a reliance on biomass in some poorer
countries, increasing pressure on forests and indoor air quality. Moreover, the poor might be
the hardest hit because of their very poor income-expenditure gap (see Figure 12).
Figure 12 – Per capita income/expenditure by decile and urban/rural areas
Source: Our calculation from the 2010 VHLSS
Notes: (i) Sample weights are applied to make the data representative for the entire population
(ii) All monetary values are adjusted for regional price indexes and inflation rates according to
2013 prices.
44
c. Energy expenditure and ownership of appliances
The main reason explaining why the richer consume more fossil fuel compared to the poorer
may come from their ownership of different kinds of assets. As illustrated in Figure 13, in
both rural and urban areas, the ownership of energy-consuming appliances changes across
household groups. There is a trend that the poorer are less likely to own any appliance
compared to the richer. Electrical appliances showing the largest differences in ownership41
in urban areas include (i) washing machine (from 5.2 percent owned by the poorest to 79.6
percent by the richest), (ii) computer (from 3.3 percent to 73.9 percent), (iii) refrigerator (19.2
to 86.8 percent), (iv) air conditioner (0 to 67.5 percent), (v) water heater (0 to 62.3 percent),
(vi) juice extractor (5 to 54.3 percent), (vii) microwave oven (0.3 to 40.6 percent). Other
electrical items with medium variation in urban ownership consist of (i) electronic appliances
(41.7 to 75.4 percent), (ii) vacuum cleaner (0.2 to 27.2 percent), (iii) electric cooker,
television and electric fan (64.6 to 94 percent).
Appliance consuming both LPG and electricity are gas and magnetic cookers, ranging from
42.8 percent owned by the urban poorest to 83.3 percent by the urban richest (see Figure
13). Besides, gasoline appliances used by urban households compose of (i) motorbikes (55
percent of the poorest to 88.3 percent of the richest) and (ii) cars (0 to 21 percent).
Moreover, 24-36 percent of urban households in all groups own pumps - an item consuming
both electricity and gasoline.
Figure 13 – Durable ownership by expenditure deciles
41
Differences in ownership are simply defined as the ownership gap for each item between the poorest and the
richest deciles.
45
Source: Our calculation from the 2010 VHLSS
Notes: Sample weights are applied to make the data representative for the entire population
The disparity in durable ownership is shown more clearly in rural areas (Figure 13). The
group of appliances owned by rural households is different from that owned by urban
households. Electrical appliances showing the largest gap in rural ownership include
refrigerator, electric cooker, electronic appliances, and electric fan. Meanwhile, items
demonstrating the medium differences across groups consist of washing machine,
television, computer, water heater, juice extractor, air conditioner, microwave oven, and
vacuum cleaner. Owning motorbike - the gasoline-consuming appliance - depicts the large
variation across rural deciles while owning a car illustrates medium difference because only
3 percent of the richest have at least one car. Other appliances such as pumping machines
and gas/magnetic cookers also show large fluctuation in ownership among rural household
groups.
Owning any energy-consuming appliance makes both urban and rural HHs spend more
money on energy. For instance, as estimated in Figure 14, on average, each urban
household tends to pay an additional 116,000 VND/month for electricity use if this household
owns at least one fridge. This gap is smaller in the case of owning car/motorbike with further
98,000 VND/month paid for gasoline use by urban households. For those owning gas
cooker, additional 58,000 VND is paid per month. Among rural households, additional
87,000 VND/month, 65,000 VND/month and 88,000 VND/month are paid for owning fridge,
car/motorbike and gas cooker, respectively. The most remarkable gap is found among the
46
urban richest 10 percent. Out of them, 88.3 percent who are car or motorbike owners tend to
pay an extra amount of 496,000 VND/month on gasoline consumption compared to the
remaining 11.7 percent. Similarly, in the same group, 86.8 percent who own fridges are likely
to spend 202,000 VND/month higher on electricity than the other 13.2 percent. The large but
smaller gap is also found among the rural richest decile. Out of them, 32 percent (fridge nonowner) can save an additional expenditure of above 147,000 VND/month on electricity.
Figure 14 – Household expenditure on energy in urban/rural areas
Source: Our calculation from the 2010 VHLSS
Notes: (i) Sample weights are applied to make the data representative for the entire population
(ii) All monetary values are adjusted for regional price indexes and inflation rates according to
2013 prices.
d. Electricity expenditure patterns
One explanation for why the poor in developing countries consume more firewood and
kerosene is due to their limited access to electricity. However, in Viet Nam, the electricity
47
access rate of the poorest decile is very high (85 percent)42 by international comparison. The
poor mainly use biomass because it is very cheap, even free. Electricity is only used by
them for certain purposes such as lighting, fans.
Based on the 2010 IBTs and the information on electricity expenditure available in the 2010
VHLSS, the amount of electricity consumption by each household is estimated.43 According
to the government’s regulation, only the poor and low-income households benefit the lifeline
band in the condition that they consume less than 50 kWh per month. However, practically,
all residential consumers consuming less than this threshold receive the subsidized rate,
which also spread benefits to higher-income households.
Figure 15 – Benefit shares from lifeline tariff in rural/urban areas in 2013
Source: Our calculation from the 2010 VHLSS
Notes: (i) Sample weights are applied to make the data representative for the entire population
(ii) Beneficiaries include households consuming less than 50 kWh per month.
(iii) Assume the volumes of electricity consumption by households are kept unchanged over
time, the latest IBTs in 2013 are applied.
As described in Figure 15, the amount of implicit subsidies from lifeline tariff flow significantly
to the urban poor (63.3 percent to the urban poorest 30 percent in urban areas, compared to
46.2 percent to the rural poorest in rural areas). Meanwhile, 31-38 percent of the subsidy
42
However, this rate of the poorest decile is still far from the national electricity access rate of 97.5 percent.
43
Although the 2010 VHLSS asks households the question on the amount of electricity consumed last month,
this information is unreliable because households tend to remember their electricity spending in cash instead of
volume.
48
amount goes to the middle-income groups (the 4th to 7th decile) in both urban and rural
areas. The rural richest 30 percent receives 15.3 percent of total subsidy amount in rural
areas while the urban richest benefits 4.5 percent.
However, this leakage to non-poor households may not be a problem because of the fact
that when this group consumes more, they pay more for what they consume over and above
the 50 kWh with lifeline tariff, and therefore they start subsidizing, first themselves and then
the poor. The more they consume the more they contribute to subsidies of the poor. As
shown in Figure 16, by taking the second block tariff of the current IBTs as the production
unit cost (1,418 VND/kWh), except the rural poorest 20 percent, other rural deciles and all
urban deciles can subsidize themselves and cross-subsidize the rural lowest quintile. This
suggests that reducing the lifeline tariff might be not a problem thanks to high cross-subsidy
between higher consumers and lower ones. This lifeline tariff reduction can be used as an
alternative mitigation measure of direct subsidy mechanism for saving administration cost,
cutting administration procedures44, improving the leakage problem and reducing the burden
of the government spending on direct subsidy.
Figure 16 – Cross subsidy among different household groups
44
See more in http://www.bacgiang.gov.vn/ves-portal/15874/Huong-dan-chi-tra-kinh-phi-ho-tro-ho-nghèo-tien-
dien.html
49
Source: Our calculation from the 2010 VHLSS
Notes: (i) Sample weights are applied to make the data representative for the entire population
(ii) All monetary values are adjusted for regional price indexes and inflation rates according to
2013 prices.
Figure 17 – Changes in unit cost and EVN’s profit/loss
Source: Our calculation from the 2010 VHLSS
Notes: (i) Sample weights are applied to make the data representative for the entire population
(ii) All monetary values are adjusted for regional price indexes and inflation rates according to
2013 prices.
50
Note that the unit cost can increase if distributing other costs (e.g, accumulated loss from
previous years, investment repayment and unexpected cost such as cost from operating gas
turbine and coal fired thermal plants to generate extra power or from the inefficiency in the
electricity production, transmission and distribution activities). Figure 17 demonstrates
changes in unit cost and EVN’s profit/loss accordingly. If unit cost raises to approximately
1,660 VND/kWh45, EVN starts getting loss from the residential sector and the richer deciles
can not subsidize themselves as well as the poorer. Lack of transparent unit cost limits our
further analysis.
Figure 18 – Distribution of electricity consumption by urban/rural deciles
Source: Our calculation from the 2010 VHLSS
Notes: Sample weights are applied to make the data representative for the entire population; The
latest IBTs in 2013 are applied.
45 This
is possible because according to Chairman of the Vietnam Energy Association, the electricity sector will
suffer loss under the sale price of 1,600 VND/kWh. Source: Bích Diệp, “Món nợ của EVN tăng lên gần 10.000 tỷ
đồng”,
http://dantri.com.vn/kinh-doanh/mon-no-cua-evn-tang-len-gan-10000-ty-dong-774817.htm,
on
4th
September 2013.
51
Figure 18 draws the distribution of electricity consumption by urban/rural household deciles.
This figure demonstrates that most of people who are without access to electricity are
among the rural poorest (accounting for 16.6 percent of this group). These ratios reduce to
8.8 percent for the second lowest decide and 4.6 percent for the third decile in rural areas.
These ratios are arround 1-2 percent among the urban poor. As also seen in Figure 8, 26.9
percent of the urban poorest households and 65.7 percent of the rural ones consume less
than 50kWh per month. The corresponding percentages for the urban and rural richest are
only 1.4 and 5.6 percent.
Looking at only households consuming less than 50 kWh and 100 kWh per month in 2010,
Figure 18 shows that expanding the electricity lifeline band from 50 kWh to 100 kWh will
benefit an additional 16.6 percent of the rural poorest households and supplemental 34.0
percent and 45.3 percent of the second and third rural lowest household deciles,
respectively. Consequently, the new lifeline expands the coverage of beneficiaries (32.0
percent) who are poor and near poor. However, more benefit goes to the middle-income
(from the fourth to seventh deciles) and the rich (the three highest deciles) in rural areas.
Additional 52.7 percent of the middle-income and further 38.3 percent of the rich in rural
areas become beneficiaries under such a modified lifeline.
In contrast, benefits from expanding the lifeline to 100 kWh/month in urban areas would go
more to the poor. An extra 42.1 percent of the poor, 20.6 percent of the middle-income and
6.2 percent of the rich become beneficiaries in urban areas (see Figure 18). This suggests
the expansion of the lifeline band from 50 kWh to 100 kWh might benefit better the urban
poorest without facing serious leakage problem.46
46
According to the IEA, “Access to electricity involves more than a first supply connection to the household; our
definition of access also involves consumption of a specified minimum level of electricity, the amount varies
based on whether the household is in a rural or an urban area. The initial threshold level of electricity
consumption for rural households is assumed to be 250 kWh per year and for urban households it is 500 kWh
per year. The higher consumption assumed in urban areas reflects specific urban consumption patterns. Both are
calculated based on an assumption of five people per household. In rural areas, this level of consumption could,
for example, provide for the use of a floor fan, a mobile telephone and two compact fluorescent light bulbs for
about five hours per day. In urban areas, consumption might also include an efficient refrigerator, a second
mobile telephone per household and another appliance, such as a small television or a computer.” Source: IEA.
