Califorinia's San Juaquin Valley: A Region in Transition
California’s San Joaquin Valley:
A Region in Transition
December 12, 2005
Tadlock Cowan, Coordinator
Analyst in Rural and Regional Development Policy
Resources, Science, and Industry Division
California’s San Joaquin Valley: A Region in Transition
Summary
CRS was requested to undertake a study of the San Joaquin Valley (SJV) and
a comparison with another U.S. region. The eight-county San Joaquin Valley, part
of California’s Central Valley, is home to 5 of the 10 most agriculturally productive
counties in the United States. By a wide range of indicators, the SJV is also one of
the most economically depressed regions of the United States. This report analyzes
the SJV’s counties and statistically documents the basis of current socioeconomic
conditions. The report further explores the extent to which the SJV shares similarities
with and differs from the Appalachian Regional Commission (ARC) area and a 68-
county Central Appalachian subregion which contains some of the most
economically distressed counties in Appalachia. The report also examines the role
of federal expenditures in the cities and counties of the SJV.
During the past twenty-five years, population growth rates in the SJV were
significantly higher than for California or the United States and their projected
growth rates over the next 20 years are also significantly higher. In 2000, the SJV
also had substantially higher rates of poverty than California or the United States.
Poverty rates were also significantly higher in the SJV than in the ARC region,
although the rate is somewhat lower than that of the Central Appalachian subregion.
Unemployment rates in the SJV were higher than in California or the United States
and the ARC area. Per capita income and average family income were higher in the
SJV than in Central Appalachia, but per capita income in the SJV was lower than in
the ARC region as a whole. SJV households also had higher rates of public
assistance income than did Central Appalachian households. Madera County ranked
among the 10 lowest per capita income Metropolitan Statistical Areas (MSAs) in the
United States in 2003, and the other 5 MSAs in the San Joaquin were all in the
bottom 20% of all U.S. MSAs. Other indicators of social well-being discussed in the
report showed that the SJV is a region of significant economic distress.
Data from the U.S. Bureau of the Census’s Consolidated Federal Funds Reports
for 2002 and 2003 showed that every SJV county received fewer federal funds than
the national per capita average or for California. Most SJV counties received
approximately $1,240- $2,800 per capita less than the national per capita rate in
2002. Madera County had $3,176 per capita less than the national per capita rate in
2003. Two rural counties adjacent to the SJV, Mariposa and Tuolomne, received
significantly higher per capita rates of federal funding in 2003 than the SJV. In 2002,
the SJV received $1,559 less per capita in federal funds than the ARC region as a
whole. The SJV also received $2,860 per capita less than the Tennessee Valley
Authority region in 2003. Other federal funds data for 2000 also show that the per
capita rate of federal spending was lower in the SJV than in the generally depressed
Central Appalachian subregion.
In addition to examining socioeconomic conditions in the SJV, the report
provides analysis of water supply and quality issues especially those concerning
agriculture, air quality concerns, and rail and shipping issues.
This report will not be updated.
Contributing Staff
Areas of ExpertiseName DivisionTelephone
Regional Economic
Development,
Agriculture, FederalTadlock CowanRSI7-7600
Expenditures, and
Project Coordinator
Economic, Social, and
DemographicGerald MayerDSP7-7815
Information
Air QualityJames McCarthyRSI7-7225
Census of Agriculture
and Electronic DataCarol CanadaKSG7-7619
Resources
EducationDavid SmoleDSP7-0624
Atilla Akgun
Shelly Butts
Electronic PublishingLaura ComayERPO7-8734
Shelley Harlan
Katie Yancey
Food StampsJoe RichardsonDSP7-7325
Geographical
Information SystemVirginia MasonGMD7-8520
Cartography
Health Indicators Pamela SmithDSP7-7048
Highways Robert KirkRSI7-7769
Medicare Paulette MorganDSP7-7317
ObesityDonna PorterDSP7-7032
Teen BirthsCarmen Solomon-FearsKSG7-7306
Transportation
Infrastructure andJohn FrittelliRSI7-7033
Economic Development
Water Supply andBetsy CodyRSI7-7229
Infrastructure
Water QualityClaudia CopelandRSI7-7227
All Divisions are CRS except Geography and Maps, a Division of the Library of Congress.
Abbreviations: RSI = Resources, Science and Industry; DSP = Domestic Social Policy; KSG
= Knowledge Service Group; ERPO = Electronic Research Products; GMD = Geography
and Map Division
Contents
Chapter 1 — An Overview of the San Joaquin Valley.....................1
In troduction ..............................................1
Contemporary Research on the SJV...............................3
Demographic Issues and the Role of Farmworkers................4
Agricultural Immigration....................................7
Employment, Poverty, and Income............................9
Regional Approaches to Economic Development....................11
In troduction .............................................11
The Appalachian Regional Commission.......................12
Tennessee Valley Authority.................................14
Delta Regional Authority...................................15
The United States-Mexico Border Health Commission...........15
The Northern Great Plains Regional Authority (NGPRA).........16
Denali Commission.......................................17
Chapter 2 — The San Joaquin Valley and Appalachia: A
Socioeconomic Comparison....................................19
Overview ...............................................19
Socioeconomic Indicators in the SJV and Appalachia, 1980-2003.......25
County and Regional Population Characteristics.................25
Appalachia’s Demographic Structure.........................27
County and Regional Poverty Rates..........................47
Other Poverty Measures: Food Stamps, Public Assistance Income,
Health Insurance, and Medicaid..........................53
County and Regional Employment and Income Measures.........66
County and Regional Educational Measures....................93
Health and Disease Rates in the SJV.........................103
Age-Adjusted Death Rates from Cancers.....................106
Health and Disease Profile of Appalachia.....................107
Crimes and Crime Rates in the SJV and Appalachia.............127
Chapter 3 — Federal Direct Expenditures in the San Joaquin Valley
and the Appalachian Regional Commission Area...................133
Scope .................................................133
The Consolidated Federal Funds Report......................134
Comparing FY2002 Federal Expenditures in the San Joaquin, the
United States, and California...........................136
Federal Funding in the SJV and the TVA for FY2003...........138
Comparing Federal Funding in the Appalachian Regional
Commission Area to Federal Funding in the SJV...........139
Federal Funding in Appalachia and the San Joaquin: The
Economic Research Service Data.......................146
Geographical Information System Mapping of Federal Funds Data.....153
Chapter 4 — The Economic Structure of the San Joaquin Valley ..........163
In troduction ............................................163
Agriculture in the SJV........................................164
Agriculture and SJV Communities..........................166
Agricultural Land Conversion..............................167
SJV Farm Characteristics..................................168
Agricultural Labor.......................................170
Agriculture’s Future in the San Joaquin......................190
The Non-Agricultural Economy of the San Joaquin.................192
Overview ..............................................192
SJV County Employment Profiles...........................193
Appalachian State Employment Profiles......................210
Labor Force Characteristics in the San Joaquin.................210
Fresno Regional Jobs Initiative.............................221
The Health Care Industry as a Growth Sector for the SJV ............223
Chapter 5 — Selected Natural Resource and Environmental Issues
in the SJV..................................................244
Water Resources of the SJV...................................244
Water Supply Infrastructure................................245
Water Quality Issues in the SJV................................248
Overview ..............................................248
Irrigated Agriculture and Water Quality......................248
Actions to Address Impaired Waters.........................250
A TMDL Example.......................................252
Financial Assistance......................................253
Managing Manure at Concentrated Animal Feeding Operations........253
Funding Sources for CAFOs...............................254
Air Quality Issues in the SJV...................................256
Ozone .................................................256
Particulate Matter (PM10 and PM2.5).........................258
Federal Assistance.......................................259
Chapter 6 — Transportation Investment and Economic Development.......260
The Federal-Aid Highway System and the SJV.....................260
The Obligation of Federal-Aid Highway Funds in the SJV............262
The Relation Between Freight Infrastructure and Economic
Development ...........................................264
Supporting the Perishable Goods Delivery Network.............264
Warehouse and Distribution Employment.....................266
High Speed Rail and Economic Development......................269
APPENDIX A: Reports and Studies on the SJV: 1980-2005..............272
Water Resources Management and Geomorphology.................272
Water Quality...............................................274
Natural Resources: Ecology....................................275
Labor and Employment.......................................276
Poverty and Income..........................................276
Population and Demography...................................277
Economic Growth and Development.............................278
Education and Training.......................................279
Socioeconomic Surveys of Central Valley Residents................280
Agriculture in California and the San Joaquin/Central Valley.........280
State University-Stanislaus................................281
