A Path to Prosperity: Preparing Our Workforce

Transcription

A Path to Prosperity:
Preparing Our Workforce
ACKNOWLEDGEMENTS
The San Diego Workforce Partnership wants to thank all of those who contributed to the development of
A Path to Prosperity: Preparing Our Workforce:
The SourcePoint Project Team, who conducted the research and analysis, and drafted the report:
Marney Cox
Director and Chief Economist
Matthew Eary
Associate Economist
Oliver Kaplan
Associate Economist
The San Diego Workforce Partnership Team, who managed the project, edited the report, and oversaw the
production process:
Terri Bergman
Director of Research
Brandi Turner
One-Stop Marketing Specialist
The project’s Advisory Committees, who provided guidance over the course of the research, and reviewed
drafts of the publication:
Sundari Baru
Center on Policy Initiatives
Tony Bingham
San Diego Workforce Partnership
Preston Chipps
San Diego State University
Don Cohen
San Diego - Imperial Counties Labor Council
Kelly Cunningham
San Diego Regional Chamber of Commerce
Tim Dong
MiraCosta Community College
Jim Gerber
Alexander Gonzalez
California State University, San Marcos
Michael Jenkins
City of San Diego, Community and Economic Development
Kelly Jenkins-Pultz
U.S. Department of Labor
John Keyon
Carolyn Lee
University of California, San Diego Extension
Cheryl Mason
California Employment Development Department
Gary Moss
Dana Quittner
Grossmont/Cuyamaca Community College District
Doug Sawyer
Bank of America
Tom Sheffer
San Diego Defense and Space Technology Consortium
Joann Stang
Solar Turbines
Michelle Sterling
Qualcomm
Deanna Weeks
East County Economic Development Corporation
And San Diego Workforce Partnership staff – Mark Cafferty, Georgieann Clem, Ron Oliver, Kathy Patoff,
and Celina Shands – as well as San Diego Association of Governments staff – Ed Schafer, Terry Beckhelm,
Kim Mathis, Beth Jarosz, and Lori Greenberg – who provided technical assistance.
The San Diego Workforce Partnership
is a proud member of America’s Workforce Network.
This publication was paid for by the State of California, Rapid Response funds, July 2001 - June 2003.
Contents of this plan are the property of the San Diego Workforce Partnership, Inc. (2002©).
A Path to Prosperity:
Preparing Our Workforce
Prepared By SourcePoint
December 2002
FOREWORD
A Path to Prosperity: Preparing Our Workforce is a watershed publication for the San Diego region.
It provides us with a vision of our economic future, and a choice in how we will shape that future.
Will we adopt policies that support economic expansion and enable all San Diegans to reap the
benefits of a strong economy, or will we leave businesses without a trained and qualified workforce
and more than a quarter of our workers earning less than a “living wage”?
A Path to Prosperity leaves us “cautiously optimistic” about the outlook for our region’s future.
Optimistic, because we have a diverse economy, with a strong projected growth in employment,
along with an expansion in the proportion of high income jobs available for our region’s residents.
Cautious, because even today we have difficulty preparing our residents to fill the region’s available
high-tech, high wage jobs. As the proportion of these jobs in our regional economy increases, our
ability to match trained individuals to these available good jobs will be tested even further.
We are also cautious because of the wide division in our region between the “haves” and “have
nots.” The San Diego regional economy will never stop producing low wage jobs, but we, as a
community, need to do better at helping those in lower-paying jobs acquire the skills they need to
advance to better jobs paying higher wages.
A Path to Prosperity is a “call to action.” It is a call to government leaders to adopt the policies
necessary to support the expansion of high-tech, high wage jobs. It is a call to business leaders to
support the education and training of their own employees. It is a call to our region’s residents –
both current and future workers – to seek and acquire the education and training they need to be
productive members of our workforce. But, most of all, it is a call to the region’s educators and
trainers to meet the needs of San Diego employers and San Diego residents in two key areas:
First, to prepare San Diegans for the high-tech, high wage jobs our burgeoning technology sector is
producing. Our region’s employers should not have to look outside of the region – and outside of
the country – for qualified employees. Our region’s best employment opportunities should be
provided to our own residents! We need more education and training opportunities preparing
individuals for jobs in industries and occupations where employee shortages exist. And we need to
make sure that these education and training opportunities provide individuals with the skills
employers say are needed. Training and employing our own residents not only benefits them, it
reduces the number of workers hired from outside the region, and lessens the burden the region’s
growth is placing on local resources and housing.
Second, but no less important, to develop education and training opportunities that will allow lowwage earners to climb “career ladders” to economic security. We need to identify these ladders, and
develop training programs that support individuals’ progress up these ladders. And we need to
offer these education and training programs in places and at times that are convenient for working
individuals, and at prices that low-wage workers can afford.
San Diego County’s civic, business, and community leaders frequently pull together to meet tough
challenges. We are optimistic that this will be the case here.
Supervisor Ron Roberts
Policy Board
Victoria Hobbs
Workforce Partnership Board
Joseph W. Craver
Workforce Investment Board
TABLE OF CONTENTS
Foreword.....................................................................................................................................xi
Executive Summary ....................................................................................................................1
Introduction ............................................................................................................................. 3
Organization of Report ............................................................................................................ 5
The Demand for Jobs ............................................................................................................... 5
The Supply of Workers ............................................................................................................. 6
Identifying Gaps ....................................................................................................................... 8
Meeting Workforce Development Challenges .......................................................................... 9
Earning A Living Wage in the San Diego Region .................................................................... 10
Communities At Risk .............................................................................................................. 11
Summary of Findings and Recommendations ......................................................................... 13
Workforce Development and Career Ladder Resources on the Internet:................................. 15
Chapter 1: The Demand for Jobs: Employment and Occupational Projections..................17
An Overview of Current and Forecast Economic and Employment Growth ............................. 19
Employment in the San Diego Region’s Economic Clusters ..................................................... 25
Analysis of Forecast Occupational Growth.............................................................................. 34
Chapter 2: The Supply of Workers: Labor Force Projections ................................................41
Population and Migration ...................................................................................................... 43
Size and Composition of the Current and Forecast Labor Force .............................................. 46
Labor Force Participation ....................................................................................................... 53
Education and Skill Levels of the San Diego Labor Force ........................................................ 55
Workforce Barriers ................................................................................................................. 57
Chapter 3: Identifying Gaps: Comparing Labor Supply and Job Demand ..........................61
Supply and Demand Mismatches in the Regional Labor Market ............................................. 63
Labor Supply and Educational Attainment ............................................................................. 65
Labor Supply and Demand in Traded Clusters......................................................................... 67
Chapter 4: Workforce Development Challenges:
Meeting Skill and Training Requirements..............................................................................75
The Value of Training............................................................................................................. 77
Current and Forecast Education and Training Requirements for the San Diego Region .......... 78
Current Training Requirements of Traded Clusters ................................................................. 80
Skill Deficits in Selected Cluster Occupations .......................................................................... 83
Regional Education and Training Capacity ............................................................................. 85
iii
Additional Opportunities for Meeting Training Requirements ............................................... 88
Chapter 5: Earning A Living Wage: The Role of Workforce Development .........................91
San Diego’s Experience with a “Living Wage”........................................................................ 93
Methods for Calculating a Living Wage.................................................................................. 94
Analysis of Living Wage Methodologies ................................................................................. 97
Living Wage Estimate for San Diego....................................................................................... 98
Basic Budgets for Other Family Types ....................................................................................102
Keeping Up with Inflation .....................................................................................................103
The Characteristics of Low Wage Earners ..............................................................................103
Living Wage Earners in the San Diego Region .......................................................................104
Workforce Development Policies to Help Individuals Earn a Living Wage ..............................106
Income Mobility and the Role of Education and Training ......................................................110
Chapter 6: Communities at Risk: Sub-regional Labor Market Imbalances .......................113
Maps ...................................................................................................................................115
Detailed Community Profiles .................................................................................................138
Appendices ..............................................................................................................................149
Appendix A
2001 Major Employers in the San Diego Region by Major Statistical Area .......................153
Appendix B
2000 Census Labor Force and Unemployment Data .........................................................157
Appendix C
Training Providers in the San Diego Region.....................................................................161
Appendix D
San Diego Basic Needs Budget Technical Information .....................................................165
Sources for Expenses of Basic Needs Budgets...................................................................166
Comparison of Percent Share of Components Between Single Adult Budgets
for the San Diego Region ................................................................................................167
Appendix E
Career Ladders in the Business Services Cluster in the San Diego Region, 2001 ................171
Career Ladders in the Defense and Transportation Manufacturing Cluster
in the San Diego Region, 2001 ........................................................................................172
Appendix F
“Soft Skills”.....................................................................................................................175
Glossary ..................................................................................................................................177
iv
LIST OF FIGURES
Figure 1.1
Economic and Employment Indicators, San Diego Region, 2002-2010...................... 20
Figure 1.2
Industries with the Largest Forecast Growth in Employment,
San Diego Region, 2000-2010 .................................................................................. 21
Figure 1.3
Industries with the Fastest Forecast Growth in Employment,
San Diego Region, 2000-2010 .................................................................................. 22
Figure 1.4
Industries with the Largest Forecast Employment Declines,
San Diego Region, 2000-2010 .................................................................................. 23
Figure 1.5
Industries with the Sharpest Forecast Rate of Decline in Employment
San Diego Region, 2000-2010 .................................................................................. 24
Figure 1.6
Employment Growth by Traded Clusters, San Diego Region, 2000-2010 .................. 26
Figure 1.7
Employment in Traded Industry Clusters, San Diego Region, 2000-2010 .................. 28
Figure 1.8
Job Growth in Traded Industry Clusters, San Diego Region, 2000-2010.................... 30
Figure 1.9
Rates of Growth in Employment in Traded Industry Clusters,
San Diego Region, 2000-2010 .................................................................................. 31
Figure 1.10 Payroll, Wages, and Firm Size for Traded Industry Clusters,
San Diego Region, 2000-2010 .................................................................................. 32
Figure 1.11 Forecast Growth in Traded Cluster Employment by Average Wage,
San Diego Region, 2000-2010 .................................................................................. 33
Figure 1.12 Occupational Employment and Wages (2000$), San Diego Region, 2000-2010 ........ 35
Figure 1.13 Five Occupations with the Most New Jobs, San Diego Region, 2000-2010................ 36
Figure 1.14 Five Fastest Growing Occupations, San Diego Region, 2000-2010 ............................ 37
Figure 1.15 Five Occupations with the Fewest New Jobs, San Diego Region, 2000-2010............. 38
Figure 1.16 Five Slowest Growing Occupations, San Diego Region, 2000-2010 ........................... 39
Figure 1.17 Occupational Growth by Wage Category, San Diego Region, 2000-2010 ................. 40
Figure 2.1
Population, Migration and Labor Force Growth, San Diego Region, 2000-2010 ......... 44
Figure 2.2
Changes in the Civilian Working-Age Population by Age, Ethnicity and Gender,
San Diego Region, 2000-2010 .................................................................................. 44
Figure 2.3
Annual Population Change Due to Migration, San Diego Region, 2000-2010 .......... 46
Figure 2.4
Labor Force Growth, San Diego Region, 2000-2010 ................................................. 47
v
Figure 2.5
Composition of the Labor Force, San Diego Region, 2000-2010 ............................... 48
Figure 2.6
Labor Force Composition in 2010 by Age, Ethnicity and Gender,
San Diego Region, 2010 .......................................................................................... 49
Figure 2.7
Labor Force by Age Groups, San Diego Region, 2000-2010 ...................................... 50
Figure 2.8
Labor Force by Gender, San Diego Region, 2000-2010 ............................................. 51
Figure 2.9
Percent Share of Labor Force by Ethnicity and Gender,
San Diego Region, 2000-2010 .................................................................................. 52
Figure 2.10 Labor Force Participation Rates by Ethnicity and Gender,
San Diego Region, 2000-2010 .................................................................................. 53
Figure 2.11 Labor Force Participation Rates by Age, Ethnicity and Gender,
San Diego Region, 2000 .......................................................................................... 53
Figure 2.12 Forecast Labor Force Participation Rates by Gender and Age,
San Diego Region, 2010 .......................................................................................... 54
Figure 2.13 Percent of Change in Labor Force Participation Rates by Age, Ethnicity and Gender,
San Diego Region, 2000-2010 .................................................................................. 55
Figure 2.14 Educational Attainment Levels of the Over 25 Population,
San Diego Region and the U.S., 1990-2000. ............................................................. 56
Figure 2.15 Enrolled Students, San Diego Region, 2000-2010..................................................... 57
Figure 2.16 Percent of High School Students that Drop Out of School Annually by Race/Ethnicity,
San Diego Region, 1997/98-1999/00......................................................................... 59
Figure 2.17 Rate of Births to Teens Ages 15-17 by Race/Ethnicity,
San Diego Region, 1997-1999 .................................................................................. 60
Figure 3.1
Labor Force and Employment, San Diego Region, 2000-2010................................... 64
Figure 3.2
Labor Force, San Diego Region, 1990-2010 .............................................................. 64
Figure 3.3
Unemployment Rate, San Diego Region, 2000-2010 ................................................ 65
Figure 3.4
Labor Supply and Demand by Education Level, San Diego Region, 2000-2010............. 66
Figure 3.5
H-1B Visa Use in Traded Clusters, San Diego Region, 2000 ....................................... 68
Figure 3.6
Labor Supply Shortages in Traded Clusters by Occupation,
San Diego Region, 2000 .......................................................................................... 72
Figure 4.1
Average Annual Wage by Education and Training Levels,
San Diego Region, 2000 .......................................................................................... 78
Figure 4.2
Occupational Employment by Required Education Level,
San Diego Region and the U.S., 2000-2010 .............................................................. 79
Figure 4.3
Education Requirements of Selected Occupations with Large Employment Growth,
San Diego Region, 2000-2010 .................................................................................. 80
Figure 4.4
Education and Training Requirements for Traded Clusters by Education Level,
San Diego Region, 1999 .......................................................................................... 82
vi
Figure 4.5
Skill Deficits in Selected Cluster Occupations ........................................................... 84
Figure 4.6
Degrees Awarded by Academic Discipline, San Diego Region, 1998......................... 85
Figure 4.7
Higher Education Degrees Awarded per 1,000,000 People,
San Diego Region and the U.S., 1998....................................................................... 86
Figure 4.8
Number of Degrees Awarded by Higher Education Institutions
San Diego Region, 1998 .......................................................................................... 87
Figure 5.1
Basic Needs Budget – Single Adult, San Diego Region, 2001.................................... 99
Figure 5.2
Percent Share of Budget Components ....................................................................100
Figure 5.3
Comparison of Working Poor Wage Rates, San Diego Region (2001$) ....................101
Figure 5.4
WOW Self-Sufficiency Standard Basic Budgets for Various Family Types,
San Diego Region, 2001 .........................................................................................102
Figure 5.5
Percent of Jobs in Occupations that Earn Less than a Living Wage
by Required Level of Education and Training, San Diego Region, 2001...................105
Figure 5.6
Education and Training Requirements for Occupations Where More than
75 Percent of Employees Earn Below the Living Wage, San Diego Region, 2001 .....106
Figure 5.7
Absolute Income Mobility by Quintile, State of California, 1988-2000 ....................111
Figure 5.8
Earnings Growth by Quintile, State of California, 1988-2000 ..................................111
vii
LIST OF MAPS
Map 1
Labor Force, 2000, by Jurisdictions and Community Planning Areas........................116
Map 2
Labor Force Growth, 2000 to 2010,
by Jurisdictions and Community Planning Areas .....................................................117
Map 3
Employment, 2000, by Jurisdictions and Community Planning Areas ......................119
Map 4
Employment Growth, 2000 to 2010,
Map 5
Balance Between Labor Force Growth and Employment Growth, 2000 to 2010,
Map 6
Commute Times to Highest Paying Technology Clusters .........................................123
Map 7
Training Providers, 2000...........................................................................................125
Map 8
Training Providers, 2000, by Jurisdictions and Community Planning Areas ..................126
Map 9
Proportion of Workers with Low Educational Attainment, 1990,
Map 10
Proportion of Highly Educated Workers, 1990,
Map 11
Proportion of Jobs with Mean Wage Less than the Regional Living Wage, 2000,
Map 12
Labor Force Participation Rates, 2000,
Map 13
Average Adjusted Gross Income, 1998, by Zip Code................................................134
Map 14
Proportion of Tax Filers Receiving the Earned Income Tax Credit, 1998,
by Zip Code ............................................................................................................135
Map 15
Utilization of the Federal Earned Income Tax Program, 1998,
by Zip Code ............................................................................................................136
viii
LIST OF PROFILES
Profile 1
The City of Chula Vista ...........................................................................................139
Profile 2
The City of Carlsbad ...............................................................................................141
Profile 3
The Community of San Ysidro ................................................................................143
Profile 4
The Community of Carmel Valley ...........................................................................145
Profile 5
The Community of Pacific Beach.............................................................................147
ix
EXECUTIVE SUMMARY
EXECUTIVE SUMMARY
INTRODUCTION
It is no secret that San Diego is a region that prizes its high quality of life. While our beautiful
location and climate are part of what makes San Diego a great place to live, our quality of life also
greatly depends on the region’s economic vitality. San Diego residents want good jobs, and
employers want skilled workers.
The recession of the early 1990s served to remind us that our economic prosperity, as stated in these
terms, should not be taken for granted. During the recession, the down-sizing of the region’s
defense industry resulted in economic contraction, high levels of unemployment, and many longtime residents leaving the region to seek work elsewhere. In search of solutions, economists
identified sixteen “traded”, or export-oriented clusters as key elements of a strategy to regain our
economic prosperity1. These traded clusters are not constrained by the size of the local market and
contain many highly productive industries that provide better-paying jobs, act as economic drivers
that bring money into the region, and drive the expansion of local sectors that provide support
services. A Path to Prosperity builds on past cluster studies supported by the Workforce Partnership
to identify labor shortages and skill deficiencies with specific attention to clusters2.
Growth in traded cluster industries has both aided our economic recovery and laid the groundwork
for future opportunities, but it has also placed new demands on our regional labor market. Training
our residents to make sure they are qualified for job opportunities in our traded clusters makes sense
for improving the entire region’s standard of living.
A Path to Prosperity addresses the role of workforce development in meeting our labor market
needs and keeping the region’s economic engine running smoothly into the next decade 3. The
study provides information on the current and future gaps between the skill set of the labor force
and the skill needs of the region’s still-restructuring economy. It evaluates labor market dynamics
in the San Diego region by comparing profiles of labor supply and employment demand in 2000
with the forecast labor force and employment in 2010. It tracks the changes in demographic
composition, education levels, and skills required of the labor force, providing a ten-year outlook
for the development of the region’s workforce. Also, because the inability to identify fluid career
ladders has frustrated workers and training providers alike, the study analyzes several labor market
equity issues. In addition to this written report, a labor market information database was
1
“San Diego Regional Economic Prosperity Strategy, Toward a Shared Economic Vision for the San Diego
Region”. San Diego Association of Governments, July 1998. “San Diego Regional Employment Clusters: Engines
of the Modern Economy”. San Diego Association of Governments, INFO, May-June 1998.
2
“The San Diego Region’s Key Industry Clusters: A Labor Market Survey 2001”. The San Diego Workforce
Partnership, 2001.
3
The study was prepared with the assistance of a Policy and a Technical Advisory Committee.
3
developed. The database can be accessed through the San Diego Workforce Partnership’s
website 4.
At present, there are two prominent labor supply problems in the regional labor market. First, at one end
of the spectrum, there are a disproportionately large number of low-wage jobs; while at the other end,
there is a shortage of high-skill workers. Second, there is a gap between jobs with high skill requirements
and the ability of the local labor force to take advantage of them.
While the structure of the region’s economy is expected to continue to support a disproportionately
large number of low-wage jobs, understanding the magnitude, type, and geographic location of
these mismatches will help answer the question, “What types of training programs does the region
need so that local workers can take advantage of the job opportunities the economy provides?” Our
research here seeks to better understand how to help individuals move up the career ladder. With
improved targeting of training programs, low-wage residents can more easily improve their skills and
productivity, enabling them to earn higher wages and share in the increasing prosperity of the region.
Furthermore, training and career ladders are consistent with current regional economic development
strategies. Training and career ladders can prepare employees for positions with high skill requirements
and provide economic mobility, which allows low-skill, low-income workers to join the middle-class.
Training provides workers with the opportunity to learn the skills they need to get better jobs. Fluid
career ladders create opportunities for hard-working residents to use those newly acquired skills.
The impetus behind training strategies is that higher skill levels increase worker productivity. Michael
Porter, a professor at the Harvard Business School, emphasizes the connection between productivity and
a rising standard of living. He notes that, “The ability to earn a high and rising standard of living
depends on increasing productivity, which in turn depends on innovation…a critical driver of innovation
output is the quality of the regional environment in which firms operate”5. One major component of a
regional environment that can help create and retain highly productive firms is high-quality human
resources. Time and again when asked what factors influence their business location decisions, hightechnology executives most often cite access to a diverse and skilled talent pool. Forbes magazine
reported that while old economy industry clusters formed around suppliers, factories, and
transportation, new economy clusters are made out of brainpower6. Additionally, a talented labor force
with ample employment opportunities will see its standard of living rise.
The mismatch between high-skilled jobs and the ability of the local labor force to take advantage of
them has resulted in labor shortages in the economy, especially of high-skill workers. Cluster studies
recently completed for the Workforce Partnership revealed that there are significant amounts of
employment opportunities for high-skill workers currently left unfilled in traded clusters. Evidence
suggests that some clusters are currently trying to meet the demand for skilled labor by “poaching”, or
importing workers from outside the local labor pool. This is seen in employers’ growing use of the H-1B
visa program to hire foreign nationals. A continuing challenge is to identify the necessary skills and
training for these positions so that more local workers will be prepared to fill them.
4
The Labor Market Information website is located at:
http://jobs.sandiegoatwork.com/sdaw/emjw_jw.jsp#Industry.
5
Porter, Michael E. Clusters of Innovation Initiative: San Diego. Council on Competitiveness, 2001.
6
Tim Fergeson, “Sun, Fun and Ph.D.’s Too”, Forbes, May 31, 1999.
4
ORGANIZATION OF REPORT
Following the Executive Summary, Chapter 1, Demand for Jobs, looks at the current economy and
growth in employment opportunities. Next, Chapter 2, Supply of Workers, profiles the labor force
according to demographic characteristics with emphasis on the type of growth expected. In Chapter
3, Identifying Gaps, the demand and supply profiles are compared to identify occupations and
industries that may experience any shortages or surpluses of labor. Then, in Chapter 4, Workforce
Development Challenges, the particular skill sets that may be lacking in the labor force for those
occupations and industries are identified. Once the requisite skills for the region are known, the
region’s training capacity is evaluated to determine whether it is or will be sufficient to fill any skill
gaps. Chapter 5, Earning A Living Wage, discusses labor market equity, including an estimate of the
local living wage and research on the dynamics between income mobility and workforce
development strategies. Chapter 6, Communities At Risk, is a sub-regional analysis used to identify
communities in the San Diego region in need of increased workforce development programs.
THE DEMAND FOR JOBS
The San Diego regional economy is projected to create over 184,000 new employment opportunities
by 2010. The indicators on the type of growth the regional economy will experience suggest that
employment is becoming increasingly more knowledge-based – a transition toward an information
economy. Employment is also becoming increasingly service-oriented. Many traditional
manufacturing industries and occupations will continue to stagnate or decline as the regional
economy follows the U.S. economy in moving away from the production and assembly of physical
goods and toward the provision of services and the production of intellectual property. Many of
these employment trends recur at different levels of analysis; they are observable among industries
as well as occupations.
The analysis of cluster employment suggests that high-technology employment and both high and
low value-added services employment will continue to grow rapidly. Growth in service employment
may also be induced by demographic shifts occurring over the next ten years: aging baby-boomers
will demand a new array of services (especially in the Health Care and Medical Services fields) as
they begin to retire and leave the labor force. The changing structure of jobs the economy is likely
to provide implies that adaptation of the region’s workforce training programs will be required to
meet new surges in the demand for labor services in certain fast-growing occupations.
5
Employment in Traded Industry Clusters
San Diego Region, 2000-2010
140,000
120,000
Employment
100,000
80,000
2000
2010
60,000
40,000
20,000
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Source: SANDAG Regional Growth Forecast.
“The greatest job growth is expected in the Medical Services, Business Services, and Visitor
Industry Services clusters.”
Occupational wage analysis shows that, in the new knowledge-based economy, job creation will be
weighted toward jobs that pay wages above the regional average wage. Most of these jobs will be
created in our region’s traded clusters. For our region’s overall standard of living to rise, we need to
retain the businesses offering these high value-added jobs. At the same time, we must provide the
education and workforce training opportunities necessary to adequately prepare our labor force.
THE SUPPLY OF WORKERS
The labor force brings with it skills and abilities specific to its demographic composition. In San
Diego’s case, more older and Hispanic workers will mean the labor force has more levels and types
of skills specific to those groups. Forecasts for the San Diego Region’s labor force indicate that
maintaining the skills of older workers to compensate for the relative shortage of baby-bust
workers in their thirties will be a coming challenge. A similar conclusion was reached by a recent
labor market study done in Pennsylvania, “As technology changes with a rapidly changing
6
economy, an older, more stable labor force could face problems adapting. Retraining older workers
and dislocated workers in new technologies will be critical to success” 7.
The San Diego labor force will also see large growth in Hispanic workers. The relatively lower
educational attainment levels of the fast-growing Hispanic share of the labor force may also lead to
lower average education levels in the labor force. Because skill and education levels equate with a
worker’s productivity and determine wage levels, a de-skilling of the San Diego labor force could
translate into lower future wages in the region. To continue to improve the standard of living for
San Diego residents, as measured by wages, increasing productivity and skill attainment levels will
be critical in the years to come.
Percent Share of Labor Force by Ethnic Groups
San Diego Region, 2000 -2010
35%
30%
Percent of Labor Force
25%
20%
2000
2010
15%
10%
5%
0%
Hispanic Male
Hispanic
Female
White Male
White Female
Black Male
Black Female
Asian Male
Asian Female
Ethnic Group by Gender
“Asians and Hispanics will make up an increasing share of the San Diego region’s labor
force, while the share of Whites will decline.”
To increase the supply of labor at various levels of skill, the current profile of the San Diego labor
force suggests two approaches. First, training should be targeted at large population groups that
are available to work yet are under-skilled. This could include focusing on the youth, elderly, and
minority populations. Second, attempts to address workforce barriers and low labor force
participation affecting certain demographic groups could bring new workers into the labor market.
The chapter analyzing the gap between labor supply and demand provides a look at the adequacy
of the current supply of labor in the region.
7
“Pennsylvania Workforce 2005”. Bureau of Research and Statistics, Pennsylvania Department of Labor and
Industry, winter, 1997-1998.
7
IDENTIFYING GAPS
It is expected that, in general, the San Diego regional labor market will remain tight, with
relatively thin surpluses of labor over the next ten years (the unemployment rate is expected to
stay between four and five percent). However, as shown by the educational attainment and
occupational analyses, there are segments of the economy with demand -supply gaps.
Our research points to two separate, yet related issues; first, the regional labor market is currently
“tightest” at the bachelor’s degree level. Second, the region’s current training capacity is least
adequate at the bachelor’s degree level. On one hand, our labor force’s educational attainment
levels are high On the other hand, it is likely that workers hold degrees in fields with a low
demand for employees, or lack intangible characteristics or skills unrelated to a degree. The labor
force data suggest San Diego has a highly educated labor force, but that the labor force may not
be adequately educated in the disciplines demanded by employers. While there are many more
workers with graduate degrees than there are jobs that require such degrees, there are
nevertheless shortages in high-skilled scientific and technical occupations in the traded clusters.
Labor Supply and Demand by Education Level
San Diego Region, 2000
Wage and Salary Employed Workers, Wage and Salary Jobs
1,000,000
900,000
800,000
700,000
600,000
500,000
2000 Labor Demand
2000 Labor Supply
400,000
300,000
200,000
100,000
No college
Associate's
degree
Bachelor's
degree
Education Level
Graduate or
professional
degree
Source: SourcePoint, Employment Development Department OES,
1990 and 2000 Census Supplementary Survey.
“The San Diego labor market is expected to remain tight, with relatively thin surpluses of
labor over the next ten years. The regional labor market is currently ‘tightest’ at the
bachelor’s degree level.”
8
While there are some planned expansions at our major universities, it is too early to determine if
the expansions will be large enough and offer courses in the areas our knowledge based economy
will demand.
MEETING WORKFORCE DEVELOPMENT CHALLENGES
In the future, employers in the region will require an increasing average level of skill from the labor
force. Although this may pose a challenge, it should also be viewed as an opportunity for the region:
jobs that require more educated and trained workers tend to pay better than jobs with low education
and skill requirements. Ultimately, as a result of the increase in skills required by employers of the
region, local residents should see their standard of living rise. The region currently has both higher
training requirements and a better capacity to train its residents than the nation (as represented by
degrees awarded per capita). However, there are still certain educational levels and occupations
where San Diego’s workers are not meeting the demand. Future adaptations in the region’s training
infrastructure are already planned, but more may need to be undertaken to move San Diego workers
up the career ladder and prepare them for future high-value added employment opportunities.
Average Annual Wage by Education and Training
$80,000
$76,108
Average Annual Wage
$70,000
$67,749
$60,000
$57,54 5
$49,007
$48,718
$50,000
$40,934
$40,000
$36,561
$34,734
$30,828
$30,634
$30,000
$20,364
$20,000
$10,000
$Professional
Degree
Doctoral
Degree
Master's
Degree
Bachelor's or
Higher +
Experience
Bachelor's
Degree
Associate’s
Degree
Vocational
Education
Work
Experience
Long-term
Training
Moderateterm
Training
Short-term
Training
Training Level
Source: California Employment Development Department Occupational Employment Survey,
compiled by SourcePoint.
“Education and training pay off. For each additional level of educational attainment, on
average, workers can expect substantial increases in annual income.”
9
EARNING A LIVING WAGE IN THE SAN DIEGO REGION
Research on the “living wage” shows there is little agreement on how poverty and a living wage are
defined. Still, some local agencies have adopted guidelines or programs that use a living wage to
achieve certain workforce development goals. Our research indicates that a single worker in the San
Diego Region in 2001 would require $11.58 per hour to be economically self-sufficient. Currently,
about one-third of the jobs in the San Diego region earn less than this living wage.
Our research found workforce development policies in the region that are intended to limit training
opportunities to occupations that pay at minimum a self sustaining wage, or provide a clear path to
such a wage. However, eliminating specific training programs that produce workers for occupations
that earn below the living wage could result in a shortage of qualified workers in occupations that
provide essential services (e.g., health assistants and child care workers).
Although, one of the most effective and well-documented ways for a worker to earn higher pay has
been through education and training, there is still concern that some workers get stuck at the
bottom of the income ladder with little opportunity to move up. Our research summarizes a recent
report from the California Employment Development Department’s Labor Market Information
Division (LMID) that analyzes wage mobility in the State. LMID found “fairly high” levels of absolute
earnings mobility, with the highest rate of mobility among the lowest earners. At the end of the
twelve-year study period (2000), one in five of the workers that started in the bottom quintile
remained there; the remaining 80 percent moved into higher income brackets. These results on
income mobility are largely consistent with research done using national samples.
Absolute Income Mobility by Quintile
State of California, 1988 to 2000
2000 Earnings Status
Same
Moved
Moved
Quintile
Up
Down
Bottom Quintile
21.3 %
78.7
N/A
Second Quintile
28.2
62.4
9.4
Middle Quintile
33.4
51.1
15.5
Fourth Quintile
39.0
41.7
19.3
Top Quintile
80.6
N/A
19.4
Source: Labor Market Information Division, California Employment Development Department, “Wage Mobility in
California: An Analysis of Annual Earnings”, April 2002.
“Income mobility has been ‘fairly high’ in California: Of those workers initially in the bottom
quintile of the earnings distribution in 1988, one in five remained in the bottom quintile by
2000.”
10
COMMUNITIES AT RISK
A sub-regional analysis illustrates that there are labor market successes concentrated in some areas of
the region and labor market problems concentrated in other parts of the region. The analysis also
indicates that several labor market characteristics are associated with each other in various
communities of the region. For example, the same areas that are highly educated tend to have higher
incomes and higher labor force participation rates. The areas that have low educational attainments
tend to have lower participation rates, lower incomes, and rely more heavily on the federal Earned
Income Tax Credit (EITC) program. The analysis of “at-risk” indicators shows that certain communities
in the region are having trouble attaining high levels of education and improving their standards of
living. These communities will likely present significant challenges to workforce development
policymakers in the future. Successfully addressing the problems of these at-risk communities may
require a significant reallocation or expansion of workforce development resources.
Proportion of Workers with Low Educational Attainment Levels, 1990
Over two-thirds of the residents over 25 in the communities of Otay Mesa, Barrio Logan, San Ysidro,
Otay, Southeastern San Diego, and National City had attained only a high school degree or less.
Other low educational attainment pockets exist in the communities surrounding Santee and El
Cajon, and San Marcos and Escondido.
“In addition to coursework that emphasizes specific skills demanded by the region’s
employers, training directed at populations in these areas will also need to focus on basic, or
‘soft’ skills, such as good work habits and literacy. The Workforce Partnership’s Work
Readiness Certificate is an example of a program in the region designed to help job seekers
acquire these skills.”
11
Map 9
San Diego Region
PROPORTION OF WORKERS
WITH LOW EDUCATIONAL
ATTAINMENT, 1990
BY JURISDICTIONS
AND COMMUNITY
PLANNING AREAS
SUMMARY OF FINDINGS AND RECOMMENDATIONS
Summary of Findings
•
The region’s labor force is expected to expand by more than 205,000 workers between 2000
and 2010 and more than 184,000 new jobs will be created, keeping the unemployment rate
low and the labor market tight.
•
The aging of the “baby-boom” population will reduce the number of prime working age
people in the labor force by 2010. At the same time, labor force participation rates for the
region are expected to rise reflecting the increase in participation from our relatively fast
growing Hispanic population.
•
The region will continue to transition toward a knowledge- and information-based
economy, leading a nationwide trend. Our export-oriented “traded” clusters are expected
to lead this trend and drive the local economy, placing new education, skill and training
demands on our labor force.
•
Two labor market problems have been identified in the San Diego region: We currently support a
disproportionately large number of low-skill, low-wage jobs, and employers have noted
shortages of high-skill workers.
•
A better balance between new high and low paying job opportunities is expected,
reflecting the continued expansion of our traded clusters within the diverse base of
emerging growth technology companies. This trend is expected to raise the region’s level of
productivity and overall standard of living.
•
The expected rise in the region’s standard of living reflects the fact that wages in the region’s
traded clusters tend to be much higher than wages in other sectors of the regional economy,
though traded clusters also contain some low-paying jobs.
•
Relatively more growth is expected in traded clusters with small average firm sizes,
suggesting a trend toward smaller firms.
•
Training requirements in the San Diego region are expected to increase over the next ten
years as occupations requiring at least a bachelor’s degree grow faster than occupations
requiring lower levels of education and training.
•
Access to education, training and career ladder information can provide the basis for
economic mobility, providing a path to prosperity by allowing low-skill, low-income workers
an opportunity to join the middle-class.