2012. World Energy Outlook - Methodology for Energy Access Analysis. Paris: OECD.
52
Almost all the poorest households (97-99 percent) use less than 100 kWh/month in rural
areas and 150 kWh/month in urban areas whereas only 33.1 percent of the rural richest
households consume less than 100 kWh/month and 14.7 percent of the urban ones use less
than 150 kWh/month. 95.7 percent of the rural richest use less than 300 kWh/month while
22.8 percent of the urban richest consume above 400 kWh/month (see Figure 18).
To expand the beneficial rates and increase the benefit levels toward the poor using the
lifeline tariff instrument, some scenarios of IBTs are assessed via answering a question that
under the assumption that all households maintain their electricty consumption during 20102013 regardless of its prices, if expanding the lifeline from 50kWh to 100kWh or maintaining
it at 50 kWh and reducing the lifeline tariff, to what extent other block tariffs should be raised
to neutralize EVN’s revenue, supporting the feasibility of the lifeline expansion proposal.
Using the electricity consumption structure from the 2010 VHLSS and adopting the current
IBTs of the year 2013, EVN is expected to attain 46,080 billion VND revenue47 (before 10
percent VAT) from the residential sector.
Five main alternative IBT scenarios are therefore proposed. They include (i) maintaining the
lifeline at 50 kWh but reducing the lifeline tariff to 600 VND/kWh (the previous lifeline tariff
before a direct subsidy of 30,000 VND/month to poor households48) while increasing other
block tariffs by an equal rate which compensates for EVN’s revenue loss, (ii) expanding the
lifeline band to 100 kWh to all less consumers but keeping its subsidized price while
increasing other block tariffs by an equal rate, (iii) expanding the lifeline band to 100 kWh to
less consumers in urban areas only but keeping its subsidized price while increasing other
block tariffs by an equal rate, (iv) expanding the lifeline band to 100 kWh to all less
consumers but reducing the lifeline tariff to 600 VND/kWh while increasing other block tariffs
by an equal rate, and (v) expanding the lifeline band to 100 kWh to less consumers in urban
areas only but reducing the lifeline tariff to 600 VND/kWh while increasing other block tariffs
by an equal rate.
47
This figure might be underestimated due to lack of information on migrants’ electricity consumption. Based on
the information of Table 7 (Sub-section 6.1), the residential and transport sectors explain 36.68 percent of total
electricity demand by volume, which is estimated to be equivalent to 52,606 billion VND out of EVN’s total
revenue of 143,419 billion VND for the year 2012. However, this estimated number does not reflect the cheaper
price applied in residential sector compared to those in other sectors.
48
Under this proposal, the direct payments to the poor aim to be abolished.
53
However, the five above scenarios can not cover a proportion of the poor who consumes
more than 50 kWh/month due to some given reasons (e.g., large households). At least 17.7
percent of the rural poorest and 71.1 percent of the urban poorest are excluded from these
proposals. To improve the coverage, five other IBT scenarios are proposed, in which the first
block’s lower price is applied to all households, irrespective of how many kWh they use.
Table 11 – Alternative IBTs scenarios (Unit: VND/kWh)
Kwh
Current Scen 1 Scen 2 Scen 3^ Scen 4 Scen 5^ Scen 6 Scen 7 Scen 8^ Scen 9 Scen 10^
0-50
1,418* 1,445* 1,548** 1,438** 1,703* 1,484*
993
993
600
600
1,913
993
1,798
600
2,201
51-100
1,418
1,445
101-150
1,622
1,653
1,770
1,645
1,948
1,698
2,188
2,365
2,057
3,129
2,517
151-200
2,044
2,083
2,231
2,073
2,455
2,140
2,757
2,980
2,592
3,944
3,172
201-300
2,210
2,252
2,412
2,241
2,655
2,314
2,981
3,222
2,802
4,264
3,430
301-400
2,361
2,406
2,577
2,394
2,836
2,472
3,185
3,442
2,994
4,555
3,664
>400
2,420
2,466
2,642
2,454
2,907
2,533
3,265
3,528
3,068
4,669
3,756
1.9%
9.2%
1.4%
20.1%
4.7%
34.9% 45.8%
26.8%
92.9%
55.2%
% increase$
1,548** 1,438** 1,703* 1,484*
600
Source: Our calculations from the 2010 VHLSS
Notes: * Households consuming less than this amount pay 600 VND/kWh.
** Households consuming less than this amount pay 993 VND/kWh.
^ The lifeline block expanded to 100 kWh only works for urban households.
$
Increase in non-lifeline block tariffs (%)
(i) Sample weights are applied to make the data representative for the entire population
(ii) All monetary values are adjusted for regional price indexes and inflation rates according to 2013 prices.
The alternative increment block tariff scenarios are presented in Table 11. Reducing the
lifeline tariff to 600 VND/kWh (Scenario 1) makes other block tariffs increase by 2 percent to
keep EVN’s revenue unchanged. Insteads, expanding the lifeline band to 100 kWh for less
consumers in urban areas only (Scenario 3) leads to 1.4 percent rise in other block tariffs.
This rise becomes much larger (9.2 percent) when the lifeline expansion is applied to all
households who consume less than 100 kWh (Scenario 2). When combining both reducing
the lifeline tariff and expanding the lifeline block, 20.1 percent increases in all other block
tariffs (Scenario 4) are required to neutralize EVN’s revenue. This figure is much smaller (4.7
percent) if only urban households become additional beneficiaries (Scenario 5).
54
When the lifeline tariff for the first 50 kWh consumption works with all consumers whatever
the number of kWh they use, scenarios 6 to 10 are proposed. Under different assumptions,
all other block tariffs in these scenarios are required to increase by significantly high ratios,
from 34.9 percent in Scenario 8 to 92.9 percent in Scenario 9. Although these scenarios can
expand substantially the coverage of the poor, a serious problem may arise due to a
possible protest from higher consumers or the richer. Therefore, it is necessary to consider
all these scenarios in terms of benefits and obstacles, which are presented in Table 12 and
Figure 19.
Table 12 – Increase in coverage and cross-subsidy amount among alternative IBT scenarios
Scen 1 Scen 2
Scen 3 Scen 4 Scen 5 Scen 6 Scen 7 Scen 8 Scen 9 Scen 10
Increase in coverage (percentage points)
Rural poorest 10%
0.0
16.6
0.0
16.6
0.0
17.7
17.7
17.0
17.7
16.6
Rural poorest 20%
0.0
25.8
0.0
25.8
0.0
27.5
27.5
26.6
27.5
26.3
Urban poorest 10%
0.0
48.5
48.5
48.5
48.5
60.6
68.6
69.7
68.6
69.3
Urban poorest 20%
0.0
44.4
44.4
44.4
44.4
61.6
70.0
74.6
69.7
74.4
Increase in cross-subsidy amount (000 VND/beneficial HH)
Rural poorest 10%
8.5
3.0
0.0
14.2
8.5
4.9
-3.8
-6.2
8.7
4.3
Rural poorest 20%
9.4
4.3
0.0
17.7
9.4
7.4
-1.9
-5.4
13.2
6.4
Urban poorest 10%
12.2
9.9
9.9
31.3
31.3
11.3
7.9
9.6
30.8
34.4
Urban poorest 20%
12.1
10.8
10.8
33.0
33.0
10.5
9.9
11.5
33.9
36.8
Source: Our calculations from the 2010 VHLSS
Note: (i) EVN’s revenue is neutralized under all IBT scenarios.
(ii) Sample weights are applied to make the data representative for the entire population
(iii) All monetary values are adjusted for regional price indexes and inflation rates according to 2013 prices.
First of all, in terms of increases in coverage and/or cross-subsidy amount, reducing the
lifeline tariff to 600 VND/kWh (Scenario 1) does not extend the coverage but each beneficial
household receives an additional 8,500 – 12,000 VND/month of implied subsidy per month.
This means that theoretically the direct transfer scheme of 30,000 VND/month bring more
benefits toward the poorest 10 percent than the application of lifeline tariff reduction. Under
Scenario 2, 82.3 percent of the rural poorest decile and 86 percent of the rural poorest
55
quintile become beneficiaries49 while these figures in urban areas are 75 and 65 percent,
respectively. These beneficial households also receive more subsidy with additional 3,0004,000 VND/month in rural areas and extra 10,000-11,000 VND/month in urban areas. These
further subsidy amount increase to 14,000-18,000 VND/month in rural areas and 31,00033,000 VND/month in urban areas if applying new lifeline tariff to 600 VND/kWh and new
lifeline band to 100 kWh to all less consumers (Scenario 4). This scenario therefore brings
more benefits toward the urban poorest 20 percent than the direct transfer scheme. Under
Scenarios 6 to 10, generally, only 1-2 percent improvement in rural coverage, however, all
rural poorest who are also beneficiaries receive smaller amount of subsdies compared to
Scenario 4. Meanwhile, the urban coverage increases up to 90-100 percent coverage
(Scenario 8) but the subsidy amount is not much better than Scenario 4.
Figure 19 – Percentage changes in HH electricity expenditure among alternative IBT
scenarios
49
Note that 16.6 percent of the poorest decile and 8.8 percent of the second lowest decile in rural areas cannot
access to electricity.
56
Source: Our calculations from the 2010 VHLSS
Note: (i) EVN’s revenue is neutralized under all IBT scenarios.
(ii) Sample weights are applied to make the data representative for the entire population
(iii) All monetary values are adjusted for regional price indexes and inflation rates according to 2013 prices.
Details on changes in electricity expenditure for the first four scenarios are shown in Figure
19. Under Scenario 1, the rural poorest benefit the most with 19.5 percent reduction in
electricity expenditure. This reduction continues with six next rural deciles at decreasing
rates. In contrast, only the urban poorest 10 percent are benefitial with nearly 2 percent fall
in electricity expenditrue. For the other deciles, their spendings on power raise insignificantly
by a maximum 2 percent. In terms of Scenario 2, a lower half of rural households pay less
by 12-17 percent and only the rural richest decile has to pay more by 4 percent. Meanwhile,
urban poorest households receive larger benefits compare to those in Scenario 2 (9.6
percent reduction in the urban poorest 10 percent’s electricity expenditure while the urban
second poorest decile pay less by 2.5 percent). These figures are much larger under
Scenario 4 with the rural poorest’s expenditure reduces by nearly a half while the urban
richest’s spending increases by approximately 20 percent.
As a result, depending on the government’s target (increases in coverage or the amount of
subsidy) and changes in the production unit cost. In addition, an acceptable combination is
needed where the government, EVN and the rich share the cost to benefit further the poor.
VII. INFLATIONARY IMPACT
7.1. The fossil fuel price impact on other industries – The PPI
In terms of the power sector, the direct and indirect impact of raising electricity prices by 20
57
percent on prices of other industries are calculated based on Equation (4) in Section 2.1 and
demonstrated in Figure 20. These effects are ranked in descending orders.
Figure 20 – Energy price impact on other industry prices
Source: Our calculation from VHLSS 2010
Note: (i) Sample weights are applied to make the data representative for the entire population
(ii) All monetary values are adjusted for regional price indexes and inflation rates according to 2013 prices.