Public Finance..............................................283
Great Valley Center Publications................................283
APPENDIX B: Data Sources......................................286
APPENDIX C: San Joaquin Valley Governments and Institutes...........287
Public Policy Analysis Groups..................................288
APPENDIX D: Central Appalachian Counties As Defined by USDA’s
Economic Research Service....................................290
APPENDIX E: Counties of the Tennessee Valley Authority..............291
APPENDIX F: Federal Direct Expenditures and Obligations by Individual
Program and San Joaquin Valley County.........................292
List of Figures
Figure 1. The San Joaquin Valley of California..........................1
Figure 2. The Appalachian Regional Commission Area and its Distressed
Counties ....................................................24
Figure 3. Percent Change in Mexican-Born Population by County,
1990-2000 ..................................................39
Figure 4. Percent of Persons Below Poverty Level by County (2000)........48
Figure 5. Percent of Households Receiving Public Assistance by County
(2000) ......................................................60
Figure 6. Median Family Income By County...........................75
Figure 7. Percent of Persons with Education Less Than High School by
County (2000) ...............................................96
Figure 8. Percent of Persons with a Bachelors Degree or Advanced
Degree by County (2000).......................................97
Figure 9. Total Federal Assistance by County, FY2000..................153
Figure 10. Total Federal Assistance Per Capita, FY2000.................154
Figure 11. Federal Assistance per Capita for Agriculture and Natural
Resources by County, FY2000 .................................155
Figure 12. Federal Assistance Per Capita for Community Resources .......156
Figure 13. Federal Assistance Per Capita for Defense and Space by County,
FY2000 ...................................................157
Figure 14. Federally Owned Land in the SJV..........................158
Figure 15. Federal Assistance Per Capita for Human Resource by County,
FY2000 ...................................................159
Figure 16. Federal Assistance per Capita for Income Security by County,
FY2000 ...................................................160
Figure 17. Federal Assistance per Capita for National Functions by County,
FY2000 ...................................................161
Figure 18. Allocation of Federal Assistance by ERS Category in California
and the SJV, FY2000.........................................162
Figure 19. SJV Land Use/Land Cover...............................168
Figure 21. Irrigated Farm Acreage by County (2000)....................182
Figure 22. Irrigated Land in Acres by County (2002)....................183
Figure 23. Average Federal Farm Payments per Farm by County (2002)....185
Figure 24. Number of Migrant Workers on Farms with Hired Labor by
County, (2002)..............................................190
List of Tables
Table 1. Appalachian Regional Commission County Economic Fiscal
Status, 2004 .................................................22
Table 2. Population: United States, California, and Counties of the SJV,
1980-2003 ..................................................29
Table 3. Population Density: United States, California, and Counties
of the SJV, 1980-2003.........................................30
Table 4. Population: United States, Kentucky, Virginia, Tennessee, West
Virginia, and Central Appalachian Counties of the Appalachian
Regional Commission, 1980-2003................................31
Table 5. Population Projections: United States, California, and Counties
of the SJV, to 2010 and 2020....................................32
Table 6. Population Projections: United States, Kentucky, Virginia,
Tennessee, West Virginia, and Central Counties of the Appalachian
Regional Commission, to 2010 and 2020..........................33
Table 7. Estimated Percent of the Population That Moved During the
Previous Year: United States, California, and Metropolitan Statistical
Areas of the SJV, 1989-2004....................................34
Table 8. Estimates of Where Persons Who Moved During the Previous
Year Lived One Year Earlier: United States, California, and
Metropolitan Statistical Areas ofthe SJV, 1989-2004.................35
Table 9. Percent of the Population Foreign-Born: United States,
California, and Counties of the SJV, 1980-2003.....................36
Table 10. Percent of Population of Hispanic Origin: United States,
California, and the Counties of the SJV, 1980-2003..................37
Table 11. Percent of the Population Mexican-Born: United States,
California, and Counties of the SJV, 1980-2003.....................38
Table 12. Distribution of Population by Race: United States, California,
and the Counties of the SJV, 1980-2003...........................40
Table 13. Distribution of Population by Gender: United States, California,
and the Counties of the SJV, 1980-2003...........................43
Table 14. Distribution of Population by Age: United States, California,
and the Counties of the SJV, 1980-2003...........................45
Table 15. Portion of the Population Below Poverty: United States, California,
and Counties of the SJV, 1980-2003..............................50
Table 16. Appalachian Regional Commission Poverty Rates, 1980-2000.....51
Table 17. Portion of the Population Below Poverty: United States,
Kentucky, Virginia, Tennessee, West Virginia, and Central
Counties of the ARC, 1980-2003.................................53
Table 18. Percent of Households Receiving Food Stamps: United States,
California, and the MSAs of the SJV, 1988-2003....................56
Counties of the SJV, 1980-2003.................................58
Table 20. Public Assistance Income: United States, Kentucky, Virginia,
Tennessee, West Virginia,and Central Counties of the ARC,
1980-2003 ..................................................59
Table 21. Percent of Population Without Health Insurance: United
States, California, and the MSAs of the SJV, 1988-2003..............63
Table 22. Percent of Population Without Health Insurance: United
States, Kentucky, Virginia, Tennessee, West Virginia, and Central
Counties of the ARC, 1988-2003.................................64
Table 23. Percent of the Population Enrolled in Medicaid: United States,
California, and MSAs of the SJV, 1988-2003.......................65
Table 24. Percent of the Population Enrolled in Medicaid: United States,
Kentucky, Virginia, Tennessee, West Virginia, and Central Counties
of the ARC, 1988-2003........................................66
Table 25. Employment in the United States, California,and the Counties
of the SJV, 1980-2003.........................................68
Table 26. Employment in the United States, Kentucky, Virginia, Tennessee,
West Virginia, and Central Counties of the ARC, 1980-2003..........69
Table 27. Labor Force Participation Rate: United States, California,
and the Counties of the SJV, 1980-2003...........................70
Table 28. Labor Force Participation Rate: United States, Kentucky,
Virginia, Tennessee, West Virginia, and Central Counties of the ARC,
1980-2003 ..................................................71
Table 29. Civilian Unemployment Rates: United States, California, and the
Counties of the SJV, 1980-2003.................................72
Table 30. Civilian Unemployment Rates: United States, Kentucky,
Virginia, Tennessee, West Virginia, and Central Counties of the ARC,
1980-2003 ..................................................73
Table 31. Per Capita Income: United States, California,and the Counties
of the SJV, 1980-2003.........................................79
Table 32. Per Capita Income: United States, Kentucky, Virginia, Tennessee,
West Virginia, and Central Counties of theARC, 1980-2003...........80
Table 33. Median Family Income: United States, California, and the Counties
of the SJV, 1980-2003.........................................81
Table 34. Median Family Income: United States, Kentucky, Virginia,
Tennessee, West Virginia, and Central Counties of the ARC, 1980-2003.82
Table 35. Average Family Income: United States, California,and the Counties
of the SJV, 1980-2003.........................................83
Table 36. Average Family Income: United States, Kentucky, Virginia,
Tennessee, West Virginia, and Central Counties of the Appalachian
Regional Commission (ARC), 1980-2003..........................84
Table 37. Wage and Salary Income: United States, California, and the
Counties of the SJV, 1980-2003.................................85
Table 38. Wage and Salary Income: United States, Kentucky, Virginia,
Tennessee, West Virginia,and Central Counties of the ARC, 1980-2003..86
Table 39. Interest, Dividend, or Net Rental Income: United States,
California,and the Counties of the SJV, 1980-2003..................87
Table 40. Retirement Income: United States, California, and the Counties
of the SJV, 1980-2003.........................................88
Table 41. Social Security Income: United States, California, and the Counties
of the SJV, 1980-2003.........................................89
Tennessee, West Virginia, and Central Counties of the ARC,
1980-2003 ..................................................90
Table 43. Supplemental Security Income (SSI): United States, California,
and the Counties of the SJV, 2000-2003...........................91
Table 44. Supplemental Security Income (SSI): United States, Kentucky,
Virginia, Tennessee, West Virginia, and Central Counties of the ARC,
2000-2003 ..................................................92
Table 45. Educational Attainment: United States, California, and Counties
of the SJV, 1990-2003.........................................94
Table 46. Educational Attainment: United States, Kentucky, Virginia,
Tennessee, West Virginia, and Central Counties of the ARC, 1990-2003.98
Table 47. Per Pupil Amounts for Current Spending of Public Elementary
and Secondary School Systems: United States, California, and Counties
of the SJV,1992-1993 and 2002-2003.............................99
Table 48. Percent of Persons Who Speak a Language Other than English at
Home: United States, California, and Counties ofthe SJV, 1980-2003..100
Table 49. Per Pupil Amounts for Current Spending of Public Elementary
and Secondary School Systems: United States,Kentucky, Tennessee,
Virginia, West Virginia, and CentralCounties of the ARC, 1992-1993