•
The San Diego region has a highly educated labor force, but the labor force may not be
adequately educated in the disciplines demanded by employers. While there are many more
workers with graduate degrees than there are jobs that require such degrees, there are
nevertheless shortages in high-skilled scientific and technical occupations in the traded clusters.
•
The region’s current education capacity is least adequate at the bachelor’s degree level.
While there are some planned expansions at the bachelor’s degree level, at this time there is
13
insufficient information available to determine whether these expansions will meet the
training requirements of the regional job market.
•
Some members of the working-age population in the San Diego region currently face
workforce barriers, such as transportation, social or health problems, that inhibit their
participation in the labor force.
•
Each new census has shown rising educational attainment levels, locally and nationally. By
ethnicity, Hispanics tend to have the lowest attainment levels, and Asians the highest.
Hispanics are expected to account for a majority of our region’s population growth over the
next 30 years, which may threaten our region’s rising educational attainment trend and
challenge the local K-12 educational community.
•
Although, there is little agreement on how to measure poverty or what constitutes selfsufficiency, our budget based living wage approach indicates that a single worker in the San
Diego region would require $11.58 per hour and work 40 hours per week to be
economically self-sufficient. In 2000 more than 25 percent of the region’s jobs earned less
than the estimated regional living wage.
Recommendations
•
Shift workforce development policies towards quality of jobs and away from supporting
aggregate job creation. Current and expected slow labor force and income growth, and low
unemployment rates will support this shift.
•
Ensure that workforce development opportunities are convenient and accessible by small
businesses because they are increasingly expected to be responsible for creating a large
majority of new jobs over the next 10 years.
•
Improve the preparation of the region’s K-12 students for participation in the labor force
and college with broader exposure to math and basic science coursework, and “soft skills”.
•
Increase the region’s capacity to produce college graduates, especially in areas reporting
tight labor markets, such as occupations requiring math and science backgrounds. Continue
to emphasize and publicize the role of community colleges and continuing education
programs at our universities in supplementing the skills of college graduates.
•
Determine the adequacy of existing workforce development opportunities, designed to overcome
skill deficiencies and barriers, located in “at risk” communities. Consider locating or expanding
workforce development opportunities in these “at risk” communities to meet their needs.
•
Consider a campaign to encourage eligible households to apply for the federal Earned
Income Tax Credit Program in order to boost the income of some low wage workers.
•
Partner with local universities that track their graduates to determine if a database can be
created that provides some insight on college degrees, additional workforce development
accomplishments, occupations and career ladders.
14
Workforce Development and Career Ladder Resources on the Internet:
O*NET OnLine
http://online.onetcenter.org
O*NET OnLine is an interactive, continually updated database of occupational information. It
includes information on the skills, abilities, knowledge, work activities, and interests associated with
various occupations. The site allows users to explore occupations, search for occupations that
require their skills, and examine related occupations.
2002 Occupational Outlook Report (San Diego Workforce Partnership)
http://www.workforce.org/pdf/2002OORweb.pdf
The Occupational Outlook Report provides detailed information on selected occupations in the San
Diego region. For each occupation profiled, it lists skill, education, training, and experience
requirements; wages; projected employment growth; promotional opportunities; and other
information. It also lists training providers in the region that offer courses that prepare individuals
for each occupation.
Workforce Partnership’s San Diego County Training and Education Providers (STEP)
www.sandiegoatwork.org
The STEP system allows users to interactively search for training providers in the San Diego region
that provide courses related to various occupations. Users can narrow the search criteria by looking
for training providers that offer specific types of training (e.g., certification, bachelor’s degree, etc.)
or that are located in specific areas of the County.
California Occupational Guides
http://www.calmis.cahwnet.gov/htmlfile/subject/guide.htm
The California Occupational Guides provide information on over 300 occupations or groups of
related occupations in California. Available information includes job duties, working conditions,
employment outlook, wages, benefits, entrance requirements, training and education
requirements, and career advancements opportunities.
Career Ladders
http://www.careerladders.org
“Career Ladders” is a project of the Packard Foundation and Northern California Bay-Area
Workforce Investment Boards that provides career ladder information on occupations in the Bay
Area.
CaCTIS – California Career & Training Information System
http://www.cactis.ca.gov
CaCTIS, designed and maintained by the California Employment Development Department, provides
information job seekers and career professionals need to make informed decisions on careers,
training and education.
CTEP – California Training & Education Providers
http://www.soicc.ca.gov/ctep/Default.asp
The CTEP database is a comprehensive listing of training and education providers throughout
California. It is a valuable guide to local training and education resources. The database has more
than 2,600 providers and allows users to search for training and education programs in private or
public schools or colleges and universities.
15
CHAPTER 1
THE DEMAND FOR JOBS: EMPLOYMENT AND
OCCUPATIONAL PROJECTIONS
Chapter 1
THE DEMAND FOR JOBS:
EMPLOYMENT AND OCCUPATIONAL PROJECTIONS
The type of labor services demanded by the economy plays a large part in determining the quality
of jobs the region provides. The disappearance of high value-added production and research jobs in
the defense industry was one of the factors that exacerbated the local recession of the 1990s.
However, since then, some of the jobs that were lost have been replaced by new, high value-added
service occupations in emerging fields, such as Communications and Biotechnology. In fact, growth
in these high-tech, high-skill cluster occupations has surpassed expectations.
Now the region’s labor market challenges revolve around the questions: Where does the region’s
employment go from here? What does the current employment structure look like and how fast
will employment grow in the future? In what sectors and occupations will new jobs and high wages
be located? Understanding the projected growth in employment will give an idea of the type of
labor force and training needed to support the regional economy in 2010.
This chapter looks at the current and forecast employment in the San Diego region in three
different ways: by detailed industries, by “traded” economic clusters, and by occupations8. In
addition to raw employment figures, the quality of jobs that will be created is also examined by
assessing wages throughout the regional economy. In general, forecasts show steady growth in
employment and suggest that the region, like the nation, will continue transitioning toward a
knowledge- and service-based economy.
AN OVERVIEW OF CURRENT AND FORECAST ECONOMIC AND EMPLOYMENT GROWTH
Employment growth in the San Diego region through 2010 is forecast to be strong, albeit slower
than the growth that occurred during the 1990s. The current and forecast regional economic trends
are summarized in Figure 2.1. Total economic output of goods and services produced in the region,
the Gross Regional Product (GRP), is expected to grow by $46.3 billion (real dollars) or 38.7 percent
over ten years. Regionwide employment will grow by 15.2 percent from 1,208,300 to 1,392,457 jobs,
adding 184,157 jobs9. In comparison, from 1990 to 2000, 231,300 jobs were added, an increase of
23.6 percent. Employment throughout the U.S. is expected to increase at approximately the same
rate as in San Diego for the next ten years, with a 15.2 percent increase, but will also drop off from
8
In some cases, the 1990 Census is the most current data for population and labor force characteristics cited
throughout the report. All forecast data is from the SANDAG Demographic and Economic Forecasting Model
(DEFM) 2030. The base year for most of the forecasts in the model is 2000. The data from the 2030 forecast
presented here are preliminary results.
9
Total employment (including self-employed and domestic workers) will grow by 12.9 percent, from 1,362,900
to 1,538,007 jobs, adding 175,107 jobs.
19
the previous decade when it increased by 17.1 percent10. Because Gross Regional Product is projected
to grow faster than the number of jobs, income indicators, such as income and payroll per capita,
will also continue to rise. This likely reflects gains in the average productivity per worker.
Figure 1.1
Economic and Employment Indicators
Indicators
Employment
2000
2010
Numerical
Change
Percent
Change
1,208,300
1,392,457
184,157
15.24%
Gross Regional Product
119.50
165.77
46.28
38.73%
GRP/Capita (2000$)
41,836
51,275
9,439
22.56%
Income per Capita (2000$)
31,754
37,439
5,685
17.90%
44.94
61.74
16.80
37.38%
Total Regional Payroll (Billions, 2000$)
Sources: SANDAG Forecast 2030, California Employment Development Department.
In greater detail, some industries are expected to grow faster and add more total new jobs than
others. The detailed industry level of analysis divides the San Diego regional economy into 57
industries11. Looking at the detailed industries with the most growth in Figure 1.2, four of the top
five industries that will add the most jobs over the next decade are service industries (Other
Services, Health Services, Other Business Services, and Restaurants), with both Other Services and
Health Services adding over 20,000 new employees12. Figure 1.3 shows the ten detailed industries
with the fastest forecast rates of growth in employment. Again, five of the top ten fastest growing
industries are in services. Fast growth rates indicate the sharpest changes in employment from the
present situation. Industries with drastic changes in employment levels may also require expansion
of related training programs.
10
Hecker, Daniel E. “Employment Outlook: 2000-2010: Occupational Employment Projections to 2010”. U.S.
Bureau of Labor Statistics, Monthly Labor Review, November 2001.
11
These are 2-digit level Standard Industrial Classification (SIC) code industry figures.
12
“Other Services” include personal services; automotive services; repair services; social services; and museums,
art galleries, and zoos. “Other Business Services” include personnel supply services; equipment rental and
leasing; mailing, reproduction, and commercial art; credit reporting; and advertising.
20
Figure 1.2
Industries with the Largest Forecast Growth in Employment
30
Number of New Employees (in thousands)
25
20
15
10
5
0
Other
Services*
Health
Services
Other
Business
Services*
Restaurants
Wholesale
Trade
Local
Education
Computer &
Data
Processing
Local
Government
Real Estate
Hotels,
Motels
2-Digit SIC Industries
* “Other Services” includes auto repair (SIC 75); miscellaneous repair services (SIC 76); social services (SIC 83); museums and
botanical and zoological gardens (SIC 84); and membership organizations (SIC 86). “Other Business Services” include
personnel supply services; equipment rental and leasing; mailing, reproduction, and commercial art; credit reporting; and
advertising.
21
Figure 1.3
Industries with the Fastest Forecast Growth in Employment
45%
Percent Change in Employment, 2000-2010
40%
35%
30%
25%
20%
15%
10%
5%
*
io
ce
s
n
at
e
cr
e
sS
er
vi
at
al
Es
t
er
th
O
Am
us
O
em
th
en
Bu
si n
ta
nd
es
Re
Re
er
vi
c
er
O
th
e
rS
rt
a
sp
o
Tr
an
at
a
D
r&
te
Co
m
pu
es
*
n*
tio
es
si n
oc
Pr
l th
He
a
ys
To
g
es
Se
rv
ic
ra
su
In
ti n
g
or
&
Sp
nc
ds
Go
o
al
s
tic
m
ac
eu
Ph
ar
d
an
ica
ls
m
M
ed
ic
in
a
lC
he
e
0%
2-Digit SIC Industries
* “Other Transportation” includes the U.S. Postal Service (SIC 43); water transportation (SIC 44); pipelines other than natural
gas (SIC 46); and transportation services (SIC 47). “Other Services” includes auto repair (SIC 75); miscellaneous repair services
(SIC 76); social services (SIC 83); museums and botanical and zoological gardens (SIC 84) and membership organizations (SIC
86). “Other Business Services” include personnel supply services; equipment rental and leasing; mailing, reproduction, and
commercial art; credit reporting; and advertising.
Of the rapid or large growth industries, only Medicinal Chemicals and Pharmaceuticals and Toys and
Sporting Goods are manufacturing industries. In fact, as Figures 1.4 and 1.5 show, many manufacturing
industries are in the group of industries that are forecast to decline. Nine of the ten slowest and smallest
growing industries are manufacturing, with the biggest decreases in the Other Instruments and Other
Industrial Machinery industries13. Employment declines are likely due to changes in technology and the
types of goods and services demanded over time. (This could include modernization and automation of
business systems where workers are replaced by capital, such as the increasing use of computers.)
13
“Other Instruments” includes the manufacturing of watches and clocks; photographic equipment;
ophthalmic goods; and surgical, medical, and laboratory instruments. “Other Industrial Machinery” includes
the manufacturing of engines, farm equipment, construction and mining equipment, metal working
equipment, and refrigeration equipment.
22
-2,000
-1,500
Job Losses
-2,500
-1,000
-500
0
Other Chemicals and Allied
Products*
Mining & Minerals
Apparel & Other Textiles
Electronic Components
Communication Equipment
Office, Computing Equipment
Other Transportation Equipment*
Aircraft,
& and
Other
Aircraft,Missiles
Missiles
& Other
Trans
Transportation
Other Industrial Machinery*
Other Instruments*
Figure 1.4
Industries with the Largest Forecast Employment Declines
San Diego Region, 2000- 2010
* “Other Instruments” includes the manufacturing of watches and clocks; photographic equipment; ophthalmic goods; and surgical, medical, and laboratory instruments.
“Other Industrial Machinery” includes the manufacturing of engines, farm equipment, construction and mining equipment, metal working equipment, and refrigeration
equipment. “Other Transportation Equipment” includes motor vehicles, ship building, railroad equipment, and miscellaneous transportation equipment, but not aircraft and
parts or guided missiles, space vehicles and parts. “Other Chemicals and Allied Products” includes industrial inorganic chemicals, plastics, soaps, paints, industrial organic
chemicals, agricultural chemicals and miscellaneous chemical products, but not pharmaceutical drugs
2 Digit SIC Industries
-20%
-10%
Percent Change in Employment, 2000-2010
-15%
-25%
-5%
0%
Other Chemicals and Allied
Products*
Electronic Components
Apparel & Other Textiles
Communication Equipment
Other Transportation Equipment*
Office, Computing Equipment
Aircraft, Missiles & and Other
Transportation
Mining & Minerals
Other Industrial Machinery*
Other Instruments*
Figure 1.5
Industries with the Sharpest Forecast Rate of Decline in Employment
* “Other Instruments” includes the manufacturing of watches and clocks; photographic equipment; ophthalmic goods; and surgical, medical, and laboratory instruments.
“Other Industrial Machinery” includes the manufacturing of engines, farm equipment, construction and mining equipment, metal working equipment, and refrigeration
equipment. “Other Transportation Equipment” includes motor vehicles, ship building, railroad equipment, and miscellaneous transportation equipment, but not aircraft and
parts or guided missiles, space vehicles and parts. “Other Chemicals and Allied Products” includes industrial inorganic chemicals, plastics, soaps, paints, industrial organic
chemicals, agricultural chemicals and miscellaneous chemical products, but not pharmaceutical drugs.
2 Digit SIC Industries
EMPLOYMENT IN THE SAN DIEGO REGION’S ECONOMIC CLUSTERS
There are four reasons for studying the labor market from a cluster perspective. First, traded clusters
that bring outside money into the region drive the rest of the economy by stimulating job growth
in local industries that provide support services. Second, the jobs in some cluster industries are high
value-added with higher salaries14. Third, clusters are the most volatile industries and will likely
experience rapid growth, creating more employment opportunities than other industries15. Fourth,
high value-added traded clusters in San Diego have witnessed pronounced labor shortages and skill
gaps. An in-depth view of current cluster labor market problems will assist policymakers, agencies,
and employers in formulating appropriate workforce development solutions.
Employment growth in San Diego’s economic clusters is expected to out-pace regional employment
growth, constituting a greater share of total regional employment in 2010. As shown in Figure 1.6,
clusters will grow by an average of 17.5 percent from 2000 to 2010, adding 74,238 new jobs.
Though clusters only constitute 35 percent of the region’s total employment in 2000, employment
growth in clusters will account for a disproportionately large 40 percent of total new growth. The
faster-than-average growth in cluster employment will mean that the share clusters constitute of
total employment will increase to 36 percent in 2010. In comparison, non-traded, locally oriented
industries will grow at a slower rate of 14 percent. Although non-traded industries constitute 65
percent of total employment in 2000, they will only account for 60 percent of new job growth.
14
As the Harvard Business School Professor Michael Porter notes, “While local clusters account for roughly twothirds of employment in an average region, [externally-oriented] traded clusters heavily drive the prosperity
and growth of a region; average wages in traded clusters are roughly $13,000 a year higher than wages in
local clusters. This is because traded clusters can achieve higher productivity, their growth is unconstrained by
the size of the local market, and their success creates much of the demand for local clusters”. Porter, Michael E.
Clusters of Innovation Initiative: San Diego. Council on Competitiveness, 2001.
15
The volatile nature of clusters means some clusters could also experience employment declines as the
regional economy continues to evolve.
25
Figure 1.6
Employment Growth by Traded Clusters*
2000
Employment
Biomedical Products
6,256
2010
Employment
4,778
Numerical
Change in
Employment
Percent
Change in
Employment
-1,478
-23.62%
Share of
Total Cluster
Employment
in 2000
1.48%
Share of
Total Cluster
Employment
in 2010
0.96%
Biotechnology & Pharmaceuticals
23,050
25,753
2,704
11.73%
5.44%
5.17%
Business Services
94,650
114,403
19,753
20.87%
22.35%
22.99%
Communications
24,943
27,203
2,260
9.06%
5.89%
5.47%
Computer & Electronics
24,075
23,325
-750
-3.11%
5.69%
4.69%
18,026
20,517
2,491
13.82%
4.26%
4.12%
20,506
25,490
4,983
24.30%
4.84%
5.12%
4,580
3,600
-980
-21.41%
1.08%
0.72%
17,337
19,034
1,697
9.79%
4.09%
3.82%
3,603
3,818
215
5.98%
0.85%
0.77%
Manufacturing
Defense & Transportation
Manufacturing**
Entertainment & Amusement
Environmental Technology
Financial Services
Fruits and Vegetables
Horticulture
Medical Services
Recreational Goods
Software & Computer Services
Visitor Industry Services
Total Cluster Employment
Non-Cluster Industries
All San Diego Industries
6,644
7,041
397
5.98%
1.57%
1.41%
71,889
93,484
21,595
30.04%
16.98%
18.78%
4,900
6,629
1,729
35.29%
1.16%
1.33%
21,290
26,761
5,471
25.70%
5.03%
5.38%
81,713
95,864
14,151
17.32%
19.30%
19.26%
423,463
497,701
74,238
17.53%
100.00%
100.00%
784,837
894,756
109,919
14.01%
1,208,300
1,392,457
184,157
15.24%
Sources: SANDAG Regional Growth Forecasts, California Employment Development Department.
* Excludes the uniformed military.
** Forecasts for the Defense and Transportation Manufacturing cluster have been adjusted to reflect the increase in federal
defense spending in the region since the events of September 11, 2001. We have assumed that from 2002 to 2010, the pace
of employment growth in this cluster will mirror the overall pace of employment growth for the region. Note that future
national defense contracts may also influence employment levels in the Communications and Biotechnology and
Pharmaceutical clusters as military research expands in the fields of bio-terrorism and surveillance technologies.
26
Looking at the current and future distribution of employment within clusters, some clusters have many
more employees than others. Figure 1.7 shows that the Business Services cluster is the largest cluster by
employment in 2000 and is forecast to remain so, employing approximately 115,000 workers in 201016.
The three largest clusters combined – Business Services, Visitor Industry Services, and Medical Services –
will account for 61 percent, or nearly two-thirds of all cluster employment in 2010. The two smallest
clusters in 2000 and 2010 are Fruits and Vegetables and Environmental Technology. In general, the
shares of employment among clusters are forecast to remain relatively static over time. However,
differences in employment growth rates mean that the Medical Services and Business Services clusters
are expected to increase their shares of total cluster employment the most. In contrast, the shares of
Computer and Electronics Manufacturing and Biomedical Products are expected to decrease slightly.
16
Much of the employment growth in Business Services is a result of the increasing number of temporary
workers (also known as “Help Supply Services”). Although these workers are counted in the Business Services
cluster, many are actually employed in other industries.
27
Cluster
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-
20,000
40,000
60,000
80,000
100,000
120,000
140,000
Figure 1.7
Employment in Traded Industry Clusters
2010
2000
Much of the employment growth in Business Services is a result of the increasing number of temporary workers (also known as “Help Supply Services”). Although these
workers are counted in the Business Services cluster, many are actually employed in other industries.
*
Employment
Growth in employment is expected to vary greatly across clusters. There are several clusters with
rapid projected growth rates that far exceed the average regional employment growth rate of 15.2
percent. Figure 1.8 shows that the most new jobs are expected to be added in the Medical Services,
Business Services and Visitor Industry Services clusters – three of the largest clusters by employment.
In sum, all the clusters with positive growth will add 74,955 jobs. Figure 1.9 shows that the fastest
growth is expected in the Recreational Goods, Medical Services, Software and Computer Services,
and Entertainment and Amusement clusters. It is noteworthy that, of all clusters, the Medical
Services cluster is expected to add the most jobs and have one of the fastest growth rates. As the
nation’s population ages and has greater need for health care, the demand for services provided by
the Medical Services cluster will only increase in the future.
The number of employees in several clusters is forecast to shrink over the next ten years (Figures 1.8
and 1.9). The clusters that are projected to have fewer employees in 2010 include Biomedical
Products, Environmental Technology, and Computer and Electronics Manufacturing. As consistent
with the trends observed at the industry level, these are mainly the manufacturing and production
clusters. In sum, these declining clusters will account for 3,208 fewer jobs in the region.
29
Business Services
Medical Services
-5,000
0
10,000
Number of New Jobs
5,000
Figure 1.8
Job Growth in Traded Industry Clusters
Biomedical Products
Computer and Electronics Manuf.
Horticulture
Financial Services
Recreation Goods Manuf.
Communications
Defense and Trans. Manuf.
Biotechnology and Pharm.
Entertainment/ Amusement
Software and Computer Services
Industry
Cluster
15,000
20,000
25,000
Industry Cluster
-30%
Biomedical Products
Computer and Electronics Manuf.
Horticulture
Communications
Financial Services
Biotechnology and Pharm.
Defense and Trans. Manuf.
Business Services
Entertainment/ Amusement
Software and Computer Services
Medical Services
Recreation Goods Manuf.
-20%
-10%
10%
Rate of Growth in Employment
0%
Figure 1.9
Rates of Growth in Employment in Traded Industry Clusters
20%
30%
40%
Figure 1.10 ranks the traded clusters from high to low by average annual wage. In 2000, the
average annual cluster wage of $45,549 was 67.3 percent ($18,320) greater than the non-cluster
average annual wage of $27,229. Across clusters however, there is a diversity of wage patterns. In
2000, the highest average wages were found in the Communications, Software and Computer
Services, and Computer and Electronics Manufacturing clusters. The lowest average wages were
found in the Visitor Industry Services, Fruits and Vegetables, and Horticulture clusters. The 2000
average annual wage of the highest-paying cluster (Communications) was nearly seven-times
greater than that of the lowest-paying cluster (Visitor Industry Services)17.
Figure 1.10
Payroll, Wages, and Firm Size for Traded Industry Clusters
2000
Payroll
(millions)
Communications
2000
Payroll
Share
$2,893.4
2000
Average
Wage
Number of
Firms in
2000
Average
Employees
Per Firm
14.86%
$116,301
525
50
Software & Computer Services
$1,689.5
8.67%
$79,360
1,440
15
Computer & Electronics Manufacturing
$1,755.1
9.01%
$72,616
303
80
Biotechnology & Pharmaceuticals
$1,619.9
8.32%
$70,259
540
43
Financial Services
$993.8
5.10%
$57,321
1,475
12
Defense & Transportation
$963.9
4.95%
$53,111
151
119
Biomedical Products
$289.2
1.48%
$46,227
125
50
$208.1
1.07%
$45,429
109
42
Manufacturing
Recreational Goods
$208.4
1.07%
$42,197
124
40
Medical Services
$2,852.8
14.65%
$39,684
3,904
18
Business Services
$3,735.4
19.18%
$38,485
6,544
15
Entertainment & Amusement
$633.1
3.25%
$30,874
630
33
Horticulture
$148.7
0.76%
$22,383
472
14
$63.2
0.32%
$17,529
356
10
Total Cluster Employment:
$1,422.8
7.30%
$17,089
3,668
22
$19,477.2
100.00%
$45,549
20,365
21
72,509
14
Non-Traded Industries
$25,467.1
$27,229
All San Diego Industries
$44,944.3
$32,922
Sources: California Employment Development Department, compiled by SANDAG.
While there are still several clusters whose wages are less than the regional average wage of $32,922,
cluster job growth is expected to be weighted toward jobs that pay more than the regional average.
As is evident in Figure 1.11, job growth in clusters whose average wage is greater than the regional
average wage is forecast to be more than two-and-a-half times greater than the number of new jobs
in clusters whose average wage is less than the regional average wage. This trend suggests that new
cluster job growth will likely play a major role in providing jobs with high wages and will increase the
need for related education and skills.
17
The average annual wage of the Communications cluster has been double its historical average over the past
two years as employees have exercised stock options.
32
Figure 1.11
Forecast Growth in Traded Cluster Employment by Average Wage
60,000
54,492
50,000
Number of New Jobs
40,000
30,000
20,000
19,747
10,000
0
Cluster Industries with Avg. Wages Less Than
Regional Avg. Wage
Cluster Industries with Avg. Wages Greater Than
Regional Avg. Wage
The number and size of firms also varies among the region’s cluster industries (Figure 1.10). The
clusters with the greatest number of firms are Business Services, Medical Services, and Visitor
Industry Services. The clusters with the fewest firms include Environmental Technology, Recreational
Goods Manufacturing, and Biomedical Products. Figure 1.10 indicates that the average firm size
among all clusters is 21 employees (substantially larger than the regional average of 14 employees).
The traded clusters with the largest average firm size are Defense and Transportation
Manufacturing, Computer and Electronics Manufacturing, Biomedical Products, and
Communications, while the traded clusters with the smallest average firm size are Fruits and
Vegetables, Financial Services, and Horticulture.
The size of a firm may have important implications for training opportunities for employees. Larger
firms may be more able to afford time off for employees to seek training, and may also have more
overhead revenue available to fund formal in-house training than do smaller companies18. The
variation in firm size among clusters suggests that some clusters may have a better inherent flexibility
of resources and revenues to support employee training than others. Because it appears smaller firms
are becoming more predominant19, training programs in the region may need to be adapted to better
meet the needs of smaller firms.
18
Frazis Harley, Maury Gittleman and Mary Joyce. “Determinants of Training: An Analysis Using Both Employer
and Employee Characteristics”. Bureau of Labor Statistics, 1998.
19
Large growth is expected in clusters with small average firm sizes, such as Business Services, Health Services,
and Software and Computer Services.
33
With strong growth expected in San Diego’s traded clusters, new employment opportunities will
continue to drive the regional economy. Clusters are expected to produce a disproportionately high
amount of middle and high-wage job opportunities compared to their share of total jobs in the
region. However, rapid growth in traded clusters may place new demands on the region’s
workforce training infrastructure to supply the required amount of appropriately skilled employees.
ANALYSIS OF FORECAST OCCUPATIONAL GROWTH
The last and most specific level of employment analysis is by occupation, or employment grouped
into categories by the functional definitions of the tasks employees perform. Figure 1.12 distributes
the current and forecast total wage and salary employment in the region into 35 broad
occupational categories ranked from high to low by mean annual wage. Growth in occupational
employment is divided into three different wage groupings: high, middle, and low-wage
occupational categories. These groupings were established so that they each constitute roughly
one-third of total occupational employment in 2000. In 2000, the occupational category with the
fewest number of employees was Electronic Data Processing and the occupational category with the
largest number of employees was Miscellaneous Sales20. The four largest occupational categories in
2000 (Miscellaneous Sales; Food and Beverage Services; Office Workers; and Teachers, Educators and
Librarians) taken together account for approximately 31.7 percent – nearly one-third – of all wage
and salary employment in the region.
20
“Miscellaneous Sales” includes sales representatives, sales engineers, rental and counter clerks, stock clerks,
cashiers, telemarketers, and models.
34
Figure 1.12
Occupational Employment and Wages (2000$)*
Chief Executives and General Managers
Law and Related Occupations
Staff Managers
Engineers
Computer and Math Scientists
Natural Scientists
Sales Agents
Management Support
Health Care Practitioners
Teachers, Educators & Librarians
Sales Supervisors & Managers
Production, Construction, Maintenance Supervisors
Miscellaneous Professionals
All High-Wage Occupations
High-Wage Occupation Shares of Total Emp.
Construction Trades
Clerical and Administrative Support Supervisors
Social Scientists
Mechanics
Precision Production
Secretaries
Service Supervisors & Managers
Protective Services
Plant, Transportation & Other Operators
Communications & Schedulers
Administrative Support Staff
Office Workers
All Middle-Wage Occupations
Middle-Wage Occupation Shares of Total Emp.
Miscellaneous Sales
Electronic Data Processing
Machine Operators
Health Services
Assemblers
Laborers
Agriculture, Forestry & Fishing
Cleaning and Miscellaneous Services
Personal Services
Food and Beverage Services
All Low–Wage Occupations
Low-Wage Occupation Share of Total Emp.
All Occupations
2000
Employment
2010
Employment
Numerical
Change
Percent
Change
Mean
Annual
Wage
(2000$)
41,035
9,441
49,431
42,951
16,014
8,617
12,689
38,520
55,568
80,277
15,989
21,079
23,726
415,337
34.37%
35,119
14,716
14,566
41,863
16,664
29,449
9,189
26,273
34,389
37,190
44,533
90,185
394,136
32.62%
117,662
7,537
22,521
22,881
29,041
39,180
16,257
35,931
12,787
95,030
398,827
33.01%
48,381
10,700
59,634
50,803
21,314
11,143
14,955
45,190
63,909
94,944
18,955
24,421
29,633
493,984
35.48%
44,763
17,746
16,778
47,838
18,444
33,229
10,187
31,230
38,177
39,780
49,856
95,761
443,789
31.87%
136,960
6,793
24,414
28,157
32,671
46,941
18,468
41,105
15,367
103,808
454,684
32.65%
1,392,45
7
7,345
1,259
10,203
7,852
5,299
2,526
2,267
6,670
8,341
14,667
2,967
3,342
5,908
78,647
42.71%
9,643
3,029
2,212
5,975
1,780
3,780
999
4,957
3,788
2,590
5,323
5,576
49,653
26.96%
19,298
-743
1,893
5,276
3,631
7,762
2,211
5,173
2,580
8,778
55,857
30.33%
17.90%
13.34%
20.64%
18.28%
33.09%
29.31%
17.86%
17.32%
15.01%
18.27%
18.55%
15.86%
24.90%
18.94%
$71,396
$62,504
$59,440
$55,147
$54,139
$53,254
$48,064
$46,520
$44,161
$43,410
$41,343
$40,757
$39,938
$50,467
27.46%
20,59%
15.9%
14.27%
10.68%
12.84%
10.87%
18.87%
11.01%
6.96
11.95%
6.18%
12.60%
$37,083
$36,944
$34,144
$31,947
$30,981
$30,300
$29,257
$27,594
$26,867
$25,663
$25,253
$24,917
$28,755
16.40%
-9.86%
8.40%
23.06%
12.50%
19.81%
13.60%
14.40%
20.17%
9.24%
14.01%
$24,899
$24,218
$21,825
$21,029
$21,029
$20,925
$20,122
$19,037
$16,036
$15,642
$20,630
15.24%
$33,536
1,208,300
184,157
Source: SANDAG Regional Growth Forecast, California Employment Development Department OES Survey,
compiled by SourcePoint.
*
1998 Occupational Employment Survey wage data was adjusted to 2000 dollars using the Employer Cost Index from the
Bureau of Labor Statistics. Wages are weighted average wages of more detailed occupational definitions. Wages have not
been adjusted upward to account for recent increases in the California minimum wage.
35
Of the 35 general occupational categories listed in Figure 1.12, the five that will add the most new
jobs are Miscellaneous Sales; Teachers, Educators, Librarians; Staff Managers; Construction Trades;
and Food and Beverage Services (Figure 1.13). These five categories alone will account for 33.9
percent of new job growth through 2010. Figure 1.14 shows that the five categories with the fastest
growth in employment are expected to be Computer and Math Scientists, Natural Scientists,
Construction Trades, Miscellaneous Professionals21, and Health Services. These occupational trends
confirm the growth patterns seen at other levels of analysis in the Health/Medical Services area. The
employment growth among Computer and Math Scientists parallels the finding from the cluster
employment analysis that the Software and Computer Services cluster is expected to be one of the
fastest growing clusters. Occupational categories that are expected to grow are service-oriented
occupations that require knowledge and information skills. Rapid growth occupations may also
indicate needed adaptations in training programs to meet the changing employment demands of
the future.
Figure 1.13
Five Occupations with the Most New Jobs
25,000
Number of New Jobs, 2000-2010
20,000
19,298
14,667
15,000
10,203
10,000
9,643
8,778
5,000
Miscellaneous Sales*
Teachers, Educators,
Librarians
Staff Managers
Construction Trades
Food and Beverage
Services
Occupation
*“Miscellaneous Sales” includes sales representatives, sales engineers, rental and counter clerks, stock clerks, cashiers,
telemarketers, and models.
21
“Miscellaneous Professionals” includes writers, artists, entertainers, athletes, radio operators, and air traffic
controllers.
36
Figure 1.14
Five Fastest Growing Occupations
35
33.09
29.31
Percent Change, 2000-2010
30
27.46
24.9
25
23.06
20
15
10
5
0
Computer and Math
Scientists
Natural Scientists
Construction Trades
Miscellaneous
Professionals*
Health Services
Occupation
*“Miscellaneous Professionals” includes writers, artists, entertainers, athletes, radio operators, and air traffic controllers.
As technology and the demand for labor services changes over time, some job functions are
projected to decline or grow only slowly. Figure 1.15 shows the occupational categories that are
expected to decline or add the fewest jobs. Figure 1.16 shows the categories where employment
will decline or grow the slowest. While the number of Electronic Data Processors will actually
decrease22, the other categories will grow at much slower rates than the regional average wage and
salary employment growth rate of 15.24 percent.
22
Although Electronic Data Processing is a computer-related occupation, it is still expected to decline as
businesses continue to automate their operations with the introduction of new technologies.
37
Figure 1.15
Five Occupations with the Fewest New Jobs
2000
Number of New Jobs, 2000-2010
1500
1000
500
0
-500
-1000
Electronic Data
Processing
Service Supervisors and
Managers
Law and Related
Occupations
Occupation
38
Precision Production
Machine Operators
Figure 1.16
Five Slowest Growing Occupations
10%
Percent Change in Jobs, 2000-2010
5%
0%
-5%
-10%
Electronic Data
Processing
Office Workers
Communications and
Schedulers
Machine Operators
Food and Beverage
Services
Occupation
The wage levels among occupations that are projected to grow run the gamut from low-wage to
high-wage jobs (Figure 1.12). A good example of this wage variation is observed between Computer
and Math Scientists and Miscellaneous Sales Employees. Both of these occupations expect a lot of
growth: The first has the fastest growth rate of 33.1 percent and the second expects to have the
largest job growth, adding 19,298 new positions. The wage distributions of these two growing
occupations demonstrate the bifurcation of wages found among jobs in the services sector. The
mean annual wage for Miscellaneous Sales employees in 2000 was $24,889 while the mean annual
wage for Computer and Math Scientists was more than double this figure at $54,139.