Steam and hot water distribution, air conditioner and ice production industry experiences the
largest impact with a price increase by approximate 5.34 percent. The second place comes
to Water exploitation, processing and supply industry (3.3 percent). The next 12 industries
change their prices by between +1.5 to +2.5 percent.
While some industries mainly suffer the direct impact because of their large cost shares for
electricity, others change their prices mostly by indirect way. Particularly, more than 93
percent of price increases in the two most-affected industries come from the direct impact
(see Figure 20). Likewise, gas distribution and residential service industries depend
substantially on the direct electricity price impact. Meanwhile, the indirect effect plays a more
important role in the next six industries, raising the direct impact of 0.4-1.2 percent to the
overall impact of 1.7-2.5 percent. This is because the cost structures of these industries rely
more on electricity-intensive intermediate inputs compared to electricity itself.
Moreover, the inter-relationships among industries, which are represented by iterations of
58
electricity price effects under a number of rounds, give an additional explanation for the large
indirect impact. Varying responses are found among different industries (Figure 21). While
the impact on some industries occurs strongly in the first round and converges immediately
in the second round, other industries are affected gradually in about eight rounds before
going to convergence.
Figure 21 - Iterations of the electricity price impact on other industries
3.000
Gas, fuel distribution by pipeline
Residental service
2.500
Fertilizer and nitrogen compound
2.000
Basic organic chemicals
Plastic and primary synthetic rubber
1.500
Paper and by-paper products
1.000
Fiber (all kinds)
Textile products (all kinds)
0.500
Real estate business service
0.000
Postal and delivery
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15
Source: Calculated from the 2007 IO table
Notes: (i) Sample weights are applied to make the data representative for the entire population
(ii) All monetary values are adjusted for regional price indexes and inflation rates according to 2013 prices.
In terms of refined products, the most impacted industries as a result of 20 percent
increases in petroleum product prices are also illustrated in Figure 21. Products exacted
from oil and gas become most affected with more than 12 percent price increase, of which
two-thirds comes directly and one-third indirectly. The next seven industries experience
more than 7 percent price increases, which are dominated by direct effects. For example,
the direct and overall impact on fishery industry is 9.1 and 9.6 percent, respectively.
Similarly, transport industries are affected with around 7-9 percent price increases, which
mainly come directly (6-8.8 percent). Followed is household service industry where the direct
impact nearly reaches the overall impact of 5.4 percent. In contrast, for many other
industries, the indirect impact dominates the direct one due to inter-dependencies amongst
industries. These industries purchase intermediate inputs from other sectors, which utilize
their large cost shares on petroleum. Notably, the fertilizer, nitrogen compound and basic
organic chemical industries spend negligible cost shares on petroleum, causing the direct
impact to become very small (only 0.3 percent). However, the indirect impact on these
59
industries is much higher (4.4 percent).50
7.2. Inflationary Impact
The inflation rate is a result of a number of factors. One of them comes from price increases
in primary goods including electricity and petroleum. As observed in Figure 22, major
changes in petroleum products (except LPG) reflected pretty well the variation in the inflation
rates in terms of directions as well as relative magnitudes with the inflation rates seem to
respond slower.
Figure 22 - Inflation vs. refined petroleum product prices
Figure 23 - Iterations of the energy price impact on the inflation rate
1.6
Electricity
1.4
Petroleum
3
2.5
1.2
2
1
0.8
1.5
0.6
1
0.4
0.5
0.2
0
0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Source: Our calculation from the 2010 VHLSS and 2007 IO Table
Notes: (i) Sample weights are applied to make the data representative for the entire population
(ii) All monetary values are adjusted for regional price indexes and inflation rates according to 2013 prices.
Due to iterations of energy price effects on other industries’ prices, iterations also happen to
the inflation rates (as shown in Figure 23). In both electricity and petroleum cases, the
inflation rates increase at gradually slower rate within 8 rounds and then converge into
50
Notes that these sectors tend to be natural gas-intensive.
60
constant values. Note that this is a function of calibrating the modeling approach used and is
therefore only an internal modeling consideration.
A 20 percent increase in electricity price leads to the inflation rate of 1.3 percent in rural
areas (Figure 24). Out of which, the direct impact is 0.58 percentage points and the indirect
impact is 0.73 percentage points.51 The indirect impact hence plays a more important role in
the sense that without considering it, the overall inflation rate might be underestimated
seriously.
Figure 24 – Inflationary impact of energy price on rural/urban households
Source: Our calculation from the 2010 VHLSS and 2007 IO Table
51
Note that the direct impact in this section is calculated based on fossil fuel expenditure shares and its price
changes while the indirect impact depends on consumption shares for non-fossil fuel goods and services as well
as their price changes caused by changes in fossil fuel prices.
61
The maximum inflationary impact of a 20 percent increase in petroleum price is 2.7 percent,
doubling the electricity price impact because households spend a much higher expenditure
share for petroleum products (see Figure 24). The indirect impact again confirms its role with
accounting for 53.6 percent of the overall inflation rate. When electricity and petroleum
products simultaneously raise their prices by 20 percent, the inflation rate spreads to 4.0
percent, of which 1.8 percentage points comes directly and 2.2 percentage points indirectly.
These results are robust among different consumption baskets as demonstrated in Table 13
with very small fluctuations (4.00 vs. 3.97 if applying GSO consumption basket - see
Appendix C for more details - or vs. 3.94 if using un-weighted consumption basket). These
results are consistent with many studies in other countries where the indirect impact varies
across regions. Whereas the indirect effect is over 60 percent of the total impact in Africa
and South and Central America, it is less than 45 percent in Asia and Pacific (Javier Arze et
al. 2010). However, in all cases it is a sizeable component of the total impact, reflecting the
fact that a high proportion of total fuel consumption is for intermediate use. Consequently, it
is important for any evaluation of the welfare impact of fuel price changes to incorporate this
indirect effect.
Table 13 – The inflationary impact – Robustness check
Inflation rate
Petroleum price
Electricity price
Petroleum and electricity
increase by 20%
increase by 20%
price increases by 20%
Direct
Indirect Total
Direct Indirect Total
Direct Indirect
impact
impact impact impact impact impact impact impact
Total
impact
Viet Nam
1) GSO consumption basket
1.22
1.55
2.77
0.48
0.73
1.21
1.70
2.27
3.97
2) 2010 VHLSS consumption basket (hhwt)
1.25
1.44
2.70
0.58
0.73
1.30
1.83
2.17
4.00
3) 2010 VHLSS consumption basket (wt)
1.24
1.44
2.68
0.60
0.73
1.33
1.84
2.17
4.01
4) 2010 VHLSS consumption basket (unweight)
1.20
1.45
2.65
0.56
0.73
1.29
1.76
2.18
3.94
2) 2010 VHLSS consumption basket (hhwt)
1.44
1.40
2.84
0.73
0.73
1.45
2.17
2.13
4.29
3) 2010 VHLSS consumption basket (wt)
1.41
1.40
2.81
0.75
0.73
1.48
2.16
2.13
4.29
4) 2010 VHLSS consumption basket (unweight)
1.37
1.41
2.77
0.70
0.73
1.43
2.06
2.14
4.20
2) 2010 VHLSS consumption basket (hhwt)
1.12
1.48
2.60
0.47
0.73
1.20
1.59
2.20
3.79
3) 2010 VHLSS consumption basket (wt)
1.11
1.47
2.58
0.49
0.73
1.22
1.60
2.20
3.80
Urban Viet Nam
Rural Viet Nam
62
4) 2010 VHLSS consumption basket (unweight)
1.09
1.48
2.57
0.47
0.73
1.20
1.56
2.21
3.77
Source: Our calculation from the 2010 VHLSS and 2007 IO Table
There is an impact difference between urban and rural households (Figure 24). Urban
households experience larger CPI increases compared to rural households (4.29 vs. 3.79
percent) when together increasing electricity and petroleum prices by 20 percent.
Additionally, the indirect impact becomes larger than the direct one in both areas. However,
the gap between the direct and indirect effects is found larger in rural areas since rural
households suffer less direct impact (1.59 vs. 2.17 percent) but higher indirect impact (2.20
vs. 2.13 percent) compared to urban households. These impacts are shown robust across
different consumption baskets (see Table 13).
As also observed in Figure 24, the poor tend to experience less inflationary impact
compared to the non-poor. In addition, the poorer are less affected directly but more hit
indirectly in absolute term. Particularly, as shown in Figure 24, when electricity prices raise
by 20 percent, the direct impact ranges from 0.36 percentage points for the rural poorest to
0.46-0.50 percentage points for the top half of rural population and from 0.71 percentage
points for the urban poorest 30 percent to 0.75 percentage points for the remaining. The
opposite is found in the indirect impact, reducing from 0.79 percentage points for the poorest
to 0.71-0.73 percentage points for the richest in rural areas and from 0.75 to 0.71-0.72
percentage points in urban areas. Similarly, when petroleum prices increase by 20 percent,
the direct impact goes the least to the poorest (0.58 percentage points in rural areas and
1.12 percentage points in urban areas), then increases and finally comes the most to the
near-rich (the 7th to 9th deciles) with a maximum 1.36 percentage points in rural areas and
1.56 percentage points in urban areas. In contrast, the poorest 10 percent mainly suffer the
indirect impact (1.72 percentage points in rural areas and 1.51 percentage points in urban
areas) whereas the richest and near rich experiences this impact the least (1.40 percentage
points in rural areas and 1.35 percentage points in urban areas).
Figure 25 – Indirect impact as percent of total impact in rural areas
63
Source: Our calculation from the 2010 VHLSS and 2007 IO Table
This difference is shown much clearer when looking at shares of indirect impact in rural
areas (Figure 25). About 75 percent of the inflationary impact indirectly affects the rural
poorest 10 percent in both scenarios. These shares drop to around 70 percent for the
second lowest decile and 65 percent for the third one, then reducing quickly when rural
households’ incomes increase and join the middle-income group. Although higher
proportions for indirect impacts are found in all deciles for both scenarios, in terms of relative
terms, rural households are much more affected indirectly by the electricity price impact
(above 62 percent for all rural deciles). In sum, although the rural poorest absorb the least
inflation rates but they tend to be most affected indirectly. Meanwhile, the direct and indirect
impacts for urban household deciles are more equal.
7.3. The inflation structure
This sub-section analyzes the components of the inflation rate, which are made by different
expenditure categories and household groups.
Figure 26 - Inflation and expenditure categories in Urban Viet Nam
(i)
Petroleum
64
(iii)
Electricity
Source: Our calculation from the 2010 VHLSS and 2007 IO Table
Figure 26 demonstrates the contribution of each expenditure category to the inflation rate in
urban areas as a result of the energy price increases. Fossil fuel is the most important
sector, delivering directly 50-51 percent to the overall inflation rate. By virtue of large
expenditure shares on food, foodstuff and food services (41.6 percent of total household
expenditure), this category comes in second place, contributing 20-25 percent to the
inflation. Besides that, additional 14-20 percent of the overall inflation rate comes from
education, housing and durable purchase categories. All these six sectors therefore
contribute 90 percent to the inflation. When comparing different urban deciles, the poorest
10 percent suffer the biggest indirect impact, which comes mainly from Food, foodstuff and
food services (explaining 53-65 percent of the indirect impact). The indirect inflationary effect
from this sector ranges from 0.98 percentage points for the urban poorest to 0.52
percentage points for the urban richest as a result of petroleum price changes and reduces
65
from 0.40 to 0.21 percentage points when electricity prices expand. On the contrary, for
higher income groups, other sectors contribute more to the indirect inflationary impact.