and 2002-2003..............................................102
Table 50. Educational Attainment of Persons in the Labor Force Who
Moved During the Previous Year: United States, California, and MSAs
of the SJV, 1989-2004........................................103
Table 51. Total Active Doctors Per 1,000 Population: United States,
California, and the Counties of the SJV, 1995-2001.................108
Table 52. Doctors Engaged in Patient Care Per 1,000 Population: United
States, California, and the Counties of the SJV, 1995-2001...........109
Table 53. Total Active Doctors Per 1,000 Population: United States,
Kentucky, Tennessee, Virginia, West Virginia, and the Central
Counties of the ARC, 1995-2001................................110
Table 54. Doctors Engaged in Patient Care Per 1,000 Population: United
States, Kentucky, Tennessee, Virginia, West Virginia, and the Central
Counties of the Appalachian Regional Commission (ARC), 1995-2001.111
Table 55. Teen Birth Rates: United States, California, and Counties
of the SJV, 1980-2003........................................112
Table 56. Infant Mortality Rates: United States, California, and Counties
of the SJV, 1980-2002........................................113
Table 57. Age-Adjusted Prevalence of Obesity and Healthy Weight: United
States, California, and Counties of the SJV, 1992-2002..............114
Table 58. Age-Adjusted Death Rates from Heart Disease: United States,
California, and Counties of the SJV, 1980-2002....................116
Table 59. Cancer Deaths: Age-Adjusted Death Rates from Cancers: United
States, California, and Counties of the SJV, 1980-2002..............117
Table 60. Age-Adjusted Death Rates from Stroke: United States,
California, and Counties of the SJV, 1980-2002....................118
Table 61. Age-Adjusted Death Rates from All Causes of Death: United
States, California, and Counties of the SJV, 1980-2002..............119
Table 62. Age-Adjusted Prevalence of Diagnosed Diabetes in Adults: United
States, California, and Counties of the SJV, 2000-2003..............120
Mellitus: United States, California, and Counties of the SJV,
1980-2002 .................................................121
Table 64. Percent of the Population Covered by Medicare: United States,
California, and MSAs of the SJV, 1988-2003......................123
Table 65. Percent of the Population Covered by Medicare: United States,
Kentucky, Virginia, Tennessee, West Virginia, and Central Counties
of the ARC, 1988-2003.......................................124
Table 66. Per Capita Monthly Medicare Expenditures for Aged
Beneficiaries in Traditional Medicare: United States, California, and
Counties of the SJV, 1990-2003................................125
Table 67. Per Capita Monthly Medicare Expenditures for Aged
Beneficiaries in Traditional Medicare: United States, Kentucky,
Virginia, Tennessee, West Virginia, and Central Counties ofthe ARC,
1990-2003 .................................................126
Table 68. Number of Crimes and Crime Rate: United States,
California, and Counties of the SJV, 1980-2003....................128
Table 69. Number of Crimes and Crime Rate: United States, Kentucky,
Virginia, Tennessee, West Virginia, and Central Counties of the ARC,
1980-2003 .................................................131
Table 70. Federal Direct Expenditures and Obligations in the SJV, FY2002.142
Table 71. Federal Direct Expenditures and Obligations in the Appalachian
Regional Commission, FY2002.................................143
Table 72. Federal Direct Expenditures and Obligations in the SJV, FY2003.144
Table 73. Federal Direct Expenditures and Obligations in the Tennessee
Valley Authority Area FY2003.................................145
Table 74. Per Capita Federal Funds By ERS Function for the SJV, FY2000..151
Table 75. Per Capita Federal Funds for Appalachia by ERS Function and
Region, FY2000.............................................152
Table 76. Farms by Size, 2002.....................................173
Table 77. Market Value of Agricultural Product Sales, 2002 ..............174
Table 78. Leading Commodities for Gross Value of Agricultural Production
by SJV and Adjacent Counties, 2003.............................176
Table 79. SJV Commodity Rank and Leading Counties by Gross Value
of Agricultural Production, 2003................................178
Table 80. SJV Irrigated Land, 2002.................................181
Table 81. SJV Federal Farm Payments, 2002..........................184
Table 82. SJV Hired Farm Labor, 2002..............................186
Table 83. SJV Farm Workers by Days Worked — Less than 150 days, 2002.187
Table 84. SJV Farm Workers by Days Worked — 150 Days or More, 2002..188
Table 85. SJV Migrant Farm Labor Valley, 2002.......................189
Table 86. Annual Employment and Average Annual Pay of the 20
Largest Industries, United States, 1990-2003......................198
Table 87. Annual Employment and Pay of the 20 Largest Industries,
California, 1990-2003........................................199
Table 88. Annual Employment and Pay of the 20 Largest Industries, Fresno
County, 1990-2003...........................................200
Table 89. Annual Employment and Pay of the 20 Largest Industries, Kern
County, 1990-2003...........................................201
Table 90. Annual Employment and Pay of the 20 Largest Industries, Kings
County, 1990-2003...........................................202
County, 1990-2003...........................................203
Table 92. Annual Employment and Pay of the 20 Largest Industries, Merced
County, 1990-2003...........................................204
Table 93. Annual Employment and Pay of the 20 Largest Industries, San
Joaquin County, 1990-2003....................................205
Table 94. Annual Employment and Pay of the 20 Largest Industries,
Stanislaus County, 1990-2003..................................206
Table 95. Annual Employment and Pay of the 20 Largest Industries, Tulare
County, 1990-2003...........................................207
Table 96. Annual Employment and Pay of the 20 Largest Industries,
Mariposa County, 1990-2003..................................208
Table 97. Annual Employment and Pay of the 20 Largest Industries,
Tuolumne County, 1990-2003..................................209
Table 98. Percent of Workers Who Usually Worked Full-Timein the
Previous Year: United States, California, and the Counties of the
SJV, 1980-2003.................................................211
Table 99. Distribution of Employed Persons by the Number of Weeks
Worked in the Previous Year: United States, California, and the
Counties of the SJV, 1980-2003................................213
Table 100. Class of Worker: United States, California,and the Counties
of the SJV, 1980-2003........................................216
Table 101. Means of Transportation to Work: United States, California,
and Counties of the SJV, 1980-2003.............................219
Table 102. Vehicles Available Per Household: United States, California,
and Counties of the SJV, 1990-2003.............................220
Table 103. Ambulatory Health Care Services, 2002.....................225
Table 104. Bakersfield MSA Occupational Employment (November 2003)
and Wage (2004 - 3rd Quarter) Data Occupational Employment
Statistics (OES) Survey Results ................................228
Table 105. Fresno MSA Occupational Employment (November 2003) and
Wage (2004 - 3rd Quarter) Data Occupational Employment Statistics
(OES) Survey Results ........................................231
Table 106. Modesto MSA Occupational Employment (November 2003) and
Wage (2004 - 3rd Quarter) Data Occupational Employment Statistics
(OES) Survey Results ........................................234
Table 107. Stockton-Lodi MSA Occupational Employment
(November 2003) and Wage (2004 - 3rd Quarter) Data
Occupational Employment Statistics (OES) Survey Results ..........237
Table 108. Visalia-Tulare-Porterville MSA Occupational Employment
(November 2003) and Wage (2004 - 3rd Quarter) Data
Occupational Employment Statistics (OES) Survey Results ..........240
Table 109. Medical Instrument Supply/Equipment, 2002................243
Table 110. Federal-Aid Highway Obligations: SJV — California — United
States .....................................................263
Table 111. Federal Direct Expenditures and Obligations for Fresno County,
FY2003 ...................................................292
Table 112. Federal Direct Expenditures and Obligations for Kern County,
FY2003 ...................................................301
Table 113. Federal Direct Expenditures and Obligations for Kings County,
FY2003 ...................................................308
County, FY2003.............................................313
Table 115. Federal Direct Expenditures and Obligations for Merced
County, FY2003.............................................319
Table 116. Federal Direct Expenditures and Obligations for San Joaquin
County, FY2003.............................................325
Table 117. Federal Direct Expenditures and Obligations for Stanislaus
County, FY2003.............................................332
Table 118. Federal Direct Expenditures and Obligations for Tulare County,
FY2003 ...................................................338
Table 119. Federal Direct Expenditures and Obligations for Mariposa
County, FY2003.............................................345
Table 120. Federal Direct Expenditures and Obligations for Tuolumne
County, FY2003.............................................349
California’s San Joaquin Valley: A Region in
Transition
Chapter 1 — An Overview of the San Joaquin Valley
Introduction. The San Joaquin Valley (SJV), an eight-county region
extending 250 miles from Stockton in the north to Bakersfield in the south (Figure
1), is a rapidly growing area that is also a severely economically depressed region
suffering from high poverty, unemployment, and other adverse social conditions.
The 27,280 square mile SJV, part of California’s Central Valley, is also home to 5
of the 10 most agriculturally productive counties in the United States, as measured
by value of total annual sales. In addition to its socioeconomic condition, the SJV
region faces significant environmental and natural resource challenges. A substantial
body of empirical research over the past 20 years has explored the socioeconomic and
environmental issues facing the SJV, with particular attention to social welfare,
agriculture, air, and water quality issues.