39
Figure 1.17
Occupational Growth by Wage Category
45%
42.71%
Share of Employment, Employment Growth
40%
35%
34.37%
33.01%
32.62%
30.33%
30%
26.96%
Share of Total 2000
Employment
Share of Total 2000-2010
Growth
25%
20%
15%
10%
5%
0%
All High-Wage Occupations
All Middle-Wage Occupations
All Low-Wage Occupations
Wage Category
Figure 1.17 (and Figure 1.12) shows the growth in occupational employment among the three
different wage groupings of high-, middle-, and low-wage occupational categories. The average
annual wage for the high-wage group in 2000 was $50,467, $28,755 for the middle-wage group,
and $20,630 for the low-wage group (Figure 1.12). On the whole, the high- and low-wage
occupational groups will have faster growth rates than the middle-wage group. The disparate rates
of growth among these groups suggest the “hour-glass” shaped wage distribution needs to be
addressed through workforce development strategies and initiatives. The graph shows that while
high-wage occupational categories only constitute 34.37 percent of total employment in 2000, they
are expected to constitute 42.71 percent of the total growth in employment through 2010. In
contrast, the share of total growth for both the middle and low-wage groups will be less than their
respective shares of total employment in 2000. The result of these trends will be that the one-third
of the occupations offering the highest wages in 2000 will account for slightly more than one-third
of total employment in 201023.
23
Growth forecasts for the top one-third of occupational categories reflect the implementation of the
SANDAG Regional Economic Prosperity Strategy. Workforce development aimed at increasing worker
productivity is a key component of the Strategy’s Recommended Actions. As stated, these actions include
”strengthening our existing industries, emerging growth companies, universities and research and
development institutions that together create new enterprises”. The strategy also contains recommendations
on the roles for business, labor and education, and local government to aid in economic diversification. The
Strategy’s focus is to retain and expand local businesses and create more well paying jobs. “San Diego Regional
Economic Prosperity Strategy: Toward a Shared Economic Vision for the San Diego Region”, San Diego
Association of Governments, July 1998.
40
CHAPTER 2
THE SUPPLY OF WORKERS:
LABOR FORCE PROJECTIONS
Chapter 2
THE SUPPLY OF WORKERS:
LABOR FORCE PROJECTIONS
This chapter examines the type of labor force the region can expect in the future and answers the
question, “What kinds of people will be working in the San Diego region?” Research findings
indicate that, for the next ten years, overall labor force growth will be steady, however the
demographic composition of the labor force is forecast to change. Shifts in the labor force will
closely mirror changes in the population. Similar to other parts of the country, the most prominent
trend in San Diego will be the aging of the labor force as the baby-boom generation nears
retirement. By topic, this chapter analyzes the expected changes in population, the demography of
the labor force, labor force participation, and education levels of the labor force. Possible workforce
barriers that may inhibit certain groups from joining the labor force are also discussed.
POPULATION AND MIGRATION
Because the labor force is a subset of the population, the labor force is highly influenced by changes
in the population. Knowing the composition of the region’s population is critical to understanding
who is working. As shown in Figure 2.1, regionwide, San Diego’s population is forecast to grow by
376,000 people over the next decade, reaching 3.2 million residents in 2010. This growth rate of
13.2 percent is slightly faster than the population growth rate seen for the prior ten-year period of
1990 to 2000, when the population grew by 11.3 percent. The working-age population, ages 15 to
79, is projected to grow from 2,070,754 in 2000 to 2,347,990 in 2010, adding 277,236 potential
workers. The working-age population growth rate of 13.4 percent is slightly greater than that of
the total population.
Taking a closer look at the changes in the ethnicity of the working-age population in Figure 2.2,
Hispanics and Asians are projected to increase the fastest, growing at paces that more than double
the average population growth rate for the region. Trends also show an aging of the population,
with the number of 55- to 64-year-old baby-boomers increasing faster than other age groups. In
contrast, slight population decreases are expected in the 35- to 44-year-old age bracket because the
baby-bust generation will begin to replace the baby-boomers. In terms of ethnicity, the bulk of
White residents fall into the older age categories, while the bulk of the Hispanic population falls
into the younger age categories. By gender, the number of men is expected to grow slightly faster
than the number of women.
43
Figure 2.1
Population, Migration, and Labor Force Growth*
Total Population
Civilian Working-age Population (15 to 79)
Population Change Due to Domestic Migration
Population Change Due to International Migration
Labor Force
Labor Force Participation Rate
2000
2,814,500
2,070,754
12,400
18,600
1,404,900
68.46%
2010
3,232,990
2,347,990
-7,100
13,500
1,610,390
68.54%
Numerical
Change
376,000
277,236
-19,500
-5,100
205,490
0.08%
Growth Rate
13.20%
13.40%
-157.26%
-27.42%
14.60%
0.10%
*
The size of the labor force is calculated using the labor force participation rate.
Figure 2.2
Changes in the Civilian Working-Age Population by Age, Ethnicity and Gender
San Diego Region, 2000-2010,
Groups
Numerical
Change
Percent
Change
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
Total
27,404
13,500
2,179
614
-13,458
-2,832
35,880
54,149
72,539
65,314
25,181
1,589
-4,823
277,237
14.42%
6.78%
1.05%
0.28%
-5.80%
-1.27%
18.50%
32.92%
62.19%
70.78%
30.16%
1.99%
-6.68%
13.39%
Numerical
Change
Percent
Change
Hispanic Male
Hispanic Female
White Male
White Female
Black Male
Black Female
Asian Male
Asian Female
Total
88,604
85,995
10,306
2,368
9,165
9,301
33,692
37,806
277,237
35.55%
33.32%
1.72%
0.38%
18.49%
17.54%
31.59%
29.48%
13.39%
Gender
Male
Female
Total
141,766
135,470
277,237
14.09%
12.73%
13.39%
Ethnicity/Gender
44
One component of regional population growth is migration. Net migration indicates the number of
people entering the region minus the number of people leaving the region. Net migration affects
the labor force because it represents people from elsewhere that may contribute to the supply of
labor. Figures 2.1 and 2.3 show that both net domestic and international migration are forecast to
decline over the next ten years. The net international migration will decline from 18,600 to 13,500
people per year. Net domestic migration, is projected to decrease more rapidly than international
migration, going from 12,400 to –7,100 people per year. Net domestic migration is projected to
drop below zero around 2005, indicating that more people will be leaving the region to live in
other parts of the country than coming to stay in San Diego.
The decline in migration can be explained as a result of two major factors: changing demographics
and changing economic opportunities. First, with regard to demographics, since migrant
populations tend to be young, as the U.S. population ages, a relatively smaller migration-age
population can be expected nationwide ten years from now. As this demographic trend causes a
decline in the overall number of migrants, it is assumed there will be a proportionate decline in net
domestic migration, meaning relatively fewer domestic migrants entering the region by 2010.
Second, results from SANDAG’s recent study of growth-slowing policies show that population
growth due to domestic migration is closely linked to strong local job prospects (in contrast, people
seem to come from outside of the country regardless of economic conditions) 24. The relative
slowdown in job growth in the region through 2010 (compared to job growth in the previous
decade) will likely attract fewer domestic migrants. The net flow of people moving into the region
is still expected to be positive because net international migration will more than offset the forecast
declines in net domestic migration. With a decreasing flow of migration, employers will have to
depend more on the homegrown labor force than they have in the past.
24
“Evaluation of Growth Slowing Policies for the San Diego Region”. San Diego Association of Governments
(SANDAG), 2001.
45
Figure 2.3
Annual Population Change Due to Migration
20.00
Net Migration (in Thousands)
15.00
10.00
Domestic
International
5.00
0.00
-5.00
-10.00
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
Year
SIZE AND COMPOSITION OF THE CURRENT AND FORECAST LABOR FORCE
The San Diego labor force, or the “supply of labor”, is projected to increase from 1,404,900 to
1,610,390, adding approximately 205,490 more workers between 2000 and 2010 (Figure 2.4). This
labor force growth rate of 14.6 percent is greater than the 13.2 percent rate of growth for the
general population and the 13.4 percent rate of growth for the working-age population25. The local
labor force growth rate is also greater than the 12 percent forecast change in the U.S. labor force for
the same period26. However, the pace of growth in the labor force from 2000 to 2010 is slower than
the change observed in the period from 1990 to 2000, when the labor force grew by 17 percent.
25
The labor force includes only civilian workers and excludes uniformed military personnel. Part of the increase
in the labor force is due to a small increase in the region’s labor force participation rate.
26
Fullerton, Jr., Howard N. and Mitra Toosi. “Labor Force Projections to 2010: Steady Growth and Changing
Composition”. Bureau of Labor Statistics, Monthly Labor Review, November 2001.
46
Figure 2.4
Labor Force Growth
1,650
1,610
1,600
Number of Workers in Thousands
1,583
1,596
1,567
1,550
1,548
1,528
1,507
1,500
1,484
1,465
1,450
1,445
1,400
1,405
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
Year
Looking more closely at the growth in the labor force, some demographic groups are projected to
grow more rapidly than others, creating a different composition in 2010. Figures 2.5 and 2.6 display
the current and forecast labor force by age, gender, and ethnicity. Similar to forecast changes in the
regional population, the most striking trend observed in the future labor force is the aging of San
Diego’s workers. Figure 2.7 shows that the largest age group category in 2000 to be 35- to 39-yearolds. In 2010, ten years later, the largest category is 45- to 49-year-olds. The group of workers ages
45 to 64 will exhibit the largest and fastest growth in labor force over the next decade. Sixty- to 64year-old workers alone will grow by 78.2 percent – faster than any other age group and much faster
than the average labor force growth for the region (Figure 2.5). Many baby-boom workers will be
on the cusp of retirement in 2010 and will begin exiting the labor force just after the 2010 horizon.
In contrast, the group of workers ages 25 to 44, capturing the “baby-bust” generation, will actually
shrink slightly by 2010. The group of workers ages 15 to 24 is expected to see positive growth as the
“echo-boom” generation comes of working age.
47
5.15%
10.04%
10.77%
11.28%
11.34%
11.65%
12.30%
11.17%
8.72%
4.87%
1.74%
0.69%
0.28%
5.00%
10.58%
12.01%
12.70%
13.62%
13.34%
11.75%
9.46%
5.92%
3.13%
1.42%
0.71%
0.34%
1,404,900
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
Total
1610,390
2010 Share of
Employment
2000 Share of
Employment
Age
Group
205,490
-0.06%
-0.02%
0.33%
1.73%
2.80%
1.70%
0.55%
-1.69%
-2.28%
-1.42%
-1.24%
-0.54%
0.15%
Numerical
Change
14.63%
-5.62%
10.97%
41.26%
78.15%
68.79%
35.24%
19.98%
0.08%
-4.59%
1.79%
2.78%
8.78%
18.07%
Percent
Change
Total
Female
Male
Gender
Total
Asian Female
Asian Male
Black Female
Black Male
White Female
White Male
Hispanic Female
Hispanic Male
Ethnicity
1,404,900
46.59%
53.41%
1,404,900
6.01%
5.64%
2.33%
2.61%
27.88%
31.78%
10.37%
13.38%
2000 Share of
Employment
Figure 2.5
Composition of the Labor Force
1,610,390
46.74%
53.26%
1,610,390
6.75%
6.57%
2.42%
2.64%
25.00%
28.05%
12.57%
16.00%
2010 Share of
Employment
205,490
0.14%
-0.14%
205,490
0.74%
0.94%
0.10%
0.03%
-2.89%
-3.73%
2.20%
2.62%
Numerical
Change
14.63%
0.15%
0.14%
14.63%
28.69%
33.66%
19.33%
16.05%
2.77%
1.17%
38.92%
37.05%
Percent
Change
1.15%
2.01%
2.22%
2.37%
2.05%
1.99%
1.54%
1.24%
0.81%
0.39%
0.14%
0.05%
0.02%
16.00%
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
Total
12.57%
0.01%
0.03%
0.13%
0.30%
0.68%
1.09%
1.33%
1.44%
1.67%
1.66%
1.73%
1.65%
0.84%
Hispanic
Female
Hispanic
Male
Age
Group
28.05%
0.12%
0.31%
0.76%
1.90%
2.95%
3.73%
3.82%
3.19%
2.81%
2.60%
2.37%
2.31%
1.19%
White
Male
25.00%
0.08%
0.17%
0.47%
1.43%
2.73%
3.18%
3.33%
2.84%
2.49%
2.43%
2.35%
2.27%
1.23%
White
Female
2.64%
0.00%
0.02%
0.04%
0.13%
0.22%
0.34%
0.38%
0.33%
0.28%
0.17%
0.25%
0.33%
0.14%
Black
Male
2.42%
0.00%
0.01%
0.02%
0.07%
0.19%
0.28%
0.39%
0.26%
0.24%
0.25%
0.26%
0.31%
0.14%
Black
Female
6.57%
0.02%
0.06%
0.11%
0.35%
0.60%
0.65%
0.68%
0.74%
0.84%
0.86%
0.83%
0.59%
0.24%
Asian
Male
6.75%
0.01%
0.04%
0.09%
0.28%
0.54%
0.65%
0.83%
0.86%
0.95%
0.94%
0.76%
0.57%
0.23%
Asian
Female
Figure 2.6
Labor Force Composition by Age, Ethnicity and Gender
(Shading indicates a category constitutes more than two percent of the total labor force)
Total
100.00%
0.28%
0.69%
1.74%
4.87%
8.72%
11.17%
12.30%
11.65%
11.34%
11.28%
10.77%
10.04%
5.15%
Figure 2.7
Labor Force by Age Groups
16%
14%
Percent Share of Labor Force
12%
10%
2000
2010
8%
6%
4%
2%
0%
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
Age Groups
The difference in sizes among generations in the labor force could create a shortage of employees
in their prime working years. One can draw two implications from this shortage. First, aging babyboomers will have to maintain and adapt their skills to stay productive as the times and technology
change, because there will be fewer younger people with new (technological) skills to replace them.
Second, members of the “echo-boom”, the youngest workers in the labor force coming in on the
heels of the “baby-bust”, may be required to accelerate their accumulation of skills to fill the
possible skill or experience gaps.
Breaking down the labor force by gender, women in the labor force will grow by 15 percent and
men by 14.3 percent in the next ten years. Although women make up a smaller share of the labor
force than men throughout the next decade, their share is expected to slightly increase because of
their slightly faster growth rate27. Figure 2.8 indicates that the share of men will decrease from 53.4
to 53.3 percent, while women will increase from 46.6 to 46.7 percent. The decreasing share of
workers ages 25 to 44 will likely mean that a declining share of women workers will be mothers
with young children28.
27
Although the population of working age men is expected to grow faster than that of women, the increased
share of women in the labor force can be accounted for by their rising rate of labor force participation.
28
Lerman, Robert I. and Stefanie R. Schmidt. “An Overview of Economic, Social and Demographic Trends
Affecting the U.S. Labor Market”. The Urban Institute, 1999. While fewer workers may need to care for young
children, more workers will likely have to care for elderly parents as the population ages.
50
Figure 2.8
Labor Force by Gender
54%
53.41%
53.26%
Percent Share of Labor Force
52%
50%
% Male
48%
% Female
46.74%
46.59%
46%
44%
42%
2000
2010
Year
As seen in Figure 2.9, Whites make up the largest share of the labor force in 2000 and 2010,
followed by Hispanics, Asians, and then Blacks. Figure 2.9 also shows how the shares of the labor
force by ethnicity change. Asians and Hispanics will make up an increasing share of the labor force,
while the share of Whites will decline. In 2010 the largest demographic blocks of the labor force will
be 45- to 54-year-old Whites and 20-to 34-year-old Hispanics. In both 2000 and 2010, the bulk of the
Hispanic labor force tends to be younger than other groups (Figures 2.5 and 2.6, see shaded cells).
Also, several demographic categories are predicted to grow rapidly. For example, population
growth and rising labor force participation rates are expected to make Black females ages 20 to 24
the fastest growing category, increasing by 132.3 percent.
51
Figure 2.9
Percent Share of Labor Force by Ethnicity and Gender
35%
30%
Percent of Labor Force
25%
20%
2000
2010
15%
10%
5%
0%
Hispanic Male
Hispanic
Female
White Male
White Female
Black Male
Black Female
Asian Male
Asian Female
Ethnic Group by Gender
The changing ethnic composition of the workforce may have an impact on the educational structure
of the workforce. According to census data, Hispanic workers have the lowest educational attainment
of any major ethnic group 29. Unless Hispanic youth and immigrants improve their education levels,
their growing numbers in the labor force will lower the overall educational attainment level in the
San Diego region. However, an increase in educational attainment levels in the labor force may occur
because of the growing presence of Asians 30. These ethnic trends are likely to be magnified in the San
Diego region (as compared to the nation) because there are large Hispanic and Asian communities
and large influxes of Hispanic and Asian immigrants. Also, evidence suggests that the problem of low
education among minorities is becoming more concentrated in males. Nationwide, Black and Hispanic
women were about twice as likely to have college degrees as men from these groups31.
29
Nationally, only 53.7 percent of Hispanics over the age of 25 had completed high school as of 2000, far lower
than the 84 percent figure for the entire population (2000 Census).
30
Nationally, as of 2000, 44 percent of Asians over the age of 25 had at least a BA, compared to 25.7 percent
for the entire population (2000 Census).
31
Affecting the U.S. Labor Market”. The Urban Institute, 1999.
52
LABOR FORCE PARTICIPATION
Labor force participation rates measure the proportion of a population that is in the labor force,
either working or looking for work. The overall labor force participation rate for the region-wide
civilian population increases only slightly from 2000 to 2010 (eight-tenths of a percentage point, see
Figure 2.1). This small amount of growth means that most of the change in the labor force is due to
population growth, not an increase in the participation rate. Labor force participation rates (as well
as their change) vary across demographic categories, as some groups are more likely to participate
in the labor force than others (Figure 2.11). In general, as shown in Figures 2.10 and 2.12, men tend
to participate at slightly higher rates than women. Figure 2.10 shows that in both 2000 and 2010, by
ethnicity, Whites and Asians tend to participate at slightly higher rates than Blacks and Hispanics.
Figure 2.12 shows that, by age, labor force participation rates take the shape of a parabola, with
low participation among young adults, a peak in participation at ages 45 to 49, and subsequent
lower participation among the elderly as they begin to retire.
Figure 2.10
Labor Force Participation Rates by Ethnicity and Gender
Ethnicity
Gender
Year
Hispanic
White
Black
Asian
Year
Male
2000
66.37%
69.00%
68.20%
70.28%
2000
75.25%
Female
62.04%
2010
67.42%
68.93%
67.32%
69.96%
2010
74.68%
62.68%
Change
1.05%
-0.07%
-0.89%
-0.32%
Change
-0.57%
0.64%
Figure 2.11
Labor Force Participation Rates by Age, Ethnicity and Gender
Age
Group
Hispanic
Male
Hispanic
Female
White
Male
White
Female
Black
Male
Black
Female
Asian
Male
Asian
Female
15-19
38.97%
27.22%
41.59%
45.18%
28.76%
29.27%
30.07%
29.96%
20-24
79.68%
65.17%
80.65%
75.71%
78.43%
65.67%
74.80%
75.41%
25-29
89.44%
70.63%
89.44%
78.82%
83.71%
61.82%
93.79%
73.99%
30-34
92.40%
66.96%
93.89%
77.56%
88.06%
71.16%
86.80%
80.71%
35-39
87.80%
68.90%
91.42%
77.92%
87.41%
79.46%
90.80%
82.84%
40-44
92.70%
62.85%
93.09%
82.64%
84.17%
69.82%
88.50%
86.74%
45-49
80.50%
65.27%
93.22%
83.27%
85.47%
98.95%
88.30%
93.76%
50-54
86.50%
67.81%
89.10%
76.64%
86.06%
73.99%
93.22%
71.56%
55-59
78.87%
56.03%
77.76%
67.80%
75.82%
70.03%
90.77%
63.21%
60-64
54.38%
33.31%
56.92%
40.37%
74.30%
30.96%
68.61%
40.49%
65-69
29.82%
21.18%
30.35%
19.00%
28.54%
11.74%
29.28%
17.38%
70-74
13.90%
6.33%
17.93%
9.21%
15.17%
11.28%
18.14%
8.29%
53
Figure 2.12
Forecast Labor Force Participation Rates by Gender and Age
100.00%
90.00%
Labor Force Participation Rate
80.00%
70.00%
60.00%
Male
50.00%
Female
40.00%
30.00%
20.00%
10.00%
0.00%
15
20
25
30
35
40
45
50
55
60
65
70
75
Age
Changes in labor force participation rates over time indicate which groups are joining or leaving the
labor force. Several demographic categories are projected to substantially increase their
participation in the labor force. For instance, Hispanic rates will increase by 1.6 percent. The
participation rate for women will increase by roughly two-thirds of a percent. In greater detail, the
shaded cells in Figure 2.13 show that there are many demographic categories where the
percentage-point change in participation rates is greater than two percent over the ten-year period.
For example, the participation rates of 40- to 49-year-old Hispanic females are projected to increase
by more than four percent.
54
Figure 2.13
Percent of Change in Labor Force Participation Rates by Age, Ethnicity and Gender
(Shaded cells indicate changes of more than 2 percent)
Age
Group
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
Hispanic
Male
0.52%
0.19%
0.00%
0.30%
0.72%
0.08%
2.54%
0.52%
0.07%
0.73%
0.88%
1.27%
-0.06%
Hispanic
Female
3.60%
2.27%
1.92%
2.39%
2.10%
4.27%
4.02%
2.15%
3.21%
1.92%
-0.28%
0.65%
0.28%
White
Male
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
1.48%
1.09%
3.89%
2.30%
0.00%
White
Female
0.04%
0.83%
1.39%
1.37%
1.47%
1.55%
2.08%
1.91%
4.30%
2.56%
0.76%
0.37%
0.09%
Black
Male
2.57%
0.44%
1.15%
1.17%
0.80%
1.78%
1.55%
0.61%
0.68%
-3.26%
1.14%
1.01%
0.85%
Black
Female
3.19%
2.17%
3.68%
1.55%
-0.01%
2.87%
-2.72%
0.91%
0.41%
2.40%
1.60%
-0.34%
-0.01%
Asian
Male
2.30%
1.17%
-0.87%
1.42%
0.12%
0.92%
0.98%
-0.82%
-2.31%
-2.12%
0.99%
0.42%
0.28%
Asian
Female
3.05%
0.23%
1.24%
-0.36%
-0.69%
-0.51%
-1.68%
1.40%
1.78%
0.49%
0.47%
0.26%
0.33%
EDUCATION AND SKILL LEVELS OF THE SAN DIEGO LABOR FORCE
While there is limited forecast information on the distribution of the San Diego labor force by
education and skill level, it is still possible to make some statements regarding the population’s
current and future educational composition. Figure 2.14 shows that in the 1990 Census, 40.8 percent
of the region’s population over 25 had only a high school degree or less, 25.3 percent had at least a
college degree, and 8.8 percent had a graduate degree. By ethnicity, in 1990, Asians tended to have
the highest educational attainment levels, while Hispanics tended to have the lowest. The figure also
shows the overall educational attainment levels of the over 25 populations of San Diego and the U.S.
for 2000. Looking at the 2000 data, the educational attainment levels of San Diegans have risen over
the past decade. In 2000, a smaller proportion of San Diegans had only a high school degree or less
than in 1990, and a larger proportion had at least a college degree32. It is also clear that the San Diego
region tends to have higher educational attainment levels than the nation as a whole.
32
San Diego educational attainment level data by ethnicity from the 2000 Census was not available for this
study; the data is scheduled to be released by the Census Bureau in the fall of 2002.
55
Figure 2.14
Educational Attainment Levels of the Over 25 Population
San Diego Region and the U.S., 1990-2000
9th to 12 th
grade
education
High school
graduate,
no college
Some
college, no
degree
7.6%
10.5%
22.8%
25.6%
8.2%
Less than
9th grade
education
Associate’s
degree
Bachelor’s
degree
Graduate or
professional
degree
1990
San Diego
16.5%
8.8%
28.4%
19.1%
19.7%
17.3%
6.0%
6.0%
3.4%
White
2.7%
8.5%
23.5%
27.5%
8.5%
18.8%
10.5%
Black
4.8%
13.3%
26.6%
32.0%
9.4%
9.4%
4.6%
13.1%
9.7%
19.4%
20.6%
9.3%
20.7%
7.2%
10.6%
11.7%
30.9%
19.3%
6.4%
13.5%
7.4%
San Diego
7.9%
9.5%
19.9%
25.6%
7.4%
18.7%
10.9%
U.S.
6.9%
8.9%
33.1%
17.5%
7.8%
17.1%
8.6%
Hispanic
Asian
U.S.
2000
Source: 1990 and 2000 Census.
Figure 2.15 shows that the number of students enrolled in high school in the region is expected to
increase through 2007, but is then predicted to begin a downward trend. The declining enrollment
is a result of the smaller forecast cohort of residents of high school age. However, despite the
declining trend in high school enrollments toward the end of the decade, there is still considerable
net growth over the entire study period. College enrollments are forecast to grow at a fairly
constant rate from 2000 to 2010, going from 150,830 to 167,060 students, an overall change of 10.8
percent. The current projected growth rate of college enrollments is slower than the projected pace
of growth of the labor force (14.6 percent). This suggests that unless San Diego increases capacity or
attracts graduates from outside the region, workers with a college education will account for a
slightly smaller share of the labor force in 2010 33.
33
Affecting the U.S. Labor Market”. The Urban Institute, 1999. The number of BAs is forecast to remain constant
nationally as well, but a relatively bigger labor force will mean that workers with BAs will decline as a
proportion of all new entrants into the labor market.
56
Figure 2.15
Enrolled Students
170
Number of Students (in Thousands)
165
160
155
150
High School
College
145
140
135
130
125
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
Year
WORKFORCE BARRIERS
Barriers to entering the workforce are basic health and social problems that keep people from
obtaining or maintaining employment 34. In some cases, prospective employees may appear
“unemployable” to companies because they lack basic work habits, or “soft skills”. Because of their
sociological nature, these barriers may need to be addressed by programs other than those geared
toward training for specific skills. Lower than average labor force participation rates for a given
demographic group may indicate the existence of a workforce barrier. Data from the County of San
Diego 35 presented here show that some groups of our region’s youth are more vulnerable to certain
barriers than others 36.
A first barrier that could inhibit entry into the labor force is difficulty finding or affording childcare.
Low-income mothers may opt out of the labor force due to the high costs of childcare, the
uncertainty of childcare programs, and transportation issues. Evidence suggests reducing the costs
34
“Barriers that could inhibit entry into the labor force other than those discussed in this section include
substance abuse, poor English language skills, and transportation problems. Prospective job seekers that abuse
substances may be more likely to have bad work habits and trouble securing employment because many
employers have “drug free workplace policies”. However, there is little data available on the effect of drug-use
on labor force participation in the San Diego region. As far as language barriers go, according to the 2000
Census, 33 percent of the region’s population speaks a language other than English at home. Of these, 45
percent (or 15 percent of the total population) speak English “less than very well”. Transportation systems that
do not meet the needs of low-income workers could act as barriers by limiting the number of employment
opportunities accessible to them.
35
“San Diego County Child and Family Health & Well-Being Report Card 2001”. County of San Diego Board of
Supervisors, 2001.
36
The 2001 Childcare Portfolio”. California Childcare Resource and Referral Network, 2001. In 2001 in San
Diego, full-time licensed care for an infant on average cost $163 per week, or $706 per month.
57
of childcare can help: A national study based on 1994 data found that, when childcare expenditures
were subsidized by 50 percent for women with incomes below the median in the Aid to Families
with Dependent Children (AFDC) program, employment increased by more than 25 percent 37. In a
different study by the California Employment Development Department, it was found that six
percent of all female part-time workers were working part-time to take care of children 38. In
contrast, only one percent of male part-time workers did so for childcare reasons. If these ratios
hold true for San Diego, a substantial number of working mothers could be helped to enter the
workforce with more affordable and accessible childcare options.
A second statistic that could indicate a workforce barrier is the high school dropout rate.
Prospective workers who have not completed high school may have trouble competing in the labor
market and may be discouraged from seeking future skill training. National data on the
employment status of dropouts versus non-dropouts shows that in 1998-1999, about 57 percent of
dropouts were in the labor force, whereas 84 percent – a much larger proportion – of high school
graduates (not enrolled in college) were in the labor force 39. Additionally, 26 percent of the
dropouts in the labor force were unemployed, whereas only 18 percent of high school graduates
were unemployed. Nationally, dropouts also have lower labor force participation rates: Of the over
25 population, dropouts participated at a rate of 42.7 percent, whereas high school graduates
participated at a rate of 64.8 percent. Figure 2.16 shows that single-year dropout rates in San Diego
are highest among Native Americans, Blacks, and Hispanics, who are more than twice as likely to
drop out as youths from other ethnic groups.
37
Connelly, Rachel and Jean Kimmel. “The Effect of Childcare Costs on the Labor Force Participation and
Welfare Recipiency of Single Mothers: Implications for Welfare Reform”. W.E. Upjohn Institute for Employment
Research, March 2001.
38
“Part-time and Seasonal Employment”. TRENDS, March 2002, Vol. 02-1, California Employment Development
Department Labor Market Information Division. With these figures for part-time female workers, it is likely
even more women stay out of the labor force entirely because of childcare factors. Also, 26 percent of all parttime workers cited their reason for working part-time as childcare and other family or personal obligations.
39
“Digest of Education Statistics 2000”. National Center for Education Statistics, 2000. See Chapter 5,
http://nces.ed.gov/pubs2001/digest.html.
58
Figure 2.16
Percent of High School Students that Drop Out of School Annually
by Race/Ethnicity, San Diego Region, 1997/98-1999/00
4.5
4
4
3.9
3.6
High School Dropout Rate
3.5
3
2.6
2.5
2.4
2
1.6
1.5
1.5
1.4
1
0.5
0
Overall
Native
American
Black
Hispanic
Pacific Islander
Ethnicity
Source: County of San Diego.
59
Asian
Filipino
White
Figure 2.17
Rate of Births to Teens Ages 15-17 by Race/Ethnicity
70
64.4
60
Births per 1,000 Teens
50
41.7
40
30
29.3
29
20
15.7
9.6
10
0
Overall
Hispanic
Black
Native American
Asian/ Pacific
Islander
White
Ethnicity
Source: County of San Diego.
A third possible barrier is teenage pregnancy. Teens that have to take on parenting duties may be
sidetracked from pursuing educational opportunities or working full-time40. Figure 2.17 shows teen
birth rates (the number of births per 1,000 girls ages 15 to 17) by ethnicity from 1997 to 1999. Data
shows that Hispanics are more than six times as likely and Blacks are more than four times as likely
as Whites to have a teenage pregnancy. High Hispanic teen birth rates may help explain the
relatively low labor force participation rates for young Hispanic females as compared to young
females of other ethnic groups in 2000 41.
40
For information on programs designed to reduce the incidence of teenage pregnancy see: Sawhill, Isabel.
“What Can Be Done to Reduce Teen Pregnancy and Out-of-Wedlock Births?” The Brookings Institution, Brief
#8, October 2001.
41
“Women of Hispanic Origin in the Labor Force”. Facts on Working Women, U.S. Department of Labor
Women’s Bureau, December, 1994.
60
CHAPTER 3
IDENTIFYING GAPS: COMPARING LABOR
SUPPLY AND JOB DEMAND
Chapter 3
IDENTIFYING GAPS:
COMPARING LABOR SUPPLY AND JOB DEMAND
This chapter examines how the current and future supply of labor in the region will match-up with
the current and future demand for labor. Our research seeks to determine whether the new
composition of the labor force will be adequately skilled to take advantage of the new employment
opportunities provided by the local economy. Stated differently, will employers be able to find the
kinds of workers they will need?
Current supply-demand “gaps” are compared with forecasts to investigate whether the gaps will
persist. Labor market supply-demand gaps are studied in three sections. First, the overall labor
market gap for the regional economy is analyzed by comparing current and future unemployment
rates. Second, labor market gaps are examined at various levels of education. Third, current labor
shortages for the traded clusters and cluster occupations are assessed using recent survey
information.
SUPPLY AND DEMAND MISMATCHES IN THE REGIONAL LABOR MARKET
A tight labor market can mean the economy is running efficiently, keeping nearly all of its labor
resources employed. The unemployment rate—representing the surplus of workers—is a good
indicator of the health of the regional labor market. As shown by Figures 3.1 and 3.2, the number
of unemployed workers in the San Diego region depicted by the gap between the size of the labor
force and employment was relatively small in 200042. While this labor force-employment gap is
forecast to be larger in 2010 than it was in 2000, it is still expected to be relatively small. In line with
this finding, Figure 3.3 shows that the unemployment rate is forecast to be stable over the next ten
years, staying in the three to five percent range 43. The persistence of low unemployment over the
next decade is likely the result of demographic changes. As the rate of population growth declines
in the future, so too will the rate of growth of the labor force. The slowdown of labor force growth
relative to the pace of job creation should act to keep the labor market tight.
42
See the Appendix for sub-regional unemployment data from the 2000 Census.
This indicates a tight labor market. Nationally, the non-inflationary rate of unemployment is estimated to be
five percent. This rate is considered full employment without the threat of igniting wage rate inflation.
43
63
Figure 3.1
Labor Force and Employment
1,650.00
1,610
Labor Force, Number of Employed Residents (in Thousands)
1,600.00
1,550.00
1,538
1,507
1,500.00
1,450.00
1,436
1,400.00
1,350.00
1,405
1,363
1,300.00
Employment
Labor Force
1,250.00
1,200.00
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
Year
Figure 3.2
Labor Force
1990
2000
2010
Labor Force
1,201,800
1,404,900
1,610,390
Employment*
1,145,700
1,362,900
1,538,010
Unemployed
56,100
42,000
72,380
4.7%
3.0%
4.5%
Unemployment Rate
* Includes self-employed workers.
64
Figure 3.3
Unemployment Rate
6.0
5.0
Unemployment Rate
4.0
3.0
2.0
1.0
0.0
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
Year
Forecast stability in the unemployment rate implies that unemployment will not be as big a
problem in the coming decade as it was in the last decade when the region experienced a recession.
As the quantity of jobs becomes less of an issue for the region, focus is shifted to the quality of jobs:
Public policies have an opportunity to be refocused on increasing worker productivity as opposed to
aggregate job creation.
LABOR SUPPLY AND EDUCATIONAL ATTAINMENT
The San Diego regional economy demands workers at all levels of education and skill. Despite the
tight labor market at the regional level, evidence suggests that a gap exists between workers and jobs
at the high-end of the labor market. By applying the distribution of educational attainment levels of
the San Diego population to the labor force, it is possible to estimate the number of workers with a
given level of education44. Likewise, occupational employment can be classified by minimum average
44
The educational attainment level data does not allow for the extraction of residents that are not part of the
working-age population (e.g., residents over 79, though technically not in the labor force, are still counted in
the educational attainment distribution). Unemployed workers were removed from the labor force by applying
national unemployment rates by level of education. Self-employed workers were proportionately removed
from the labor force at each education level. Because the amount of labor supply was estimated using census
data for San Diego County, it omits workers residing outside of the County (e.g., those living in either Mexico
or Riverside County).
65
training and education requirements45. Comparing these two distributions gives a picture of labor
supply and demand by education level. When the number of workers exceeds the number of jobs at a
given education level, there is a surplus of workers. When the number of workers is smaller than the
number of jobs at a given education level, the result is a shortage. These gaps at different levels of
education may vary from the overall condition of the regional labor market.
Figure 3.4 shows the supply and demand for labor by education level in 2000. The supply bars
represent the number of wage and salary-employed workers at each level. The demand bars
represent the number of wage and salary jobs. Demand is greater than supply for both the “No
college” and “Bachelor’s degree” levels. Supply is greater than demand at the “Associate’s degree”
and “Graduate or professional degree” levels.