Figure 27 - Inflation and expenditure categories in Rural Viet Nam
(i)
Petroleum
(ii) Electricity
Source: Our calculation from the 2010 VHLSS and 2007 IO Table
This trend is shown clearer in rural areas (see Figure 27). Spending the most on food,
foodstuff and food services (61.3 percent of total expenditure) makes the rural poorest 10
percent facing the biggest indirect impact caused by Food and foodstuff (59-69 percent).
When rural households become richer, the contribution of this sector to the overall inflation
rate shrinks from 0.46 percentage points for the poorest to 0.26 percentage points for the
richest in the case of electricity and ranges from 1.19 to 0.64 percentage points in terms of
66
petroleum. Similar to urban areas, other sectors contribute increasingly to the indirect impact
for richer households.
Figure 28 - Inflation and household deciles in Viet Nam
Source: Our calculation from the 2010 VHLSS and 2007 IO Table
In terms of different household groups (Figure 28), the magnitude of the overall inflation rate
also relies on expenditure share of each group in the economy. As a result, the richer
contribute more to the inflation. Particularly, the top 3 deciles deliver 52 percent of the
inflation rate while the poorest and near poor (the first 3 deciles) make up only 14 percent.
7.4. Possible mitigation measures
Although the poorer tend to suffer the least inflation rate, these households are the least
able to absorb shocks due to their monthly budget constraint. Currently, there exist various
mitigation measures toward the poor, including (i) National Targeted Program for Poverty
Reduction (aiming to provide preferential credit, free health insurance, education support for
poor households; land, water and electricity for ethnic households; housing and clean water
for poor communes; regular cash assistance and emergency relief to vulnerable population
groups); (ii) Unemployment Insurance; (iii) Transport Expense Support for Agricultural
Enterprises; (iv) Support Programs for Vulnerable Population (e.g., transfer of cash
equivalent to 5 liter of kerosene per year for lighting to ethnic and poor households in areas
without access to electricity grid; support fishermen who buy new vessel with large capacity
or who switch to more fuel efficient vessel machine; support diesel cost in the amount of 3-8
million VND per fishing trip); (v) National Employment Promotion Fund; and (vi) Lifeline Tariff
67
for Low-Income Households and cash transfer scheme of 30,000 VND/month. However,
under the social safety-net programs, the benefits account for only 4 percent of household
income on average and the coverage rates are still small with only 37 percent of bottom 20%
population in 2006 (World Bank). In addition, these programs do not cover other vulnerable
groups that are most affected by energy price increase, including: (i) migrant and informal
workers (the latter group includes 37 million people, accounting for 75.5 percent of total
employment); (ii) the near poor and the transitory poor; (iii) the urban poor – this group is
growing and actually accounts for the highest absolute number of poor people; and (iv)
household businesses and farmers who use energy as inputs for production.
To mitigate the inflationary impact on the poor, additional measures are considered,
including (i) further targeted electricity and petroleum price subsidy to the poor and lowincome households (such as lifeline tariff expansion and petroleum voucher/rebate); (ii)
conditional cash transfer program to the targeted groups (e.g., transfer of cash equivalent to
100 kWh to poor households); (iii) connect households in rural and remote areas to grid to
ensure uniformity in prices and reduce monopoly power of local utility providers; (iv) provide
free or subsidized LPG cookers and tanks to poor households to prevent reversing to
biomass fuels for cooking, which is less efficient and more harmful for health and
environment; (v) exempt valued added taxes (VAT) or import taxes for basic foods stuffs to
limit the indirect impact of energy price hikes on food inflation, (vi) higher taxation on energyintensive appliances to reduce energy demand; (vii) improvement of public transportation
system and bus fare reduction for switching households’ habit from car and motorbike to
public transport use; (viii) provide access to low-cost housing (with reliable and affordable
utilities) to the urban poor and migrants, who often have to rent and are subject to high
electricity prices imposed by their landlords; and finally (iv) mitigation measures can be
spread out if price increases in reality are spread out, for example over 3 years instead 1
year. Various measures may be applied simultaneously. For example, tax exemption for
LPG consumption or direct subsidy to transport sector was implemented in Turkey and
Nigeria; improvement of public transport or setting price ceiling on public transport fares in
Ghana; application of different lifeline bands in various countries (e.g., Uganda: below
15kWh, Kenya: below 50 kWh, Peru: below 100kWh, Jordan: below 160 kWh). Besides, tax
exemptions for basic foodstuffs were carried out in Jordan and Namibia. Other governments
apply energy rebate to targeted groups (e.g., diesel rebated to farmers in Turkey) or
(un)conditional cash transfer scheme in a majority of countries (for instance, Jordan in 1986,
68
Yemen in 1996, Armenia in 1999, Brazil in 2003, Indonesia in 2005, China in 2006, Malaysia
in 2008, Iran in 2010, India in 2011, Mauritania in 2012) as well as improve social protection
system (such as eliminating primary and secondary school fees, funding for health care in
poor areas, increasing the minimum wage in Ghana and Jordan). See Appendix D for more
details.
Normally, two complement mitigation measures to the electricity price impact on the poor
include direct transfer scheme and tariff-based subsidies. Lifeline tariffs provide a minimum
level of electricity consumption at a subsidized price, while consumption exceeding the
minimum is charged at significantly higher prices, such as full cost-recovery price.
Meanwhile, the intent of providing cash transfers is to assist poor and vulnerable households
in paying their electricity bills. This assistance prevents households from depleting their
limited assets or reducing consumption to such an extent that their livelihoods are
threatened. Opponents of tariff-based subsidies criticize their lack of progressiveness,
because all households benefit equally, and criticize the absence of energy-saving
incentives (Lampietti et al., 2007). Direct cash transfers are criticized for their lack of
targeting efficiency and effectiveness.
This sub-section will consider different scenarios of these two kinds of mitigation measures,
which aims to assist low-income households as part of a poverty reduction strategy and
address energy poverty, as well as VAT exemption measure for basic foods stuffs, which
contribute mainly to household expenditure and hit the poorest segment of Viet Nam the
most.
Figure 29 – Crude Oil Index and Food & Foodstuff Index
69
Source: SBS, Bloomberg
In terms of the latter mitigation measure, the trend of food and oil prices seems to go handin-hand. As described in Figure 29, the world crude oil price experienced exponential growth
and peaked by May 2008. At the same time, the highest Food and Foodstuff index was also
reached in Vietnam. Both crude oil and food indexes declined after that and then started to
grow again. An obvious example supporting this fact is that during July 2013 after three
petroleum price modifications, a series of food and foodstuffs started to increase in prices by
10-20 percent in Ho Chi Minh City.52
A basket of important food products is listed in Table 14. Rice is the most important staple
food. This food is more important for the poorer groups of the population, with the poorest
sharing their highest budget on rice (25.7 percent for the rural poorest and 13.4 percent
among the urban poorest). On the contrary, the richest segment spends the least on rice
(4.2 percent in rural areas and 1.6 percent in urban areas). Pork is the second most
consumed food, ranging from 5.8-7.8 percent for the poorest 10 percent of households to
1.9-3.6 percent for the richest decile. Other important food includes poultry (mostly chicken
and duck meat), fish and shrimp, oils and fats. All five types of food explain 43 percent of the
rural poorest’s budget and 13.4 percent of total spending by the bottom 10 percent in urban
52
Hải Minh, “Giá các mặt hàng ở chợ bán lẻ bắt đầu tăng”, http://www.nhandan.com.vn/tphcm/tin-
chung/item/20878102.html, on 29th July 2013.
70
areas. These shares diminish when households are wealthier and reach the bottom for the
richest segment of the population (13 percent in rural areas and 7 percent in urban areas).
Table 14 – Expenditure shares on the most consumed food
Food items
Expenditure share (%)
1st
2nd
3rd
4th
5th
6th
7th
8th
9th
10th
Rural areas
Rice
25.67 20.40
16.49
14.40
12.14
10.58
9.06
8.18
6.78
4.29
Pork
6.82
6.47
6.29
6.17
6.05
5.87
5.51
5.26
5.03
3.59
Poultry
3.85
3.87
3.78
3.80
3.76
3.44
3.47
3.53
3.54
2.60
Shrimp, fish
4.94
4.33
4.24
4.19
4.15
3.99
3.63
3.47
3.19
2.04
Oil & fats
1.66
1.47
1.35
1.22
1.06
0.91
0.88
0.79
0.73
0.52
Total
42.9
36.5
32.2
29.8
27.2
24.8
22.6
21.2
19.3
13.0
Urban areas
Rice
13.43
9.67
7.77
6.53
5.42
5.04
4.41
3.71
3.20
1.80
Pork
5.78
5.52
5.32
4.94
3.98
4.02
3.61
3.30
3.36
1.89
Shrimp, fish
4.22
4.44
3.60
3.21
2.83
3.07
2.71
2.38
2.18
1.42
Poultry
2.82
2.88
3.07
2.66
2.71
2.67
2.54
2.47
2.68
1.64
Oil & fats
1.08
0.91
0.78
0.71
0.63
0.62
0.54
0.47
0.46
0.24
Total
27.3
23.4
20.5
18.0
15.6
15.4
13.8
12.3
11.9
7.0
Source: Our calculation from the 2010 VHLSS
According to the VAT Law (the National Assembly XIIth session, 3rd session, No.
13/2008/QH12 dated 3/6/2008), the 5 percent rate is applied to goods and services including
unprocessed crop and livestock products and others. If exempting completely VAT on rice
and pork, the payment on rice can drop by 3.2 percent (= 5 percent – 1.8 percent) or 4.3
percent (5 percent – 0.7 percent) in the cases of petroleum or electricity price shock.
Similarly, the price of pork can diminish between 3 percent and 4.1 percent.
Table 15 – The magnitude of inflationary mitigation resulting from a potential VAT exemption
Food items
Energy price reduction (percentage points)
1st
2nd
3rd
4th
5th
6th
7th
8th
9th
10th
Rural areas
Rice
1.28
1.02
0.82
0.72
0.61
0.53
0.45
0.41
0.34
0.21
Pork
0.34
0.32
0.31
0.31
0.30
0.29
0.28
0.26
0.25
0.18
71
Total
1.62
1.34
1.14
1.03
0.91
0.82
0.73
0.67
0.59
0.39
Urban areas
Rice
0.67
0.48
0.39
0.33
0.27
0.25
0.22
0.19
0.16
0.09
Pork
0.29
0.28
0.27
0.25
0.20
0.20
0.18
0.17
0.17
0.09
Total
0.96
0.76
0.65
0.57
0.47
0.45
0.40
0.35
0.33
0.18
Source: Our calculation from the 2010 VHLSS
Under this mitigation measure, all households benefit greatly directly (Table 15). 1.62
percentage points are removed from the inflation rate among the rural poorest 10 percent
while 0.96 percentage points are dropped in the urban poorest segment. Likewise, 0.18-0.39
percentage point reductions serve the urban and rural richest. As a result, the poorest
relatively becomes those most benefited from these mitigation measures. Noting that lower
taxes lowers government reveues, and thus lowers their ability to spend and invest on
measures which would benefit households. Yes but it is also another regressive subsidy.