Figure 1. The San Joaquin Valley of California
This report documents the basis of current socioeconomic and environmental
concerns in the SJV and assesses the role of federal assistance to the cities, counties,
residents, and businesses of the SJV. The report also explores the extent to which
the SJV shares similarities with and differs from other economically depressed areas
in the United States. It reviews the role of federal assistance in the SJV relative to the
role of federal assistance in Appalachia, specifically federal funding to the
Appalachian Regional Commission (ARC) area. The ARC is a federal agency
created in 1965. Its jurisdiction is a 410-county region spread across 13 states from
Alabama to New York.
The report’s major analytical focus is the 8 counties that compose the SJV:
Fresno, Kern, Kings, Madera, Merced, San Joaquin, Stanislaus, and Tulare.
Particular data in the report also focus on the SJV’s Metropolitan Statistical Areas
(MSAs): Stockton-Lodi, Bakersfield, Fresno, Madera, Modesto, and Visalia-
Porterville. A limited, but more detailed comparison is also developed with the
Central Appalachian subregion, a 68-county area in Tennessee, Virginia, Kentucky,
and West Virginia delimited by the USDA’s Economic Research Service and based
on Bogue and Beale’s Economic Areas of the United States.1 Two rural counties
adjacent to the SJV, Mariposa and Tuolumne, are also examined in the report to
provide a further comparison and contrast to the socioeconomic characteristics of the
SJV.
Data discussed in the text occasionally make reference to the Greater Central
Valley of which the SJV composes the southern portion. The Great Valley Center
in Modesto, a regional research institute, divides the Great Central Valley into 3
subregions: the North Valley encompasses 7 counties (Shasta, Tehama, Glenn,
Colusa, Butte, Yuba, and Sutter); the Sacramento Region has 4 counties (Yolo,
Sacramento, Place, and El Dorado); and the San Joaquin Valley. The North Valley
is less urbanized and less developed. The Sacramento Region has had the most
extensive development through its linkages to San Francisco.2
How federal assistance in the SJV and Appalachia is distributed among various
categories and their per capita rates of expenditure are also a focus of the report. A
key consideration is how federal assistance is currently distributed in the SJV and
how it differs from current federal expenditures in Appalachia.
The geography of global economic activity in 2005 is, in significant ways, quite
different from that of 25 years ago. An increasingly complex set of relationships
between local and global scales of economic activity has implications for SJV labor
markets, household consumption, the formation of growth coalitions, technological
innovation and growth, residential and transportation patterns, and human capital
issues. Federal assistance has been important in each of these policy issues in the
past and is likely continue as an important factor in future development and change
in the SJV. Concern with the challenges facing the SJV has led to efforts there to
1 Bogue, Donald J. and Calvin Beale. Economic Areas of the United States. New York:
Free Press. 1961.
2 Great Valley Center. The State of the Great Central Valley of California: Assessing the
Region Via Indicators. Modesto, California. July, 1999.
begin considering a wide range of issues from a regional perspective. The SJV now
has federally recognized regional status: a federal interagency task force on the
economic development of the Central SJV was created in 2000 by Executive Order.3
This chapter reviews the history of regional approaches to socioeconomic
development and discusses the federal role in the creation and support of specific
regional development commissions: the Tennessee Valley Authority (TVA), the
ARC, the Delta Regional Authority, the U.S.-Mexico Border Health Commission,
the Denali Commission, and the Northern Great Plains Regional Authority. Each of
these federally authorized commissions targeted federal funds to development issues
specific to their geographic regions.
This section selectively surveys contemporary socioeconomic research on the
SJV, drawing on an extensive bibliography of research in Appendix A.
Contemporary Research on the SJV
In his 1987 Carl Sauer Memorial Lecture, Berkeley geographer James J. Parsons
argued that there were at least three categorical ways of approaching the SJV.4 First,
and most common, was to ignore the SJV or to view it as irrelevant to the largely
urbanized character of the state. He noted that in a mid-1980s publication listing the
100 best places in California the refurbished Capitol building in Sacramento was the
only attraction from the entire Central Valley to make the list. A second way of
considering the SJV was as a symbol “of capitalism gone rampant, of all that is bad
about profit-based, large-scale, labor intensive irrigated agriculture.” Here, Parsons
referred to Frank Norris’s Octopus, a story of the role of the railroad in what is today,
Kings County. John Steinbeck’s The Grapes of Wrath and Carey McWilliams
Factories in the Field also represented a way of seeing the Valley focused largely on
the social and human effects of agricultural production in the 1930s. In a similar
vein, news and stories of contemporary industrial agriculture in the Valley reinforce
this particular dimension of the SJV. For Parsons, a noted cultural geographer, a
third way of looking at the Valley was actually to see and appreciate the Valley as the
3 Executive Order 13173: Interagency Task Force on the Economic Development of the
Central SJV, October 25, 2000. Executive Order 13359, October 4, 2004, amended the
original Order to designate the Secretary of Housing and Urban Development as the Chair
of the task force.
4 Parsons, James J.. A Geographer Looks at the SJV. 1987 Carl Sauer Memorial Lecture.
[Http://geogr aphy.berkeley.edu/Pr oj ectsResources/]
Publications/Parsons_SauerLect.html. While agriculture and the SJV are practically
synonymous, oil production was also an important factor in the development of the SJV.th
At the turn of the 20 century, the Kern River Field was producing 70% of California’s oil,
and California was the country’s leading oil producer. Today, Kern County produces 10%
of the United States oil, making it the leading oil producing county in the United States. See
Greater Bakersfield Chamber of Commerce, Kern County Petroleum. January 2002.
[http://www.bakersfieldchamber.org/ community.asp].
result of a consciously built and cultivated cultural landscape that has made
California agriculture a modern “wonder of the world.”5
Substantial research over the past decade has focused on the SJV in an effort
to describe, analyze, and plan for the challenges facing the region. Population growth
and change, global changes in the organization of agriculture, pressures on natural
resources stemming from population growth and agricultural production, human
resource concerns, environmental issues, employment, growth management concerns,
housing, and transportation represent some of the policy issues on which researchers
have focused particular attention. The general economic growth and development
in the Central Valley as a whole between 1999-2004 has not significantly changed
much of the basic economic distress of the region. Even with an increase in income
over that period, the Central Valley region may have lost ground because incomes in
the state grew faster than they did in the Valley. Between 1997 and 2002, Central
Valley’s per capita income grew by 19% while the state’s per capita income rose
25%.6 An overview of some of the most recent research and key findings is presented
below.
The SJV Region at a Glance — 2000Demographic Issues and the
Role of Farmworkers. Although
Counties: Fresno, Kern, Kings, Madera,agriculture is perhaps the most
Merced, San Joaquin, Stanislaus, andsignificant socioeconomic feature of the
TulareSJV today, the SJV is undergoing
Total area: 27,280 square miles; 17% ofchanges that suggest a more diversified
the land area of Californiaeconomic base over the next 20 years
Total population: 3.3 million; 10% ofwill be necessary to support the region’s
California’s populationgrowth. The Bureau of the Census, for
Ethnic composition: 53% white, 34%example, projects the population of the
Hispanic, 8% Asian/Pacific Islander, 4%San Joaquin to grow by 39% from 2003
African American, and 1% Nativeto 2020, with some counties (e.g.,
AmericanMerced and San Joaquin) projected to
Age distribution: 0-9 years old, 18%;
10-19 years old, 16%; 20-44 years old,grow by more than 55%, meaning that
Adult educational attainment: 66% arelive in the SJV by 2020. In contrast,
high school graduates; 14% have
bachelor’s degree
Source: Great Valley Center. The Economic
Future of the SJV: Growing a Prosperous
Economy that Benefits People and Place.
2000
5 Parsons, 1987. Op.Cit., p. 4.
6 Great Valley Center. Assessing the Region Via Indicators: The Economy, 1994-2004.
January. Modesto, California. 2005.
7 Projections of U.S. population growth are from the U.S. Department of Commerce, Bureau
of the Census, U.S. Interim Projections by Age, Sex, Race, and Hispanic Origin, available
(continued...)
the state is projected to grow approximately 24% over that period, with the United
States growing about 15%. The SJV currently attracts a large proportion of lower-
skilled workers from across the state as well as from significant international
migration. At the same time, the South SJV is also losing its higher-skilled workers.8
Between 1995 and 2000, these counties had a net migration increase in the number
of adults without high school diplomas and a net decrease of college graduates.9
Along with the Sacramento metro region and the Riverside-San Bernardino
region, the SJV was among the three fastest growing regions in the state, accounting
for nearly 4 of every 10 new residents of the state during the 1990s.10 While natural
increase was the largest component of population change in the Valley during the
1990s, international migration was also a significant source of the San Joaquin’s
growth, as was migration from coastal areas where housing costs rose significantly
during the decade. Between 1995 and 2000, two of every three international
migrants to the SJV were Latino.11 During that same period, the South SJV
experienced net domestic migration losses for every group except African
Americans. More than half of domestic out-migrants were white.