Figure 3.4
Labor Supply and Demand by Education Level
Wage and Salary Employed Workers, Wage and Salary Jobs
1,000,000
900,000
800,000
700,000
600,000
500,000
2000 Labor Demand
2000 Labor Supply
400,000
300,000
200,000
100,000
No college
Associate's
degree
Bachelor's
degree
Education Level
Graduate or
professional
degree
Source: SourcePoint, Employment Development Department OES, 1990 and
2000 Census, 2000 Census Supplementary Survey.
Several implications can be drawn from these differences. First, because there are more workers
with graduate degrees than there are jobs that require such degrees, it is likely that many highly
educated workers in the region are employed in occupations for which their full educational
attainment is under-utilized. For example, a worker with a graduate degree may be employed at a
job that only requires a bachelor’s degree. Second, many workers may hold graduate degrees in
fields other than those demanded by the local economy (they are mismatched by their educational
discipline). Third, “intangible” worker characteristics other than the degree someone holds likely
play a large role in determining whether or not someone gets a job that requires their level of
45
Employment (the demand for labor) excludes self-employed workers.
66
education 46. In this case, educational attainment may not directly correlate with the occupation of
the worker.
While the data show there are not enough high-skill jobs in general, employers in the region are
still reporting a shortage of qualified workers for certain occupations (e.g., math and science
occupations, as shown by the cluster gap analysis in the following section). So, even though the
region is experiencing an overall surplus of highly educated workers, there nevertheless appear to
be labor shortages in some areas of the economy.
A surplus of highly educated workers makes it increasingly difficult for low-educated workers to increase
their economic position unless they have access to education and training resources. To increase
efficiency in the regional labor market, the challenge for local workforce development institutions will
be to design policies and programs to better equate the education of workers (by both educational level
and discipline) with the types of jobs available.
LABOR SUPPLY AND DEMAND IN TRADED CLUSTERS
This section focuses on local labor shortages in ten of the fifteen clusters studied in prior survey reports.
The ten clusters surveyed include Biomedical Products, Biotechnology and Pharmaceuticals, Business
Services, Computer and Electronics Manufacturing, Communications, Defense and Transportation
Manufacturing, Entertainment and Amusement, Medical Services, Software and Computer Services, and
Visitor Industry Services. Shortages within clusters are examined using survey data in two ways47. First,
comparisons of H-1B visa hiring patterns are made among clusters to gauge general shortages of highskill employees. Second, specific occupations with labor shortages within clusters are discussed. This
group includes occupations for which employers noted skill deficiencies, or current or expected
shortages.
H-1B Visa Use Patterns Among Clusters
H-1B visas are issued by the Immigration and Naturalization Service (INS) so that companies can hire
high-skilled foreign nationals. Workers under the H-1B visa program are often hired because local
employers cannot find the talent they need in the region. This is an indication of a shortage of
workers with certain skill sets in the region. It also represents employment opportunities missed by
the local labor pool.
As shown in Figure 3.5, survey data from ten of the fifteen traded clusters indicate that 1,593 jobs
were filled using H-1B visas in 2000. These positions were at 659 firms, representing nine percent of
all cluster firms. This means that firms that used H-1B visas hired an average of approximately three
H1-B visa workers. If the 1,593 H-1B employees were to be hired on an annual basis, based on
projections for 2002, it would constitute 1.36 percent of the total job openings in the ten clusters
surveyed 48.
46
The “intangible” characteristics that also affect a worker’s employability could include “soft” skills, language
competency, or specific skills required for a job. For example, an Electrical Engineer may have a college degree
but poor interpersonal skills. See Figure 4.5 in Chapter 4 for more examples of skill deficits.
47
“The San Diego Region’s Key Industry Clusters: A Labor Market Survey 2001”. The San Diego Workforce
Partnership, 2001.
48
Projected job openings represent total projected new hires, including both turnover and newly created
positions.
67
Figure 3.5
H-1B Visa Use in Traded Clusters
Cluster
Biomedical Products
Biotechnology and
Pharmaceuticals
Firms Using H-1B
Visas
Percent of Firms
Using H-1B Visas
Number of H-1BHired Employees
in Past Year
New H-1B
Employees as
Percent of Total
Projected
Openings
10
8.00%
15
1.82%
96
31.79%
364
7.47%
168
7.33%
414
0.96%
75
25.95%
104
1.77%
Communications
Defense and Transportation
Manufacturing
41
6.82%
102
1.64%
8
6.84%
42
2.70%
Entertainment
10
2.84%
4
0.04%
Medical Services
Software and
Computer Services
51
3.31%
50
0.47%
151
14.33%
153
1.89%
49
7.62%
345
1.31%
659
9.00%
1,593
1.36%
Business Services
Computer and Electronics
Manufacturing
All
Source: “The San Diego Region’s Key Industry Clusters: A Labor Market Survey 2001”. The San Diego Workforce
Partnership, 2001.
Data on H-1B visa use from the ten clusters surveyed suggests that four of the clusters are much
more reliant on foreign workers from outside the region and outside the country than others.
Figure 3.5 shows that Biotechnology and Pharmaceuticals, Business Services, Computer and
Electronics Manufacturing, and Software and Computer Services exhibit relatively high usage of H1B visas. The clusters with the greatest number of firms that reported using H-1B visas to fill
employment needs were Business Services (168) and Software and Computer Services (151). The
clusters with the highest percentages of firms using H-1B visas were Biotechnology and
Pharmaceuticals (31.79 percent), Computer and Electronics Manufacturing (25.95 percent) and
Software and Computer Services (14.33 percent). The most H-1B workers were hired in the Business
Services cluster (414), however the share of new H-1B hires as a percent of total projected job
openings was largest in Biotechnology and Pharmaceuticals (7.47 percent).
68
H-1B visa use patterns suggest that some clusters are in great need of workforce development and
training initiatives that will help supply workers with skills currently lacking in the local labor force.
The occupational analysis that follows gives a more detailed picture of the kinds of occupations the
local labor force is failing to fill.
Labor Supply and Demand in Traded Cluster Occupations
While some clusters utilize the H-1B visa program more than others, employer survey responses
indicate that there are current and possibly future shortages of workers in specific occupations
across nine of the ten clusters surveyed 49. To assure that data was collected on those occupations
deemed the most representative of employment trends in each cluster, occupations included in the
survey were selected by an industry advisory committee based on three criteria. These criteria
included considering the size of employment in each occupation; selecting occupations for inclusion
from all industries within a cluster (for breadth); and determining which occupations were
important or of growing importance to the industry. Although the survey only contains information
on a select group of occupations, it should provide clues on shortages in the most important areas
of cluster employment.
To determine if there is a shortage of workers in the San Diego region for an occupation within a cluster,
an occupation had to meet one of four “shortage criteria” used in evaluating employer responses. First,
did employers report difficulty in finding qualified applicants? Second, did employers recruit relatively
large numbers of workers from outside the region? Third, were many workers in this occupation hired
using H-1B visas (or did many firms report hiring for this occupation using H-1B visas)? Fourth, did
employers report that workers in a given occupation had inadequate skills to perform essential tasks? 50
According to the occupational employment shortage indicators presented in Figure 3.6, roughly
one-third (31 of 85) of the surveyed occupations are in short supply. Employment in these “shortage
occupations” represents roughly ten percent of all cluster employment (35,951 of 423,463 jobs). This
does not mean there is necessarily a ten percent shortage of workers in the traded clusters.
However, it does suggest there is a broad and sizeable shortage of labor for occupations in the
region’s traded clusters. In addition, shortages may be likely to continue into the future in
occupations where employers expect faster-than-average employment growth rates. The highlights
from the analysis of the shortage indicators in Figure 3.6 are listed below:
49
The Entertainment and Amusement cluster did not match any occupational shortage criteria. The shortage
occupations discussed here are sub-categories of the 35 broad occupational categories discussed in Chapter 1.
50
Because the survey did not include the same number of occupations for each cluster, it may appear that
there are greater labor shortages in certain clusters with many shortage occupations simply by virtue of the
fact that a greater number of occupations were surveyed.
69
•
The two clusters reporting the largest labor supply shortages are Biotechnology and
Pharmaceuticals and Communications.
•
The shortage of Software Engineers in the Software and Computer Services cluster affects the
most firms (482).
•
Occupational shortages were reported across clusters. Electrical and Electronic Engineers are in short
supply in the Biomedical Products, Defense and Transportation Manufacturing, and Computer and
Electronics Manufacturing clusters. Software Engineers are in short supply in both the Communications
and Software and Computer Services clusters.
•
Occupations for which employers reported the greatest number of specific skill deficiencies are
in the Medical Services cluster. Newly hired Certified Home Health Aides, Non-certified Home
Health Aides, and Occupational Therapists are reported to be deficient in all five of the skills
rated most important by employers (skill deficiencies are examined in greater detail in Figure
4.5 in Chapter 4). Employers in this cluster also reported having to recruit workers from outside
the region.
•
Occupations in the Medical Services cluster had the highest rates of turnover: Non-Certified Home
Health Aides (58 percent), Certified Home Health Aides (44 percent) and Occupational Therapists (30
percent).
•
Occupations for which employers encountered the most difficulty finding qualified applicants
are ASIC Engineers in Communications, Computer Programmers in Defense and Transportation
Manufacturing, Optical Goods Workers in Biomedical Products, and Bio-statisticians in
Biotechnology and Pharmaceuticals.
•
ASIC Engineers in the Communications cluster is the only occupation to meet all four of the shortage
criteria, suggesting a possibly significant shortage for workers with these skills. While there are
relatively few positions in this occupation, the number of new jobs is expected to grow by 19 percent
over one year, which suggests the shortage could persist over time.
•
Labor shortages were reported in some of the largest occupational categories, including Waiters
and Waitresses (10,940) and Restaurant Cooks (4,175) in Visitor Industry Services, Software
Engineers in Software and Computer Services (3,038), and Test Engineers (1,459) in
Communications.
•
The highest use of H-1B visas was for Biological Scientists, with 31.71 percent of Biotechnology
and Pharmaceuticals firms reporting using an H-1B visa, and Bio-statisticians, with 28.57 percent
of firms reporting use of workers with H-1B visas.
•
Occupations with the greatest percent of employees hired using H-1B visas are, among
Biotechnology and Pharmaceuticals firms, Life Scientists, with 8.79 percent of all employed Life
Scientists hired in 2000-2001 using H-1B visas; and among Communications firms,
Communications Systems Engineers, with 8.22 percent of all employed Communications Systems
Engineers hired in 2000-2001 using H-1B visas.
70
Turnover rate
3
1-year Turnover
2
Cluster1
17%
36%
2%
3%
15%
2%
9%
0%
8%
11%
0%
16%
31%
9%
13%
25%
25%
13%
13%
12%
4%
6%
12%
23%
44%
58%
30%
11%
10%
15%
13%
4
20
-83
77
9
114
12
47
-12
135
380
389
657
39
103
29
-21
139
24
41
63
8
-20
-80
13
0
0
295
202
69
19
Forecast 1-year
6%
14
6%
139
-12%
-68
10%
99
2%
97
8%
135
3%
44
8%
49
-8%
0
12%
255
50%
380
35%
563
67%
959
6%
101
9%
239
19%
67
-3%
164
18%
243
10%
56
8%
102
4%
127
6%
16
-4%
39
-15%
46
11%
66
0%
137
0%
116
10%
624
5%
606
5%
265
0% 1,491
5
Employment in
2000
61
10
327
119
680
15
788
22
608
88
1,392
21
344
32
618
2
144
12
1,093
120
761
0
1,110
175
984
302
709
61
1,094
137
152
38
750
185
788
104
245
32
490
60
1,459
63
138
8
478
59
550
126
118
52
235
137
391
116
3,038
329
4,175
404
1,291
197
10,940 1,472
Openings6
BIOM
BIOM
BIOT
BIOT
BIOT
BIOT
BIOT
BIOT
BIOT
BUS
BUS
BUS
BUS
CEM
CEM
COMM
COMM
COMM
COMM
COMM
COMM
DTM
DTM
DTM
MEDS
MEDS
MEDS
SCS
VIS
VIS
VIS
Number of Firms
Employing
38
15
148
77
111
128
124
30
67
236
127
387
230
160
71
19
111
60
200
92
76
41
34
52
37
28
92
482
78
143
83
Recruit Outside
3.5
2.0
2.2
2.5
H-1B Use:
Percent of Firms
Hiring8
12.50%
10.53%
13.64%
13.33%
16.67%
14.29%
20.00%
12.20%
12.12%
28.57%
31.71%
16.67%
25.00%
19.35%
2.00%
3.23%
2.97%
4.62%
4.35%
5.88%
4.13%
2.08%
6.25%
8.22%
3.57%
2.33%
5.72%
2.10%
2.29%
6.91%
8.79%
H-1B Use:
Percent of Total
1.09
1.00
1.17
1.10
1.23
1.05
2.00
1.13
1.13
1.14
1.14
Mean Difficultly
Finding Qualified
Applicants10
Employment
9
the Region7
Growth Rate
Forecast 1-year
Growth
4
Source: “The San Diego Region’s Key Industry Clusters: A Labor Market Survey 2001”. The San Diego Workforce Partnership, 2001. Compiled by SourcePoint.
Occupation
Electrical and Electronic Engineers
Optical Goods Workers
Biological Scientists
Bio-Statisticians
Chemical Technicians
Chemists
Life Scientists
Physical Scientists
Product Inspectors, Testers, Graders
Drafters
Inspectors and Testers
Systems Analysts
Telemarketers and Solicitors
Electrical Engineers
Electrical Technologists
ASIC Engineers
Communications Systems Engineers
Digital and Hardware Engineers
Network Systems Administrators
Software Engineers
Test Engineers
Computer Programmers
Mechanical Engineers
Certified Home Health Aides
Non-certified Home Health Aides
Occupational Therapists
Software Engineers
Restaurant Cooks
Travel Agents
Waiters and Waitresses
Figure 3.6
Labor Supply Shortages in Traded Clusters by Occupation, San Diego Region 2000 (See notes on next page)
Employment Characteristics
Shortage Criteria
100%
100%
100%
20%
60%
20%
40%
40%
Percent
Deficiency of Top
5 Skills11
Notes to Figure 3.6
1
Cluster Abbreviations
BIOM: Biomedical Products
BIOT: Biotechnology and Pharmaceuticals
BUS: Business Services
CEM: Computer and Electronics Manufacturing
COMM: Communications
DTM: Defense and Transportation Manufacturing
MEDS: Medical Services
SCS: Software and Computer Services
VIS: Visitor Industry Services
2
1-year Turnover
3
Turnover Rate
The number of employees in a given occupation that are not expected to be
working at the same company and position one year from the date of the
survey.
1-year turnover expressed as a percent of all employees in a given
occupation.
4
Forecast 1-year
Growth
The number of new employees employers expected to add within one year
of the date of the survey.
5
Forecast 1-year
Growth Rate
6
Openings
The number of new employees expected to be added as a percent of the
current total number of employees.
The total number of spaces to be filled in the next year, including both
forecast growth and forecast turnover.
7
Recruit Outside the
Region
Respondents to the survey were asked whether they “always” (4),
“frequently” (3), “sometimes” (2), “rarely” (1), or “never” (0) recruit outside
San Diego for an occupation. Occupations are considered to have shortages
if their scores are 2.00 or greater, indicating that, on average, firms
“sometimes” recruited outside San Diego.
8
H-1B Use: Percent of
Firms Hiring
9
H-1B Use: Percent of
Total Employment
The percent of an industry’s firms that have ever used H-1B visas to hire for a
given occupation.
The percent of current employees in a given occupation that were hired in
the last twelve months with H-1B visas.
10
Mean Difficulty
Finding Qualified
Applicants
Respondents to the survey were asked whether they had “great difficulty”
(2), “some difficulty” (1), or “no difficulty” (0) finding qualified applicants
for each occupation. Occupations are considered to have shortages if their
scores are 1.00 or greater, indicating that, on average, firms had “some
difficulty” finding qualified applicants.
11
The number of skills in which workers in certain occupations were found to
be deficient, expressed as a percent of the five skills surveyed.
Percent Deficiency of
Top 5 Skills
72
•
Occupations in the Business Services cluster that are expected to both have rapid growth in
demand and experience labor supply shortages include Telemarketers and Solicitors (67 percent
expected one-year growth rate), Inspectors and Testers (50 percent), and Systems Analysts (35
percent).
•
A decrease in the demand for employees in some occupations may help alleviate the supplydemand gap in the future. Occupations with employee shortages that expect declining rates of
growth include Biological Scientists (-83 percent) and Product Inspectors, Testers and Graders (12 percent) in Biotechnology and Pharmaceuticals, Communications Systems Engineers in
Communications (-21 percent), and Mechanical Engineers (-80 percent) and Electrical and
Electronic Engineers (-20 percent) in Defense and Transportation Manufacturing 51.
Consistent with the ten-year occupational growth forecasts presented in Chapter 2, occupations
requiring scientific and technical (computer) skills are experiencing shortages, and demand for these
occupations is expected to continue to grow. The occupations with employee shortages could affect
a broad cross-section of the regional economy. However, with information available on where the
labor force needs to be strengthened, future workforce development policies can focus training
resources toward preparing more workers for occupations in high demand.
51
Declines in some of these occupations could be reversed in light of the increases in defense related spending
since the events of September 11, 2001.
73
CHAPTER 4
WORKFORCE DEVELOPMENT CHALLENGES:
MEETING SKILL AND TRAINING
REQUIREMENTS
Chapter 4
WORKFORCE DEVELOPMENT CHALLENGES:
MEETING SKILL AND TRAINING REQUIREMENTS
The comparison of labor supply and demand discussed in Chapter 3 identifies several areas of the
San Diego regional economy where there is a shortage of workers with the skills needed by
employers. This chapter seeks to address the demand-supply gaps by identifying the types of
training the region’s workers require so they can better fill local job openings. More precisely, this
means describing the current and future education and skills the labor force must have to compete
in an increasingly knowledge-based economy. This also means looking at the current training
capacity of the region in hopes of evaluating how the training infrastructure needs to be improved.
Taking action to improve workforce training will enhance the quality of life of our region’s workers
by helping them get better-paying jobs and will also help employers find the skills they need. The
sections in this chapter include regional training requirements for select occupations, training
requirements in employment clusters, skill deficits in clusters, and regional training capacity, as well
as additional strategies to meet training requirements.
THE VALUE OF TRAINING
Before we look at any training requirements, an examination of the value of training shows why
meeting training requirements is so important. Improving the skills of workers so they can get
better jobs helps provide economic mobility. As Figure 4.1 shows, there is a clear link between
education and income. Education in the San Diego region definitely pays off: On average, annual
wages increase with the attainment of educational milestones. For example, people with an
associate’s degree earned an average of $40,934 per year in 2000. After obtaining a bachelor’s
degree they, on average, earned an additional $8,000 per year. Access to education and training
facilities is important for labor force preparation and mobility.
77
Figure 4.1
Average Annual Wage by Education and Training Levels
$80,000
$76,108
$67,749
$70,000
Average Annual Wage
$60,000
$57,545
$49,007
$48,718
$50,000
$40,934
$40,000
$36,561
$34,734
$30,828
$30,634
$30,000
$20,364
$20,000
$10,000
$Professional
Degree
Doctoral
Degree
Master's
Degree
Bachelor's
or Higher +
Experience
Bachelor's
Degree
Associate's
Degree
Vocational
Education
Work
Experience
Long-term
Training
M o d e r a t e - Short-term
term
Training
Training
Training Level
Source: California Employment Development Department Occupational Employment Survey, compiled
by SourcePoint.
CURRENT AND FORECAST
EDUCATON AND TRAINING REQUIREMENTS FOR THE SAN DIEGO REGION
This section discusses the current and future structure of the education and training requirements of
employment in the San Diego region. Figure 4.2 shows the educational requirements of total
occupational employment in San Diego and the U.S.52 in 2000 and 2010 by four levels of education:
graduate degree, bachelor’s degree, associate’s degree, and high school diploma. According to the
graph, a little over two-thirds of the jobs in the region require no post-secondary education. However,
findings suggest that the San Diego regional labor market has and will continue to have slightly greater
skill requirements than the nation as a whole. The San Diego market has slightly more jobs that require
graduate degrees, bachelor’s degrees, and associate’s degrees than does the U.S., and slightly fewer jobs
that require only a high school education or less. In 2000, 32.4 percent of the jobs in San Diego were
listed as requiring at least some college, whereas only 28.7 percent of jobs required that level of
education in the U.S. labor market.
Data presented in Figure 4.2 also show the forecast changes in the educational structure of
occupational employment in the region and the nation from 2000 to 2010. The forecasts show that,
over the next decade, both the local and national labor markets will add more jobs that require
post-secondary education than jobs that require only a high school degree or less. For example, in
San Diego, the number of jobs that require at least a bachelor’s degree is expected to grow by
approximately 21 percent, reflecting faster growth than jobs requiring other levels of education.
The share of jobs in the region that require a bachelor’s degree or a bachelor’s degree and work
52
Hecker, Daniel E. “Employment Outlook: 2000-2010: Occupational Employment Projections to 2010”. U.S.
Bureau of Labor Statistics, Monthly Labor Review, November 2001.
78
experience is expected to increase by one percentage-point. While the educational requirements of
the regional labor market are relatively stable over the forecast period, they do reflect a slow trend
of increasing skill requirements. In Chapter 3, it was shown that the greatest shortage of workers
was at the bachelor’s degree level. Evidence presented here on the changes in training
requirements provides further confirmation: To better meet current and future training
requirements, regional workforce development strategies will need to include plans for increasing
the number of bachelor’s degrees in the labor force.
Figure 4.2
Occupational Employment by Required Education Level
San Diego Region and the U.S., 2000-2010
Percent of Employment Requiring a Given Level of Education
100%
3.71%
90%
19.63%
3.84%
3.40%
17.20%
20.61%
3.50%
18.20%
80%
8.10%
70%
9.02%
8.70%
8.70%
Master's/ doctorate/ professional degree
60%
Bachelor's degree, or a bachelor's degree
and work experience
50%
Some post high school training
(associate's degree or vocational)
40%
Work experience, on-the-job training
67.65%
71.30%
66.84%
69.50%
San Diego 2010
US 2010
30%
20%
10%
0%
San Diego 2000
US 2000
Year
Source: California Employment Development Department Occupational Employment Survey,
Bureau of Labor Statistics.
At each education level, it is possible to more precisely identify the types of training that will be
required by looking at occupational growth. Certain occupations are forecast to grow rapidly, likely
creating an increased demand for the skills associated with those occupations in the future. Figure 4.3
shows the occupations that are forecast to grow the most over the next ten years by education level53.
For example, Paralegal Personnel are forecast to grow rapidly over the next ten years and usually
require at least an associate’s degree. An increase in the demand for paralegals means the region will
require more workers with training and skills in areas such as word processing, oral communication,
and legal research 54. If the case of paralegals is at all representative of other occupations, it is likely
that additional training will be required to help the labor force meet the new skill demands.
53
The occupations in Figure 4.3 were selected because, of the top ten occupations expected to add the most
jobs over the next ten years in each education requirement category, they were projected to have the fastest
growth rates. The occupations listed in this chapter are more detailed than those listed in Chapter 1. There are
a total of 35 occupational categories in Chapter 1, whereas the occupations here come from a total of over 400
categories.
54
“Occupational Outlook Report 2002”. The San Diego Workforce Partnership, 2002.
79
Figure 4.3
Education Requirements of Selected Occupations with Large Employment
Growth
Occupation
Educational
Requirement
Biological Scientists
Ph.D. Degree
1,431
2,172
Life Scientists, NEC
Ph.D. Degree
1,531
Postsecondary Teachers, NEC
Ph.D. Degree
6,305
Management Analysts
M.A./M.S. Degree
Graduate Assistants, Teaching
M.A./M.S. Degree
Computer Support Specialists
Computer Engineers
Systems Analysts, Elec. Data Processors
Employment
2000
Employment
2010
Numerical
Change
Percent
Change
740
51.73%
1,955
424
27.71%
7,973
1,668
26.46%
1,589
1,981
393
24.71%
1,102
1,373
272
24.66%
B.A./B.S. Degree
5,807
9,794
3,987
68.65%
B.A./B.S. Degree
4,681
7,701
3,020
64.53%
B.A./B.S. Degree
5,505
8,994
3,489
63.37%
B.A./B.S. + experience
4,411
6,194
1,783
40.42%
Engineers, NEC
B.A./B.S. Degree
5,953
7,985
2,032
34.13%
Paralegal Personnel
A.A./A.S. Degree
1,447
2,146
699
48.29%
Teacher Aides, Paraprofessional
A.A./A.S. Degree
5,997
7,771
1,774
29.58%
Vocational
3,006
3,818
813
27.04%
Health Care Profs., Paraprofs., NEC
A.A./A.S. Degree
6,380
7,989
1,608
25.21%
Engineering, Related Techs, NEC
A.A./A.S. Degree
3,868
4,463
595
15.38%
Amusement, Recreation Attendants
Short-term training
5,261
8,127
2,866
54.46%
Hand Workers, NEC
Short-term training
7,139
9,838
2,699
37.80%
Hand Packers and Packagers
Short-term training
7,167
9,461
2,294
32.01%
Engineering, Math, Natural Science Mgrs.
Hairdressers, Hairstylists
Sales and Related Workers, NEC
Guards and Watch Guards
Moderate-term training
6,442
8,233
1,791
27.80%
Short-term training
12,139
15,233
3,094
25.48%
Source: California Employment Development Department Occupational Employment Survey, compiled by SourcePoint.
CURRENT TRAINING REQUIREMENTS OF TRADED CLUSTERS
Additional information on training requirements is available for San Diego’s traded clusters.
Because of the central role clusters play in the San Diego regional economy in improving the
region’s standard of living, they are also a central piece of programs designed to equate the
region’s labor force with employment demands. This analysis of the training requirements of clusters
will help policymakers understand what kind of training our local residents will need to take
advantage of the many high value-added job opportunities clusters have to offer.
To start with a general perspective on current training demands, Figure 4.4 shows each cluster’s
average minimum training requirements. Based on 1999 data, for each cluster, the table shows the
percent of employment in that cluster requiring a certain level of education. While only 32.4
percent of the total jobs in the regional economy require post-secondary education, 39.3 percent of
the jobs in clusters require post-secondary education. Organizing the training requirements of
80
clusters in this way allows one to determine which clusters require highly skilled labor and which do
not. For example, 8.9 percent of jobs in the Medical Services cluster require a professional degree,
representing doctors, surgeons, dentists, and other highly trained medical professionals.
Two of the clusters with the largest employment in 2000, Business Services and Medical Services,
appear to have a fairly even distribution of employment by education level, In contrast,
employment in Visitor Industry Services – another cluster with many employees – is weighted
toward jobs with low educational requirements.
The clusters with the lowest training requirements are Visitor Industry Services, Entertainment and
Amusement, and Recreational Goods Manufacturing. Each of these clusters has a high proportion of
jobs that only require short-term, on-the-job training. Approximately three-quarters of Visitor
Industry Services employment required little or no training. As seen in Chapter 1, these clusters also
have low average wages. The low educational requirements of these clusters are consistent with
their large amounts of low value-added employment.
Other clusters require large proportions of skilled workers. For example, approximately seventy
percent of the positions in Biotechnology and Pharmaceuticals and Software and Computer Services
require a bachelor’s degree or higher. These two clusters, along with the high-end positions in
Medical Services, Communications, and Financial Services, appear to place the greatest training
demands on the region’s training infrastructure.
81
Moderate-term
Training
Short-term
Training
7.4%
0.5%
18.4%
6.7%
13.7%
25.7%
0.2%
3.1%
0.0%
9.9%
0.1%
1.3%
2.3%
0.5%
0.8%
12.8%
7.5%
10.6%
40.2%
14.5%
24.7%
11.7%
6.0%
6.3%
3.4%
9.6%
6.8%
2.9%
4.5%
9.7%
1.7%
2.4%
6.0%
5.2%
10.2%
9.7%
9.7%
41.7%
24.1%
0.0%
0.0%
0.0%
5.4%
14.0%
9.3%
1.9%
23.2%
0.9%
16.3%
29.0%
0.0%
0.0%
0.0%
4.7%
20.1%
3.8%
7.7%
8.9%
28.0%
6.3%
20.5%
0.0%
0.0%
1.0%
7.1%
3.1%
0.0%
3.3%
4.8%
6.3%
9.1%
65.4%
0.0%
0.0%
0.0%
9.9%
10.9%
5.6%
3.0%
15.3%
7.2%
4.7%
43.4%
0.0%
8.9%
0.0%
0.1%
0.4%
1.7%
11.3%
4.0%
20.8%
6.1%
0.4%
27.3%
4.0%
11.4%
10.0%
2.6%
3.1%
1.8%
5.9%
11.5%
44.1%
24.6%
0.0%
0.0%
0.0%
8.8%
1.8%
0.0%
2.5%
14.4%
2.1%
19.3%
51.2%
0.0%
1.0%
3.2%
16.0%
52.2%
3.7%
5.2%
2.2%
0.2%
8.2%
8.1%
0.0%
2.4%
0.0%
0.7%
0.0%
0.8%
3.2%
6.8%
0.9%
13.7%
0.0%
8.4%
2.4%
6.5%
8.4%
6.8%
7.7%
4.8%
2.7%
8.4%
74.7%
40.7%
Long-term
Training
17.2%
Work
Experience
Bachelor’s
Degree
10.5%
Associate’s
Degree
Bachelor’s
Degree plus
Work
Experience
0.0%
Master’s
Degree
0.0%
Doctoral
Degree
0.0%
First
Professional
Degree
Biomedical
Products
Biotechnology &
Pharmaceuticals
Business Services
Communications
Computer &
Electronics
Manufacturing
Defense & Trans
Manufacturing
Entertainment &
Amusement
Environmental
Technology
Financial
Services
Medical Services
Recreational
Goods
Software &
Computer
Services
Visitor Industry
Services
All 13 Clusters
Post-Secondary
Vocational
Education
Figure 4.4
Education and Training Requirements for Traded Clusters by Education Level*
* Cluster educational requirements are estimated using 3-Digit SIC cluster-industry employment shares and 3-digit SIC industry
staffing patterns. Because the staffing patterns only include occupations in an industry if there are at least 50 employees, the
educational requirements of jobs in industries with few employees in a given occupation were not included.
82
SKILL DEFICITS IN SELECTED CLUSTER OCCUPATIONS
Chapter 3 presented survey information identifying 31 occupations for which employers are facing
labor shortages, and identified nine of the 31 as occupations for which employers found workers’
skills deficient (Figure 3.6). The skill deficiencies and average educational requirements for these
nine occupations are listed in Figure 4.5. Almost 36,000 people are employed in the 31 skill-deficient
occupations, and over 14,000 of these people are employed in the nine where workers are found to
be skill deficient. This suggests that skill deficiencies could be present in forty percent of all jobs in
the “shortage” occupations 55.
The skills listed represent both highly technical skills that require long-term or intensive training
(“ability to prepare technical drawings”, “ASIC module design”) as well as “soft” skills (Electrical
and Electronic Engineers lack “interpersonal skills”). The skill shortages also appear in occupations
that represent a variety of educational requirements. Some occupations, such as Non-certified Home
Health Aides, require no formal education, only skills. Others, such as ASIC Engineers, require both a
college degree and specific technical skills. The three shortage occupations in the Medical Services
cluster noted frequent deficiencies in all five of the skills surveyed for those occupations. So, while
data on training requirements showed there are general attainment levels that workforce
development policies should strive to achieve, there are also very specific skills, which are found to
be lacking in the labor force.
55
Again, the survey data only covers 85 occupations in ten of the fifteen clusters. Data was only collected on
the level of deficiency for the five most important skills for each occupation, as determined by industry experts.
83
Figure 4.5
Skill Deficits in Selected Cluster Occupations
Occupation
Occupational Therapists
Cluster
Medical Services
Educational
Requirements
A.A./A.S.
Non-certified Home Health Aides
Medical Services
None
Certified Home Health Aides
Medical Services
High school
Drafters
Telemarketers and Solicitors
Business Services
Business Services
A.A./A.S.
High school
ASIC Engineers
B.A./B.S.
Physical Scientists
Communications
Biotechnology and
Pharmaceuticals
Biomedical Products
B.A./B.S.
Waiters and Waitresses
Visitor Services
None
B.A./B.S.
Skill Deficit
Ability to document progress reports
Ability to develop treatment plans and
exercise plans to gain or regain skills
Ability to apply patient care procedures
Ability to assess patient mobility and
ability to perform fine and gross motor
activities
Ability to apply human anatomy and
physiology knowledge
Ability to apply health and sanitation
standards
Ability to use good interpersonal
communication techniques
Ability to work as a team member
Ability to make beds
Ability to apply knowledge and practice of
general house-keeping duties
Ability to apply nursing practices and
procedures
Ability to apply personal care procedures
Ability to apply patient care procedures
Ability to provide in-home patient care
Ability to feed patients
Ability to prepare technical drawings
Oral commincation skills
Ability to apply sales techniques
Ability to speak continuously for 2 or more
hours
Ability to write module specifications for
ASIC design
Knowledge of concepts and practices
within the field
Knowledge of advanced mathematics
Ability to estimate time and cost of
projects
Interpersonal skills
Knowledge of types of food and
beverages
Source: "The San Diego Region's Key Industry Clusters: A Labor Market Survey 2001”. San Diego Workforce
Partnership, 2001.
84
REGIONAL EDUCATION AND TRAINING CAPACITY
This section looks at how education and training institutions in the region are working to meet the
region’s employment requirements. Currently, there are approximately 287 institutions that provide
some type of career training56. Detailed information from the National Science Foundation is only
available for the subset of these training providers involved in higher education. Figure 4.6 shows
that in 1998, the most recent year for which there is data, there were 7,029 associate’s degrees,
11,491 bachelor’s degrees, 5,119 master’s degrees, 796 professional degrees, and 555 doctorate
degrees awarded in the region. By subject area, the largest number of degrees in the region was
awarded in the “non-sciences/ unknown” category (5,647), followed by “business and
management” (4,058), “life sciences” (2,355), and “social sciences” (2,162).
Figure 4.6
Degrees Awarded by Academic Discipline
Discipline
Architecture and Environmental Design
Arts and Music
Business and Management
Communication and Librarianship
Interdisciplinary or Other Sciences
Law
Other Non-Sciences or Unknown Disciplines
Psychology
Religion and Theology
Social Service Professions
Vocational Studies and Home Economics
Education
Engineering
Geosciences
Humanities
Life Sciences
Math and Computer Sciences
Physical Sciences
Science and Engineering Technologies
Social Sciences
All Disciplines
A.A./A.S. B.A./B.S. M.A./M.S. Prof. Ph.D. All Levels
6
9
15
574
81
391
97
5
4,058
756
2,011
1,282
9
9
451
38
4
502
8
8
782
9
18
78
677
4,297
1,281
61
8
5,647
95
1,291
323
165
1,874
77
39
21
17
79
225
304
315
426
57
2
800
1,926
28
257
1,616
25
769
33
540
133
63
2
22
12
20
56
114
956
158
15
1,243
2,355
368
1,384
361
102
140
252
495
201
16
964
17
178
86
48
329
545
499
7
39
2,162
154
1,651
322
35
7,029
11,491
5,119
796
555
24,990
Percent of all U.S. Degees
Forecast U.S degree growth rate, 1998 to 2010
U.S. growth rate applied to San Diego
1.25%
8.53%
7,628
0.98%
12.68%
12,948
1.20% 1.00% 1.19%
2.81% 2.38% 1.07%
5,263
815
561
27,215
Source: National Science Foundation
56
San Diego Workforce Partnership. San Diego County Training and Education Provider (STEP) database,
www.sandiegoatwork.com.