Figure 30 – Share of rice subsidy in rural/urban areas
Source: Our calculation from the 2010 VHLSS
72
Figure 30 depicts expenditure shares on rice and pork by each decile in rural and urban
areas, which also reflect budget shares in the total subsidy if adopting the above mitigation
measures. Obviously, the rice market is divided equally among household deciles with only
a little smaller share found in the poorest 10 percent and a slightly larger share spent on the
richest 10 percent. However, a clearer bias of benefits towards the rich is found in the case
of pork price subsidy, with the poorest receive only 4-5 percent of subsidy budget while the
richest absorb 14-16 percent. Regarding to the food VAT exemption measure, the overall
rice price subsidies are 549.6 billion VND/month in rural areas and 180 billion VND/month in
urban areas. Similarly, these subsidies in case of pork meat are 263.2 billion VND/month in
rural areas and 126.2 billion VND/month in urban areas.
In terms of direct and indirect subsidy measures, depending on the relative importance of
these objectives, the volume and the rate for the lowest block may change (Fisher, Sheehan
& Colton, 2008). If the primary aim is to assist low-income households, then the lifeline tariff
must be well-targeted, so that it balances the need to benefit the largest possible proportion
of poor households; and benefit as few non-poor households as possible. It must also be set
at a volume and rate that provides sufficient assistance. If the primary aim is to reduce
energy poverty, then the lifeline tariff volume must be at the energy poverty line specified as
the minimum level of electricity needed; and the rate must be set so that it is affordable for
households to be above the energy poverty level. Three scenarios of mitigation measures
are taken into acouunt to protect the bottom decile from electricity price increase by 10% per
annum, which is expected to be in line with overall inflation rate of 7% being expected over
the medium.
1. Cash transfer to the poor without changes in the existing lifeline volumes and tariffs
2. Cash transfer to the poor with lifeline tariff for the rural poorest in the bottom decile
adjusted down to VND 600 kWh in order to encourage them to use electricity instead
of biomass
3. Cash transfer to the poor with lifeline volumes adjusted down to 20 kWh and 40 kWh,
which is defined by EVA as the energy poverty lines, in order to reduce leakages to
non-poor
73
Table 16 - Indicators for Assessing Existing Mitigation Mechanisms
ProgresScenarios
Mitigation measures
Cover-
Leak-
sive
age
age
/Regres-
Pover-ty Pover-ty Bene-fitrate
gap
Notes
Cost
sive
(i) Lifeline tariff (993
VND/kWh) for lowusers of no more than
1. Baseline
50 kWh/month
(Current
(ii) Direct subsidy of
IBTs)
30,000 VND/HH/month
to the MOLISA's poor
(i) Indirect subsidies: 908.2 billion
64.56%
16.40%
1.79
11.61% 2.79%
0.21
VND (production unit cost: 1,418
VND/kWh)
(i) MOLISA's poor HHs in 2012:
100%
0%
8.55
11.39% 2.70%
1.00
9.64%, poverty rate: 11.7%
(ii) Direct subsidies: 773.6 billion
list
(iii) Both (i) and (ii)
VND
100%
16.40%
4.96
11.34% 2.67%
0.58
(i) EVN's profit increases by 375.2
(i) Lifeline tariff (993
VND/kWh) for low2. Electricity
users of no more than
prices
50 kWh/month
billion VND (production unit cost:
64.56%
16.40%
1.79
11.76% 2.82%
0.21
(ii) Indirect subsidies: 1,120.3 billion
VND
(iii) Inflation rate: 0.46%
increase by
7%
1,517 VND/kWh)
(ii) Direct subsidy of
30,000 VND/HH/month
to the MOLISA's poor
100%
0%
8.55
11.54% 2.74%
1.00
(i) Direct subsidies: 773.6 billion
VND
list
Table 17 - Indicators for Assessing Existing Mitigation Mechanisms (cont.)
(iii) Both (i) and (ii)
prices
increase by
7%
16.40%
4.53
11.43% 2.70%
0.53
(i) Lifeline tariff (600
(i) EVN's profit reduces by 377.8
VND/kWh for rural HHs
billion VND (production unit cost:
and 993 VND/kWh for
3. Electricity
100%
urban HHs) for low-
64.56%
16.40%
1.88
11.66% 2.80%
0.22
1,517 VND/kWh)
(ii) Indirect subsidies: 1,873.4 billion
users of no more than
VND
50 kWh/month
(iii) Inflation rate: 0.46%
(ii) Direct subsidy of
30,000 VND/HH/month
to the MOLISA's poor
100%
0%
8.55
11.54% 2.74%
1.00
100%
16.40%
3.85
11.38% 2.67%
0.45
(i) Direct subsidies: 773.6 billion
VND
list
(iii) Both (i) and (ii)
4. Electricity
(i) Lifeline tariff (993
prices
VND/kWh) for low-
increase by
users of no more than
7%
20 kWh/month for rural
(i) EVN's profit increases by 1,366.7
64.56%
16.40%
2.74
11.82% 2.85%
0.32
billion VND (production unit cost:
1,517 VND/kWh)
(ii) Indirect subsidies: 128.8 billion
74
HHs and 40
VND
kWh/month for urban
(iii) Inflation rate: 0.46%
HHs
(ii) Direct subsidy of
30,000 VND/HH/month
to the MOLISA's poor
100%
0%
8.55
11.54% 2.74%
1.00
100%
16.40%
7.69
11.51% 2.73%
0.90
(i) Direct subsidies: 773.6 billion
VND
list
(iii) Both (i) and (ii)
(i) Lifeline tariff (600
(i) EVN's profit increases by 1,270.2
VND/kWh) for low-
billion VND (production unit cost:
users of no more than
20 kWh/month for rural 64.56%
5. Electricity
HHs and 40
prices
kWh/month for urban
increase by
HHs
7%
(ii) Direct subsidy of
30,000 VND/HH/month
to the MOLISA's poor
16.40%
2.74
11.82% 2.85%
0.32
1,517 VND/kWh)
(ii) Indirect subsidies: 225.3 billion
VND
(iii) Inflation rate: 0.46%
100%
0%
8.55
11.54% 2.74%
1.00
100%
16.40%
7.26
11.49% 2.73%
0.85
(i) Direct subsidies: 773.6 billion
VND
list
(iii) Both (i) and (ii)
7.5. Limitation of Results
The main limitation of this analysis comes from lack of updated data. The latest versions of
IO table and VHLSS are only available for years 2007 and 2010, which may not capture
recent changes. Another limitation of the 2010 VHLSS is that it does not capture migrants
who generally came to cities to find jobs and higher pay. The UNDP study of urban poverty53
in 2009 shows that migrants (without ho khau) are more likely to be poor, especially those
moving after 2008. They face higher vulnerability as a consequence of crisis, with three
quarters of them suffering economic risks. In complementary to that finding, RIM (20092011) finds a large inflationary impact on such vulnerable migrants, who tend to be double
hit by low wage increases and higher living cost. This impact is partially resulted from the
electricity and petroleum price increases, especially since the beginning of the process of
phasing out electricity and fuel subsidies in 2011.
53
UNDP: Urban Poverty Survey (UPS) 2009: 1,637 households/individuals in Hanoi and 1,712 in Ho Chi Minh
city (including migrants)
75
There exists a debate on whether the immediate energy price impact can be found amongst
the poor migrants. The answer is unclear. On the one hand, the poor migrants tend to be the
least affected because of their low energy consumption. For example, in terms of power use,
the most common electrical appliances owned by them include a neon light, an electric rice
cooker and a fan. Most migrants use a tourist gas-fired cooker, which helps them save
electricity costs. Very few migrants, usually households, have a TV, a refrigerator, or an airconditioner since they expect to stay in their place for a much longer period than single
migrants. Some students also own private computers.
On the other hand, the energy price impact might hit migrants the most because they tend to
be among the most vulnerable group. The income earned by migrants is limited and they
have to save money for other purposes, such as studying or sending remittances back
home. Therefore many migrants (e.g., motorcycle taxi drivers, construction workers and
vendors) suffer increases in energy costs in a sense that their income is low and unstable
whilst these increases add up their existing economic difficulties. In addition, many of them
live in rented accommodation and face high and bias electricity charges. For instance,
according to Giang (2010), landlord-imposed electricity charges ranged between 1,000 and
2,500 VND per kWh in Ha Noi for any amount of power consumed by renters, with 1,5002,000 VND per kWh being the most common fee. The tariffs were lower in Hai Phong but
remarkably higher in Ho Chi Minh City, with the range of 2,000-3,500 VND per kWh. These
charges were far higher than the standard tariff of 600 VND per kWh for the first 50 kWh.
The current electricity subsidies are rather uniformly distributed, but their removal would lead
to a relatively greater decrease in real income in poor households. Complimentary social
protection policies can mitigate the expected income loss for poor and vulnerable
households. However, this raises the issue of financing. Currently, energy subsidies are
implicit and do not have a separate budget line in the State budget. Moving from implicit to
explicit energy compensations will make the costs visible, and the response may be
politically unappealing. However, even in a situation of limited fiscal flexibility, appropriate
mitigation policies can be justified as instruments that provide the government with the
necessary political space and time to introduce unpopular energy tariff reforms. In this
section, we describe simulations of different mitigation measures aimed at protecting the
76
poor against increases in electricity tariffs. The simulations consider both distributional and
cost effects.
VIII. CONCLUSION
Over two decades, Viet Nam’s impressive economic growth has relied heavily on extensive
usage of energy. However, low growth rate associated with high inflation in recent years has
forced Viet Nam to embark on a structural reform program, which aims to a sustainable
growth model based on efficiency. Accordingly, the Government’s efforts to phasing out
energy subsidies has been initiated since the late 2000’s, with narrowing the lifeline band
from 100 KWh to 50 KWh per month and increasing retail price of electricity to all users
under IBT structure.
Importing a majority of refined petroleum products results to Viet Nam’ great dependence on
international prices, which are predicted to increase. Likewise, electricity - another critical
energy source - is expected to have demand increasing strongly and therefore able to rely
on million tons of imported coal for power generation, leading to the tariff reliance on the
international base. In addition, lower tariffs compared to those in most countries in the region
leave a big price gap for Viet Nam to expand. Based on the historical time series data of
energy prices, scenarios with maximum 20 percent increases in petroleum products and
electricity prices are therefore applied. Attracted by less data and model intensity
requirement, the IO model is selected to estimate the energy price impact on other
industries’ prices using the latest input-output table in 2007. These energy price-induced
effects are then averaged taking categories’ expenditure shares as weights, which are
collected from the latest VHLSS in 2010.
Below are our main findings

Household businesses
o
HBs in transport and fishery sectors tend to be the hardest hit by petroleum
price increases:
77

Energy (mostly diesel and gasoline) explains 50-60% of business cost.

Around 45% of household income comes from these business
activities.
o
HBs in forestry/agricultural services and wholesale & retail sectors (except for
motorbikes/cars) tend to be less impacted by petroleum price increases:

More than 50% of household income origins from wholesale and retail
businesses, but energy (mostly gasoline and diesel) accounts for only
20% of these businesses’ costs.