The high rate of Latino immigration presents several issues. Latino immigrants
tend to: be younger than the state average, have lower high school graduation rates,
lack fluency in English, be disproportionately low-skilled, have higher birth rates and
related family sizes, and higher rates of family poverty.12 In some SJV communities,
as many as two-thirds of the residents have not finished high school and half of the
7 (...continued)
at [http://www.census.gov/population/www/projections/popproj.html]. Projections for
California are from the State of California, Department of Finance, Population Projections
by Race/Ethnicity for California and Its Counties 2000-2050, Sacramento, California, May
proj ections/p1.htm] .
8 In a study of the Central Valley’s migration patterns, the Southern SJV (Madera, Fresno,
Kings, Kern, and Tulare counties) was distinguished from the Northern SJV (San Joaquin,
Stanislaus, and Merced counties). Johnson, Hans P. and Hayes, Joseph M. The Central
Valley at a Crossroads: Migration and Its Implications. Report. Public Policy Institute of
California, San Francisco, CA. November. 2004.
[http://www.ppic.org/ content/pubs/R_1104HJ R.pdf]
9 Ibid., p.47.
10 Johnson, Hans P. A State of Diversity: Demographic Trends in California’s Regions.
California Counts: Population trends and Profiles, Vol.3, No.5, May. Report. Public Policy
Institute of California, San Francisco, CA. November. 2002.
[http://www.ppic.org/ cont ent/pubs/CC_502HJ CC.pdf]
11 Ibid.
12 Reed, Deborah, Laura E. Hill, Christopher Jepsen, and Hans P. Johnson. 2005.
Educational Progress Across Immigrant Generations in California. Public Policy Institute
of California, San Francisco. September. [http://www.ppic.org/content/
pubs/R_905DRR.pdf]; Johnson, Hans P. 2001. “The Demography of California
Immigrants.” Paper based on testimony before the Little Hoover Commission Hearing on
Immigrant Integration, March 21, 2001. Public Policy Institute of California, San Francisco.
March.
households with children under 18 have incomes below the poverty line. Low-skilled,
part-time, seasonal employment is often the norm for many of these immigrants.
Labor intensive agricultural production in the fruit, vegetable, and horticultural
sectors is often the most viable source of employment. As hired farm labor jobs
decline, educating and training the immigrant community for higher-wage jobs will
present the SJV with considerable challenge.13
Predicting future population is a complicated exercise. Domestic and
international immigration, racial and ethnic composition of the population, and birth
rates of different social groups are a complex set of variables that influence
population growth rates. Birth rates are also influenced by personal characteristics
such as educational attainment, marital status, and income level. As educational
attainment and income rise, there tends to be a decrease in average birth rate. Third
and fourth generation immigrants, for example, tend to have lower birth rates on
average than earlier generations. A demographic analysis by the Public Policy
Institute of California concluded that, while second and third-generation Californians
do have lower birth rates than their earlier relatives, the declines are the result of
changing educational levels, income, and other personal characteristics.14 These
personal characteristics, rather than the particular immigrant generation, had
significant direct effects on birth rates.
Lower costs in the SJV compared to the state have attracted businesses to the
region over the past decade. Many businesses are attracted by the low-cost labor and
the relatively low land prices. Between 1990 and 2000, however, overall job growth
still lagged behind population growth in the SJV.15 Unemployment has been a
persistent problem in the Valley, typically at a rate nearly twice the national average
and significantly higher than the state average. In 2000, the SJV had an
unemployment rate of nearly 12%, while the U.S. and California averages were 5.8%
and 7% respectively. Individual counties, (e.g., Madera and Merced), had even
higher unemployment rates. Since 1980, the unemployment rate for the Valley has
ranged from 9.5%-12% (See Table 29, Chapter 2). Agriculture remains the major
economic engine of the regional economy. The agricultural sector offers much
seasonal employment, but pays relatively low average annual wages. For example,
in Parlier, a small community in Fresno County, 29% of the 4,511 labor force was
employed in agriculture in 2000. Median family income there was $24,300 and 33%
of the families in the community fell below the poverty line.16
13 Between 1992 and 2002, hired farm labor in the SJV declined 35.6%, from 377,853 jobs
in 1992 to 243,079 jobs in 2002. National Agricultural Statistics Service, U.S. Census of
Agriculture 1992, 1997, 2002.
14 Hill, Laura E. and Hans P. Johnson. Understanding the Future of Californians’
Fertility: The Role of Immigrants. Public Policy Institute of California, San Francisco, CA.
April, 2002. [http://www.ppic.org/content/pubs/R_402LHR.pdf]
15 Johnson, Hans P. 2002. Op.Cit, p.8
16 Farm Foundation. Immigrants Change the Face of Rural America. Issue Report, January,
The proportion of the population living in poverty in the SJV is high, nearly
22% in 2002.17 Rural poverty in particular in California may be re-created through
the expansion of low-wage, immigrant-intensive agriculture. The globalization of
agricultural production, particularly as it is affected by the North American Free
Trade Agreement (NAFTA) is considered by many to be a significant factor in the
structure of California agriculture. Poverty in rural Mexico, the demand for low-
wage labor in California’s fruit, vegetable, and horticultural sectors, and the existence
of family and village networks that grew from a history of migration to the United
States help sustain a stream of immigration to the fields of the SJV. This
combination of “push,” “pull,” and “network” effects appears to make both
immigration and the expansion of farm jobs on which immigrants depend
self-perpetuating.18
Agricultural Immigration. Immigration plays a significant role in the
demographic characteristics of the SJV and California, and this is likely to continue.
Since 1995, the Central Valley as a whole has received substantially more migrants
from other parts of California than it sends to the rest of California. The counties of
Madera, Fresno, Kings, Tulare, and Kern have received the most international19
migrants of any area of the Central Valley. Economically dominated by industrial
agriculture, these counties also are characterized by very high rates of poverty among
immigrants. This presents challenges to the region’s social services, especially for
health care and education providers. The growth in immigration in rural California
is generally regarded as a phenomenon directly related to the changing structure of
agriculture.20 Greater integration of farms under the control of agribusiness, the
increased use of immigrant farm labor hired through contractors, and a continuing
shift from owner-operated farms to hired-labor corporations characterize21
contemporary agricultural production in the SJV.
Because the economic structure of the rural sector in general is not well
diversified, newly arrived immigrants find very few opportunities outside the
agricultural sector. Immigrants often crowd into rural colonias — incorporated
towns resembling overgrown labor camps — whose population during the harvest
season often surges to several times their normal size. In 1997, California rural
colonias comprised 7 of the 20 U.S. cities in which the highest percentage of people
17 Reed, Deborah . California Counts: Recent Trends in Income and Poverty. Public Policy
Institute of California, San Francisco, CA. February, 2004.
[ h t t p : / / www.ppi c.or g/ cont ent / pubs/ CC_204DRCC.pdf ]
18 Ibid.
19 Johnson, Hans and Joseph Hayes. The Central Valley at a Crossroads: Migration and Its
Implications. Public Policy Institute. San Francisco. November 2004.
20 See Krissman, Fred. “Cycles of poverty in rural California towns: Comparing McFarland
and Farmersville in the southern SJV. Paper presented at the conference, Immigration and
the Changing Face of Rural California. Asilomar, California, June12-14, 1995; Palerm,
Juan V. Farm Labor Needs and Farm Workers in California, 1970-1989. California
Agricultural Studies Report #91-2. University of California-Santa Barbara. 1991.
21 These changes in the structure of agriculture are explored in greater detail in the section
of this report concerning the SJV’s economic structure.
in concentrated poverty were foreign-born.22 Unlike the small-scale farming
operations of the Midwest, agriculture in California has long been dominated by large
operations relying on a mobile labor force. Agricultural production in the SJV is,
accordingly, at the center of changes in the structure of agriculture; continuing
immigration into the SJV reflects these changing patterns.
Since the early 1990s, there has been a shift away from migrant labor towards
resident-based labor. Unlike many other farming regions of the United States, the
extended growing season in the SJV permits many workers the opportunity for year-
round farm labor. While harvesting may be seasonal, the great variety of crops in the
region makes it possible for farm workers to reside in one area and find work for
much of the year. A report on farm workers in Kern County, cites a 1995 Kern
County Consolidated Plan that counted 10,240 resident farm workers and 19,570
migrant workers during peak season.23 This study noted that the number of
permanent farm workers had steadily increased and is expected to continue. Some
permanent residents with established networks may move out of farm labor and into
industries such as food packing, processing, transportation, or retail trade. Other
residents may provide food or housing services to newly arrived farm workers. The
young, Hispanic migrant workers, especially those without established networks in
the communities, continue to meet much of the demand for low-skilled labor
intensive agriculture.24 If present trends continue, the newly arrived will become
residents and move out of farm labor to provide opportunities for yet another wave
of agricultural immigrants. For the communities where many farm workers reside,
however, low farmworker earnings limit the potential for significant economic
growth.