85
Figure 4.7 shows the number of degrees awarded per one million people by different levels of education.
One can see that San Diego has a slightly stronger educational infrastructure by total volume of degrees
than the nation, as it generally awards more degrees per capita. However, San Diego awards fewer
degrees per capita at one level of education: bachelor’s degrees. San Diego has the greatest labor market
shortage at the bachelor’s degree level, requires slightly more bachelor’s degrees in the labor force than
the U.S., and will require an increasing number of bachelor’s degrees in the future, but does not produce
as many bachelor’s graduates per capita per year as the U.S. This speaks strongly for augmenting
bachelor’s degree programs in the region57. To move local workers into high-value added jobs and meet
employer needs in the region, this analysis suggests educational policymakers expand bachelor’s degree
programs in areas where there are current shortages and where there is expected to be future growth (see
Figures 3.5, 4.3, and 4.5). For example, with existing shortages in high technology and biotechnology
occupations, it is probable that the number of degrees that have been recently conferred in those
disciplines is not sufficient to meet current labor market demands.
Expansion of the region’s college programs alone will not suffice. According to data presented in
Chapter 2, large segments of the region’s population have low educational attainment levels and
are not adequately prepared for college (see Figure 2.14). Part of the solution to the current
shortage of skilled labor will have to include better preparation at the K-12 level, and encouraging
the region’s junior high and high school students to pursue coursework in math and science basics.
Figure 4.7
Higher Education Degrees Awarded per 1,000,000 People
San Diego Region and the U.S., 1998
10,000
9,000
8,000
Degrees per 1,000,000 People
7,000
6,000
SD
US
5,000
4,000
3,000
2,000
1,000
A.A./A.S.
B.A./B.S.
M.A./M.S.
Ph.D.
Professional
All Degrees
Degree
Source: The National Science Foundation.
57
Some expansions in college enrollment capacity in the region are already planned. Several of these new
programs and growing enrollments are described later in this section.
86
Figure 4.8 shows which higher education institutions in the region award the most degrees at each
level of education. The largest schools by degrees awarded are San Diego State University (SDSU),
the University of California at San Diego (UCSD), National University, San Diego City College, and
the University of San Diego. The two largest campuses, SDSU and UCSD, award approximately 45
percent of all higher education degrees in the region.
Education and training providers in the region are responding to market demands with plans
already underway to expand the current training capacity. In hopes of preparing more workers to
fill the high-skill positions that will be available in the San Diego labor market, several of the
higher education institutions in the region are planning to open new schools and departments
and increase enrollments. San Diego State University plans to create several new Ph.D. programs
over the coming years and also plans to increase total enrollments from 25,079 students in 2000
to 32,910 students in 2010, an increase of 31 percent 58.
Figure 4.8
Number of Degrees Awarded by Higher Education Institutions
City
Zip
Code
San Diego
San Diego
San Diego
San Diego
San Diego
San Diego
San Diego
San Diego
San Diego
San Diego
San Diego
San Diego
San Diego
San Diego
La Mesa
La Mesa
Chula Vista
El Cajon
El Cajon
El Cajon
Escondido
Oceanside
San Marcos
San Marcos
La Jolla
92121
92101
92101
92108
92101
92108
92106
92101
92111
92126
92182
92110
92131
92110
92042
92041
92010
92019
92020
92020
92027
92056
92096
92069
92093
Institution
California School Prof Psych at San Diego
California Western School of Law
Kelsey -Jenney College
National University
New School of Architecture
Pacific College of Oriental Medicine
Point Loma Nazarene College
San Diego City College
San Diego Mesa College
San Diego Miramar College
Thomas Jefferson School of Law
United States International University
University of San Diego
Coleman College
ITT Technical Institute
Southwestern College
Christian Heritage College
Cuyamaca College
Grossmont College
Westminster Theological Seminary in CA
Mira Costa College
California State University San Marcos
Palomar College
University of California at San Diego
Region Total
A.A./A.S
.
117
48
2,160
895
289
212
264
700
210
884
164
1,086
7,029
B.A./B.S.
1,135
6
360
4,783
58
977
99
69
139
644
3,221
11,491
Degree Level
M.A./M.S
Professiona
.
l
4
235
1,714
58
2,182
134
206
426
308
28
11
17
86
404
102
5,119
796
Ph.D.
Total
72
49
68
56
310
555
76
235
117
2,897
6
49
418
2,160
895
289
7,033
134
320
1,711
339
333
700
139
210
884
28
164
730
1,086
4,037
24,990
Source: The National Science Foundation.
The University of California at San Diego projects that student enrollments will increase from 21,000
in 2001 to approximately 29,000 in 2010, an increase of 38 percent. In the fall of 2002, UCSD will
58
SDSU Full-Time Equivalent Planning Estimates. Estimates represent full-time equivalent students and assume
securing additional capital and lease funding. New Ph.D. programs have been proposed in Audiology, Hearing
Science, Sociology, Earth Sciences, Geophysics, and Evolutionary Biology.
87
open a sixth college that will emphasize the interrelationships between culture, art, and
technology. The college will initially enroll 340 students per class, with total college enrollment
eventually projected to reach 3,500 students 59. UCSD plans to open a school of pharmacology by
2005, which will award Ph.D.’s in Pharmacy, Chemistry, and Pharmaceutical and Biomedical
Sciences60. They project 60 Doctor of Pharmacy students per class by 2005, with a total enrollment of
240 students. There are also plans to add a school of management with coursework that will
emphasize the intersection of business and high technology. The school plans to enroll 600 full-time
master’s students, 500 part-time and executive M.B.A. students, and 50 doctoral students.
As the comparison of labor supply and demand and training requirements indicates, it is important
that these kinds of plans and projections are met. Many of the planned educational programs are
geared toward occupations where cluster employers identified shortages of high-skill labor (e.g.,
Software and Computer Services, Biotechnology and Pharmaceuticals). Although the current
forecast growth rate for bachelor’s degrees in the U.S. is 12.7 percent (Figure 4.8), the San Diego
region can surpass this rate if the plans of local educators are successfully implemented. Both, UCSD
and SDSU, two institutions that educate a large share of the region’s higher education students,
project enrollments to increase by over 30 percent. Awarding an increasing number of bachelor’s
degrees in San Diego in the future at a faster rate than for the nation as a whole and a faster rate
than the expected 21 percent growth rate for jobs requiring a bachelor’s degree could go a long
way toward meeting our region’s labor market needs. Policymakers should work to ensure that the
necessary funding is made available for these planned expansions in higher education programs.
ADDITIONAL OPPORTUNITIES FOR MEETING TRAINING REQUIREMENTS
As changes in technology and the region’s demographics give rise to concerns of greater skill
shortages, several new and creative workforce development strategies could be implemented to help
meet the region’s training requirements. A first strategy involves finding ways to keep skilled workers
from leaving the workforce through part-time solutions such as “job sharing”. A recent report on
part-time and seasonal employment released by the California Employment Development Department
(EDD) notes that while just 12 percent of prime working-age workers in California were part-time in
2000, 46 percent of elderly workers (65 and over) were part-time61. This suggests elderly residents in
San Diego and elsewhere in the State could take advantage of further part-time employment
opportunities as an incremental step toward retirement, allowing them to remain in the workforce.
Job sharing options could also help retain mothers with young children who, for example, may have
difficulty finding child care. Two-thirds of all part-time workers in California were women and the
majority of women part-time workers reported working part-time for family and personal reasons.
Clearly, people in some demographic categories prefer part-time employment options if they are
available because they better accommodate their lifestyles. More part-time options could increase
both labor force participation and the overall supply of skills in the region’s workforce.
A second strategy involves identifying how training programs can better serve displaced and
underemployed62 workers to help them improve their skills in the currently restructuring regional
economy. In addition to helping retain workers in the labor force, part-time employment also
59
“Reinventing the University Campus”. http://sixth.ucsd.edu/cwnomination.pdf.
“New UCSD School to Meld Tech, Management Skills”. San Diego Union Tribune, October 18, 2001.
61
“Part-time and Seasonal Employment”. TRENDS, March 2002, Vol. 02-1, California Employment Development
Department Labor Market Information Division.
62
In this context, “underemployment” refers to working less than full-time hours.
60
88
represents an opportunity for skill training. The same Employment Development Department report
shows that, in California during 2000, nearly one out of five non-farm workers were employed parttime and nearly a third of these workers worked part-time to pursue schooling or training. Because
the majority of part-time employment is found in relatively low-wage occupations in services and
retail trade63, many part-time workers are prime candidates for skill training64.
It may also be worthwhile to direct training efforts at underemployed seasonal employees. The EDD
report notes that an estimated one out of nine non-farm jobs was seasonal. If such a ratio holds for
San Diego, it could mean an estimated 133,000 workers of the 1.2 million total wage and salary
workers in the region in 2000 were seasonal. Again, this represents a substantial opportunity for
off-season training programs. Construction, retail trade, and school-related occupations were all
identified as highly seasonal.
63
Seven out of ten part-time hourly wage earners were paid less than $10 per hour in California in 2000
compared to four out of ten full-time workers.
64
Although some workers may prefer part-time work to pursue training or for other reasons, some part-time
jobs do not provide worker benefits, and this would be a drawback.
89
CHAPTER 5
EARNING A LIVING WAGE:
THE ROLE OF WORKFORCE DEVELOPMENT
Chapter 5
EARNING A LIVING WAGE:
THE ROLE OF WORKFORCE DEVELOPMENT
st
California and its many regions entered the 21 century with a rapidly growing and changing
economy, driven by technological innovation. These changes are pushing the education and skill
requirements to participate in the state’s economic growth steadily higher. Technological change is
affecting the way work is conducted throughout the economy, not just in the technology industries.
During the 1990s, reports began to emerge that showed income inequality has risen sharply in
California over last two decades. Income inequality grew faster in California than the nation, but
not because of faster growth at the top of the income distribution. Instead, the greater increase in
inequality in the state resulted from a more substantial drop in income at the mid-to-lowest levels
65
of the income distribution . There are two primary causes of this rising inequality: earnings based
on skill, and immigration. Earnings based on skill measure the differential in earnings between
more and less skilled workers, where skill is defined in terms of years of schooling and work
experience. In California, the proportion of lower skilled individuals has increased relative to the
proportion of higher skilled individuals. In addition, immigration has contributed to the state’s
population growth, and the proportion of low-income immigrants has been greater than the
proportion of high-income immigrants.
Since education and skill development play a large part in determining income, an important role
for workforce development is to help individuals increase their earning power. One means of
measuring a region’s success in this area is to look at the proportion of residents who earn at least
enough to purchase life’s necessities. This chapter looks at various means for calculating the wage
that is required to “live” in San Diego. It then determines how well our region is doing at producing
jobs that pay this “living wage”, and finally evaluates various workforce development policies that
could improve the region’s performance in this area.
SAN DIEGO’S EXPERIENCE WITH A “LIVING WAGE”
A number of local agencies in San Diego have adopted guidelines or programs based on a “living
wage” concept. The San Diego Metropolitan Transit Development Board (MTDB) voted to enact a
“responsible bidder” policy during September 2001. The policy requires that all MTDB and
contracted bus drivers earn a living wage of $8.35 per hour with health benefits or $9.60 per hour
66
without health benefits .
65
Public Policy Institute of California, “The Distribution of Income in the State of California”, 1996. Also,
“California’s Rising Income Inequality: Causes and Concerns”, 1999.
66
The MTDB wage uses the Consumer Price Index to adjust for inflation.
93
The San Diego Workforce Partnership uses wage standards to implement the region’s Workforce
Investment Act (WIA) programs in two different ways. First, the Workforce Partnership uses a
minimum beginning salary standard to determine whether or not to contract with given training
providers. To be eligible to receive funding from the Workforce Partnership (whether through
direct payment or a Workforce Partnership voucher from an individual client), training providers
must train “low-income adults” for jobs that will lead to wages of more than $300 per week or $9
per hour, and train dislocated workers for jobs that will lead to wages of more than $400 per week
67
or $14 per hour .
Second, the Workforce Partnership uses a “self-sufficiency” wage to determine whether employed
individuals can be eligible for additional “One-Stop Career Center” services and training. For
68
employed adults, the Workforce Partnership Policy Board voted to establish a self-sufficiency wage
standard at 150 percent of the Federal Lower Living Standard Income Level (LLSIL). The LLSIL is
based on a family budget methodology, which varies by the number of people in a family. For one
person (no family) in the year 2000, 150 percent of the LLSIL was $16,365 annually, or about $7.86
per hour for a person working full-time.
The City of San Diego uses self-sufficiency wage standards when deciding whether or not to
69
authorize business development incentives for private firms . For a firm to be eligible for financial
incentives from the City, it must make a commitment to hire at least ten full-time employees
through One-Stop Career Centers and must meet one of three additional criteria: 1) pay these
employees the self-sufficiency wage for a family of four of $14.40 per hour; 2) pay these employees
an alternative self-sufficiency wage rate, provided it is approved by the Workforce Partnership; or 3)
demonstrate that there exist career ladders that will allow employees to advance to higher wages in
the future. For the self-sufficiency wage standard, the City also uses the 150 percent of the LLSIL
adopted by the Workforce Partnership.
MiraCosta College, located in Oceanside, uses “family living wage” criteria to evaluate its vocational
programs. One of the college’s goals is for its students to obtain skills and knowledge that will
allow them to earn a family living wage, which is defined as a regionally adjusted poverty level for
a family of four. When deciding what vocational curricula to offer, college staff take into
consideration whether prospective occupations will provide family living wages. An analysis of the
various ways of calculating a living wage could help these agencies determine how effective their
policies are at meeting their goals.
METHODS FOR CALCULATING A LIVING WAGE
Since 1994, a number of localities have tried to calculate the dollar level of a living wage for their
communities. These localities have adopted a variety of methods for making this calculation, five of
which are reviewed in this section. The first is negotiation over what the rate should be among
interested parties. The second is to set a wage based on some higher percentage of the federal or
state minimum wage standards. The third is to base the wage on industry-specific “prevailing
67
Waivers may be available for programs that train for jobs with starting salaries below $9 per hour where
there is a documented career ladder and path leading to demand occupations and self-sufficiency.
68
The San Diego Consortium Policy Board.
69
Community and Economic Development Strategy FY2002-2004 Action 1, City of San Diego, FY2002-2004.
94
wages”. The fourth is to base the rate on the federally defined Poverty Guideline. The fifth method
is to use a budget approach to understand how much self-sufficiency costs.
Negotiation
Negotiations between local policymakers and organized labor or other living wage advocates within a city
council or other local decision-making forum have been a common path chosen to set living wage rates. In
the typical pattern, labor groups or local living wage coalitions (such as the Association of Community
Organizations for Reform Now, ACORN) make a wage rate proposal before a city council. While advocates
may use formal assessments as a starting point, the approved wage rate may reflect both what they
determine a family in that geographic location minimally needs, and what they think they have a fair
chance of getting adopted. There is anecdotal evidence that suggests the wage rate of $11.00 per hour
including health benefits established in Santa Cruz, CA was agreed upon using this method.
Minimum Wage
Some localities have set their living wage rate based on some multiple of the federal or state minimum
wage. This allows localities to adapt broader minimum wage laws for their higher costs of living. For
70
example, Hudson County, New Jersey set its living wage at 150 percent of the federal minimum wage .
71
Similarly, California’s minimum wage is set at more than 130 percent of the federal minimum wage .
Prevailing Wage
Prevailing wage laws require that workers on certain public projects be paid a specified minimum
wage (typically termed the “prevailing wage”). Depending on the state, the wage rates used may
be taken from local collective bargaining agreements or may be the result of calculations to
determine what wage rates are “prevailing” in a given community. Some communities, such as
Memphis and New York City, have set their living wage rates according to the prevailing wage rate.
Federal Poverty Guideline
A fourth method for setting a living wage rate is to use the Federal Government’s Poverty Guideline
to represent a wage that (statistically) lifts a worker (and his or her family) above the official
72
poverty level income threshold . Living wage rates have been set based on the official Poverty
Guideline in three different ways. The first technique involves setting the hourly wage rate
73
equivalent to the Poverty Guideline for a given family size . In the second, the wage is set as some
higher percentage of the Poverty Guideline. Third, the Guideline, a national statistic, is adjusted up
by a geographically specific cost of living differential, in effect tailoring the poverty level to a
geographic region. This third procedure has been a popular way for some in California communities
to determine a living wage, including San Jose.
70
The federal minimum wage is currently $5.15 per hour.
The California minimum wage is currently $6.75 per hour.
72
The Poverty Guideline for 2001 is $17,650 for four persons (www.aspe.hhs.gov/poverty). The Guideline was
and is still calculated by taking three times the price of a basket of food because, historically, food accounted
for 31 percent of a consumer’s expenses. It is a guideline for minimum sustenance.
73
In the San Diego region, the San Diego Metropolitan Transit Development Board based its $8.35 per hour
wage for bus drivers on the poverty line for a family of four.
71
95
For San Diego, in 2001, an estimate using this method for the average family size of three people
74
could be made with the formula used by San Jose . The hourly poverty-level wage for three people
is $7.03 (based on $14,630 per year divided by 2080 work hours per year). Multiplying the hourly
poverty wage by a cost of living differential of 126.7 percent, the difference between national
average prices and prices in San Diego, yields $8.91 per hour. San Jose and other locations have
added an additional $1.25 per hour if health care is not provided by employers (based on estimates
for the average cost of health care per low-wage worker). For San Diego, this would equal $10.16
per hour.
$7.03 per hour * 126.7% = $8.91 per hour Living Wage Rate
$8.91 per hour + $1.25 per hour for health insurance = $10.16 per hour
Methods based on the Federal Poverty Guidelines have been the most popular for determining
wage rates. Approximately twenty-five percent of living wage levels were set using the official
75
poverty level in some manner . The use of the Poverty Guideline is likely so ubiquitous because it is
the official threshold used by the Federal Government to assess whether poor citizens are eligible
76
for many means-tested programs, and is regarded as a credible and reliable measure of poverty .
Basic Needs Budget
Redefining the concept of poverty in relation to need was endorsed in 1995 by a National Academy
of Sciences (NAS) panel charged with recommending ways to fix how the poor are measured
77
nationally . Although the panel’s recommendations for revising how the Poverty Guideline is
calculated have not yet been adopted by the Federal Government, a needs-based poverty definition
could be used to set a living wage level in the San Diego region. The goal of a needs-based
approach in addressing self-sufficiency is to identify what wage is needed to meet an individual’s or
78
family’s cost of living . Typical cost categories included in assessing basic needs are food, rent,
utilities, childcare, clothing, and transportation. A needs-based approach is advantageous because,
as in San Diego’s case, the wage would be tailored to reflect that a region’s costs of living might
vary drastically from the national average cost of living. The drawbacks of a needs-based approach
are that it is not standardized like the current poverty measure and it is more complex to calculate.
The precedent for using a basic needs budget to define a living wage was set by the City of
74
The source for the cost of living differential is the ACCRA Cost of Living Index, Fourth Quarter, 1999. The
index compares prices at a single point in time. The differential is listed in the U.S. Census Bureau’s Statistical
Abstract of the United States, 2000 online edition. It assumes a mid-management standard of living. This is not an
exact fit for the low-wage population targeted by a living wage, however it still provides a useful comparison. Other
cities, including San Jose, have used the Economic Research Institute’s (ERI) Relocation Assessor. One reason San Jose
opted for ERI’s product was that ACCRA does not produce a differential for San Jose or the Bay Area.
75
“The Living Wage and Federal Measurements of Poverty”. Employment Policies Foundation, www.epf.org.
76
In means-tested programs, an individual must meet certain criteria (e.g., low-income) to be eligible for
benefits. The Poverty Guideline, maintained by the Department of Health and Human Services (HHS), is used
for this purpose because it is set during the current year. The Poverty Threshold, a slightly different measure
maintained by the Census Bureau, is used for statistical purposes to set the income level for estimating the
official poverty rate. However, the Poverty Thresholds are not published until the summer after the calendar
year that is being measured. The Guidelines were designed for practical use because the Threshold numbers
are already dated by the time they are released.
77
Short, Kathleen, U.S. Census Bureau, Current Population reports, P60-216, “Experimental Poverty Measures:
1999”, U.S. Government Printing Office, Washington, D.C., 2001.
78
Pearce, Diana. “The Self-Sufficiency Standard for California”. Wider Opportunities for Women (WOW),
November 2000.
96
Richmond, California in October, 2001 when it passed a budget using 1999 California Budget Project
figures. Richmond set the living wage at $11.42 per hour, $12.92 per hour without employerprovided health insurance.
So far, these budget-based efforts to set a living wage have evaluated local costs for each city or
region. We have identified four advocacy groups that produce budget-based costs for the San
Diego region: The California Budget Project (CBP), The Center on Policy Initiatives (CPI), The
79
Economic Policy Institute (EPI), and Wider Opportunities for Women (WOW) . But, without official
federal guidance on how to proceed, two questions arise in the construction of these budgets:
What are the “basic necessities” for a low-income working individual or family? And, what data
sources should be used to measure the costs of these necessities?
ANALYSIS OF LIVING WAGE METHODOLOGIES
San Diego’s criterion for selecting a living wage methodology should be that it provides the best
estimate of the minimum wage necessary to live in San Diego. The first three methodologies
discussed – negotiation, a multiple of the minimum wage, and prevailing wage – are not based on
the cost of living in a region. Negotiation may use a calculation of costs as a starting point (though
not necessarily), but, in the end, likely arrives at a figure far from what is required to live. A
multiple of the minimum wage may improve on a region’s existing wage floor, but it does not
ensure that this improvement is enough to cover a region’s cost of living. Adopting a prevailing
wage as the living wage may also improve on a region’s existing wage floor, but again, it does not
ensure that the wage will cover a region’s costs.
In theory, using the Federal Poverty Guideline as a base should yield a viable living wage level. After
all, the federal poverty measure was originally developed to assess income adequacy. However,
most would agree that the poverty measure has become increasingly problematic as a measure of
income adequacy. The problems with the measure of poverty have led some assistance programs to
use a multiple of the poverty standard to measure need (e.g., extending Medicaid coverage to
families earning 50 percent more than the poverty threshold).
Since the official poverty measure was first developed and implemented during the early 1960s, it
has only been updated to reflect inflation. Two of the most noted criticisms of the poverty
measure are attributable to its methodological structure. First, the federal poverty measure is
based on the cost of a single item, food. Second, it assumes a fixed ratio between food and all
other needs (housing, clothing, transportation, etc.). This fixed ratio does not allow for some costs
to rise faster than food. A third criticism of the poverty measure is that it has not kept pace with
the demographic changes that have occurred in the nation since its inception during the 1960s. At
that time the demographic model was the two-parent family with a stay-at-home wife.
A fourth criticism of the federal poverty measure is that it does not vary by geographic location,
neglecting the substantial geographic differences in the cost of living. The differences in the
79
November 2000. “San Diego Snap Shot: Making Ends Meet”. Center on Policy Initiatives, 2001.
www.onlinecpi.org. “Making Ends Meet: How Much Does It Cost to Raise a Family in California?” Sacramento:
California Budget Project, September 2001. www.cpb.org. The CBP Budget covers both San Diego and Imperial
Counties. “Basic Family Budget Calculator”. Economic Policy Institute, 1999.
http://www.epinet.org/datazone/fambud/budget.html.
97
80
cost of living between areas are particularly large for housing . While this fourth drawback
could be adjusted for as discussed in the “Federal Poverty Guideline” section, the other three
drawbacks cannot.
LIVING WAGE ESTIMATE FOR SAN DIEGO
Of the five ways to estimate the living wage reviewed in this study, the budget-based procedure
seems best suited to assess income adequacy and self-sufficiency. The proposed budget-based
approach presented here uses national level cost of living data and adjusts it for local cost of living
differences. This procedure can be applied broadly to any jurisdiction in the country, and allows for
standardized comparisons. The results of our basic needs budget approach are presented in Figures
5.1 and 5.2. The Figures show the budget categories, including health care and taxes, as well as the
sources of the expense estimates (mostly national data that has been adjusted to San Diego based
on a geographical cost of living adjustor). According to our budget approach, an individual working
81
full-time needs to earn $11.58 per hour, or $24,077 annually to be self-sufficient in San Diego .
80
November 2000.
81
To obtain the hourly living wage, monthly expenses were multiplied by 12 to get yearly figures. These yearly
figures were then divided by the conversion factor of 2,080 work hours per year. Cost of living adjustments
could be applied category by category, rather than using the same adjustment factor for all categories. See
Appendix D for further technical details of the budget.
98
$217.39
$116.99
Health Care
Clothing/ Personal
99
Hourly Wage, Employer-Provided Health Insurance
* See Appendix D for more information on calculating the basic needs budget.
Source: Compiled by SourcePoint.
$1.59
$9.99
Health Care per Hour
$2,006.49
$24,077.91
$11.58
Hourly Living Wage Rate
Annually
$376.04
Total Monthly Taxes
Monthly
$4,512.51
$0.00
Total Annual Taxes
EITC
$176.36
$2,494.19
$19,565.40
$1,630.45
$1,841.96
CA State Income Tax
National Medical Expenditure Panel Survey
Health Care per Hour Subtracted from Hourly Wage
12 Months per Year
2080 Hours per Year
Form 540; 2000 CA Tax Table (1.45% Tax Rate, Est.)
Form 1040EZ (15% Tax Rate)
Federal Rate = 7.65%
ACCRA Adjustor (U.S. Statistical Abstract)
$148.22 WOW's 10% of Other Expenses Assumption (Not Taxes)
$275.43
Fed Income Tax
$15,442.28
1.267
USDA Low-Cost Food Plan
Source
HUD Fair Market Rent National Average
$356.51 National Transportation Survey; IRS Cost-per-mile Rate
$212.98
San Diego
Adjusted
Monthly
Amount
$637.30
Fed Payroll Tax
Yearly Pre-tax Income
$1,286.86
$281.38
Transportation
Subtotal
$168.10
Monthly Expense/ Earnings
Food
Rent/ Utilities
National
Monthly
Geographical
Amount
Adjustor
$503.00
Figure 5.1
Basic Needs Budget – Single Adult*
The budget-based local living wage rate assumes a minimum level of expenses a person would
need for basic self-sustenance (shelter, food, health care, transportation, clothing, and taxes).
Expenses are sparse in that they do not include any common luxury expenses such as savings,
college tuition, major durable goods, or food away from home. The Rent/ Utilities and Food
costs are based on low-income level standards. For Health Care and Transportation, average
national per person expenses are used. It is assumed that when health care is employerprovided, it is an average level of coverage. Health Care costs include both insurance premiums
82
and out-of-pocket expenses . It is also assumed that low-income individuals commute the same
distances to work as the average person and require a car in the San Diego region.
Transportation costs include gas, insurance, vehicle registration fees, maintenance costs and
depreciation, as measured by the IRS cost-per-mile rate, but not the cost of purchasing a car.
Figure 5.2 shows the percent share each expense category contributes to the budget-based cost
of living estimate for an individual in San Diego. The Rent/ Utilities category contributes the
largest amount to the total, accounting for 32 percent of the budget. While this share may
seem high, it is consistent with the statistic that over half of all San Diegans spend a third of
their income or more on rent or mortgage payments. Note that Food accounts for only onetenth of the total budget instead of the one-third it was assumed to be when the Poverty
Guidelines were enacted. This provides further evidence that the Federal Poverty Guideline,
which is based on three times the cots of food, may need to be revised.
Figure 5.2
Percent Share of Budget Components
Total Budget: $24,077 ($11.58 per hour)
Total Taxes
19%
Rent/ Utilities
32%
Clothing/ Personal
7%
Health Care
14%
Food
10%
Transportation
18%
Source: SourcePoint.
82
See Appendix D for more detailed information on Health Care costs.
100
Figure 5.3 provides additional information on hourly wages that can be used to compare against
the budget-based approach. The Figure shows hourly wage amounts for different programs and
family circumstances. The $11.58 per hour wage derived using the budget-based approach is
considerably higher than the California minimum wage, Poverty Guidelines and geographically
adjusted Poverty Guidelines, as well as some other living wage rates based on basic needs budgets.
Even after adjusting for cost of living differences, the Federal Poverty Guideline for the nation is still
below the California minimum wage. The San Diego budget-based hourly wage of $11.58 per hour
is more than 70 percent higher than the California minimum wage. San Diego’s budget-based
approach for an individual is nearly eight percent higher than the Federal Poverty Guideline for a
family of four, adjusted for cost of living differences.
The budget-based living wage estimate for San Diego is 35 percent higher than the WOW SelfSufficiency Standard estimate for an individual in San Diego. Because they are both budget-based
approaches, it is possible to compare individual budget categories and other adjustments. Most of the
differences between these similar approaches were in Health Care costs and the application of the
cost of living adjustment. The budget-based approach suggested in this study applied the cost of
living adjustment across all budget categories, effectively raising the cost estimate to live in San Diego
by nearly 27 percent. The WOW Self-Sufficiency Standard’s cost estimates for all but Rent/ Utilities and
Health Care were nearly the same as the budget-based approach before the cost of living adjustment
was applied. The cost of Rent/Utilities was nearly the same under each method. However, the WOW
Self-Sufficiency Standard cost estimate for Health Care was over 120 percent lower for than for this
study’s budget-based approach ($98 per month compared to $217 per month).
Figure 5.3
Comparison of Working Poor Wage Rates
San Diego Region (2001$)
$14.00
$11.58
$12.00
$10.75
$10.00
Wage Standard
$9.05
$8.35
$8.49
San Diego
MTDB
"Responsible"
Wage
National
Poverty
Guideline, 4
Persons
$8.00
$6.75
$6.00
$5.23
$4.30
$4.00
$2.00
$National
Poverty
Guideline, 1
Person
Poverty
Guideline, 1
Person,
Adjusted for
San Diego
California
State
Minimum
Wage (2002)
Wages in Dollars per hour
101
WOW SelfSufficiency
Standard for 1
Adult in San
Diego
National
Poverty
Guideline, 4
Persons,
adjusted for
San Diego
Budget-Based
Living Wage
Estimate for 1
Adult in San
Diego
BASIC BUDGETS FOR OTHER FAMILY TYPES
Figure 5.4 shows WOW’s self-sufficiency basic needs budgets for various other family types in the San
Diego region using 2001 expenses. The WOW Self-Sufficiency budgets vary both by the number of
83
people in a family and the ages of the children . It becomes clear that an adult and an infant have
significantly greater living costs than a single adult, and would require much more income to afford
basic necessities. Because of greater child and health care costs, it costs over $2.00 more per hour for a
single adult to raise an infant than to raise a teenager ($14.61 per hour versus $11.54 per hour, not
shown). Note that the wage each adult must earn for a two-parent, two-child family to be self-sufficient
is five percent less than the budget-based wage for an individual. This demonstrates how basic budgets
and expenses do not increase proportionately with the number of individuals in a family because larger
families are able to achieve economies of scale by sharing expenses (e.g., housing).
Figure 5.4
WOW Self-Sufficiency Standard Basic Budgets for Various Family Types
San Diego Region, 2001*
Family Type
Monthly
Expenses
Rent/ Utilities
Food
Transportation
Child Care
Health Care
Clothing/ Personal
Total Taxes
Monthly (Sum of Expenses)
Hourly (per Adult)
Annually
Health Care per hour
Hourly, No Health Care
1 Adult
1 Infant
1 Adult
1 Preschooler
1 School Age
2 Adults
1 Preschooler
1 School Age
$850
$254
$233
$661
$254
$226
$441
$850
$393
$233
$922
$254
$265
$411
$850
$540
$444
$922
$317
$307
$507
$2,921
$16.60
$35,061
$1.47
$14.61
$3,330
$18.91
$40,004
$1.45
$17.47
$3,885
$11.04
$46,626
$1.80
$9.24
2 Adults
1 Preschooler
1 School Age
1 Teenager
$1,182
$657
$444
$922
$372
$358
$606
$4,540
$12.89
$54,465
$2.14
$10.75
Source: Pearce, Diana. The Self-Sufficiency Standard for California. Wider Opportunities for Women (WOW),
November 2000.
* 2000 expenses were adjusted to 2001 dollars for comparative purposes using the Consumer Price Index (CPI).
83
These budgets also differ from the SourcePoint budget because they use different data sources for living
expenses. See the “Sources for Expenses of Basic Needs Budgets” in Appendix D.
102
KEEPING UP WITH INFLATION
Many adopted living wages use the Consumer Price Index (CPI) to annually adjust for the effects of
inflation. Rising prices can erode the recipient’s purchasing power. While it is important to preserve a
living wage’s purchasing power, tying a wage standard to an index is not as important in today’s low
inflation environment and presents two problems. First, an automatic wage increase based on the CPI
does not take into account the substitution effects on consumption patterns as relative prices of
substitute goods or services change over time. Because the CPI is a fixed basket of goods, it only
reflects price changes of goods or services in that basket. Second, society’s standard of living and
opinions about those standards also change over time. Indexed increases do not allow the living
standard incorporated in the budget to be revisited. The budget-based approach can avoid both of
these problems. Recalibrating the budget on a periodic basis would account for substitution effects
and changes in living standards.
THE CHARACTERISTICS OF LOW WAGE EARNERS
To provide information on the likely target populations of workforce development policies, this
section discusses the demographic characteristics of low wage earners both throughout the nation
and in California. The national and California profiles each examine the characteristics of workers who
earn less than two dollars above the minimum wage. However, because the 2001 national minimum
wage of $5.15 per hour is more than a dollar below the 2001 California minimum wage of $6.25 per
hour, caution is advised when making comparisons between the two different population samples.
Nationally, of the 13.5 million hourly workers who earned between $5.15 and $7.15 an hour in 2001,
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one-in-four (25.5 percent or 3.4 million) are parents with children under 18 years of age . Less than
one-in-four of these low-income parents (24.3 percent or 834,000) are single mothers, and one-inthirty (2.9 percent or 102,000) are single fathers. Most low-income parents are married (72.8 percent
or 2.5 million). Half of all employees who earn between $5.15 and $7.15 an hour are unmarried
individuals who have never been a parent. Most employees who earn low hourly wages are young.
More than half (50.7 percent or 6.8 million) of hourly employees in this pay bracket are between 16
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and 25 years of age . Less than one-in-four (23.5 percent) are between the ages of 26 and 40, and the
remainder (25.8 percent) are 41 years or older. Of those who earn between $5.15 and $7.15 per hour,
nearly one-in-three (28.5 percent or 3.8 million) are high school or college students. Over four-in-ten
of the 13.5 million hourly workers (42 percent) who earned $286 or less a week ($7.15 for 40 hours of
weekly work) lived in a household with an annual income equal to or greater than $50,000. One-infour (27.2 percent) lived in households that earned $25,000 or less annually.