Cost shares of energy among forestry/agricultural service businesses
are around 30-35% on average, but the petroleum price impact is
mitigated thanks to their household income diversification (only 15%
coming from these businesses)

Expenditure patterns:
o
Food and foodstuff are the most important consumption items (44% of total
household expenditure), especially for rural households (46.2%) and the poor
(e.g., 61.3% for the rural poorest 10%). The richer spend lower expenditure
share on food (e.g., 32-37% for the rural and urban richest 10%).
o
Expenditure shares on fuel are around 10% across household groups. The
poorer and rural households consume less fossil fuel but more biomass fuel.
As a result, the richest 10% consume one quarter of total fossil fuel value
while only 3% of this fuel value goes to the bottom decile.

Out of household fuel expenditure, gasoline explains nearly 45%,
followed by electricity (~30%), LPG (15%), and biomass (around 10%).
However, in terms of fuel consumption, 70% of household energy
demand comes from biomass, a very cheap or even price-free fuel.

Despite smaller fossil fuel expenditure shares, the poor might be the
most affected by energy price reform because of their very poor
income-expenditure gap and their more reliance on biomass, which
increases pressure on forests and indoor air quality.

To what extend households spend their income on fossil fuel depends on which energyintensive assets (especially refrigerators and cars) they own. The poorer less rely on
fossil fuel because they have fewer assets.
78

Lifeline tariffs:
o
Do not cover 15% of the poorest decile, who are without access to electricity,
compared to only 2.5% for the whole population.
o
Only cover 65% of the rural poorest and 25% of the urban poorest, who
consume less than 50kWh per month.
o
50-60% of implicit/cross-subsidies flow toward the poorest 30%, who tend to
be less consumers and subsidized by higher consumers (the non-poor). The
leakage to the non-poor may not be a problem if unit cost of electricity is
predictable (or transparent) and reasonable (e.g., keeping the distribution loss
low).
o
Expanding the lifeline from 50 kWh to 100 kWh might benefit better the urban
poorest (an extra 40%) without facing serious leakage problem.

The inflationary impact:
o
The maximum inflationary impact is 2.7% for a 20% increase in petroleum
prices and 1.3% for a 20% increase in electricity prices. More than a half of
this inflation rate comes indirectly through the energy price impact on other
sectoral prices. These results are robust among different consumption
baskets.
o
Urban HHs experience the larger inflation rates compared to rural HHs (4.29
vs. 3.79% when simutaneously increasing electricity and petroleum prices by
20%). Rural HHs suffer less direct impact (1.59 vs. 2.17% points) but higher
indirect impact (2.20 vs. 2.13% points) compared to urban HHs.
o
The poor experience slightly less inflationary impact compared to the nonpoor but they are harder hit by indirect impact, especially in rural areas (75%
of the inflation faced by the rural poorest 10% comes from indirect impact).

Inflation components:
o
Fossil fuel delivers directly 50% to the overall inflation rate; food and foodstuff
contribute 20-25%; education, housing and durable purchases 14-20%.
o
The poor suffer the bigger indirect impact, which comes mainly from food and
foodstuff. However, due to much higher share of total expenditure in
residential sector, the richer contribute more to the inflation (the top 3 deciles
79
deliver 52% of the inflation rate while the lowest three deciles make up only
14%).
80
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83
APPENDIX A
Review of the methodologies54
Concerning the interpretation of results, certain inner characteristics of the methodologies
and models used, as well as peculiarities of the data and assumptions used should be
highlighted.
The CGE model estimates impacts across the economy, and includes the estimation of
some policy-responses, such as the substitution (to some extent) of energy for capital and
labor. On the other hand, the CGE analysis:
o
Does not account for other macroeconomic feedbacks, such as the reallocation of
investments in new energy efficient technology (e.g. through private investment) to
offset the growing cost of fossil fuels (apart from the reallocation of subsidy savings).
Worth noting, the avoided costs resulting from these investments may trigger more
consumption and economic growth (i.e., rebound effect).
 Implication: the results are likely overestimating the negative economic impacts of
subsidy removal in the short term, and underestimating the positive medium to
longer-term impacts.
o
Assumes that market dynamics will not change energy prices other than the removal of
subsidies (i.e., prices are largely exogenous). The mix of energy supply is not further
optimized after the introduction of subsidies, an analysis that can be done with LEAP,
and for which the harmonization of assumptions is crucial.
 Implication: the results are likely overestimating the negative economic impacts of
subsidy removal in the short term (prices may not increase as much as indicated),
and underestimating the positive medium to longer-term impacts -although, in this
case, the point made above (i.e., investment to improve energy efficiency) would
54
This part is written by Andrea M. Bassi, Ph.D., Andrea M. Bassi, Ph.D., KnowlEdge Srl (email:
andrea.bassi@ke-srl.com, web: www.ke-srl.com)
84
become less marked and relevant.
o
Tests various scenarios on the reallocation of the avoided public expenditure
(subsidies), to understand the economy-wide impacts of subsidy removal. This analysis
indicates that the reallocation of avoided expenditure mitigates the negative economic
impacts of subsidy removal. On the other hand, it does not provide indications on how
the reallocation should be formalized and implemented (what type of policy instrument,
and for which specific sectors/actors).
 Implication: while the analysis is useful for policy assessment, a more detailed study
of the sectors that are most impacted by the increase in prices has to be carried out
to better understand to which extent the impact takes place across the value chain,
and whether there is room to counter a potential reduction in economic performance
in strategically relevant sectors and vulnerable actors. The I-O analysis fills part of
this gap by analyzing the impacts of subsidy removal on inflation, with a higher
disaggregation of economic sectors and actors.
The I-O model is more detailed than the CGE model in the representation of sectors and
households groups. It focuses specifically on the relations existing between subsidy
removal, energy prices, value chain and inflation. This is done to assess economic impacts
on energy intensive sectors and vulnerable household groups. There are specific
assumptions and methodological constraints to consider when using the results of the I-O
analysis:
o
Results for different levels of price increases are shown to be linear with the scale of
subsidy reform. On the other hand, the higher the change in price, the higher should be
the policy-induced response of the system (e.g., lower consumption, through energy
source substitution, energy efficiency and conservation). As a result, the impact may
become non-linear, with the growth of inflation progressively declining with higher
policy-induced price increases.
 Implication: the results are likely overestimating the negative economic impacts of
subsidy removal in the short term, and underestimating the positive medium to
longer-term impacts.
85
o
The I-O model does not consider technological change, both endogenous (baseline)
and policy induced. A reduction in energy intensity for fossil fuels would reduce the
pressure on energy prices and inflation.
 Implication: inflation may be overestimated, and the results should be interpreted as
the “maximum impact” on inflation from a given amount of subsidy removal. This is
not to be considered a negative criticism, as it provides an upper boundary for
inflation, which is crucial information for policy formulation.
o
How energy prices could change globally is key to the estimation of inflation. For
instance, removing subsidies while global prices decline will have smaller short-term
impacts on the national economy (assuming that national energy prices are influenced
by global markets). This is particularly relevant in the I-O analysis because:
(i) Cost pass through is assumed to be 100%. This may not necessarily be the case,
especially for sectors competing on price with foreign industries.
(ii) Consumers are assumed not to change behavior, regardless of variations in energy
prices. This also may not necessarily be the case.
 Implication: the results of the analysis are likely overestimating policy-induced
inflation. This is possibly true especially for middle and higher income households,
having access to resources to reduce their energy consumption, as well as to a
broader range of (also imported) products.
86
APPENDIX B
The 2007 IO Table codes
Code
In Vietnamese
In English
1
Thóc
Paddy
2
Mía cây
Sugarcane
3
Cây hàng năm khác
Other annual crops
4
Cao su mủ khô
Raw rubber
5
Cà phê nhân xô
Coffee beans
6
Chè lá và chè búp tươi
Tea
7
Cây lâu năm khác
Other perennial plants
8
Trâu, bò
Buffaloes, cows
9
Lợn
Pigs
10
Gia cầm
Poultry
11
Các sản phẩm chăn nuôi khác
Other livestocks & poultry
12
Dịch vụ nông nghiệp và các sản phẩm nông nghiệp
Agricultural services& other agricultural
khác chưa được phân vào đâu
products
13
Gỗ tròn (gỗ khai thác)
Round timber
14
Sản phẩm lâm nghiệp khác; Dịch vụ lâm nghiệp, dịch
Forestry services& other forestry
vụ trồng rừng và chăm sóc rừng
products
15
Thuỷ sản khai thác
Fishery
16
Thủy sản nuôi trồng
Fish farming
17
Than khai thác các loại (than sạch)
Coal
18
Dầu thô
Crude oil
19
Khí đốt tự nhiên
Natural gas
20
Đá, cát, sỏi, đất sét
Stone, sand, gravel, clay
21
Các loại khoáng sản khai khoáng khác còn lại
Other non-metal minerals
22
Dịch vụ hỗ trợ khai thác mỏ và quặng
Mining support services
23
Thịt đã qua chế biến và bảo quản; các sản phẩm từ
Processed, presersed meat & by-meat
thịt
products
24
Thủy sản đã qua chế biến và bảo quản; các sản phẩm Processed, presersed fishery & by-fish
từ thủy sản
25
products
Rau, quả đã qua chế biến và bảo quản
Processed, presersed vegetables& fruits
26
Dầu mỡ động thực vật
Oil & fats
27
Sữa và các sản phẩm từ sữa
Milk & by-milk products
28
Gạo
Rice
29
Bột các loại
Flour
30
Đường
Sugar
87
31
Cacao, sôcôla và mứt kẹo, các sản phẩm bánh từ bột Cocoa, chocolate, candy, cake
32
Cà phê đã qua chế biến
Coffee, processed
33
Các loại thực phẩm khác còn lại (mì ống, mỳ sợi và
Other foodstuff
các sản phẩm tương tự; các món ăn, thức ăn chế biến
sẵn; gia vị, nước chấm, giấm, men bia…)
34
Thức ăn chăn nuôi
Animal feed
35
Rượu
Alcohol
36
Bia
Beer
37
Đồ uống không cồn, nước khoáng
Non-alcohol water, soft drinks
38
Thuốc lá điếu
Cigarettes
39
Sợi các loại
Fiber
40
Sản phẩm dệt các loại
Textile products
41
Trang phục các loại
Costume
42
Da, lông thú đã thuộc, sơ chế; vali, túi xách, yên đệm
Leather, fur, suitcase, bags, saddle
và các loại tương tự.