Because agriculture in the SJV is so reliant on low-wage, low-skilled farm labor,
and because low-wage, low-skilled labor is attracted to the SJV for employment in
agriculture, some observers believe that the region could be caught in a vicious
22 Taylor, J. Edward, Philip L. Martin, Michael Fix. Poverty Amid Prosperity: Immigration
and the Changing Face of Rural California. Urban Institute Press, Washington, D.C. 1997.
23 Housing Assistance Council. Taking Stock: Rural People, Poverty, and Housing at the
Turn of the 21st Century. December 2002.
24 Beginning in the 1990s, many migrants to Kern County came from areas of Mexico not
traditionally sources of agricultural labor. The Mixtecs, an indigenous group from Oaxaca,
with a distinctive language and culture, are recent settlers. They, along with migrants from
Central America, do not have the support networks that traditional Mexican immigrants
have. Housing Assistance Council. 2002. Op. Cit. According to the 2001-2002 National
Agricultural Workers Survey, Mexico-born crop workers were from almost every state of
their native country. The largest share (46%) were from the traditional sending states of west
central Mexico: Guanajuato, Jalisco, and Michoacan. However, an increasing share were
from non-traditional states. The share from the southern part of Mexico, comprising the
states of Guerrero, Oaxaca, Chiapas, Puebla, Morelos and Veracruz, doubled from nine
percent in 1993-1994 to 19% in 2001-2002. See U.S. Department of Labor, National
Agricultural Workers Survey 2001 - 2002 A Demographic and Employment Profile of
United States Farm Workers. March, 2005. [http://www.doleta.gov/
agworker/report9/toc.cfm]
cycle.25 As long as agriculture dominates the economies of the small towns in the
SJV, farm labor will continue to regard the area as an employment destination. This
can encourage the expansion of agriculture and, with it, the expansion of a low-wage,
low-skilled workforce. As discussed below, there are countervailing forces on an
ever-expanding agriculture. These forces include an increasing substitution of labor
by technology as well as longer standing pressures on smaller, less efficient farming
operations. Still, the many farm workers who immigrate from Mexico to the SJV are
seeking seasonal, minimum wage agricultural jobs. The concern of some observers
is that as poor, immigrant farmworkers move to the SJV, as well as other
agriculturally significant areas, rural poverty may be re-created. Rather than
agriculture being a temporary employment stop for newly arrived immigrants before
moving on to better paying jobs, the rural farmworkers may have no opportunities
beyond low-paying agricultural work. In part, this may occur because there are so
few employment alternatives and the farmworkers themselves are generally poorly
prepared for jobs requiring a more educated employee.
Migrant and resident farmworkers comprise distinct populations whose needs
differ. Migrant workers without networks, at least those studied in the Kern County
case, experience the worst employment, job security, and housing conditions. Farm
workers and recent immigrants tend to live in relative isolation from the mainstream
and middle-class Hispanic population in the county. Consistent with historical
socioeconomic class processes, the county’s Hispanic population that has acquired
some economic success and increased English fluency begins to identify less with
newly arrived immigrants.26
A second important distinction within the farmworker population is that of
farmworker families and single men living by themselves. The case study of Kern
County farm workers pointed to an important transition in the SJV from single
workers remitting wages back to their families in Mexico to farm labor families
moving and residing together in the SJV.
Employment, Poverty, and Income. In a study of the labor markets in
Fresno, Madera, and Tulare Counties, the Fresno Bee examined changes in 600
occupations from the third quarter of 2002 to the first quarter of 2004.27 Its review
found that, in a region dominated by low- wage farm and service-related jobs, the
SJV lagged behind the rest of the state in average job earnings. Population growth,
however, spurred job growth in construction, medical doctors, teachers, and nurses.
Of the 10 occupations in Fresno and Madera counties with the most workers, only 2
— nurses and elementary school teachers — have average wages above $29,000, a
threshold set by the Regional Jobs Initiative.28 In Fresno and Madera counties,
25 Taylor, J. Edward, Philip L. Martin, Michael Fix. 1997. Op. Cit.
26 Housing Assistance Council. 2002, Op. Cit., p.77.
27 Schultz, E.J. “What people earn.” Fresno Bee. November 7, 2004.
28 The Fresno Regional Jobs Initiative (RJI), formed in 2001, is working to create 30,000
jobs in the Fresno Metropolitan Statistical Area by 2009 paying at least $29,000 per year.
The RJI is pursuing an “industrial cluster” strategy based on 8 clusters that build on existing
(continued...)
farmworkers were the largest employment category (20,000 workers) followed by
office clerks (10,000 workers) in 2003. Farmworker jobs, however, are declining.
In 1996, the Fresno Bee reported that the farm industry had a monthly average of
72,800 employees in Fresno and Madera counties, accounting for about 21% of the
work force. In 2003, it reported the monthly farm employment average was 53,800,
or 15% of the work force.
The proportion of the population living in poverty in the SJV is high, nearly
22% in 2002.29 This compares to a rate of approximately 13% for California. The
SJV also had the highest rate of poverty among eight geographic regions in
California.30 During the past three decades, increases in female employment, female-
headed families, immigration, and economic changes that have produced greater
gains for college-educated workers compared to those with a high school diploma
have been especially influential in family income changes.31 For the state as a
whole, poverty was much lower in 2002 than in 1992, and the income levels of low-
income families showed more growth during that decade than did the income levels
of high-income families. These gains in poverty reduction over the past decade,
however, do not overcome the longer term growth in poverty and income inequality
in the state. Poverty and income inequality were higher in California in 2002 than
in 1969.32
Fresno, the largest metropolitan area in the region, has taken steps to begin
changing its economic structure for the future. To reduce persistent unemployment,
the Fresno Regional Jobs Initiative (RJI) aims to create 30,000 net new jobs that pay
at least $30,000 per year. In 2002, the three leading sectors of employment in the
SJV were government (260,000 jobs), agriculture (225,000 jobs), and health services
(85,000 jobs). Manufacturing, especially in California’s smaller metropolitan areas,
however, is also important to the region’s economic health.33 Manufacturing is an
28 (...continued)
and emerging economic sectors in the region.
29 Reed, Deborah . California Counts: Recent Trends in Income and Poverty. Public Policy
Institute of California, San Francisco, CA. February, 2004. The poverty rate is measured
as the share of people who live in families with income at or below the official federal
threshold. For example, in 2000, a family with two adults and two children was considered
poor if its annual income was below $17,463.
[ h t t p : / / www.ppi c.or g/ cont ent / pubs/ CC_204DRCC.pdf ]
30 Ibid., page 11. The eight geographic areas are the Sacramento region, the San Francisco
Bay area, the Central Coast, the SJV, Los Angeles County, the Inland Empire, and San
Diego County.
31 Ibid., page 12.
32 Ibid., page 13.
33 Milken Institute. Manufacturing Matters: California’s Performance and Prospects.
Report prepared for the California Manufacturers and Technology Association. Santa
Monica, California. August 2002.
important stage of value-added production and its continued and expanded role in
agriculture is regarded as an important source of future economic growth.34
Regional Approaches to Economic Development
Introduction. There is a resurgence of interest in regional economic
development alliances in many parts of the United States.35 A 2001 statewide survey
of California residents found that a substantial majority believe that local
governments should take a regional approach with respect to land use, environmental,
transportation, and related growth issues that focuses more on public-private
partnerships rather than regional government.36 Proponents of regional approaches
share the view that the historic pattern of community-based economic development
may no longer address the complexity of development issues that can characterize a
larger geography. The fiscal problems in many states are also creating pressures on
many communities to seek new solutions to providing essential community services
through pooling resources.
Congress has had a long history of support for regional authorities based on
federal-state partnerships such as the TVA and the ARC. Both the TVA and the
ARC have continued to support economic development and social change in their
respective regions. A substantial body of literature exists on the impact of these
regional authorities. While there are differences in opinion about the development
successes of these authorities, a 1995 empirical assessment of ARC’s impact over 26
years in the region’s 391 counties, concluded that the programs did produce
significant growth. Using a methodology based on paired communities, the authors
concluded that growth was significantly faster in the 391 Appalachian counties than
it was in the control counties. This also held true for Central Appalachia, the poorest
subregion in the ARC. Another reported result was improved local planning in ARC
counties compared to the control counties.37
Congress has authorized several new regional authorities to deal with common
concerns including the Denali Commission (1998), the Delta Regional Authority
(2002), and the Northern Great Plains Regional Authority (2002). Most recently,
legislation for other regionally based approaches to economic development has been
34 Collaborative Economics. The Economic Future of the SJV. Report prepared for New
Valley Connexion, a partnership of the Great Valley Center and Office of Strategic
Technology, California Trade and Commerce Agency. January 2000.
35 See National Association of Development Organizations Research Foundation. 2003.
Federal State Regional Commission: Regional Approaches for Local Economic
Development. April. Washington, D.C. For a selective overview of 5 case studies of
regional development organizations, see Multi-Region Economic Development Strategies
Guide: Case Studies in Multi-Region Cooperation to Promote Economic Development.
National Association of Regional Councils. 2000.