The demographics of low wage earners are slightly different in California. Of the 2.6 million
hourly workers throughout California who earned between $6.25 and $8.25 per hour in 2001,
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almost half (49.8 percent or 1.3 million) are parents of children under 18 years of age . Less than
one-in-three of these low-income parents (31.3 percent or 412,000) are single mothers, and one-infive (24.1 percent or 247,000) are single fathers. About a quarter of low-income parents are married
84
Living Wage Research, Characteristics of Low Wage Earners, tabulated from the March 2001 Current
Population Survey.
85
Population Survey.
86
Population Survey.
103
(24.1 percent or 317,000). A little more than a quarter (28.3 percent or 742,000) of all employees
who earn between $6.25 and $8.25 per hour are unmarried individuals who have never been a
parent. Also, there are low-wage workers of all ages. More than two-in-five (43.8 percent) of the
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hourly employees in this pay bracket are between 16 and 25 years of age . Another third of lowwage hourly workers (29 percent) are between the ages of 26 and 40, and the remaining quarter
(27.1 percent) are over the age of 40. Only one-in-four (23.7 percent or 628,000) are high school or
college students. Nearly two-in-five of the 2.6 million hourly workers (38.6 percent) who earned
$8.25 or less (for 40 hours of weekly work) lived in a household with an annual income equal to or
greater than $47,000. Just over a quarter (28.5 percent) lived in households that earned $25,000 or
less annually.
LIVING WAGE EARNERS IN THE SAN DIEGO REGION
Estimating the proportion of the regional population that earns less than the budget-based living
wage comes down to a question of measurement. The number of workers that are paid less than
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the living wage can be measured by both occupations and jobs . In 2000, 32.4 percent of the jobs in
the region were in occupations that on average earned below the 2001 single-person budget-based
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living wage . Based on 1998 data, an estimated 26 percent of the jobs (and thus, workers) in the
90
region earned below the living wage .
Figure 5.5 shows the distribution of sub-living wage jobs in the regional economy by required levels
of education and training. According to the graph, the Short-term Training category had the
highest proportion of jobs in occupations that earned below the living wage in 1998 (87 percent). In
contrast, once a worker has attained at least a Bachelor’s Degree, it is very improbable he will be
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earning below the living wage . Also somewhat surprising, despite rising returns of income to
education, a sizeable proportion of jobs that require Associate’s Degrees and Vocational Training
are nevertheless in occupations that on average earn below the living wage (thirteen percent for
both categories). Two implications can be drawn from these results: First, many of the occupations
that earn below the living wage are not the focus of workforce development and training programs
in the region because they require no formal training (only Short-term Training); second, there are
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still some occupations that require training that still earn below the living wage (see Figure 5.6).
87
Population Survey.
88
Note: occupational wages do not take into account the increase in the California state minimum wage to
$6.75 per hour effective January 1, 2002.
89
California Employment Development Department Occupational Employment Survey (OES), SANDAG Regional
Growth Forecast.
90
Calculated based on the California Employment Development Department Occupational Employment Survey
(OES) using wage quartile data by occupation.
91
Individuals with professional degrees who earn less than a living wage are members of the clergy.
92
Figure 5.6 lists only those occupations that require more than Short-term Training – occupations for which
training providers used to provide programs.
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Figure 5.5
Percent of Jobs in Occupations that Earn Less than a Living Wage
by Required Level of Education and Training
Short-term Training
87%
Training Level
Moderate-term Training
21%
Long-term Training
11%
Work Experience
12%
Vocational Education
13%
Associate's Degree
13%
Bachelor's Degree
5%
Bachelor's or Higher + Experience
Master's Degree
Doctoral Degree
Professional Degree
4%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Percent of Jobs
Source: California Employment Development Department, compiled by SourcePoint.
105
Figure 5.6
Education and Training Requirements for Occupations
Where More than 75 Percent of Employees Earn Below the Living Wage
Occupation
Teachers, Preschool
Merchandise Displayers, Window
Trimmers
Residential Counselors
Psychiatric Technicians
Manicurists
Hairdressers, Hairstylists
Data Keyers – Composing
Housekeeping Supervisors
Food Batchmakers
Pressers – Delicate Fabrics
Cooks – Restaurant
Furniture Finishers
Wood Machinists
Machine Operators (Textile and Other)*
Bakers – Manufacturing
Education/Training Level
75th %
Wage (2001$)
Mean Annual
Wage (2001$)
Bachelor's Degree
$10.67
$19,847
Bachelor's Degree
Bachelor's Degree
Associate’s Degree
Work Experience
Long-term Training
Long-term Training
Long-term Training
Long-term Training
Long-term Training
$11.00
$11.30
$10.85
$7.07
$9.16
$11.50
$10.93
$8.43
$8.69
$9.78
$9.95
$10.47
$9.63
$9.64
$20,181
$20,105
$19,124
$14,241
$17,076
$19,674
$20,634
$16,753
$16,580
$17,971
$19,114
$19,178
$18,007
$18,133
* The wage for Machine Operators is an average of several different machinist occupations.
WORKFORCE DEVELOPMENT POLICIES TO HELP INDIVIDUALS EARN A LIVING WAGE
This section discusses three possible workforce development policies that can help low wage
workers earn a living wage. The three policies are: 1) using the “living wage” as a guideline for
occupational training programs; 2) training and the development of career ladders and career
lattices; and 3) promotion of the Earned Income Tax Credit (EITC).
1. A “Living Wage” Guideline for Training Programs
One possible way to ensure that individuals who receive training can go on to earn at least a living wage is
to use the budget-based living wage calculated in this chapter (or an alternative wage standard) as a wage
floor to identify occupations for which to provide training. In practice, a living wage guideline would ensure
that training resources are focused only on those occupations that would allow the recipients of training to
afford basic necessities. Reasoning suggests implementation of such a policy will have repercussions that
could affect the region’s labor market and the ability of low-wage workers to earn a “living”.
The obvious result of instituting a living wage floor in training programs will be that many poor
workers will learn skills that will help them earn a true “living” in the San Diego region. Higherwage occupations also generally have greater skill requirements, so training for higher-wage
occupations may result in a better skilled pool of workers. However, a workforce development
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living wage guideline that eliminates training for low-wage occupations could also lead to a
93
shortage of adequately skilled workers in these occupations .
With a decreased supply of quality workers in low-wage occupations, employers may be forced to
raise wages to attract skilled workers. Alternatively, employers may have incentives to raise wages
to comply with the region’s workforce development standards if they wish to have publicly funded
training available for the occupations they employ. Either way, some of the wage increases will
likely be absorbed by employers, which could cause employers to reduce the number of workers
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they hire . Additionally, a part of the incidence of the wage increases would likely fall on
consumers, meaning higher prices for products and services. Since service industries are so highly
dependent on labor inputs, labor shortages and wage increases could have drastic effects on the
prices of certain services.
The price increases due to increasing labor costs for services could potentially have large impacts on
both our region’s general population and our low-income residents. To begin with possible impacts
on the general population, some occupations, such as Certified Home Health Aides, receive low wages
yet provide essential services to our region. Although this occupation does not require substantial
training, employers noted a severe shortage of adequately skilled workers (Figure 3.6), and the
demand for the services this occupation provides is expected to surge in the future as a result of an
aging population. Consequently, the elimination of publicly funded training for these kinds of
occupations because they pay low wages could exacerbate the current shortage and would affect the
well-being of society as a whole.
Additionally, because low-income residents tend to spend a large share of their income on
consumption, they are hit especially hard by rising prices. Higher prices for services that low-wage
workers depend on may worsen the region’s cost of living problems and their ability to “make ends
meet”. For instance, many low-income families rely on childcare services, which help adult workers
maintain steady employment. Child care workers tend to earn low wages: approximately $8.38 per
hour in San Diego in 2001, well below the budget-based living wage calculated for a single worker
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of $11.58 per hour .
Should the Workforce Partnership or other workforce development institutions implement the
budget-based living wage as a guideline, training for this occupation (and others like it) would no
longer be supported by public funding. With fewer well-trained childcare workers, quality childcare
will become more costly. It is possible that diminished access to childcare could serve as a barrier to
entering the workforce for mothers with young children (see Chapter 2). So, while training for
living wage occupations will help low-wage workers meet their living expense needs, at the same
time, a policy that limits the number of quality service employees may also inflate their expenses if
it affects the prices of products and services they typically consume.
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Cessation of training could have additional implications for the “shortage occupations” in clusters identified
in Chapter 3 that earn below the living wage (Figure 3.6). Furthermore, there will still be a demand for jobs
that pay less than the living wage as they provide essential services for the regional economy. With living wage
workforce development guidelines, workers with little or no training will fill the jobs for which training
providers used to provide programs.
94
Small minimum wage increases have been shown to have little or no employment effects. However, because
a large wage increase would be necessary to bring minimum wage workers up to the living wage standard, it
likely would also have a more noticeable employment impact.
95
“The 2001 Child Care Portfolio”. California Child Care Resource and Referral Network, 2001. In 2001 in San
Diego, full-time licensed care for an infant on average cost $163 per week, or $706 per month.
107
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2. Training and the Development of Career Ladders and Lattices
A career ladder can be a path within a single occupation that leads to higher pay that an individual
can follow by acquiring knowledge and skills, and taking on more responsibilities. It can also be a
path through which, by acquiring additional skills and knowledge, an individual can move to
different occupations that pay higher wages within a single company or industry. Similarly, more
loosely defined “career lattices” are paths that allow individuals to apply their existing knowledge
and skills to completely different occupations that offer higher wages in completely different
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industries (skills are transferable) .
Well-defined career paths combined with access to the appropriate training opportunities to
acquire needed skills can lead to significant economic mobility. However, several impediments to
discovering and utilizing available career ladders have been identified. First, it is often the case that
many individuals lack sufficient job market information and are thus not aware of available career
paths. Second, there may be few or inadequate education and training programs to help individuals
acquire the skills they need to advance along specific career paths. Third, with the increasing trend
toward small firms in the San Diego region, there may be fewer opportunities to be promoted
within a company, compared to times past (i.e., small firms may only have entry-level and executive
positions, with few openings in-between).
As possible solutions, improving the dissemination of information on career paths, and providing
skill assessment and occupational matching services could help individuals make better career
decisions. Coordinating between employers and training providers could aid the development of
training programs that complement common career paths laid out by employers. Training programs
that assess what skills and knowledge an individual may already have can help fill any skill or
knowledge gaps that may be impeding their advancement within a given occupation or industry. To
account for the trend of smaller companies, new career ladder strategies may have to place more
focus on linking promotional opportunities between firms that employ similar occupations rather
than on providing career paths within a single firm. Also, it may be necessary to move low-wage
employees in industries with insufficient career ladder opportunities to industries with more
developed career ladders.
3. Promotion of the Earned Income Tax Credit (EITC)
The EITC is a monetary credit paid to workers (hence “earned”) whose incomes fall below an income
threshold, administered by the Internal Revenue Service (IRS). The EITC is a refundable credit where
claimants need have no minimum tax burden to be eligible. However, incomes do have to fall below
certain eligibility cut-offs and filers must be between the ages of 25 and 65. The income eligibility cut-offs
in 2001 were approximately $10,700 per year for single filers and $32,100 per year (Adjusted Gross Income,
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AGI) for filers with multiple children .
At the living wage rate of $11.58 per hour, or $24,100 per year, calculated in this report, a single adult
working full-time is not eligible for the EITC because annual earned income exceeds the income eligibility
96
For online personal skill assessment and occupational information, see http://online.onetcenter.org. Other
career information resources on the Internet are listed at the end of the Executive Summary.
97
See Appendix E for examples of career ladders in the Business Services and Defense and Transportation
Manufacturing clusters.
98
“Earned Income Credit: Are You Eligible?” IRS Publication 596, 2001.
108
threshold. Single wage earners earning between $1 and $10,709 are eligible for a credit ranging between
$1 and $364. The amount of the credit available to earners starts low ($2) for low-wage earners, then rises
to a maximum amount of $364 for individuals earning between $4,750 and $5,949, and then decreases for
higher wage earners until it reaches its minimum of $1 for those earning $10,709. At no income level
eligible for the EITC does the credit even begin to bring an individual’s earnings to a living wage. In 1998,
the average amount of EITC credit claimed in the region was $1,535, which equates to an additional 75
cents per hour for a single worker (at 2,080 hours per year).
As one of several policies intended to assist the working-poor, the EITC has several interesting
characteristics. First, since filers must submit their income information in their tax return to receive
the credit, the policy can discriminate among filers to ensure that only poor families are assisted.
Second, again because the EITC uses tax returns, EITCs can discriminate between families of
99
different sizes . Third, the credit functions as an incentive to work because it is a form of additional
non-taxable income for recipients. Fourth, the Employment Policies Institute observes that the EITC
avoids the social stigma normally associated with welfare programs, “There is no social stigma for
100
program participants because tax information is private” .
The Federal EITC is a boon for local efforts to reduce working poverty because it brings funds into
the region from a higher level of government. However, a common problem with the functioning
of the program is that not all those who are eligible for the credit claim it. This may occur, for
example, because low-income residents are unaware the program exists. A relatively simple way to
improve the effect of Federal EITC payments on working poverty in the San Diego region is to make
sure local residents take advantage of the program. To ensure the program does not go under-used,
it may be helpful to identify areas where an outreach campaign to inform eligible residents how to
101
claim the credit might have the greatest effect (see Map 15 in Chapter 6).
As James Gerber, an Advisory Committee member and Professor at San Diego State University
argues, the influx of EITC funds could have additional benefits for the region as claimants will have
102
more disposable income to spend . Increased spending creates additional sales tax revenue for
local governments and stimulates growth in other parts of the local economy. In theory, local
governments could justifiably allocate funds for publicity campaigns aimed at increasing EITC claim
rates because they will recoup this much from the sales tax revenues generated by the program. A
publicity campaign could be a net gain for the region because it would likely impose little or no cost
on local governments while benefiting low-income residents. Specifically, it may be worthwhile to
encourage employers and training providers who assist low-income residents to take on a more proactive role in promoting the credit, as well as focus publicity efforts on communities with large
103
proportions of Hispanic residents, for they also tend to under-claim the credit .
99
Several EITC supplements from other states actually have refund rates that depend on the number of
children in the family.
100
Employment Policies Institute. “The Case for a Targeted Living Wage Subsidy”, June 2001.
101
For outreach strategies and resources to publicize the EITC, see the Center on Budget and Policy Priorities’
“Earned Income Tax Credit Outreach Kit 2001” at http://www.cbpp.org/eic2001/.
102
Gerber, James B. “Could a Local Anti-Poverty Program Pay for Itself?” San Diego Dialogue’s Cross-Border
Economic Bulletin, April 2002. See the discussion of Map 15 in Chapter 6 concerning the funding of an EITC
promotional campaign.
103
Phillips, Katherin Ross. “Who Knows About the Earned Income Tax Credit?” The Urban Institute, Series B, No.
B-27, January 2001.
109
INCOME MOBILITY AND THE ROLE OF EDUCATION AND TRAINING
One of the most effective and well-documented ways for a worker to earn higher pay has been
through education and training (see Figure 4.1). Additional education and training makes a worker
more valuable because he becomes more productive. Nationwide data from the 2001 Current
Population Survey reveals that individuals earning $5.15 to $7.15 an hour have notably different
levels of education compared to individuals earning between $8.15 and $10.15 per hour. The main
educational difference between these two groups is the prevalence of high school dropouts.
Workers who earn between $5.15 and $7.15 an hour have a high school dropout rate (31 percent)
twice that of workers earning between $8.15 and $10.15 an hour.
A recent report from the California Employment Development Department’s Labor Market
104
Information Division (LMID) analyzes wage mobility in California . The report examines the wages
of a large sample of California workers of all ages and income levels drawn from administrative
105
data collected by the California Employment Development Department . The results were largely
consistent with research done using national samples. LMID found “fairly high” levels of absolute
earnings mobility, with the highest rate of mobility among the lowest earners.
Overall, the study’s findings for the matched longitudinal sample revealed that median real
earnings grew from $39,652 in 1988 to $49,054 in 2000, an increase of 24 percent. The change in
earnings varied: Approximately 30 percent of the sample showed a decline in real earnings, while
another third of the workers showed gains of more than 50 percent. These differences indicate a
fluid earnings ladder, with ample opportunity to move up or down.
The LMID study also examined mobility among earnings quintiles and categories. The workers were
classified into wage quintiles and categories based on their real annual earnings in 1988. Their wage
quintile and category positions were then examined in 1992, 1996, and 2000 using two different
measures. The first assessed the sample’s mobility compared to the entire California workforce in each
year (“absolute” mobility). The second method measured the shifts in the relative positions of earnings
among the sample of workers over time (“relative mobility”). As shown in Figure 5.7, absolute mobility
was “fairly high”: Of those workers initially in the bottom quintile of the earnings distribution in 1988,
approximately 38 percent remained in the bottom quintile in 1992. By 2000, one in five of these workers
remained in the bottom quintile. At the other end of the distribution, 80 percent of the workers in the
top quintile in 1988 were still earning wages in the top quintile twelve years later.
104
“Wage Mobility in California: An Analysis of Annual Earnings”. Labor Market Information Division,
California Employment Development Department, April 2002.
105
Data extracted from EDD’s Base Wage Database and ES-202 File. Data are reported quarterly by nearly all
California employers. Individual workers are identified by social security number, providing the ability to track
earnings over a long period of time.
110
Figure 5.7
Absolute Income Mobility by Quintile
State of California, 1988-2000
Same
Moved
Moved
Quintile
Up
Down
Bottom Quintile
21.3 %
78.7
N/A
Second Quintile
28.2
62.4
9.4
Middle Quintile
33.4
51.1
15.5
Fourth Quintile
39.0
41.7
19.3
Top Quintile
80.6
N/A
19.4
Source: Labor Market Information Division, California Employment Development Department, “Wage Mobility
in California: An Analysis of Annual Earnings”, April 2002.
The second measure of mobility – a worker’s relative mobility – compares each individual’s position
over time with others in the same longitudinal sample. This definition of mobility does not consider
“time in the workforce” as an indicator of economic mobility. By this measure there is less mobility.
Approximately half of the workers who had earnings in the bottom quintile in 1988 remained in the
bottom quintile in 2000 relative to their positions with other workers in the sample. These results
indicate that a worker in the bottom quintile of earnings has a 50-50 chance of moving up faster than
106
other workers in the same cohort .
The study analyzed mobility from the perspective of movement among earnings categories over
time. Of the workers earning less than $12,000 in 1988 (adjusted for inflation) approximately 15
percent remained in this category by 2000. At the other end of the earnings spectrum, more than 77
percent of the individuals in the top quintile retained their top position.
Finally, as shown in Figure 5.8, the study calculated the percentage change in annual earnings by
initial quintile. Those in the bottom quintile nearly doubled their real annual earnings over the 12
years. The top quintile showed a 9.2 percent gain, most occurring before 1992.
Figure 5.8
Earnings Growth by Quintile
State of California, 1988-2000
Median Earnings
in 1988 (2000$)
Median Earnings
in 2000 (2000$)
Bottom Quintile
$15,323
$29,178
Second Quintile
$28,119
$36,115
28.4
Middle Quintile
$39,720
$46,500
17.1
Fourth Quintile
$53,627
$59,802
11.5
Top Quintile
$76,343
$83,399
9.2
Percent Change
1998-2000
90.4
Source: Labor Market Information Division, California Employment Development Department, “Wage Mobility
in California: An Analysis of Annual Earnings”, April 2002.
106
If all workers in the bottom quintile experienced a doubling of earnings, this method would record no
improvement because there was no change relative to each other.
111
Other facts reported in the LMID study on wage mobility included:
•
Real earnings declined for the California workforce as a whole over the 12-year study period.
•
Lower-paid workers were more likely to be employed in retail trade, agriculture, and services.
•
Workers employed in low-wage sectors who changed industries experienced higher earnings
gains over the 12-year study period.
•
Between 55 and 81 percent of workers stayed in their initial (1988) industry of employment.
This percentage has increased over the 12-year study period, resulting in a growing “stickiness”
of low-wage careers in these industries.
112
CHAPTER 6
COMMUNITIES AT RISK: SUB-REGIONAL
LABOR MARKET IMBALANCES
Chapter 6
COMMUNITIES AT RISK:
SUB-REGIONAL LABOR MARKET IMBALANCES
The sub-regional analysis provides information on the current and forecast geographical distribution of
workers, jobs, and training providers in the San Diego region. The purpose of this analysis is to
determine where the largest spatial imbalances exist in the regional labor market. The information in
this chapter is presented in fifteen maps and five detailed profiles of sub-regional geographies. For
example, some of the maps in this chapter help identify which communities have the greatest mismatch
between employment and the labor force (where jobs are located relative to workers). Other maps
highlight geographical pockets of both “at-risk” populations and areas with relatively large amounts of
high-skill workers. The conclusions from this chapter will help regional policymakers and planners better
understand where adapting or augmenting training programs may help to correct any regional labor
market imbalances.
MAPS
Map 1: 2000 Labor Force
This map identifies current large pockets of labor supply by communities and jurisdictions in the region107.
The darkest shaded areas are communities with large amounts of workers. In general, when some areas have
more workers than others, it is because they have both large working-age populations and relatively high
labor force participation rates. Understanding which areas have large pockets of labor supply should assist
policymakers and planners in targeting labor force programs. This information may also aid employers in
locating their operations near large pools of labor.
Chula Vista has the largest labor force of all geographies analyzed with nearly 80,000 workers. The
map shows that many workers also live in the cities of Carlsbad, El Cajon, Escondido, and Oceanside.
These five largest labor force pockets contain approximately 21 percent of the region’s total labor
force. In contrast, communities such as East Elliot, Scripps Addition, and the “unincorporated” areas
in East County had relatively small populations and were thus home to few or no workers.
Map 2: Labor Force Growth, 2000 to 2010
Map 2 shows which communities and jurisdictions in the region are forecast to add the most new
workers from 2000 to 2010. Large labor force growth is due to either increases in the size of the
working-age population (ages 15 to 79; especially in those demographic categories with higher
than average labor force participation rates), or increases in the labor force participation rates of
large
demographic
107
Map 1 does not reflect levels of unemployment.
115
San Diego Region
LABOR FORCE, 2000
BY JURISDICTIONS
AND COMMUNITY
PLANNING AREAS
San Diego Region
LABOR FORCE GROWTH
2000 TO 2010
BY JURISDICTIONS
AND COMMUNITY
PLANNING AREAS
categories 108. In contrast, small or negative labor force growth is due to either declines in the
working-age population (including a demographic mix shifted toward categories with lower than
average participation rates), or large pockets of populations with declining labor force participation
rates. This information may help planners and trainers adjust labor force policies to better serve
future high-growth areas and identify where new programs may be needed.
Chula Vista is expected to have the largest labor force growth of any community in the region, adding
over 26,000 new workers. However, the map also shows that other communities that will add many new
workers are located in the north coastal section of the County. Mira Mesa, Carmel Valley, San Dieguito,
San Marcos, Carlsbad, Vista, Oceanside, Santee and Centre City (downtown San Diego) also expect
substantial increases in the labor force. In contrast, several communities expect labor force losses over the
next ten years (unshaded areas), including Carmel Mountain Ranch, Rancho Peñasquitos, Imperial Beach,
City Heights, and Coronado.
Map 3: 2000 Employment
Map 3 shows the current employment in the region by communities and jurisdictions.
Understanding the current location of large pockets of employment will help planners identify
areas to target employer-based workforce development and education programs. The largest
employment centers include the communities of Centre City, the University area, Mira Mesa, Kearny
Mesa, and Carlsbad. Roughly 28 percent of the region’s 1,208,300 total jobs were located in these
five communities109.
Map 4: Employment Growth, 2000 to 2010
Map 4 shows the forecast number of new jobs that will be created in each community and
jurisdiction in the region. Understanding where the most new jobs are expected to be located in
the future will help planners modify current employer-based workforce development programs and
create new programs focused on growing centers of employment. Furthermore, identifying areas
with high employment growth will shed light on areas that may require additional transit and
housing capacity. Planning transit and housing options in areas with large employment growth will
help reduce traffic and commute times.
The largest growth in employment in the region is expected in Chula Vista, where approximately
17,224 jobs will be added. Carlsbad, Otay Mesa, Vista, and Oceanside also expect substantial job
growth. The combined forecast employment growth of these five communities amounts to 69,622
jobs, accounting for 38 percent of the region’s total forecast employment growth.
108
Growth in the working-age population is usually the main cause of labor force growth. However, an area
could expect little population growth but still have large labor force growth if it has large populations in age,
race, and gender categories whose labor force participation rates are expected to increase (i.e., there are the
same amount of people, but a larger share are working). For example, if an area has a relatively large
population of White Females ages 55 to 59, whose labor force participation rate is forecast to increase by 4.3
percentage points, it will likely see future labor force growth (see Figure 3.13).
109
See Appendix A for a list of the region’s largest employers by Major Statistical Area (MSA).
118
San Diego Region
EMPLOYMENT, 2000
BY JURISDICTIONS
AND COMMUNITY
PLANNING AREAS
San Diego Region
EMPLOYMENT GROWTH
2000 TO 2010
BY JURISDICTIONS
AND COMMUNITY
PLANNING AREAS
Map 5: Balance Between Labor Force Growth and Employment Growth, 2000 to 2010
Map 5 shows the expected balance between labor force and employment growth in each
community and jurisdiction in the region from 2000 to 2010. The balance between labor force and
employment growth is calculated by subtracting the forecast growth in employment from the
growth of the labor force110. The possible future labor demand-supply mismatches identified here
are relevant to labor market planning because they could influence where employers locate –
employers want to locate in areas where they can find an ample supply of workers. Information
from this map may help planners identify areas that need either employer incentive programs to
stimulate employment growth or smart-growth housing initiatives to encourage workers to live
closer to employment centers.
Some areas such as Otay Mesa, Chula Vista, San Dieguito, and Carmel Valley are forecast to add
more workers than jobs (they will add at least 3,000 more workers than jobs). The largest imbalance
in this direction is forecast to occur in Otay Mesa, which is expected to add 10,134 more workers
than jobs. However, because there were 11,654 more jobs than workers in Otay Mesa in 2000, the
expected boom in labor force growth means the labor market of that community is actually forecast
to be in better balance by 2010. Other areas such as Vista, Poway, Kearny Mesa, and the University
area expect the opposite; they are forecast to add more jobs than workers (they will add at least
1,000 more jobs than workers). The largest imbalance is forecast to occur in Vista, which is expected
to add 7,501 more jobs than workers. The labor market in Vista was relatively balanced in 2000;
large job growth means there will likely be many more jobs than workers in the future. Still other
areas are forecast to have relatively balanced growth between the labor force and employment.
Areas that are expected to exemplify balanced growth include Spring Valley, Mission Valley, and
Carlsbad.
Map 6: Commute Times to Highest Paying Technology Clusters
Using recently collected survey data, Map 6 shows the commute times to the region’s densest center
of technology cluster employment, which is in zip code 92121. An estimated 47 percent of all of the
region’s highest-paying technology cluster workers are employed in this zip code (more than any
other zip code)111. The region’s four highest paying technology clusters in 2000 are Biotechnology
and Pharmaceuticals, Communications, Computer and Electronics Manufacturing and Software and
Computer Services 112. These four clusters accounted for 22 percent of all cluster employment and
eight percent of the region’s total employment in 2000. The contour lines on the map delineate the
average morning commutes times to a point in the center of zip code 92121 in the Torrey Pines,
University,
110
A balance between the size of the labor force and the number of jobs does not assure that residents will
both work and live in the same community, but it does show where this is most likely to occur. See Maps 2 and
4 for the magnitudes of growth.
111
“Where the Tech Workforce Lives”. San Diego Regional Economic Development Corporation (SREDC), 2001.
Note: SREDC states that the best attempt was made to ensure the survey included a representative sample of
firms in the region. However, the survey results have not been verified for accuracy and were based on
employer responses, not random sampling. The survey covers roughly 38 percent of the workers employed in
the four technology clusters.
112
Average annual wage and employment data for the region’s traded clusters is presented in Chapter 1.
121
San Diego Region
BALANCE BETWEEN
LABOR FORCE GROWTH
AND EMPLOYMENT
GROWTH, 2000 TO 2010
BY JURISDICTIONS
AND COMMUNITY
PLANNING AREAS
Map 6
San Diego Region
COMMUTE TIMES
TO HIGHEST PAYING
TECHNOLOGY CLUSTERS
and Sorrento Hills communities. The map helps identify areas with the most and least geographic
access to high paying cluster employment.
Approximately 55 percent of the high-technology workers employed in zip code 92121 live within a
30-minute commute, with a large proportion living in the surrounding zip codes. Four percent of
the high-technology workers in zip code 92121 commute to work from outside San Diego County 113.
Maps 7 and 8: 2000 Training Providers
Maps 7 and 8 geographically identify the communities in which the most training providers are
located 114. The maps show that training providers are concentrated in certain areas in the region
and that training provider coverage is also wide spread. The training provider information on this
map can be used to compare whether the locations of training providers coincide with large
employment and labor force areas. Knowing the location of our region’s training providers can help
determine if there are any communities with little geographical access to training.
Map 7 shows that there are many training providers located within the boundaries of the City of
San Diego, as well as in North County along Highway 78. Map 8 shows that communities with many
different trainers include Kearney Mesa, Mira Mesa, Mission Valley, El Cajon, and La Mesa. Other
locations with large training capacities (though few training providers) include areas with large
institutions of higher education 115. Some of these areas are the University area where UC San Diego
and UC San Diego Extension are located; the College area which is home to San Diego State
University; San Marcos with CSU San Marcos; Chula Vista with National University; Centre City with
San Diego City College; and Linda Vista with the University of San Diego116. The San Dieguito/
Carmel Valley and East County areas have relatively few training providers.
Map 9: Proportion of Workers with Low Educational Attainment Levels, 1990
Map 9 uses 1990 Census data to show which communities in the region have high proportions of
residents over 25 that attained only a high school-level education or less. This information is useful
to identify the location of low-skill population “pockets” that are likely in need of workforce
development. The location of low-skill pockets can be compared to training provider information to
determine whether these areas have access to training centers nearby.
113
“Where the Tech Workforce Lives”. San Diego Regional Economic Development Corporation (SREDC), 2001.
San Diego Workforce Partnership. San Diego County Training and Education Provider (STEP) database
(www.sandiegoatwork.com). Of an estimated 277, 219 total training providers in the region were plotted.
115
A challenge in assessing the region’s training resources is measuring the degree capacity of trainers in the
region. Future research focused on the region’s training capacity could provide a better picture of the
(geographical) gaps that may exist in the region’s training infrastructure (for example, annual output of
students by degree level and discipline).
116
Area names such as the “College Area” are official community designations used for planning purposes by
the City and County of San Diego. See Figure 4.8 in Chapter 4 to locate other areas with higher education
institutions by zip code.
114
124
Map 7
San Diego Region
TRAINING PROVIDERS
2000
Map 8
San Diego Region
TRAINING
PROVIDERS, 2000
BY JURISDICTIONS
AND COMMUNITY
PLANNING AREAS
Map 9
San Diego Region
PROPORTION OF WORKERS
WITH LOW EDUCATIONAL
ATTAINMENT, 1990
BY JURISDICTIONS
AND COMMUNITY
PLANNING AREAS
More than two-thirds of the residents over 25 in the communities of Otay Mesa, Barrio Logan, San
Ysidro, Otay, Southeastern San Diego, and National City had attained only a high school degree or
less (other low educational attainment pockets exist in the communities surrounding Santee and El
Cajon, Escondido and San Marcos, and between Centre City and Lemon Grove). Data on training
providers shows there are 11 training providers located in these South County communities. With
some access to training yet persisting low levels of educational attainment, a challenge for
workforce development could be getting residents of these communities to enroll in programs to
pursue further education and training. It could also be the case that the demand for training
services may still exceed the training capacity in these communities. In addition to coursework that
emphasizes the acquisition of specific skills demanded by the region’s employers, training directed
at populations in these communities will also need to focus on basic, or “soft” skills and education
in areas such as good work habits, literacy, and G.E.D. preparation 117. Further research is
recommended to get a better understanding of the causes of persistent educational attainment
gaps and what can be done to remedy them.
Map 10: Proportion of Highly Educated Workers, 1990
Map 10 shows the proportion of residents with high educational attainment levels from 1990
Census data. The proportion indicates the percent of residents that attained a bachelor’s degree or
higher. The map helps to geographically identify “high skill” pockets – areas that could possibly
supply high-skill workers that are currently in high demand by employers, especially employers in
the region’s technology clusters. As far as training is concerned, highly educated workers may have
different training needs than less educated workers. For example, highly educated workers may
require specific skill upgrade training (they may also require “soft“ skill training for improvements
in areas such as interpersonal skills, but do not require basic skill training in areas such as literacy).
Some communities with the largest proportion of highly educated residents include Carmel Valley
and Del Mar, both with more than sixty percent of the over 25 population holding at least a
bachelor’s degree 118. According to the map, the largest pocket of highly educated workers in the
region runs from San Dieguito in the north to La Jolla in the south. A second pocket can be found
adjacent to Poway, which includes the communities of Carmel Mountain Ranch, Sabre Springs,
Scripps Miramar Ranch, and Rancho Encantada.
Map 11: Proportion of Jobs with Mean Wage Less Than the Regional Living Wage, 2000
Map 11 identifies communities and jurisdictions where a large proportion of employment is in
occupational categories that, on average, earn below the 2001 San Diego living wage of $11.58 per
hour. The nine broad occupational categories identified as on average paying below the regional
living wage include Food and Beverage Services; Personal Services; Cleaning and Miscellaneous
117
Other “soft” skills include work ethic, courtesy, teamwork, self-discipline, conformity to prevailing norms,
and language proficiency. For further information on “soft” skills, see Appendix F and Houghton, Ted and
Tony Proscio. “Hard Work on Soft Skills: Creating a Culture of Work in Workforce Development”, Public/Private
Ventures Group, 2001. www.ppv.org.
118
While it is plausible to infer that communities with large highly educated populations have many educated
workers, it is not guaranteed, as not all highly educated residents participate in the labor force (e.g., some may
not be working age).
128
Map 10
San Diego Region
PROPORTION OF
HIGHLY EDUCATED
WORKERS, 1990
BY JURISDICTIONS
AND COMMUNITY
PLANNING AREAS
Map 11
San Diego Region
PROPORTION OF JOBS
WITH MEAN WAGE LESS
THAN THE REGIONAL
LIVING WAGE, 2000
BY JURISDICTIONS
AND COMMUNITY
PLANNING AREAS
Services119; Agriculture, Forestry & Fishing; Laborers; Assemblers; Health Services; Machine
Operators; and Miscellaneous Sales 120. As noted in Chapter 6, 32.4 percent of jobs in the region
were in these eight occupations 121. Identification of where these jobs are located highlights areas in
need of workforce development programs, training resources, and career ladders.
Communities with the largest proportion of jobs that earn less than the living wage include Mission
Beach (57 percent), Mission Bay (56.2 percent), Alpine (46.9 percent), Ocean Beach (46.9 percent),
Pacific Beach (45.9 percent) and Del Mar (43.3 percent). These communities are some of the region’s
key tourist areas that provide entertainment and visitor services. Communities with some of the
lowest proportions of employment in sub-living wage occupational categories include the College
Area (20.3 percent), Centre City (23.7 percent), and the University area (23.9 percent).
Map 12: 2000 Labor Force Participation Rates
Map 12 shows estimated labor force participation rates by communities and jurisdictions in 2000.