43
Giày, dép các loại
Shoes, sandal
44
Gỗ (đã qua chế biến) và các sản phẩm từ gỗ
Wood & by-wood products
45
Giấy và các sản phẩm từ giấy
Paper & by-paper products
46
Các sản phẩm in ấn, sao chép bản ghi các loại
Printing products
47
Than cốc và các sản phẩm phụ khác từ lò luyện than
Coke coal & by-products
cốc
48
Xăng, dầu các loại
Refined petroleum
49
Các sản phẩm khác chiết xuất từ dầu mỏ, khí đốt
Other oil, gas products
50
Hoá chất cơ bản
Basic organic chemicals
51
Phân bón và hợp chất nitơ
Fertilizer & nitro compound
52
Plastic và cao su tổng hợp dạng nguyên sinh
Plastic & primary synthetic rubber
53
Sản phẩm hóa chất khác; sợi nhân tạo
Other chemical products
54
Thuốc, hoá dược và dược liệu
Medicine & pharmacy
55
Sản phẩm từ cao su
By-rubber products
56
Sản phẩm từ plastic
By-plastic products
57
Thủy tinh và sản phẩm từ thủy tinh
Glass & by-glass products
58
Xi măng các loại
Cements
59
Sản phẩm từ khoáng phi kim loại chưa được phân vào Other non-metal mineral products
đâu
60
Sắt, thép, gang
Steel & iron
61
Các sản phẩm bằng kim loại khác còn lại
Other metal products
62
Linh kiện điện tử; Máy vi tính và thiết bị ngoại vi của
Electronic devices, computers
máy vi tính
63
Thiết bị truyền thông (điện thoại, máy fax, ăng ten,
Telecomunication equipment (phone,
modem…)
modem..)
88
64
Sản phẩm điện tử dân dụng
Household electric appliances
65
Sản phẩm điện tử khác còn lại và sản phẩm quang
Other electronic products
học
66
Mô tơ, máy phát, biến thế điện, thiết bị phân phối và
Motor, electric generators
điều khiển điện
67
Pin và ắc quy
Cell & battery
68
Dây và thiết bị dây dẫn
Electric conductor
69
Thiết bị điện chiếu sáng
Electric light equipment
70
Đồ điện dân dụng (tủ lạnh gia đình, máy rửa bát, máy Refrigerator, dishwasher,
giặt, máy hút bụi,…)
washingmachine...
71
Thiết bị điện khác
Other electric equipments
72
Máy thông dụng
General-purpose machines
73
Máy chuyên dụng
Special-purpose machines
74
Ô tô các loại
Cars
75
Xe có động cơ rơ moóc (trừ ô tô)
Other motor vehicles
76
Tàu và thuyền
Ships & boats
77
Môtô, xe máy
Motorbikes
78
Phương tiện vận tải khác còn lại
Other transport vehicles
79
Giường, tủ, bàn, ghế
Beds, cabinets, tables, chairs
80
Đồ kim hoàn, đồ giả kim hoàn và các chi tiết liên quan; Jewelry, music instruments, sports
81
82
Nhạc cụ; Dụng cụ thể dục, thể thao; Đồ chơi, trò chơi
equipments, toys
Thiết bị, dụng cụ y tế, nha khoa, chỉnh hình và phục
Medical and dental, orthopedic and
hồi chức năng
rehabilitation equipments
Sản phẩm công nghiệp chế biến khác chưa được phân Other industrial products, repairing&
vào đâu; Dịch vụ sửa chữa và bảo dưỡng máy móc,
maintaining services
thiết bị
83
Điện, dịch vụ truyền tải điện
Electricity
84
Khí đốt, phân phối nhiên liệu khí bằng đường ống
Gas, gas distribution by pipeline
85
Phân phối hơi nước, nước nóng, điều hoà không khí và Distribution of steam, hot water, air
sản xuất nước đá
conditioner, ice production
86
Khai thác, xử lý và cung cấp nước
Water exploitation, processing& supply
87
Quản lý và xử lý nước thải, rác thải
Waste, waste water management&
processing services
88
Xây dựng nhà các loại
House construction
89
Xây dựng công trình đường sắt và đường bộ, Xây
Construction of rail, road, public & other
dựng công trình công ích, Xây dựng công trình kỹ
civil works
thuật dân dụng khác
90
Xây dựng chuyên dụng
Special-purpose construction
91
Bán, sửa chữa ô tô và xe có động cơ khác, Bán, bảo
Services of selling, repairing,
dưỡng và sửa chữa mô tô, xe máy, phụ tùng và các bộ maintaining motor vehicles& auxiliary
89
92
phận phụ trợ của mô tô, xe máy
parts
Bán buôn (trừ ô tô, môtô, xe máy và xe có động cơ
Wholesale & retail (excluding motor
khác), Bán lẻ (trừ ô tô, môtô, xe máy và xe có động cơ vehicles)
khác)
93
Vận tải hành khách đường sắt
Railway passenger transport
94
Vận tải hàng hóa đường sắt
Railway goods transport
95
Vận tải bằng xe buýt; Vận tải hành khách bằng đường Bus & other road passenger transport
bộ khác
96
Vận tải hàng hóa bằng đường bộ; Vận tải đường ống
Road goods & pipeline transport
97
Dịch vụ vận tải hành khách đường thủy
Waterway passenger transport
98
Dịch vụ vận tải hàng hoá đường thủy
Waterway goods transport
99
Dịch vụ vận tải hành khách hàng không
Airline passenger transport
100
Dịch vụ vận tải hàng hoá hàng không
Airline goods transport
101
Dịch vụ kho bãi và các dịch vụ hỗ trợ cho vận tải
Parking& transportation support services
102
Bưu chính và chuyển phát
Postal & delivery services
103
Dịch vụ lưu trú
Residental services
104
Dịch vụ ăn uống
Food services
105
Dịch vụ xuất bản
Publishing services
106
Điện ảnh, truyền hình, ghi âm và xuất bản âm nhạc
Film, music recording& publishing
services
107
Phát thanh, truyền hình
Radio, television services
108
Dịch vụ viễn thông
Telecom services
109
Dịch vụ lập trình máy vi tính, dịch vụ tư vấn và các
Computer programing services,
dịch vụ khác liên quan đến máy vi tính và dịch vụ
consulting& other infomation services
thông tin
110
Dịch vụ tài chính (Trừ bảo hiểm và bảo hiểm xã hội)
Financial (excluding insurance) services
111
Bảo hiểm phi nhân thọ và tái bảo hiểm
Non-life insurance& re-insurance
services
112
Bảo hiểm nhân thọ; Bảo hiểm xã hội
Life & social insurance services
113
Dịch vụ tài chính khác
Other financial services
114
Dịch vụ kinh doanh bất động sản
Real estate business services
115
Dịch vụ pháp luật, kế toán và kiểm toán
Legal, accounting& auditing services
116
Dịch vụ của trụ sở văn phòng; Dịch vụ tư vấn quản lý
Office services, management consulting
services
117
Dịch vụ kiến trúc, kiểm tra và phân tích kỹ thuật
Architectural, testing& technically
analying services
118
Nghiên cứu khoa học và phát triển
Research & development
119
Dịch vụ quảng cáo và nghiên cứu thị trường
Advertising& marketing services
120
Dịch vụ chuyên môn, khoa học và công nghệ khác
Other professional, science &
90
technology services
121
Dịch vụ thú y
Veterinary services
122
Cho thuê máy móc, thiết bị (không kèm người điều
Services for renting machine&
khiển); cho thuê đồ dùng cá nhân gia đình; cho thuê
equipment, personal applicances
tài sản vô hình phi tài chính
123
Dịch vụ lao động và việc làm
Employment service
124
Dịch vụ của các đại lý du lịch, kinh doanh tua du lịch;
Traveling services, tour business,
Dịch vụ hỗ trợ liên quan đến quảng bá và tổ chức tua
traveling support services
du lịch
125
Dịch vụ điều tra và đảm bảo an toàn
Investigation& security services
126
Dịch vụ vệ sinh nhà cửa, công trình cảnh quan
Sanitation services for house &
landscape
127
128
Dịch vụ hành chính, hỗ trợ văn phòng và các hoạt
Adminstration services, office& other
động hỗ trợ kinh doanh khác
business support services
Dịch vụ do hoạt động của Đảng cộng sản, tổ chức
Services of communist party, political-
chính trị - xã hội, quản lý nhà nước an ninh quốc
socio organizations
phòng; bảo đảm xã hội bắt buộc cung cấp
129
Giáo dục và đào tạo (trừ đào tạo cao đẳng, đại học và Education& training (excluding college,
sau đại học)
universities& post-graduates)
130
Dịch vụ đào tạo cao đẳng, đại học và sau đại học
College, universities& post-graduates
131
Dịch vụ y tế
Healthcare services
132
Dịch vụ chăm sóc, điều dưỡng tập trung và dịch vụ trợ Care services
giúp xã hội không tập trung
133
Sáng tác, nghệ thuật và giải trí; Dịch vụ của thư viện,
Arts & entertainment, library services,
lưu trữ, bảo tàng và các dịch vụ văn hoá khác
museum and other services
134
Xổ số, cá cược và đánh bạc
Lottery, betting& gambling services
135
Thể thao; vui chơi giải trí
Sports, entertainment
136
Dịch vụ của các hiệp hội, tổ chức khác
Other services
137
Dịch vụ sửa chữa máy vi tính, đồ dùng cá nhân và gia Repairing services for computers& other
138
đình và dịch vụ phục vụ cá nhân khác
household appliances
Dịch vụ làm thuê công việc gia đình trong các hộ gia
Household services, self-consumption
đình; các sản phẩm vật chất tự tiêu dùng của hộ gia
products, international organization
đình; Dịch vụ của các tổ chức và cơ quan quốc tế
services
91
APPENDIC C
The inflationary impact using GSO consumption basket
%
Petroleum price
Electricity price
Petroleum and electricity
increase by 20%
increase by 20%
price increase by 20%
Direct Indirect Total Direct Indirect Total
Direct Indirect
Total
consumption impact impact impact impact impact impact impact impact impact
Food
0.082
0.000
1.600
1.600 0.000
0.669
0.669
0.000
2.269
2.269
Foodstuffs
0.244
0.000
2.602
2.602 0.000
0.863
0.863
0.000
3.465
3.465
Outside eating
0.074
0.000
0.882
0.882 0.000
0.496
0.496
0.000
1.378
1.378
Electricity*
0.024
0.000
0.000
0.000 20.00
0.000
20.00 20.000
0.000
20.000
Petroleum*
0.061
20.000 0.000
20.00 0.000
0.000
0.000 20.000
0.000
20.000
Telecommunication
0.027
0.000
0.987
0.987 0.000
0.388
0.388
0.000
1.375
1.375
Equipment and housewares
0.087
0.000
1.059
1.059 0.000
0.699
0.699
0.000
1.758
1.758
Apparel, headwear and footwear
0.073
0.000
1.494
1.494 0.000
1.214
1.214
0.000
2.708
2.708
Beverages and Tobacco
0.040
0.000
1.705
1.705 0.000
0.844
0.844
0.000
2.549
2.549
Medicine and Health
0.056
0.000
1.044
1.044 0.000
0.768
0.768
0.000
1.812
1.812
Education
0.057
0.000
0.795
0.795 0.000
0.703
0.703
0.000
1.498
1.498
Cultural, recreation and tourism
0.038
0.000
1.109
1.109 0.000
0.809
0.809
0.000
1.918
1.918
Other goods and services
0.033
0.000
1.653
1.653 0.000
0.931
0.931
0.000
2.584
2.584
construction materials*
0.076
0.000
1.467
1.467 0.000
0.939
0.939
0.000
2.406
2.406
Transport*
0.028
0.000
3.793
3.793 0.000
0.634
0.634
0.000
4.427
4.427
1.22
1.55
2.77
0.73
1.21
1.70
2.27
3.97
Housing, water, gas and
The inflation rate
0.48
Notes: Electricity and Petroleum consumption shares are defined by the 2010 VHLSS consumption basket (2.4
percent and 6.1 percent, respectively). Then the consumption sectors of Housing, water, gas, construction
materials and Transport are calculated by subtracting the corresponding energy shares from those of
sectors defined by GSO.