36 Baldassare, Mark. PPIC Statewide Survey: Special Survey on Land Use. Public Policy
Institute of Californian, San Francisco, California, 2001.
37 Isserman, Andrew and T. Rephann. “The economic effects of the Appalachian Regional
Commission: An empirical assessment of 26 years of regional development planning.”
Journal of the American Planning Association, 61(3), Summer, 1995.
introduced in the109th Congress. In March, 2005, the Regional Economic and
Infrastructure Development Act of 2005 (H.R. 1349) was introduced. The bill would
organize four regional commissions under a common state-federal framework. It
reauthorizes the Delta Regional Authority and the Northern Great Plains Regional
Authority and creates the two new regional commissions: the Southeast Crescent and
the Southwest Border Regional Commission. Every county or parish that is currently
included in a commission or would be included in the proposed legislation is
similarly included in that same commission under this bill. While the bill follows the
organizational model of the ARC, it does not include the ARC or the Denali
Commission in its framework. The bill has been referred to the Subcommittee on
Domestic and International Monetary Policy, Trade, and Technology of the House
Financial Services Committee.
Regional authorities created by Congress share the general economic
development logic that real competitive advantage exists in addressing development
issues in economically distressed areas from a regionally cooperative stance rather
than communities vying in a zero-sum competition. A regional development
approach may contribute to communities regarding themselves as economic partners
with interdependencies rather than simply rivals. Federal regional commissions offer
assistance to the some of the most economically distressed areas largely by providing
a framework for federal and private investment. These federal regional commissions
are generally responsible for developing area-wide planning, establishing regional
priorities, recommending forms of interstate cooperation, and coordinating regional
growth strategies with stakeholders. Local Development Districts (LDD), sub-state
multi-jurisdictional local government-based organizations, are the principal entities
through which development assistance is structured. While each federal regional
commission may have certain distinctive elements, the more recently established
federal regional commissions are organized and structured to build on the strengths
of the ARC model.
The Appalachian Regional Commission. The ARC was created in 1965
in response to the persistent socioeconomic challenges in the Appalachian region:
poverty, isolation and neglect, absence of basic physical infrastructure,
underdevelopment, and stagnation. President Kennedy had earlier formed a cabinet-
level commission, chaired by Franklin Roosevelt, Jr., to study the problems of the
region and to develop a plan for addressing the long-standing problems. That38
commission issued its report in 1964. The report encouraged a state-federal
partnership to focus on the region in new ways that went beyond the existing
categorical grant programs of state and federal governments. Congress enacted the
38 Appalachia: A Report by the President’s Appalachian Regional Commission.
Washington, D.C., U.S. Government Printing Office, 1964. Interestingly, the Commission
was immediately confronted by a problem of research strategy: whether to concentrate on
the most distressed part of Appalachia, the largely rural interior area of marginal farms and
coal mining, or concern itself with the entire area from southern New York to Northern
Mississippi. They chose the latter approach, at the same time recognizing that the statistical
case would have been more compelling had the chronically depressed interior been treated
separately. Subsequent analyses of the region have categorized the area in ways that take
into consideration the variance among counties and subregions of Appalachia.
Appalachian Regional Development Act of 1965 (P.L.89-4) to carry out the
Commission’s recommendations through the new ARC.
The ARC was established as a unique organization, with a governing board
comprised of a federal cochair appointed by the President and confirmed by the
Senate, and the Governors of the 13 member states. The regional development
program requires the consensus of both the federal cochair and the majority of
Governors to set programs and policies. The federal co-chair and the Governors
must vote each year to allocate funds for various ARC programs. Between 1965 and
timbering and mining), as well as basic infrastructure, vocational education facilities,
and health facilities and services. Between 1965 and 2002, Congress appropriated
a total of $9.2 billion for Appalachian programs, with $6.2 billion allocated for the
Appalachian Development Highway System (ADHS) and $3.0 billion for ARC’s
economic and human development programs.39 The ADHS was a critical component
for the development program of Appalachia for two reasons. First, the new interstate
highway system had largely bypassed Appalachia. Second, a system of reliable roads
would link more isolated parts of Appalachia to potential economic growth centers.40
The Appalachian Regional Development Act has been amended over the years
to expand the number of counties in the program. Today, there are 410 counties
which are classified into four categories of economic development: Distressed,
Transitional, Competitive, and Attainment. Each category is based on three
indicators of economic viability: per capita income, poverty, and unemployment.
Since 1983, the ARC has designated the most distressed counties for special funding
consideration. In 2002, ARC incorporated into its strategic plan an enhanced
program for meeting the needs of distressed counties. In FY2002, there were 118
distressed counties in 10 states, although most were in Central Appalachia
(Kentucky, West Virginia, Tennessee, and Virginia). The number of distressed
counties increased each year from 1997-2002.
Annual appropriations from Congress permit the ARC to make grants to public
and private non-profit organizations in the region. Each state prepares a four-year
plan and an annual strategy statement to address the five goals in ARC’s strategic
plan: (1) education and workforce training, (2) physical infrastructure, (3) civic
capacity and leadership, (4) dynamic local economies, and (5) health care. LDDs,
39 Appalachian Regional Commission, 2002 Annual Report. Washington, D.C., ARC, 2003.
The Appalachian Development Highway System (ADHS) and access road construction were
designed to break Appalachia’s isolation and encourage economic development. By
FY2002, approximately 85% of the highway system was either open to traffic or under
construction. See Appalachian Highway Development Program (ADHP): An Overview.
CRS Report 98-973E, December, 1998.
40 Since FY1999, annual funding for completing the ADHS has been provided from the
federal Highway Trust Fund in the Transportation Equity Act for the 21st Century (P.L.105-
2003. Although funds were provided through the Highway Trust Fund, ARC exercised
programmatic control over the funds. The program was reauthorized at $470 million
annually FY2005-2009 with the Safe, Accountable, Flexible, and Efficient Transportation
Equity Act of 2005 (HR3) and signed into public law on August 10, 2005.
governed by local government officials and leaders from the member counties,
typically assist with grant applications consistent with state and regional priorities.
Throughout its 40 years, the ARC has developed a record of helping small,
distressed communities move closer to the economic mainstream. A key element of
the ARC model is the network of 72 multi-county development districts that are
responsible for helping local officials and communities assess, plan, and implement
socioeconomic development initiatives. The ARC structure is unique because it is an
intergovernmental partnership that, while preserving a direct federal role in
investment decisions, also maintains a strong emphasis on state priorities and
decision making.
In 2002, Congress reauthorized the ARC through the Appalachian Regional
Development Act Amendments of 2002. (P.L.107-149). In addition to adding four
counties to the region, the reauthorization also included several new provisions
regarding the ARC’s activities. Among them were:
!The ARC was required to use at least half of its project funds to
benefit distressed counties;
!A new telecommunications program was authorized;
!A new Interagency Coordinating Council on Appalachia was
established to increase coordination and effectiveness of federal
funding in the region;
!An entrepreneurship initiative was authorized to encourage
entrepreneurial education, improve access to debt and equity capital,
develop a network of business incubators, and help small
communities create new strategies for small businesses;
!A new regional skills partnership program was established to
encourage collaboration among businesses, educational institutions,
state and local governments, and labor organization to improve skills
of workers in specific industries.
Tennessee Valley Authority. TVA is a unique federal corporation charged
with responsibility for regional development and power generation in the Tennessee
Valley. It is one of the largest producers of electric power in the United States and
the nation’s largest public power system. Through 158 municipal and cooperative
power distributors, TVA serves about 8.3 million people in an 80,000-square-mile
region covering Tennessee and parts of Kentucky, Virginia, North Carolina, Georgia,
Alabama, and Mississippi. The TVA power system consists of three nuclear-
generating plants, 11 coal-fired plants, 29 hydroelectric dams, six combustion-turbine
plants, a pumped-storage plant, and about 17,000 miles of transmission lines. TVA
also manages the Tennessee River, the nation’s fifth-largest river system, and offers
economic development and environmental assistance throughout the region.
Congress authorized the TVA with the Tennessee Valley Authority Act of 1933
(P.L.73-17). The act created the TVA as a federal corporation to address important
problems facing the valley, such as flooding, providing electricity to homes and
businesses, and replanting forests. Other TVA responsibilities written in the act
included improving navigation on the Tennessee River and helping develop the
region’s business and farming. The establishment of the TVA marked the first time
that an agency was directed to address the total resource development needs of a
major region.
The President appoints three TVA Directors, who are confirmed by the Senate
and serve staggered nine-year terms. That Board of Directors has sole authority for
determining the rates that TVA and its distributors charge for power. Although TVA
was formed to build dams and improve navigation on the Tennessee River, only 11%
of its installed capacity comes from 114 hydropower units. About 65% is provided
by 59 coal-fired power plants. Another 24% percent comes from nuclear reactors.
The small remainder is derived from gas turbines.