The labor force participation rate indicates the proportion of the working-age population that is
either employed or currently looking for work. The labor force participation rate of the region as a
whole in 2000 was 68.5 percent. The sub-regional participation rates are based on regional
participation rates and the demographics of each community. Participation rates vary from one
community to the next because, regionally, some demographic categories have higher participation
rates than others and each community has a unique demographic composition.
Communities with high labor force participation rates suggest a strong labor force and work
environment. Alternatively, low participation rates in a given geography could indicate the
presence of workforce barriers that are inhibiting a sizeable proportion of the working-age
population from working. As discussed in Chapter 3, several examples of workforce barriers that
may be affecting the working-age population of the region are teen pregnancies, unavailability of
affordable childcare, and dropping out of high school. The identification of communities that are
“at-risk” according to labor force participation rates could help policymakers geographically focus
programs intended to help remove workforce barriers.
Communities with exceptionally high labor force participation rates include Otay Mesa (79.2
percent), Otay, Ocean Beach, Harbor, and Mission Valley. San Ysidro (62.2 percent) and
Southeastern San Diego are examples of communities with some of the lowest labor force
participation rates in the region. These and other similar communities could be more greatly
impacted by barriers.
119
“Miscellaneous Services” includes maids, janitors, and building services employees. This category was
included because, while its mean wage was greater than the living wage, its median wage fell below the living
wage.
120
“Miscellaneous Sales” includes sales representatives, sales engineers, rental and counter clerks, stock clerks,
cashiers, telemarketers, and models.
121
This does not mean that 32.4 percent of the region’s jobs pay less than the living wage. However, using
percentile wage data, it can be estimated that 26.3 percent of the region’s jobs pay less than the regional
living wage.
131
Map 12
San Diego Region
LABOR FORCE
PARTICIPATION
RATES, 2000
BY JURISDICTIONS
AND COMMUNITY
Map 13: 1998 Average Adjusted Gross Income
Map 13 shows the average annual Adjusted Gross Income (AGI) for each zip code in the region in
1998, the most recent year for which data is available122. The average annual AGI is another
indicator that helps identify communities in the region that are “at-risk” and may possibly require
additional workforce development resources. The regional average annual AGI was $45,257123. The
average annual AGIs in the region ranged from a high of $372,108 in zip code 92067 (Rancho Santa
Fe), to a low of $13,100 in zip code 92055 (Pendleton-De Luz).
Map 14: Proportion of Tax Filers Receiving the Earned Income Tax Credit, 1998
Map 14 shows the proportion of tax filers receiving the Federal Earned Income Tax Credit (EITC), or
the EITC claim rate in 1998 by zip code. As noted in Chapter 6, the income eligibility cut-offs in 2000
were approximately $10,300 per year for single filers and $31,100 per year for joint filers 124.
The map shows where there are relatively many low-income residents receiving federal income
supplements, possibly indicating “at-risk” populations. However, it is encouraging that areas with
high claim rates also indicate areas with low-income residents who are employed and are aware of
assistance programs available to them. In comparison with Map 13, the EITC claim rates are roughly
inversely correlated with average income levels: Zip codes with low average incomes tend to claim
the EITC at a high rate.
The average EITC claim rate for the region was 14.2 percent. Seventy-eight zip codes of the 120 for
which there is data had lower claim rates than the regional average. The claim rates of zip codes in
the region range from 2.7 percent (92131) to 50.5 percent (91980). According to the map, there is a
band of communities along the U.S.-Mexico border where a high proportion of tax filers claimed
the credit. There is also a pocket of high EITC claim rates in the communities between Balboa Park,
National City and Lemon Grove.
Map 15: Utilization of the Federal Earned Income Tax Program
Map 15 illustrates trends of utilization of the Earned Income Tax Credit (EITC) program in the San
Diego region based on data from 1990 and 1998. A common problem with the functioning of the
program is that not all those who are eligible for the credit claim it. A relatively simple way to
improve the effect of Federal EITC payments on working poverty in the San Diego region is to
make sure local residents take advantage of the program. To ensure the program does not go
under-used, it may be helpful to identify areas where an outreach campaign to inform eligible
residents how to claim the credit might have the most effect125.
122
Adjusted Gross Income is defined by the Internal Revenue Service (IRS) as Gross Income minus adjustments
to income. See the Glossary for more information.
123
All AGI amounts are in 1998 dollars.
124
“Earned Income Credit: Are You Eligible?” IRS Publication 596, 2000.
125
For outreach strategies and resources to publicize the EITC, see the Center on Budget and Policy Priorities’
“Earned Income Tax Credit Outreach Kit 2001” at http://www.cbpp.org/eic2001/.
133
San Diego Region
AVERAGE ADJUSTED
GROSS INCOME, 1998
BY ZIP CODE
San Diego Region
PROPORTION OF TAX
FILERS RECEIVING
THE EARNED INCOME
TAX CREDIT, 1998
BY ZIP CODE
Map 15
San Diego Region
UTILIZATION OF
THE
FEDERAL EARNED
INCOME TAX
PROGRAM, 1998
Map 15 identifies areas of the region with pockets of residents that may be eligible for the Federal
EITC program but are currently not claiming the credit 126. It shows the percent of tax filers claiming
the EITC in 1998 compared to the percent of households whose income falls below the income
eligibility cut-off from the 1990 Census 127 for each zip code. Since geographies with a large number
of low-income residents would expect a large proportion of claimants, geographies with both low
incomes and low claim rates suggest there is a large share of eligible filers who are not taking
advantage of the program. These types of communities are where an EITC publicity campaign may
be helpful in increasing participation in the program.
Fourteen zip codes met the criteria of having both below average EITC claim rates and over onethird of households earning incomes that fell below the EITC income eligibility cut-off of
approximately $31,000 (in 1998 dollars). These zip codes identified as most likely to be
underutilizing the EITC program relative to other areas include 91915, 91941, 91942, 92036, 92055,
92060, 92066, 92069, 92101, 92103, 92107, 92109, 92110, and 92672. In these zip codes, there were
161,675 filers, yet only 14,675 claimants (an average claim rate of 9.1 percent)128. Assuming
underutilization of the EITC program in these fourteen zip codes, if the claim rates in these areas
could be raised to the 1998 regional average claim rate of 14.2 percent, an additional 8,177 filers
would claim the credit. If these additional filers on average received the regional average credit of
$1,535, it would result in an extra $12.6 million going to some of the region’s poorer workers.
As James Gerber, an Advisory Committee member and Professor at San Diego State University
argues, this influx of funds could have additional benefits for the region as the claimants will have
more disposable income to spend129. Increased spending creates additional sales tax revenue for
local governments and stimulates growth in other parts of the local economy. If the $12.6 million
were spent at the average sales tax rate of one percent assumed by Gerber 130, local governments
would receive $63,000 dollars in additional tax revenues. So, in theory, this amount of funding
could justifiably be spent by local governments on publicity campaigns aimed at increasing EITC
claim rates because they will recoup this much from the tax revenues generated by the program. A
publicity campaign could be a net gain for the region because it would likely impose little or no cost
on local governments while benefiting low-income residents. It may be worthwhile to direct these
publicity campaigns at employers and trainers of low-income residents, as well as communities with
large proportions of Hispanic residents, for they also tend to under-claim the credit 131.
126
“Rewarding Work: The Impact of the Earned Income Tax Credit in Greater San Diego”. The Brookings
Institution, EITC Series, June 2001.
127
1990 Census data on household income is used to estimate the share of families that are eligible for the
EITC.
128
Note, some of these areas are military bases and may have lower claim rates and fewer eligible nonclaimants than the general population. This may be so because many young recruits may be ineligible: They
may not meet the program’s minimum age requirement, and, because, many in the military are single, they
would be subject to a lower income-eligibility cut-off. Furthermore, the sample of tax filers in the military may
not be representative because many file taxes in their home states.
129
Gerber, James B. “Could a Local Anti-Poverty Program Pay for Itself?” San Diego Dialogue’s Cross-Border
Economic Bulletin, April 2002.
130
We assume 50 percent of personal income is spent on taxable items.
131
Phillips, Katherin Ross. “Who Knows About the Earned Income Tax Credit?” The Urban Institute, Series B,
No. B-27, January 2001.
137
DETAILED COMMUNITY PROFILES
For a more comprehensive picture of sub-regional differences in the San Diego region, this section
presents profiles of five representative communities that describe various labor force and
employment characteristics. The cities and communities in this section were chosen to be profiled
because they exemplify important labor force and employment issues facing the region. To ensure
that the profile communities are indeed significant pieces of the regional labor market, they were
selected on the criteria of having relatively large proportions of the region’s labor force. The
profiles should prove helpful for directing marketing efforts for existing training programs or
locating sites for new training programs.
Profile 1: The City of Chula Vista – A Large Labor Force
In 2000, the City of Chula Vista had a larger proportion of the region’s labor force than any other
jurisdiction or community. Approximately 80,000 workers lived in Chula Vista in 2000, constituting
roughly 5.6 percent of the total regional labor force. Roughly half of the population was Hispanic,
and another third White. Chula Vista had a slightly lower than average labor force participation
rate of 65.7 percent, but a sizeable working-age population. The labor force in Chula Vista is
expected to grow rapidly over the next ten years. By 2010, there will be approximately 26,000 more
workers living in Chula Vista, representing an increase of 33.4 percent. The rapid expected growth
rate means Chula Vista’s share of the total regional labor force is expected to increase to 6.6
percent over the forecast time period.
According to 1990 Census data, Chula Vista could be considered an “at-risk” community on the basis
of educational attainment levels. Approximately half of the over 25 population reported only
completing high school or less. In a ranking of communities in the region by the percent of the
population over 25 that only attained a high school degree or less, Chula Vista falls in the bottom
fifth of all communities. Alternatively, only 17.6 percent of the over 25 population had a B.A. or
higher. Chula Vista also had a lower than average Adjusted Gross Income in 1998 and a higher than
average EITC claim rate.
In terms of employment and occupations, a significant number of the region’s jobs are in Chula
Vista. 12.6 percent of the jobs in Chula Vista in 2000 were classified as Miscellaneous Sales
occupations and another 8.6 percent as Food and Beverage Services. In both the present and future,
the size of the labor force is expected to far outnumber the available jobs. In 2000, there were
approximately 26,000 more workers in Chula Vista than there were jobs, and the number is
expected to grow to 35,000 by 2010. This means that many Chula Vistans will commute outside the
city boundaries to arrive at work each day. According to high-technology cluster firm survey data,
approximately five percent of the region’s high-tech workers lived in Chula Vista in 2001.
A discussion of the labor market trends of Chula Vista would be incomplete without mentioning the
forecast growth in the neighboring community of Otay Mesa (part of the City of San Diego). With
the increased cross-border commerce and traffic resulting from the North American Free Trade
Agreement (NAFTA), the Otay Mesa Port of Entry is now the largest commercial border crossing
along the California-Mexico border. With new freeways and border crossings being planned (State
Routes 905 and 11), Otay Mesa is expected to continue to grow over the next decade. An estimated
138
The City of Chula Vista
2000 Census Demographics
Total Population in 2000
173,556
Hispanic
49.6%
White
34.3%
Black
4.7%
Asian
11.5%
Average
Median Age Households Household Size
33
57,705
2.99
Highest Level of Educational Attainment (1990 Census)
Total Population 25 and Over
84,817
Less than 9th
Grade
9.6%
9th to 12th
Grade
14.8%
High School
Graduate, No
College Some College
25.5%
24.3%
AA
8.2%
BA
11.8%
Labor Force
Labor Force in 2000
Percent Share
of Regional
Labor Force in Labor Force in
2000
2010
79,137
5.6%
105,576
Percent Share of
Regional Labor
Force in 2010
6.6%
Numerical
Change in
Labor Force,
2000-2010
26,439
2000 Labor
Percent Change
Force
in Labor Force, Participation
2000-2010
Rate
33.4%
65.7%
Employment
Employment in 2000
Employment in
2010
52,273
69,497
Numerical
Change in
Employment
17,224
2000 Labor
Force Employment
Gap
26,864
Forecast
Difference
between Labor
Force and
Employment
Growth
9,215
Average
Adjusted
Gross Income
EITC Claim Rate
(AGI)
18.7%
$33,696
Average Claim
Amount
$1,570
Percent of Jobs
Paying Sub-Living
Wages in 2000
35.0%
Occupational Employment in 5 Largest Occupations in 2000
Percent of
Total
Employment
Occupation
Miscellaneous Sales
12.3%
8.2%
8.0%
Office Workers
7.2%
Healthcare Practitioners
5.5%
Sum
41.2%
High-Tech Cluster Employment
Percent of
Percent of
County's High- County's HighTech Cluster
Tech Cluster Percent of County's
Workers
Companies High-Tech Cluster
Residing in
Located in Workers Employed
Percent of Regional Population in
Chula Vista
Chula Vista
in Chula Vista
2000
5.7%
5.0%
0.4%
7.1%
Training Providers
Number of Training Providers
Percent of
County's
Total Training
Providers
Located in
Chula Vista
6
2.9%
Earned Income Tax Credit (Tax Year 1998)
Total Amount
of Credit
Total Number
Claimed
of EITC (Thousands of
Total Number of Tax Returns
Returns
Dollars)
66,876
12,493
$19,618,550
Graduate
Degree
5.8%
11,000 homes are already under development 132. This magnitude of growth has large repercussions
for the labor market. A community with only 3,100 workers in 2000, Otay Mesa is forecast to have
approximately 27,000 workers by 2010. This increase of over 700 percent represents the fastest
forecast labor force growth rate in the region. Otay Mesa also expects employment to nearly
double: It will add another 14,000 jobs by 2010.
Because of the size of the Chula Vista labor force and the massive growth expected in Otay Mesa,
the question arises of whether the training providers in those communities are able to meet the
current and future training needs. The list of training providers compiled by the Workforce
Partnership indicates that there are six training providers located in Chula Vista, including National
University and Southwestern Community College. Looking at the relatively low educational
attainment levels and large forecast labor force growth, Chula Vista, Otay Mesa, and other similar
areas will likely require more training and workforce development resources in the years to come.
Fortunately, there has been some proactive planning: The Otay Mesa Higher Education Center is
due to be completed in 2004 and enrollments are expected to grow to 10,000 students by 2010 133.
While this example should go a long way toward meeting the training needs of the border
communities, it is important that workforce development policymakers ensure that the resources
dedicated to these areas are indeed sufficient.
Profile 2: The City of Carlsbad – An Employment Center
The City of Carlsbad was selected for study because it is currently a sizeable center of employment
in the region and is forecast to remain so. In 2000, 53,543 jobs were located in Carlsbad,
representing roughly 4.4 percent of total regional employment. There were approximately 11,000
more jobs in Carlsbad than there were workers. While the communities of Centre City, University,
Mira Mesa, and Kearny Mesa had more jobs than Carlsbad in 2000, Carlsbad is expected to be
second only to Chula Vista with the greatest growth in employment in the region. Carlsbad is
forecast to add 14,976 new jobs from 2000 to 2010, an employment growth rate of approximately
28 percent. The increase in the number of jobs is expected to outnumber the increase in the labor
force, indicating that the trend of workers commuting to their jobs in Carlsbad from elsewhere will
continue 134.
In comparison with Chula Vista, the population of Carlsbad is older, with a median age of 39, and
more White. The 1990 educational attainment levels of the over 25 Carlsbad population are
relatively evenly distributed, with roughly one-third of the population completing high school or
less, and another third holding at least a B.A. The Adjusted Gross Income in Carlsbad in 1998 was
higher than the regional average income, at $62,770. Carlsbad residents also claimed the EITC at the
lower than average rate of seven percent.
132
“About Otay Mesa”. Otay Mesa Chamber of Commerce. www.otaymesa.org.
The Otay Mesa Higher Education Center, also known as Project Synergy, is currently being developed by the
Southwestern Community College District (SCCD), in partnership with the Sweetwater Union High School
District (SUHSD), San Diego State University (SDSU), and the Centro de Enseñanza Técnica y Superior (CETYS).
Students will be able to obtain degrees in computer science, technology, teacher education, child
development, business administration, international business, criminal justice, social service, biotechnology,
Latin American studies, and manufacturing engineering. “Major Projects Under Development in Otay Mesa”.
Otay Mesa Chamber of Commerce. www.otaymesa.org.
134
Census data suggests that many residents of Carlsbad work outside of the city limits.
133
140
The City of Carlsbad
78,247
Hispanic
11.7%
White
83.1%
Black
0.9%
Average
Households Household Size
31,521
2.46
Asian
4.3%
Median Age
38.9
High School
Graduate, No
18.4%
26.0%
AA
9.5%
BA
23.7%
Numerical
Change in
Labor Force,
2000-2010
14,794
Percent Change
in Labor Force,
2000-2010
34.8%
2000 Labor
Force
Participation
Rate
68.9%
2000 Labor
Force Employment
Gap
-10,998
Forecast
Difference
between Labor
Force and
Employment
Growth
-182
Average
Adjusted
Gross Income
EITC Claim Rate
(AGI)
7.0%
$62,770
Average Claim
Amount
$1,324
Less than 9th
Grade
43,800
4.1%
9th to 12th
Grade
6.3%
Labor Force
Labor Force in 2000
Percent Share
of Regional
Labor Force in
2000
42,546
3.0%
Labor Force in
2010
57,340
Percent Share of
Regional Labor
Force in 2010
3.6%
Employment
Employment in 2000
53,543
Employment
in 2010
68,519
Numerical
Change in
Employment
14,976
Percent of Jobs
Paying Sub-Living
Wages in 2000
36.5%
Percent of
Total
Employment
Occupation
Miscellaneous Sales
11.6%
Office Workers
7.3%
6.1%
Assemblers
4.9%
Staff Managers
4.6%
Sum
34.4%
Percent of Regional
Population in 2000
Percent of
Percent of
County's High- County's HighTech Cluster
Tech Cluster Percent of County's
Workers
Companies High-Tech Cluster
Residing in
Located in Workers Employed
Carlsbad
Carlsbad
in Carlsbad
2.8%
3.0%
8.4%
3.1%
Training Providers
Percent of
County's
Total Training
Providers
Located in
Carlsbad
8
3.8%
Total Number
of EITC
Returns
34,875
2,447
Total Amount
of Credit
Claimed
(Thousands of
Dollars)
$3,240,000
Graduate
Degree
12.0%
In Carlsbad, the five largest occupations by employment are Miscellaneous Sales, Office Workers,
Food and Beverage Services, Assemblers, and Staff Mangers. Carlsbad was home to an estimated
eight-and-a-half percent of all high-tech cluster companies and employed roughly three percent of
the region’s high-tech workers. With 36.5 percent of employment in Carlsbad in occupations that,
on average, earn below the living wage, Carlsbad differs little from the regional average in
providing adequate wages (32.4 percent of the region’s jobs are in occupations that, on average,
pay less than the living wage).
Eight training providers are located in Carlsbad, representing roughly four percent of all San Diego
County training providers. The large expected growth in employment in Carlsbad suggests it may be
a good focal point for future employer-based training programs. However, the educational
attainment and income data suggest that the residents of Carlsbad are currently less “at-risk” of
staying at the bottom of the career ladder compared to residents of other communities.
Profile 3: The Community of San Ysidro – A Community “At-Risk”
According to some indicators, the community of San Ysidro, which lies on the U.S.-Mexico border,
could be classified as “at-risk” of falling behind the rest of the region in both educational
attainment and standard of living. 1990 Census data on educational attainment levels shows that
over 75 percent of the over 25 population of San Ysidro had only attained a high school education
or less – a much greater proportion than the regional average of 41 percent. Only 7.3 percent of the
population had attained a B.A. or graduate degree. The estimated annual average Adjusted Gross
Income (AGI) for San Ysidro was $20,933 135, over two times lower than the regional average AGI.
Furthermore, San Ysidro had a large average EITC claim amount of $1,782 and a much higher than
average EITC claim rate of 35.7 percent. Although the EITC claim rate is relatively high, it is still
possible that such a poor (and Hispanic and Spanish-speaking) community is underutilizing the
program.
The population of San Ysidro is overwhelmingly Hispanic, 89 percent, according to the 2000 Census.
With a median age of 26, the San Ysidro population is much younger than the population of other
areas. Also of note, with an average household size of 3.89 persons, the households in San Ysidro
tend to be much larger than the average household in the region.
In 2000, there were 10,635 workers in the labor force in San Ysidro. Relatively little labor force
growth is expected in the next ten years. San Ysidro had a lower than average labor force
participation rate in 2000 with 62.2 percent of the working-age population in the labor force (the
regional average is 68.5 percent). Viewing the low labor force participation rate as another “at-risk”
indicator, San Ysidro could be representative of communities where residents face barriers to
entering the workforce.
There were 7,344 jobs in San Ysidro in 2000. 1,504 jobs are expected to be added by 2010. Currently,
the largest occupations are Miscellaneous Sales and Food and Beverage Services. High-technology
cluster survey data show there are no high-tech cluster firms in San Ysidro and very few high-tech
workers reside there.
135
The income estimate for San Ysidro is based on data for zip code 92173.
142
The Community of San Ysidro
26,953
Hispanic
89.0%
White
5.3%
Black
2.2%
Asian
3.5%
Median Age
26
9th to 12th
Grade
21.2%
High School
Graduate, No
College
17.8%
Some
College
12.1%
AA
5.4%
Average
Households Household Size
6,922
3.89
12,120
Less than 9th
Grade
36.2%
BA
4.7%
Labor Force
Labor Force in 2000
Percent Share
of Regional
Labor Force in
2000
10,635
0.8%
Labor Force in
2010
10,262
Numerical
2000 Labor
Percent Share of
Change in Percent Change
Force
Regional Labor Labor Force, in Labor Force, Participation
Force in 2010
2000-2010
2000-2010
Rate
0.6%
-373
-3.5%
62.2%
Employment
Employment in 2000
7,344
Employment
in 2010
8,848
Numerical
Change in
Employment
1,504
2000 Labor
Percent of Jobs
Force Paying Sub-Living Employment
Wages in 2000
Gap
25.7%
3,292
Forecast
Difference
between Labor
Force and
Employment
Growth
-1,877
Percent of
Total
Employment
Occupation
Miscellaneous Sales
12.3%
8.2%
8.0%
Office Workers
7.2%
5.5%
Sum
41.2%
Percent of
Percent of
County's High- County's HighPercent of
Tech Cluster
Tech Cluster County's High-Tech
Workers
Companies
Cluster Workers
Residing in Located in San
Employed in San
2000
San Ysidro
Ysidro
Ysidro
1.2%
0.3%
0
0
Training Providers
Percent of
County's
Total Training
Providers
Located in
San Ysidro
1
0.5%
Total Number
of EITC
Returns
15,757
5,620
Total Amount
of Credit
Claimed
$10,015,000
Average
Adjusted
Gross Income Average Claim
EITC Claim Rate
(AGI)
Amount
35.7%
$20,933
$1,782
Graduate
Degree
2.6%
According to training provider data, there is only one training provider currently located in the
community of San Ysidro. The closest center of training for San Ysidro residents is Chula Vista, where
six more training providers are located. The low levels of educational attainment, low average
income, low labor force participation rate, and small number of training providers suggest that San
Ysidro and other similar communities are prime targets for an increased allocation of the region’s
training resources and funds over the next ten years.
Profile 4: The Community of Carmel Valley – A Pocket of Highly Educated Workers
Located in the northern part of the City of San Diego, Carmel Valley exemplifies a community with
a high density of highly educated residents of working age. According to 1990 Census data, 65.1
percent of the over 25 population in Carmel Valley held at least a B.A. Over a quarter of the
population held a graduate degree of some kind. These numbers represent some of the highest
attainments in the region (for a community of its size) and have likely only increased through 2000,
as the region’s overall educational attainment levels have risen over the past decade. The
educational attainment levels of Carmel Valley also correlate with the mean household income of
the community: In 1998 the average Adjusted Gross Income was $102,603, far higher than the
regional AGI of $47,056. Furthermore, in 1998, Carmel Valley had an extremely low EITC claim rate,
with only 2.9 percent of filers claiming the credit.
Eighty percent of the population is White, and Asians comprise another 15 percent. In 2000, 14,304
workers lived in Carmel Valley, constituting approximately one percent of the regional labor force.
The community expects rapid labor force growth. With a forecast labor force growth rate of 50
percent over the next ten years, Carmel Valley will add roughly 7,000 workers. Consistent with the
high levels of educational attainment, Carmel Valley’s labor force participation rate of 73.2
indicates that residents participate in the labor force at one of the highest rates in the region.
In 2000, there were 7,215 jobs in Carmel Valley. However, currently there are many more workers
than jobs and it is forecast to remain that way – many residents of Carmel Valley will continue to
commute outside of the community to get to work. The occupations with the largest presence in
2000 include Office Workers and Administrative Support Staff. With 3.6 percent of all high-tech
workers living in Carmel Valley, the share of high-technology cluster workers residing in the
community is disproportionate to its share of regional population and labor force. High-technology
companies likely locate in the vicinity of Carmel Valley because it is a high-educational attainment
pocket and, vice versa, many highly educated workers reside there because of its close access to
high-wage employment.
There are no training providers located in Carmel Valley. Although areas with high educational
attainment levels tend to be in less need of training than areas with low attainment levels, highly
educated workers may still require training programs that help them maintain and adapt their skills
over time to meet new labor market demands. This type of skill-maintenance training may be more
commonly provided at the workplace. Carmel Valley is in close proximity to UC San Diego and the
UC San Diego Extension program, which offer many high-skill training programs.
144
The Community of Carmel Valley
Hispanic
5.8%
25,248
White
79.4%
Black
0.6%
Average
Household
Households
Size
9,497
2.65
Asian
14.3%
Median Age
36
High School
Graduate, No
6.4%
15.1%
AA
8.1%
BA
38.3%
Numerical
Change in
Labor Force,
2000-2010
7,092
Percent Change
in Labor Force,
2000-2010
49.6%
2000 Labor
Force
Participation
Rate
73.2%
2000 Labor
Force Employment
Gap
7,089
Forecast
Difference
between Labor
Force and
Employment
Growth
5,145
Average
Adjusted
Gross Income
EITC Claim Rate
(AGI)
2.9%
$102,603
Average Claim
Amount
$1,209
7,859
Less than 9th
Grade
1.7%
9th to 12th
Grade
3.7%
Labor Force
Labor Force in 2000
Percent Share of
Regional Labor Labor Force
Force in 2000
in 2010
14,304
1.0%
21,396
Percent Share of
Regional Labor
Force in 2010
1.3%
Employment
Employment in 2000
7,215
Numerical
Employment in
Change in
2010 Employment
9,162
1,948
Percent of Jobs
Paying Sub-Living
Wages in 2000
31.1%
Percent o f Total
Employment
9.3%
8.9%
8.9%
7.0%
5.6%
39.5%
Occupation
Miscellaneous Sales
Office Workers
Administrative Support Staff
Sum
2000
1.0%
Percent of
County's HighTech Cluster
Workers
Residing in
Carmel Valley
3.6%
Percent of
County's
High-Tech
Cluster
Companies Percent of County's
Located in High-Tech Cluster
Carmel Workers Employed
Valley
in Carmel Valley
1.8%
2.3%
Training Providers
Number of Providers
Percent of
County's Total
Training
Providers
Located in Chula
Vista
0
0
Total
Amount of
Credit
Claimed
Total Number of (Thousands
EITC Returns of Dollars)
11,209
320
$387,000
Graduate
Degree
26.9%
Profile 5: The Community of Pacific Beach – A Pocket of Jobs Receiving Sub-Living Wages
Pacific Beach is a community that is representative of areas in the region with large proportions of
employment in occupations that, on average, earn less than the regional “living wage” of $11.58
per hour. In Pacific Beach in 2000, approximately 45.9 percent of all jobs were in occupations that,
on average, earned less than the living wage, a figure substantially higher than the regional
average of 32.4 percent. Looking at the top five occupations by employment, of the 10,647 jobs in
the community, twenty percent were in Food and Beverage Services and another 13.2 percent were
in Miscellaneous Sales. This employment distribution fits with the community’s reputation of
providing many visitor and entertainment services.
Pacific Beach had higher than average educational attainment levels in 1990, with over forty percent
of the over 25 population holding at least a B.A. In 2000, there were 24,343 workers living in Pacific
Beach. Relative to other communities in the region, Pacific Beach expects little if any growth in both
the labor force and employment through 2010. With a labor force that currently is substantially larger
than the number of jobs, many workers commute from Pacific Beach to jobs located elsewhere in the
region. However, the community’s relatively high educational attainment levels and the moderate
average income ($39,681) suggest that a sizeable share of workers commute to Pacific Beach to fill the
sub-living wage positions.
The substantial amount of low value-added employment in Pacific Beach is largely a result of the
types of visitor services demanded. According to the plan outlined in the Regional Economic
Prosperity Strategy (REPS), as residents and tourists demand higher-quality, higher-value services,
businesses providing those services will require better-trained employees. As this process intensifies
over the next decade, the low-skill workers currently employed in Pacific Beach will likely require
skill upgrades and see their standard of living rise. In 2000, there were four training providers
located in the community. By providing additional training programs in Pacific Beach in the future,
low-skill workers could have increased access to skill-upgrade training near their places of work.
146
The Community of Pacific Beach
Hispanic
11.3%
White
84.1%
Black
1.4%
Asian
3.2%
Less than 9th 9th to 12th
Grade
Grade
2.9%
5.3%
High School
Graduate, No
College
18.0%
Some
College
24.6%
40,296
Median Age Households
31.3
20,724
Average
Household
Size
1.93
28,320
AA
7.5%
BA
27.4%
Labor Force
Labor Force in 2000
Percent Share of
Regional Labor Labor Force
Force in 2000
in 2010
24,343
1.7%
24,326
Numerical
Change in
Percent Share of
Regional Labor Labor Force,
Force in 2010 2000-2010
1.5%
-17
2000 Labor
Force
Percent Change
in Labor Force, Participation
2000-2010
Rate
0.0%
72.0%
Employment
Employment in 2000
10,405
Numerical
Employment in Change in
2010 Employment
10,647
242
2000 Labor
Force Percent of Jobs
Paying Sub-Living Employment
Wages in 2000
Gap
45.9%
13,938
Forecast
Difference
between Labor
Force and
Employment
Growth
-259
Percent of Total
Employment
Occupational Employment
20.0%
Miscellaneous Sales
13.2%
Office Workers
6.5%
5.7%
4.6%
Sum
50.0%
Percent of
County's HighTech Cluster
Workers
Residing in
2000
Pacific Beach
1.7%
2.4%
Percent of
County's
High-Tech
Cluster
Companies Percent of County's
Located in High-Tech Cluster
Pacific Workers Employed
Beach
in Pacific Beach
1.8%
1.2%
Training Providers
4
Percent of
County's Total
Training
Providers
Located in
Pacific Beach
1.9%
Total
Amount of
Credit
Total Number
of EITC Returns
Claimed
25,818
1,846 $1,479,000
EITC Claim Rate
7.2%
Average
Adjusted
Gross
Income
(AGI)
$39,681
Average Claim
Amount
$801
Graduate
Degree
14.3%
APPENDICES
Appendix A
2001 Major Private Sector Employers in the San Diego Region1
by Major Statistical Area
Number of
MSA
Firm Name
North Agouron Pharmaceuticals
City
Alaris Medical Systems
Employees
1,300
Number of
MSA
Firm Name
Central
Alvarado Hospital Medical Center
710
Cox Cable San Diego Inc.
BAE Systems
1,400
Golden Eagle Insurance
Childrens Hospital & Health Care
2,210
Hotel Del Coronado
Cohu Electronics
1,054
Cox Communications
Cubic Corporation
Hyatt Regency
650
1,125
Employees
1,278
750
838
1,000
750
Marriott Hotel And Marina
1,200
National Steel & Shipbuilding Company
2,946
Cymer, Inc.
787
Paradise Valley Hospital
1,271
First American Credco
800
Raytheon Systems
Geico And Affiliates
1,697
San Diego Zoo
General Atomics
1,400
Scripps Mercy Hospital
550
900
1,683
Green Hospital At Scripps Clinic
773
Sempra Energy Corporation
Genprobe
550
Sheraton Harbor Island Hotel
750
Hamilton Sundstrand
620
Solar Turbines Inc-Lindbergh
1,574
Hewlett Packard Company
2,016
Southwest Marine Inc
Kaiser Permanente Medical Care
2,520
MSA Total (Total Firms = 15)
Kyocera America Inc.
766
Maxwell Technologies
650
South
Mitchell International
774
Suburban Scripps Memorial Hospital-Chula Vista
Motorola Broadband Communications
600
Sharp Chula Vista Medical Center
NCR Corporation
950
Nordstrom
500
Pacific Bell
1,115
Pilkington Barnes Hind Inc.
613
Pomerado Hospital
563
Qualcomm
Rancho Bernardo Inn
Remec Inc.
Salk Institute
East
BF Goodrich Aerospace Division
Barona Casino
Suburban Chemtronics Inc.
7,000
510
717
3,813
870
850
1,500
1,600
6,470
754
North
Acushnet Company
Scripps Memorial Hospital-La Jolla
1,273
County
Callaway Golf
Sea World
1,600
West
892
Four Seasons Resort
650
838
700
2,500
Legoland
Solar Turbines Inc-Kearny Mesa
1,267
Scripps Memorial Hospital-Encinitas
Sony Technology Center
3,600
Southern California Edison
576
Taylor Made Golf Company
1,580
504
2,309
La Costa Resort Hotel And Spa
Sharp Memorial Hospital
The Scripps Research Institute
596
Sycuan Gaming Center
4,450
Teradyne
2,500
1,650
Science Applications Intl Corporation
Sempra Energy Corporation
940
17,130
Grossmont District Hospital
Viejas Casino & Turf Club
1,196
700
Tri-City Medical Center
517
2,200
700
1,800
10,218
Titan Corporation
900
Toppan Electronics Inc.
550
Town And Country Hotel
500
North
Hunter Industries
TRW-Avionics Systems Division
500
County
Palomar Medical Center
East
San Diego Wild Animal Park
720
Signet Armorlite
557
Union-Tribune Publishing Company
United Parcel Service
University Of San Diego
1
1,826
507
1,100
Watkins Manufacturing Company
59,224
Regional Total (Total Firms = 82)
Employers with 500 or more employees at one site.
Source: SANDAG Activity Centers Inventory.