92
APPENDIX D
Literature Reviews on Mitigation Measures55
Country
Reform
Year
Mitigation
Method
Target Groups
Measures
Amenia
Electricity
price reform
1999 Poverty Family Cash transfer of dram 1,450
Benefit
(approximately US$2.70)
Poor households (18-25%) means tested
conditional on electricity bill
payment and efficient consumption
(1% of GDP)
Armenia
Electricity
1999 Cash transfers Two one-off cash transfers to help Poverty Family Benefit households
price reform
cope with higher electricity prices
and other households (9%)
considered to have difficulties
paying their bills
Armenia
Electricity
price reform
1999 Dual-rate
Allow households to benefit from
electricity
discounted night tariffs, and
meters
remove the need for energy
Low-income households
suppliers to use high cost
generators during peak times of
use
Brazil
Electricity
sector
1993 Targeted fuel
subsidy
privatization
Subsidize the supply of fuels to the Inefficient thermal power plants of
inefficient thermal power plants of Amazonia, a politically sensitive
Amazonia, financed by a levy on
region
electricity tariffs
Brazil
Electricity
sector
1995 Cross
subsidies
Provide lower electricity tariffs for
Low-income households
low-income households
privatization
Brazil
Fuel price
liberalization
2001 Subsidies for
ethanol
The government introduced a new
tax on the importation and
producers and marketing of petroleum products to
the
raise revenue
transportation
costs of
hydrocarbons
Brazil
Fuel price
liberalization
2001 LPG used by
The government introduced a new Low-income families
low-income
tax on the importation and
families
marketing of petroleum products to
raise revenue
55This
Appendix is prepared by Nguyen Tu Chi, from IISD-GSI.
93
Brazil
Fuel price
liberalization
2002 Subsidies for
Thermal power plants in
the supply of
Amazonia, a politically sensitive
fuels to thermal
region
power plants in
Amazonia
Brazil
Fuel price
2003 Bolsa Familia
Conditional cash transfers
Low-income families (means test)
liberalization
Brazil
Electricity
sector
rural people, funded by levies on
privatization
electricity tariffs
Dominican Electricity
Republic
Ghana
2003 Free electricity Provide free electricity to 10 million 10 million rural people
2009 BonoLuz
subsidy
consumers to claxim a subsidy for
reduction
the use of the first 100 kWh
Fuel price
LEAP
deregulation
Ghana
Ghana
Use coupons for the poorest
Provide cash transfers to
National Health Indigent exemption for the
deregulation
Insurance
registration and coverage of very
Scheme
poor households
deregulation
The bottom 20% of the poor
households in extreme poverty
Fuel price
Fuel price
Low-income families
2005 Assistance to
the poor
Elimination of fees for state-run
The bottom 20% of the poor
The poor
primary and secondary schools;
increase in public-transport buses;
price ceiling on public-transport
fares; funding for health care in
poor areas; increase in the
minimum wage; and investment in
electrification in rural areas.
India
Kerosene
2009 Targeted
subsidy
Public
removal
Distribution
Allocate PDS kerosene to ration
Quote differ by income and LPG
card holders
connections
Transfer cash directly to the poor
People below the poverty line
Distribute two payments of
Poor households (19.2 million)
System (TPDS)
India
Kerosene
and LPG
2011 Direct Cash
Subsidies
subsidy
removal
Indonesia
Fuel price
increase
2005 Unconditional
Cash Transfer– IDR300,000 (around US$30)
Bantuan
directly to poor families
Langsung
Tunai (BLT)
Indonesia
Kerosene
2009 Conversion
Freely distribute a starter pack,
subsidy
from Kerosene consisting of a stove and a
removal
to LPG
20 million hhs
compact-built 3-kg gas cylinder;
then reduce distribution of
94
kerosene in targeted areas
Iran
Indirect oil
subsidy cut
2007 Electronic
cards system
The price of rationed gasoline was Rationing required the
well below the full price.
implementation of a
for gasoline
comprehensive vehicle registration
rationing and
system and personalized
quotas
distribution and management of
the gasoline quotas.
Iran
Indirect oil
subsidy cut
2010 Unconditional
About 80% of the revenue from
All population
Cash Transfer price increases was redistributed
to households as bi-monthly cash
transfers
Iran
Indirect oil
subsidy cut
2010 Enterprise
support
About 20% of the revenue from
7,000 enterprises deemed to be
price increases was provided to
affected by the reform
enterprises to support restructuring
for reducing their energy intensity
(direct assistance and sales of
limited quantities of fuels at
partially subsidized rates)
Iran
Indirect oil
subsidy cut
2010 Multitier tariffs Unit tariffs were set using
on electricity,
escalating schedules differentiated
natural gas,
by quantity used and region. Large
and water
household consumers were
Small users, mostly the poor
charged prices marginally higher
than in international markets
Jordan
Oil subsidy
removal
2005 Compensation Minimum wage increase; one-time Multiple groups
package (7% of bonus to low-income government
GDP)
employees; cash transfers to nongovernment employees and
pensioners; tax exemptions for 13
basic foodstuffs; projects to
combat unemployment and
poverty
Jordan
Oil subsidy
removal
Jordan
1986 National Aid
Fund
Provide cash social assistance to
The poor
the poor
Power sector 2008 Lifeline tariff
Lifeline tariff for those using less
Small consumers (less than 160
reform
than 160 kWh per month was
kWh/month)
maintained with the help of crosssubsidization
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Kenya
Power sector 2003 Mitigating
Rural electrification program that
rationalizatio
has helped increase the number of
measures
n and pricing
connections from 650,000 in 2003
reform
to 2 million at present; revolving
Multiple groups
fund for deferred connection fee
payments; commercial bank loans
for connection fees; life-line tariff
for households that consume less
than 50 kWh per month, which is
cross-subsidized by rates imposed
on larger consumers; crosssubsidies from urban to rural
consumers, as tariffs are uniform
across these areas.
Malaysia
Fuel price
2008 Cash transfers Cash grants to fishermen and
increase
Vehicle owners
vessel owners to compensate in
part for fuel price increase; rebates
to private vehicle owners,
especially smaller vehicles
Mauritania Formulabased pricing
2011 Emergency
relief measures - comprised mostly reversible
for petrol
Mauritania Formulabased pricing
UM40 billion (3.4 percent of GDP) The poor
measures
2012 Unconditional
Each household receives UM
15,000 households in four rural
Cash Transfer 15,000 monthly (equivalent to half areas deemed to have high food
for petrol
of the legal minimum wage) via a
insecurity
bank transfer
Mexico
Electricity
Tariff subsidy
tariff reform
Tariffs are subsidized for
Customers who consume less and
customers who consume less and reside in warm areas
reside in warm areas
Moldova
Electricity
Nominative
Cash transfer which helps cover
tariff increase
Targeted
the cost of electricity, gas, district
Categorical privileges
Compensation heating, hot water, cold water,
(NTC)
Namibia
Fuel price
deregulation
2008 Mitigating
measures
coal, and firewood
Zero-rate VAT on selected food
Multiple groups
items; rebate facilities for food
importers; food distribution
program to feed the most
vulnerable; subsidized rural pump
prices by subsidizing
transportation costs to remote
areas
Niger
Fuel subsidy
Tickets
Direct subsidy to the transport
reduction
modérateurs
sector (less than 0.1 percent of
Transport sector
GDP)
96
Nigeria
Fuel subsidy 2011 Urban mass
Increase mass transit availability
reduction
by facilitating the procurement of
transit
Established bus operators
diesel-run vehicles (subsidized
loans, reduced import tariffs, etc.) 1600 buses
Nigeria
Nigeria
Fuel subsidy 2011 Maternal and
Expand conditional cash transfer
reduction
child health
program; and upgrade facilities at
services
clinics
Pregnant women in rural areas
Fuel subsidy 2011 Public works
Provide temporary employment in Poor youth and women
reduction
environmental projects and
maintaining education and health
facilities
Nigeria
Fuel subsidy 2011 Vocational
Establish vocational training
reduction
centers to help tackle the problem
training
Youth
of youth unemployment
Pakistan
Fuel and
Benazir Income Cash transfers to help the poorest The poor
electricity
Support
families and to cushion the
price
Programme
negative effects of price increases
increase
(BISP)
Philippines Power sector 2006 Lifeline tariff
restructuring
structures
A lifeline tariff schedule at a
3 million poor households
subsidized rate for poor
households (5-50% discount)
Philippines Oil
deregulation
2008 Pro-poor
Financed by windfall VAT revenue The poor
spending
from high oil prices and included
programs
electricity subsidies for indigent
families, college scholarships for
low-income students, subsidized
loans to convert engines of public
transportation to less costly LPGs,
and subsidized rice to low-income
families; also a conditional cash
transfer program
Poland
Coal reform
1998 Social and
Provide welfare benefits to
labor market
dismissed workers (especially
programs
younger coal workers) while they
33,000 workers
transitioned into retirement or into
new jobs, including soft loans for
the establishment of a business,
and services provided from newly
established employment agencies.
Peru
Electricity
tariff increase
Lifeline tariff
Subsidize households if they use
less than 100 kWh per month
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Peru
Fuel and
Provide households with cash
Poor households in vulnerable
electricity
2005 Juntos
transfers in the short run and to
communities
tariff increase
improve access to education and
health services in the long run
Turkey
Oil price
1999 Tax exemption Forego both value added and
liberalization,
for LPG
state-owned
consumption
All population
pecial consumption tax for LPG
enterprise
privatization,
and
competitive
energy
market
Turkey
Oil price
2006 Tax exemption Exemption from value added tax
liberalization,
for public
state-owned
transportation
and excise tax
Public transport companies owned
and managed by municipalities,
villages, or special provincial
enterprise
administrations
privatization,
and
competitive
energy
market
Turkey
Oil price
2007 Rebate for
The amounts of aid are calculated Farmers
liberalization,
diesel used in
according to the area of the land
state-owned
agriculture
used in growing specified crops,
enterprise
and paid according to a schedule
privatization,
defined by the cabinet
and
competitive
energy
market
Uganda
Power tariff
Lifeline tariff
Lifeline tariff (USh 100/kWh) for
adjustments
structures
poor domestic consumers for
Poor domestic consumers
power consumption of up to 15
kWhs a month.
Yemen
Fuel price
increase
1996 Social Welfare Provide conditional cash transfers All population
Fund
to households - coverage was
expanded and transfers increased
in line with subsidy reform period
Yemen
Fuel price
increase
2000 Conversion
Promote the conversion from
from kerosene kerosene to LPG for residential
to LPG
use
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Yemen
Fuel price
Public Works
increase
Provide short-term employment
Small-scale contractors
and support through a laborintensive public works program
Yemen
Fuel price
Social Fund for Promote community and small-
increase
Development
The poor
and microenterprise- development
and provide short-term
employment for both the transitory
and chronically poor
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