153
606
1,723
525
4,131
100,986
Appendix B
2000 Census Labor Force and Unemployment Data
Civilian
Population over
16
California
San Diego region
Cities
Carlsbad
Chula Vista
Coronado
Del Mar
El Cajon
Encinitas
Escondido
Imperial Beach
La Mesa
Lemon Grove
National City
Oceanside
Poway
San Diego
San Marcos
Santee
Solana Beach
Vista
County Areas
Alpine
Bonita
Bonsall
Borrego Springs
Bostonia
Camp Pendelton North
Camp Pendelton South
Casa de Oro - Mt. Helix
Crest
Fairbanks Ranch
Fallbrook
Granite Hills
Harbison Canyon
Hidden Meadows
Jamul
Julian
La Presa
Lake San Marcos
Lakeside
Pine Valley
Rainbow
Ramona
Rancho San Diego
Rancho Santa Fe
San Diego Country Estates
Spring Valley
Valley Center
Winter Gardens
25,447,467
2,077,399
Unemployed
Labor Force
Civilian
Unemployment
Rate
Unemployed as
% of 16+ pop
(incl. military)
Labor Force
Participation
Rate
Percent Share of
Regional
Unemployment
1,110,274
78,259
15,977,879
1,319,517
6.9%
5.9%
4.3
3.6
62.8%
63.5%
60,997
125,079
13,957
3,815
69,150
46,171
96,727
18,632
44,093
18,396
36,954
116,741
35,063
923,048
40,198
39,317
10,875
64,675
1,565
4,870
255
73
3,408
1,282
3,771
1,438
1,402
930
2,127
4,138
791
36,358
1,453
1,252
256
2,944
40,328
76,065
7,694
2,548
43,745
32,681
61,197
11,897
28,614
11,595
19,891
72,201
23,785
593,740
25,956
27,552
7,158
41,170
3.9%
6.4%
3.3%
2.9%
7.8%
3.9%
6.2%
12.1%
4.9%
8.0%
10.7%
5.7%
3.3%
6.1%
5.6%
4.5%
3.6%
7.2%
2.5
3.8
1.2
1.9
4.8
2.8
3.9
7.2
3.1
4.9
5.3
3.4
2.2
3.8
3.6
3.1
2.3
4.5
66.1%
60.8%
55.1%
66.8%
63.3%
70.8%
63.3%
63.9%
64.9%
63.0%
53.8%
61.8%
67.8%
64.3%
64.6%
70.1%
65.8%
63.7%
2.0%
6.2%
0.3%
0.1%
4.4%
1.6%
4.8%
1.8%
1.8%
1.2%
2.7%
5.3%
1.0%
46.5%
1.9%
1.6%
0.3%
3.8%
9,900
9,585
2,703
2,129
11,037
1,707
2,397
14,901
2,121
1,417
20,678
2,617
2,715
3,098
4,393
1,227
22,895
3,830
14,157
1,133
1,601
11,266
15,063
2,490
6,643
19,192
5,185
14,983
312
331
78
47
514
57
78
476
90
31
836
61
65
60
124
9
1,017
70
561
19
17
398
418
17
162
791
94
431
6,736
5,726
1,642
1,172
6,781
1,016
1,214
9,268
1,409
567
12,132
1,809
1,911
1,548
2,808
864
14,889
1,103
9,295
769
790
7,464
10,852
1,201
4,548
12,531
3,481
10,324
4.6%
5.8%
4.8%
4.0%
7.6%
5.6%
6.4%
5.1%
6.4%
5.5%
6.9%
3.4%
3.4%
3.9%
4.4%
1.0%
6.8%
6.3%
6.0%
2.5%
2.2%
5.3%
3.9%
1.4%
3.6%
6.3%
2.7%
4.2%
3.1
3.4
2.9
2.2
4.6
0.8
1.4
3.2
4.2
2.2
3.9
2.3
2.4
1.9
2.8
0.7
4.3
1.8
3.9
1.7
1.1
3.5
2.7
0.7
2.4
4
1.8
2.8
68.0%
59.7%
60.7%
55.0%
61.4%
59.5%
50.6%
62.2%
66.4%
40.0%
58.7%
69.1%
70.4%
50.0%
63.9%
70.4%
65.0%
28.8%
65.7%
67.9%
49.3%
66.3%
72.0%
48.2%
68.5%
65.3%
67.1%
68.9%
0.4%
0.4%
0.1%
0.1%
0.7%
0.1%
0.1%
0.6%
0.1%
0.0%
1.1%
0.1%
0.1%
0.1%
0.2%
0.0%
1.3%
0.1%
0.7%
0.0%
0.0%
0.5%
0.5%
0.0%
0.2%
1.0%
0.1%
0.6%
Source: U.S. Bureau of the Census, Census 2000.
157
Appendix C
Training Providers in the San Diego Region
Community Name
Kearny Mesa
Mira Mesa
Centre City
SAN MARCOS
EL CAJON
LA MESA
Mission Valley
ESCONDIDO
OCEANSIDE
VISTA
College Area
Clairemont Mesa
Linda Vista
CHULA VISTA
La Jolla
Peninsula
Scripps Miramar Ranch
Southeastern San Diego
CARLSBAD
ENCINITAS
NATIONAL CITY
Navajo
Pacific Beach
Uptown
Greater North Park
University
Midway-Pacific Highway
Rancho Bernardo
Mid-City: City Heights
Mid-City: Eastern Area
Mid-City: Kensington-Talmadge
Ramona
Valle De Oro
IMPERIAL BEACH
POWAY
SOLANA BEACH
Barrio Logan
Greater Golden Hill
Mission Bay Park
Otay Mesa-Nestor
San Ysidro
Tierrasanta
Mid-City: Normal Heights
Crest-Dehesa
Lakeside
North County Metro
Spring Valley
Bonsall
Region Total*
Percent of
Number of
All
Trainers
Providers
27
12.3%
21
9.6%
12
5.5%
11
5.0%
8
3.7%
8
3.7%
8
3.7%
7
3.2%
7
3.2%
7
3.2%
7
3.2%
6
2.7%
6
2.7%
5
2.3%
5
2.3%
5
2.3%
5
2.3%
5
2.3%
4
1.8%
4
1.8%
4
1.8%
4
1.8%
4
1.8%
4
1.8%
3
1.4%
3
1.4%
2
0.9%
2
0.9%
2
0.9%
2
0.9%
2
0.9%
2
0.9%
2
0.9%
1
0.5%
1
0.5%
1
0.5%
1
0.5%
1
0.5%
1
0.5%
1
0.5%
1
0.5%
1
0.5%
1
0.5%
1
0.5%
1
0.5%
1
0.5%
1
0.5%
1
0.5%
219
100.0%
Source: San Diego Workforce Partnership.
San Diego County Training and Education Provider (STEP)
database (www.sandiegoatwork.com).
Cities designated by all capital letters.
* There are 277 total training providers in the region; of these,
we were only able to geographically locate 219.
161
Appendix D
San Diego Basic Needs Budget Technical Information
Rent/Utilities
2002 Fair Market Rents from the Department of Housing and Urban Development (HUD) for 1bedroom units. Rents for 356 Metropolitan Statistical Areas (MSAs) were averaged to obtain a
national figure.
Food
U.S. Department of Agriculture’s (USDA) Low-Cost Food Plan for a Male age 20-50 years old for
September 2001.
Transportation
Transportation costs were calculated by multiplying the average costs per mile by the average number
of miles the average American travels in a year. Vehicle costs were estimated using the Internal Revenue
Services’ (IRS) cost-per-mile rate for 2001 of 34.5 cents per mile. The average miles traveled were taken
from the 1995 National Transportation Survey1, assuming that a person should be able to afford all
essential, non-social trips (i.e. to work, appointments etc.).
Health Care
Data from the 1997 National Medical Expenditure Panel Survey (NMEPS)2 was used for average
insurance premium costs and out-of-pocket expenses for employer-provided coverage for a single
person. At minimum, insurance plans in the NMEPS cover hospital and physician costs (some plans in
the survey may also include co-payments, uncovered expenses such as dental care and prescriptions,
and insurance deductibles). Costs were inflated from 1997 dollars to 2001 using the Consumer Price
Index (CPI) for U.S. urban wage earners.
Clothing/ Personal
Personal expenses were assumed to be ten percent of all other expenses (not including taxes) based
on a rule used by W.O.W.
Taxes
Tax amounts were calculated as a function of total income (total income equals expenses plus
income-related taxes).
Federal Income: IRS Form 1040EZ 2001 tax table (approximately 15% of income).
Federal Payroll: 7.65% of income.
State Income: California Franchise Tax Board Annual Report, 1999; based on the 2000 California
tax table. Includes standard deductions and $60 Renter's Credit (approximately 1.45% of
income).
Assumptions
All hourly calculations were made using 2080 work hours per year. All costs from years other than
2001 were adjusted to 2001 using the Consumer Price Index for urban wage earners.
1
Bureau of Transportation Statistics, www.bts.gov.
Table II.C.1 (1997). Average total single premium (in dollars) per enrolled employee at private sector
establishments that offer health insurance by firm size and state: United States, 1997; $2,050.82 annually. Table
II.C.2 (1997) Average total employee contribution (in dollars) per enrolled employee for single coverage at
private-sector establishments that offer health insurance by firm size and state: United States, 1997; $319.99
annually.
2
165
2nd quintile of costs from Consumer
Expenditure Survey for fixed costs; AAA
surveys for gas; CA Dept. of Insurance
Statistical Analysis Bureau; National Personal
Transportation Survey for distances.
PacAdvantage 2000 Rate Information;
National Medical Expenditure Survey.
10% of all other costs.
Sales taxes for miscellaneous items (not food);
Commerce Clearing House State Tax
Handbook; CA Franchise Tax Board forms.
15% income tax rate lowered to 7-10% for
low-income earners.
7.65% per dollar earned.
Transportation
Health Care
Clothing/Personal
California State
Taxes
Federal Taxes
Payroll Taxes
(Social Security,
Medicare)
CA Energy Commission 1995 Driver
Diary Study; IRS cost-per-mile rate.
USDA’s Low-cost Food Plan (national).
Food
Personal and Dependents tax credits;
personal exemption.
2001 Payroll tax rates.
Child Tax Credit; Rate Reduction
Credit; Renter’s Tax Credit.
Kaiser, Blue Cross HMO; The State of
Health Insurance (UCLA); Healthy
Families Program.
1999 National Consumer Expenditure
Survey.
HUD’s Fair Market Rents (San Diego,
FY 2001).
USDA’s Low-cost Food Plan (national).
HUD’s Fair Market Rents (San Diego, FY 2000).
Rent/ Utilities
California Budget Project
W.O.W. Self -Sufficiency Standard
Expense/ Item
Sources for Expenses of Basic Needs Budgets
Standard Deductions; 15% tax
rate.
7.65% per dollar earned.
State Renter’s Tax Credit.
10% of all other costs.
National Medical Expenditure
Survey.
National Personal
Transportation Survey for
distances; IRS cost-per-mile rate.
National Average of HUD’s Fair
Market Rents (FY 2002).
USDA’s Low-cost Food Plan
(national).
SourcePoint
Comparison of Percent Share of Components
Between Single Adult Budgets for the San Diego Region
100%
90%
80%
70%
18%
7%
6%
19%
20%
7%
10%
14%
9%
Percent
60%
50%
14%
18%
11%
43%
10%
35%
32%
CBP
SourcePoint
10%
0%
WOW
Healthcare
Food
Rent/ Utilities
10%
30%
20%
Clothing/ Personal
Transportation
16%
40%
Total Taxes
Budget
167
Appendix E
Inside Sales Representative
Payroll Clerk
Inbound Customer Service or Sales Representative
Accounting Clerk
1. Account Executive
Represent.
2. Sales Representative
Project Manager
Source: Business Services Industry Cluster’s Advisory Committee. Compiled by SourcePoint 2001.
Telemarketers
& Solicitors
Account
Collectors
Legal
Secretaries
Accounting
Clerks
Systems
Analysts
Inspectors &
Testers
Sales Agents
Customer Service Representative
Architects
Drafters
Lawyers
Paralegal
Personnel
Project Architect
Employment
Interviewers
25%
25-50%
0%
0%
20-60%
1.
2.
3.
4.
1. Recruiting Assistant
2. Administrative Assistant
3.Community Relations
4. Reception
Recruiter
Staffing Assistant
Recruiter
Recruit. Assistant
25%
Account. Assistant
Assistant Financial Manager
10-50%
90%
Second Position
Admin. As sistant
Entry Level Position
Quality Assurance
Representative
Second
Position Filled From
Outside (%)
1. Receptionist
2. Administrative Support Representative
Payroll/ Accounting
Clerk
Occupational
Area
Financial
Managers
Administrative
Services
Managers
Accountants
& Auditors
Advanced Knowledge of
Payroll Laws ♠
1. Telephone ♠
2. Customer Service & Sales
Skills ♠
1. Telephone Presentation ♠
2. Customer Service
& Sales Skills Presentation ♠
1. Computer ♠
2. Task Management ♣ ♠
1. Detail Oriented ♣
2. Computer ♠
1. Phone ♣
2. Communication ♣
3. Computer ♠
4. Presentation ♣
5. Time Management ♣
6. Administrative Skills ♠
1. Project Type/ Years Experience ♣
2. Team Leader ♣
1. Project Type/ Years Experience ♣
2. Knowledge Tech. Systems ♠
1. Computer ♠
2. Budgeting ♣
3. Technical Skills ♠
3. Technical ♠
4. Negotiation/ Presentation ♠
3. CAD Proficient ♠
3. Arch. Practice/ Legal ♣
7. Organization ♣
8. Legal Knowledge of
Interviewing ♠
9. Interviewing Skills ♠
10. Maturity ♣
3. Basic Accounting ♠
3. Writing ♣
4.Communication ♠
3.Organization ♣
Skills Required For Promotion
♠ = responsibility of the employer
♣ = responsibility of the employee
Career Ladders in the Business Services Cluster in the San Diego Region, 2001
5-20%
5-30%
1. Supervisor of Repairers
2. Maintenance Worker
1. Maintenance Electrician
2. Journeyman Levels 1-5
3. Tr ainee D
1. Journey Person
2. Journeyman Lev els 1-5
3. Trainee D
1. Journey Person
2a. Master Machinist
2b. CNC Operator
2. Trainee D
Layout Mechanic
1. Assembler II
2. Assembler
2. Trainee D
1. Journey Person
2. Maintenance Helper
1. Maintenance Electrician
2. Improver Levels 1-3
3. Electric. Trainee E
1. Trainee
3. Pipefitter Trainee E
1. Trainee
2. Machi nist
2. Shipfitter Student
Mechanic
1. Assembler I
2. Assembler
2. Welder Student
Assembler
Electricians
Plumbers,
Pipefitters,
Steamfitters
General Machinists
Shipfitters
Sheet Metal
Mechanics
Electrical &
Electronic
Assemblers
Welders
Assemblers &
Fabricators
50%
10-25%
1. Run Multiple Machines ♣
2. Read Blueprints♣
3. Skills Upgrade♠
4. Attendance♣
1. Cut Plasma♠
2. Weld Stainless♠
3. TIG Welding♠
1. Read Blueprints♠
2. Ship Board Installation♠
1. Team Work♣
2. Attendance♣
3. Eye Hand♣
1. H018 Welding Certificate♠
2. MIG Welding♠
3. Cut Plasma♠
4. Prepare Material ♠
1. Mechanical Fit-up Skills♣
2. Read Blueprints♣
1. Time in Grade♠
2. Independent Work♠
1. Dimensions & Tolerances ♠
2. Solid Modeling♣
1. Time in Grade♠
1. Time in Grade♠
2. Precision Instruments♠
1.Communication♠
2. Troubleshoot ♣
3. Organizational Skills♣
2. Fiber Optics♠
3. Troubleshoot ♠
4. AC- DC Theory♠
2. Attendance♣
3. Job Perform. ♣
4. Silver Brazing Certificate♠
3. Hand & Power Tools♠
4. Soldering ♠
5. Complicated Work♠
5. Stick Welding
SMAW♠
6. Flux Core Welding
FCAW♠
3. Soldering♠
4. Complicated Work♠
5. Cable Way & HookUp♠
6. T-1 Welding♠
6. Pipe Welding
Certificate♠
7. Joint Development ♠
8. Identify Fittings &
Materials ♠
5. Job Performance ♣
6. In-Place Value
Repair♠
7. Bore & Hold
Tolerances ♠
4. T-1 Welding♠
5. Burning♠
6. Fit Aids ♠
4. More Diversified
Tasks ♠
5. Painting, Drywall♠
3. Interaction Skills♠
3. Fastener Mechanics♣
3. Interaction Skills♠
3. CAD Design♠
Skills Required For Promotion
♠ = responsibility of the employer
♣ = responsibility of the employee
1. Independent Work♣
2. Know Policies & Procedures ♠
Source: Defense and Transportation Manufacturing Industry Cluster’s Advisory Committee. Compiled by Sourcepoint 2001.
1. Supervisor
2. Assembler Intermediate
0-10%
10%
10-20%
10-30%
0-75%
30%
25%
10-15%
15-50%
10%
10-30%
Senior Electronic Inspector
Senior Systems
Acceptance Inspector
Second Position
1. Staff Engineer
2. Engineer II
3. Electrical Engineer
1. Software Developer II
2. Software Engineer
1. Staff Engineer
2. Mech. Engineer
1. Technician II
2. Senior Engineering Technician
Software Engineer
General
Maintenance
Repairers
Entry Level Position
Associate Engineer
Engineer I
Associate Elect. Engineer
Software Developer I
Associate Software Developer
Associate Engineer
Associate Mechanical Engineer
Technician I
Engineering Technician
Associate Software Engineer
1.
2.
3.
1.
2.
1.
2.
1.
2.
Occupational
Area
Electrical and
Electronic
Engineers
Computer
Engineers
Mechanical
Engineers
Engineering
Technicians
Computer
Programmers
Inspectors and
Testers
Second
Position Filled
From Outside (%)
Career Ladders in the Defense and Transportation Manufacturing Cluster in the San Diego Region, 2001
Appendix F
“Soft Skills”
“We hire the smile,” says a spokesman for the hospitality industry. “We can train the skills.”
Increasingly, in an economy dominated by communication and teamwork – whether electronic or
face to face – the “smile” that employers say they want is really just shorthand for a cluster of
personality traits, social graces, facility with language, and personal habits that many older working
people take for granted and most find hard to list.
–
Excerpted from: Houghton, Ted and Tony Proscio. “Hard Work on Soft Skills: Creating a
Culture of Work in Workforce Development", Public/Private Ventures Group, 2001.
www.ppv.org.
Employer “Soft Skill” Requirements:
•
Oral communication skills
•
Life long learning/ continuous education
•
Problem solving skills
•
Customer service skills
•
Interpersonal skills
•
Ability to work as a team member
•
Record keeping skills
•
Ability to work under pressure
•
Verbal presentation skills
•
Motivational skills
•
Ability to read and follow directions
•
Knowledge of various cultural backgrounds
•
Ability to work independently
•
Willingness to work weekends/ holidays and extra hours
–
This “Soft Skills” list was developed from the responses of local employers participating in
the Workforce Partnership’s Occupational Outlook surveys over the last eight years.
San Diego Workforce Partnership’s
Work Readiness Certificate Program
The San Diego Workforce Partnership developed the Work Readiness Certificate Program by
having local leaders identify 24 skills required for success on the job, including communication,
worksite behavior, teamwork, academics, and customer service. Individuals who receive the
certificate have demonstrated their competency in all 24 of the required skills. For more
information contact the Workforce Partnership or visit www.workforce.org.
175
GLOSSARY
GLOSSARY
Term/Acronym
Definition/Description
AA
Associate of Arts degree.
Adjusted Gross
Income (AGI)
A number used for tax purposes defined as gross income minus
adjustments to income. Gross income is all income from all sources
(other than tax-exempt income). Adjustments to income include
deductions for moving expenses, alimony paid, a penalty on early
withdrawal of savings, and contributions to an individual retirement
arrangement (IRA).
At-risk
A term used in this study primarily to identify communities with
residents that may have trouble moving up the career ladder and
improving their standards of living. Criteria for being considered "atrisk" include low levels of educational attainment, high levels of
unemployment, low incomes, low labor force participation rates
(facing workforce barriers) and high EITC claim rates.
BA
Bachelor of Arts degree.
Basic Needs Budget
A personal budget of itemized expenses that is used to determine
the costs of basic necessities in estimating a "living wage".
Career Ladder
A path within an occupation that an individual can follow by
acquiring knowledge and skills, and taking on more responsibilities
that will lead to higher pay. It can also be a path through which, by
acquiring additional skills and knowledge, an individual can move to
different occupations that pay higher wages within a single
company or industry.
Career Lattices
Paths that allow individuals to apply their existing knowledge and
skills to similar or different occupations that offer higher wages in
completely different industries (skills are transferable).
179
Cluster – Biomedical
Products
Produces instruments, medical devices, equipment, and other
apparatus primarily for consumption by the medical field. Includes
the following SICs: 3821, laboratory apparatus & furniture; 3827,
optical instruments & lenses; 3841, surgical and medical instruments;
3842, surgical appliances & supplies; 3844, x-ray apparatus & tubes;
3845, electromedical equipment; and 3851, ophthalmic goods.
Cluster –
Biotechnology and
Pharmaceuticals
Includes sectors engaged in researching, manufacturing, or
processing a broad range of biological, chemical, and medical
products, as well as medical and industrial chemicals and
preparations. Includes the following SICs: 2819, industrial inorganic
chemicals, nec; 2833, medicinals & botanicals; 2834, pharmaceuticals
preparations; 2835, diagnostic substances; 2836, biological products
excluding diagnostic; 2869, industrial organic chemicals, nec; 2899,
chemical preparations; 8731, commercial pysical research; 8733,
noncommercial research org.; and 8734, testing laboratories.
Cluster – Business
Services
Includes sectors that provide a variety of professional services to
local business establishments, including management, legal, and
personnel supply services. Includes the following SICs: 2741,
miscellaneous publishing; 2752, commercial printing, lithographic;
7311 and 7319, advertising agencies; 7334, photocopying &
duplication services; 7361, employment agencies; 7363, help supply
services; 7375, information retrieval services; 7376, computer
facilities management; 7377, computer rental & leasing; 7389,
business services, nec; 8111, legal services; 8712, architectural
services; 8720, accounting, auditing, & bookkeeping; 8741,
management services; 8742, management consulting services; and
8748, business consulting, nec.
Cluster –
Communications
Includes sectors primarily engaged in researching and manufacturing
communications-related products. Also includes sectors that provide
point-to-point communications services such as cellular and digital
phone and pager services. Includes the following SICs: 3661,
telephone & telegraph apparatus; 3663, radio & TV communications;
3669, communications equipment, nec; 4812, radiotelephone
communications;
4813,
telephone
communications,
except
radiotelephone; 4899, communications services; 8711, engineering
services; and 8731, commercial physical research.
180
Cluster – Computer
and Electronics
Manufacturing
Includes sectors that manufacture and assemble electronic components
and products. Includes the following SICs: 3571, electronic computers;
3572, computer storage devices; 3577, computer peripheral equipment,
nec; 3629, electrical industrial apparatus, nec; 3651, household audio &
video equipment; 3671, electron tubes; 3672, printed circuit boards;
3674, semiconductors & related devices; 3675, electronic capacitors;
3676, electronic resistors; 3677, electronic coils & transformers; 3678,
electronic connectors; 3679, electronic components, nec; 3695, magnetic
& optical recording media; 3699, electrical equipment & supplies, nec;
and 3825, instruments to measure electricity.
Cluster – Defense
and Transportation
Manufacturing
Includes sectors engaged in manufacturing or assembling aircraft,
ships, boats, and defense related products. Includes the following
SICs: 3511, steam engines & turbines; 3721, aircraft; 3724, aircraft
engines & engine parts; 3728, aircraft parts & equipment, nec; 3731,
ship building & repairing; 3732, boat building & repairing; 3761,
guided missiles & space vehicles; 3769, space vehicle equipment; and
3812, search & navigation equipment.
Cluster –
Entertainment and
Amusement
Includes sectors engaged in arranging and providing amusement,
recreation, and entertainment services. Includes the following SICs:
4830, radio & TV broadcasting stations; 7812, motion picture & video
tape production; 7819, services allied to motion picture production;
7922, theatrical producers & services; 7941, sports clubs, managers, &
promoters; 7992, public golf courses; 7996, amusement parks; 7999,
amusement & recreation, nec; 8412, museums & art galleries; and
8422, botanical & zoological gardens.
Cluster –
Environmental
Technology
Includes sectors that manufacture products with environmental
applications. Includes the following SICs: 3564, blowers & fans; 3569,
general industrial machinery, nec; 3589, service industry machinery,
nec; 3823, process control instruments; 3824, fluid meters & counting
devices; 3826, analytical instruments; and 3829, measuring &
controlling devices, nec.
Cluster – Financial
Services
Includes sectors engaged primarily in deposit banking, extending
credit in the form of loans, and the exchange of securities and
commodities. Includes the following SICs: 6035, saving institutions,
federally chartered; 6036, saving institutions, not federally chartered;
6061, credit unions, federally chartered; 6062, state credit unions;
6091, non-deposit trust facilities; 6099, functions related to deposit
banking; 6140, personal credit institutions; 6162, mortgage bankers
& loan correspondents; 6163, loan brokers; and 6282, investment
advice.
181
Cluster – Fruits and
Vegetables
Includes sectors engaged in the production and maintenance of
fruit, melons, tree nuts, and vegetable crops. Includes the following
SICs: 0161, vegetables & melons; 0171, berry crops; 0172, grapes;
0174, citrus fruits; 0175, deciduous tree fruits; 0179, fruits & tree
nuts, nec; 0762, farm management services; 2033, canned fruits &
vegetables; and 2449, wood containers, nec.
Cluster – Horticulture
Includes sectors engaged in the production and maintenance of
ornamental plants, nursery crops, and food crops grown under cover.
Includes the following SICs: 0181, ornamental nursery products;
0182, food crops grown under cover; 0191, general farms, primarily
crop; 0711, soil preparation services; 0781, landscape counseling &
planning; and 0783, ornamental shrub & tree services.
Cluster – Medical
Services
Includes sectors primarily offering health services to the general
public through hospitals, medical facilities, and offices. Includes the
following SICs: 7352, medical equipment rental; 8011, offices &
clinics of doctors of medicine; 8021, offices & clinics of dentists; 8049,
offices of health practitioners, nec; 8062, general medical & surgical
hospitals; 8063, psychiatric hospitals; 8069, specialty hospitals, except
psychiatric; 8071, medical laboratories; 8072, dental laboratories;
8092, kidney dialysis centers; 8093, specialty outpatient facilities, nec;
and 8099, health & allied services, nec.
Cluster –
Recreational Goods
Manufacturing
Includes companies that manufacture recreational goods, sporting
and athletic goods, and toys. Includes the following SICs: 3942, dolls
& stuffed toys; 3944, games, toys & children's vehicles, except dolls
and bicycles; and 3949, sporting & athletic goods, nec.
Cluster – Software
and Computer
Services
Includes sectors that provide services such and computer
programming, prepackaged software, and software development.
Includes the following SICs: 7371, computer programming services;
7372, prepackaged software; 7373, computer integrated systems
design; 7374, computer processing & data preparation services; 7379,
computer related services, nec; 8711, engineering services; and 8731,
commercial physical/biological research.
Cluster – Visitor
Industry Services
Includes sectors such as hotels and motels, restaurants, travel agencies,
and car rental companies. Includes the following SICs: 4489, water
passenger transportation, nec; 4499, water transportation services,
nec; 4512, air transportation, scheduled; 4581, airports, flying fields, &
airport terminal services; 4724, travel agencies; 4725, tour operators;
5812, eating places; 5813, drinking places; 7011, hotels & motels; 7021,
rooming & boarding houses; 7032, sporting & recreational camps;
7033, trailer parks & campsites; 7041, organization hotels & lodging
houses; and 7514, passenger car rental.
182
Cluster (Traded)
Groups of complementary, competing and interdependent industries
that drive wealth creation in a region.
Consumer Price
Index
An index that reflects the price inflation of consumer goods by
evaluating the change in prices of a basket of goods that includes
products a typical consumer would purchase (maintained by the
Department of Labor's Bureau of Labor Statistics).
EDD
California Employment Development Department.
Earned Income Tax
Credit (EITC)
A monetary credit paid to workers (hence “earned”) whose incomes
fall below an income threshold administered by the Internal
Revenue Service (IRS). The income eligibility cut-offs in 2000 were
approximately $10,300 per year for single filers and $31,100 per year
for joint filers.
Education
The acquisition of general knowledge and basic skills (in a degreeawarding program).
EITC
See Earned Income Tax Credit.
Employer Cost Index
An index of employer costs maintained by the Department of
Labor's Bureau of Labor Statistics. The index reflects changes in
wages over time and can be used to adjust wages for inflation.
GED
General Educational Development test. Passing the GED is the
equivalent of obtaining a high school diploma.
H-1B Visa
A visa program administered by the Immigration and Naturalization
Service (INS) that allows skilled foreign nationals to work in the U.S.
for a limited period of time.
Inflation
A continuing or sustained rise in the general price level.
Labor Force
The subset of the (civilian) population between the ages of 15 to 79
that is working or looking for work.
Labor Force
Participation Rate
The proportion of a population that is in the labor force, either
working or looking for work.
Living Wage
A wage level that allows an individual or a family to afford basic
living necessities (e.g. food, rent, clothing, etc.)
Mean
Median
The sum of all data values divided by their number. Average.
The value of the middle item when data are arranged in order of
size; a measure of central tendency.
183
Mobility (Economic)
Nominal
Normal Distribution
The opportunity to increase personal income and wages over time.
Not adjusted for inflation.
A symmetric, bell-shaped probability distribution.
NSF
National Science Foundation. An independent agency of the U.S.
government, established in 1950 to promote the progress of science;
to advance the national health, prosperity, and welfare; and to
secure the national defense.
OES
Occupational Employment Survey. A survey of employment and
wages conducted at the occupational level by the Bureau of Labor
Statistics.
Per Capita
Poverty
Per person.
A state of destitution; falling below the Federal Poverty Guideline.
Poverty Guideline
An income threshold used by the federal government to determine
what proportion of the population is poor, or "living in poverty".
The Poverty Guideline for 2001 is $17,650 for four persons
(www.aspe.hhs.gov/poverty). The Guideline was and still is calculated
by taking 3 times the price of a basket of food because, historically,
food accounted for 31 percent of a consumer’s expenses. Although
the Poverty Guideline was intended to be a guideline for minimum
sustenance, it has been erroneously applied to the living wage
context as an indicator of a wage an individual or family would
require to afford their basic living expenses.
Quintile
When a data set is divided into five equal parts, a quintile represents
one of the five parts. "Bottom Quintile" – the lowest fifth of the
data. "Upper Quintiles" – the highest fifth of the data [data are
arranged in order of size].
San Diego Association of Governments.
SANDAG
SDSU
Shortage Occupation,
Cluster
San Diego State University.
An occupation in a traded cluster that met at least one of four
“shortage criteria” used in evaluating employer responses: First, did
employers report difficulty in finding qualified applicants? Second,
did employers recruit relatively large numbers of workers from
outside the region? Third, were many workers in this occupation
hired using H1-B visas (or did many firms report hiring for this
occupation using H1-B visas)? Fourth, did employers report that
workers in a given occupation had inadequate skills to perform
essential tasks?
184
SIC
Skill
Standard Industrial Classification. A classification system developed
by the Executive Office of the President, Office of Management and
Budget, to classify establishments by the types of activities in which
they are engaged.
The ability to perform a work-related task.
Smart Growth
A compact, efficient, and environmentally sensitive pattern of
development that provides people with additional travel, housing, and
employment choices by focusing future growth away from rural areas
and closer to existing and planned job centers and public facilities.
Soft Skills
Basic personality traits, social graces, and education and literacy that
make a worker employable. Examples of “soft” skills are work ethic,
courtesy, teamwork, self-discipline, conformity to prevailing norms,
and language proficiency.
Training
Instruction leading to the acquisition of specific skills.
Training Level –
Associate’s Degree
A degree that usually requires at least two years of full-time
academic study.
Training Level –
Bachelor’s degree
A degree that generally requires at least four years, but not more
than five years, of full-time academic study.
Training Level –
Bachelor’s or Higher
Degree, Plus Work
Experience
A combination of education and experience usually required for
management occupations. All of these occupations require
experience in a related nonmanagement position for which a
bachelor’s or higher degree is usually required.
Training Level –
Doctoral Degree
A Ph.D. or other doctoral degree that usually requires at least 3
years of full-time academic study beyond a bachelor’s degree.
Training Level – First
Professional Degree
A degree that usually requires at least 3 years of full-time academic
study beyond a bachelor’s degree.
Training Level –
Long-Term On-theJob Training
On-the-job training or combined work experience and formal
classroom instruction of more than 12 months. Includes formal and
informal apprenticeships that may last up to 5 years. Long-term onthe-job training also includes intensive occupation-specific,
employer-sponsored programs that workers must successfully
complete. Also included in this category is the development of a
natural ability – such as that possessed by musicians, athletes, actors,
and other entertainers – that must be cultivated over several years,
frequently in a nonwork setting.
185
Training Level –
Master’s Degree
A degree that usually requires 1 or 2 years of full-time academic
study beyond a bachelor’s degree.
Training Level –
Moderate-Term onthe-Job Training
Combined on-the-job experience and informal training acquired
over a period of 1 to 12 months.
Training Level –
Postsecondary
Vocational Award
Certificate or other award given at the conclusion of programs lasting
only a few weeks or more than a year. Does not include degree
programs.
Training Level –
Short-Term On-theJob Training
On-the-job experience or instruction consisting of
demonstration of job duties or 1 month or less of training.
a
short
Training Level – Work
Experience in a
Related Occupation
Work experience required for first-line supervisors/ managers of
service, sales, and related production or other occupations; or
management occupations.
Training
Requirement
The minimum level of education or training (skills) needed to
perform the essential tasks of a given occupation.
UCSD
University of California at San Diego.
Underemployment
Working less than full-time hours; also, working in an occupation
that does not fully utilize one’s education or training.
Unemployment Rate
The percentage of persons in the labor force (persons working, or
actively seeking work) who are not working for pay in any form.
Value-Added
The monetary amount a worker contributes to a good or service in
the production process.
Workforce Barriers
Basic health and social problems that keep people from obtaining or
maintaining employment. In some cases, prospective employees may
appear “unemployable” to companies because they lack basic work
habits, or “soft skills”. Workforce barriers may depress rates of labor
force participation.
Workforce
Development
The task of educating workers and helping them acquire the skills
that are demanded by employers.
Working-age
Population (Civilian)
The civilian population ages 15 to 79 years old that could potentially
be employed.
186
SAN DIEGO WORKFORCE PARTNERSHIP, INC.
The San Diego Workforce Partnership, Inc. (Workforce Partnership) has been in operation
since 1974, when a joint powers agreement between the City and the County of San Diego
created what is now a public/private nonprofit corporation. The Workforce Partnership’s
mission is:
To coordinate a comprehensive workforce development system that ensures
a skilled, productive workforce and supports a healthy economy throughout
the San Diego region.
The Workforce Partnership has long created workforce solutionsSM for the region’s employers and individuals through public and private partnerships. We provide cost-effective,
quality programs and services that promote self-sufficiency and address the current and
long-term needs of the region’s employers. This is largely accomplished through the
Partnership’s regional network of One-Stop Career Centers – including its online center,
www.SanDiegoAtWork.com – and its targeted adult and youth employment and training
programs. These resources provide job seekers and employers with universal access to
labor market information and comprehensive employment resources.
For more information about the Workforce Partnership, visit www.SanDiegoAtWork.com,
or contact us through the information below.
Additional copies of A Path to Prosperity: Preparing Our Workforce are available for $25
each. Copies of the report Summary are available for $10 each. To order, please contact the
San Diego Workforce Partnership Strategic Alliances Department at path@workforce.org,
or at the phone number listed below.
San Diego Workforce Partnership, Inc.
1551 Fourth Ave, Suite 600, San Diego, CA 92101
619-238-1445 office • 619-544-9675 fax • www.SanDiegoAtWork.com
Lawrence G. Fitch, President and CEO
$25
ISBN 0-9716120-1-3

A Path to Prosperity: Preparing Our Workforce

Transcription

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