Bringing electrical power to the Tennessee Valley was arguably the greatest
contribution to improving the social well-being of TVA residents. Even by
Depression standards, the Valley was a significantly impoverished, underdeveloped
area in 1933. Electrical power not only improved the lives of individuals, the power
attracted industry that brought relatively well-paid jobs to the Valley. Today,
although TVA is still popularly regarded as a multi-purpose agency, the great
majority of its resources are targeted to power-generation and transmission. While
it is beyond the scope of this report to assess the efficiency or effectiveness of TVA
as a regional development agency, TVA today has critics, including Members of
Congress. While Valley residents recall TVA’s role in alleviating poverty during the
Depression, many of the Valley’s contemporary residents have raised concerns about
TVA’s contribution to air pollution through its reliance on coal-fired plants,
perceived mismanagement, and a series of high-profile conflicts with Valley
residents, e.g., the Tellico Dam controversy.41
Delta Regional Authority. The Delta Regional Authority (DRA) was
authorized by the 2002 farm bill, the Farm Security and Rural Investment Act (P.L.
107-171). The Authority serves 240 counties and parishes in the Mississippi River
delta areas of Alabama, Arkansas, Illinois, Kentucky, Louisiana, Mississippi,
Missouri, and Tennessee. Working through State Economic Development Agencies,
DRA targets economically distressed communities and assists them in leveraging
other federal and state programs focused on basic infrastructure development,
transportation improvements, business development, and job training services. The
act requires that at least 75% of funds be invested in distressed counties and parishes
and pockets of poverty, where 50% of the funds are earmarked for transportation and
basic infrastructure improvements.
The United States-Mexico Border Health Commission. In recognition
of the need for an international commission to address dire border health problems,
the Congress enacted the United States-Mexico Border Health Commission Act of
41 For a discussion of critical perceptions of the TVA by Members of Congress,
TennesseeValley residents, and researchers, see Richard Munson. Restructure TVA: Why
the Tennessee Valley Authority Must Be Reformed. Northeast-Midwest Institute, 1997.
[http://www.nemw.org/tvareport.htm]; William. U. Chandler, Myth of TVA: Conservation
and Development in the Tennessee Valley, 1933 — 1983. Ballinger, Cambridge,
Massachusetts, 1984.
an agreement with Mexico to establish a binational commission to address the unique
and severe health problems of the border region. In 1997, Congress approved funding
for a commission through the U.S. Department of Health and Human Services,
Office of International and Refugee Health. In 2000, the U.S.-Mexico Border Health
Commission (USMBHC) was created through an agreement by the U.S. Secretary of
Health and Human Services and the Secretary of Health of Mexico. In December,
2004, the USMBHC was designated as a Public International Organization by
Executive Order.42
The USMBHC comprises the U.S. Secretary of Health and Human Services and
Mexico’s Secretary of Health, the chief health officers of the 10 border states and
prominent community health professionals from both nations. Each section, one for
the United States and one for Mexico, has 13 members. The Commissioner of each
section is the Secretary of Health from that nation. Each Commissioner may
designate a delegate. The chief state health officer of the 10 border states is a
statutory member of the Commission, and the other 14 members are appointed by the
government of each nation.
The economic burden on the two countries from increased immigration is
significant. Much of the border area is poor and health resources are scarce. Rapid
population growth is putting further pressure on an already inadequate medical care
infrastructure, which further decreases access to health care. The large and diverse
migrant population increases the incidence of communicable diseases such as
HIV/AIDS and tuberculosis, as well as chronic illnesses such as diabetes, certain
cancers, and hypertension. The numerous problems and concerns affecting the
border region have broad repercussions for both nations.
The USMBHC was created to serve all the people who reside within 62 miles
on either side of the U.S.-Mexican international boundary line. The border area is
comprised of six Mexican states and four U.S. states. The original agreement was
in effect for five years (1994-1999); it is automatically extended for additional
five-year periods unless either party gives notice of withdrawal.
The Northern Great Plains Regional Authority (NGPRA). The
NGPRA is a newly created federal-state-provincial partnership that includes Iowa,
Minnesota, Nebraska, North and South Dakota, and the Provinces of Manitoba and
Saskatchewan. In 1994, Congress passed the Northern Great Plains Rural
Development Act (P.L. 103-318). The following year, the Northern Great Plains
Rural Development Commission was established. In 1997, the Commission issued
its regional development report to Congress and the Commission was sunset. Later
that year, the Commission set up an operating arm, NGP, Inc., to implement the
Commission’s recommendations. Discussions with the region’s congressional
delegation led to a plan to create a regional development authority similar to the one
Congress created for the Delta Authority. The Farm Security and Rural Investment
Act of 2002 (P.L.107-171, Section 6028) established the NGPRA to implement the
42 Executive Order 13367, United States-Mexico Border Health Commission. December 21,
Commission’s plan and authorized $30 million to be appropriated each year
(FY2002-2007) to support the Authority’s programs.
At the local level, the NGPRA relies on the existing network of the Economic
Development Administration’s (EDA) designated economic development districts
to coordinate efforts within a multi-county area. These EDA districts, known as
LDDs, are regional entities with extensive experience in assisting small
municipalities and counties improve basic infrastructure and help stimulate economic
growth. They also serve as the delivery mechanism for a variety of other federal and
state programs, such as assistance to the elderly, aging, economic development,
emergency management, small business development, telecommunications,
transportation and workforce development programs.
The NGPRA has identified four areas for its strategic planning: (1) Agriculture
and Natural Resources, (2) Economic and Policy Analysis, (3) Information
Technology, and (4) Leadership Capacity Development. Given the central role of
agriculture in the regional economy, the Authority is integrating into its planning (1)
shifts in consumer demand toward organic foods, (2) a recognition of the shift to
supply-chains in production and the corresponding need to develop identity preserved
commodities, sand (3) the emerging importance of non-food commodities, (i.e., bio-
based industrial commodities). A central objective is to turn the Great Plains into an
internationally recognized center for biomass research and use. These agricultural
plans also are grounded more broadly in transforming the transportation systems of
the region, developing local and regional leadership capacity, and expanding the
availability and use of information technologies within the region.
Denali Commission. The Denali Commission, created by the Denali
Commission Act of 1998 (P.L.105-245), is a federal-state partnership focusing on
development concerns in rural Alaska. The Commission supports job training and
other economic development services in rural communities, particularly distressed
communities, many of which have very high rates of unemployment. The
Commission also promotes rural economic development and provides power
generation and transmission facilities, modern communication systems, water and
sewer systems and other physical infrastructure needs. Project areas include energy,
health facilities, solid waste facilities, elder and teacher housing, and domestic
violence facilities.
The Governor of Alaska and a representative nominated by Congress and
appointed by the Secretary of Commerce serve as co-chairs of the Commission. The
Denali Commission Act also provides for a five member panel of statewide
organization presidents, or their designees, to be appointed by the Secretary of
Commerce. These members include the president of the University of Alaska,
president of the Alaska Municipal League, president of the Alaska Federation of
Natives, president of the Alaska State AFL-CIO, and president of the Associated
General Contractors of Alaska.
In FY2003, appropriations provided nearly $100 million in funding to the
Denali Commission. Funding sources included general appropriations for energy
and water, the Trans-Alaska Pipeline Liability Fund, USDA Rural Utilities, the U.S.
Environmental Protection Agency, and the U.S. Department of Health and Human
Services.
Chapter 2 — The San Joaquin Valley and
Appalachia: A Socioeconomic Comparison
Overview. The San Joaquin Valley shares certain socioeconomic
characteristics with other U.S. regions where poverty and limited economic
development opportunities have persisted for decades. When the Appalachian
Regional Commission was created in 1965, Appalachia, especially Central
Appalachia, was practically synonymous with U.S. white, rural poverty. Forty years
and billions of public and private dollars later, the region has changed. Appalachia
has cut poverty among its population of 23 million by approximately half and
increased high school graduation rates by 70%. While socioeconomic indicators still
show the region lagging behind the United States as a whole, the deepest poverty,
isolation, and underdevelopment that characterized much of the region in the past has
lessened over the past 40 years.
Like Central Appalachia, with its historic dependence on coal mining, the San
Joaquin is historically tied to a traditional extractive economy. Extractive
economies, whether based on timber, mining, or agriculture, may produce trajectories
of development that differ from industrial forms of economic growth and change.
How that shapes the SJV’s opportunities for creating new competitive advantage is
central to an understanding of the region’s future. Some researchers have suggested
that the effects on the Appalachian region of decades of mining created its own
dynamic of development and underdevelopment.43 Research on the Central Valley
has also suggested that agriculture is producing a “landscape of inequality” there that
will become even more pronounced in the future without concerted efforts to create44
new paths of economic mobility for all SJV residents.
High unemployment and low per capita incomes have long characterized many
Appalachian counties as data in this chapter show (Table 1). Similar patterns are
observable in the SJV. The geographic isolation of Appalachia, however, is one of
the major factors in its development history. While Appalachia saw an outflow of
residents as they searched for economic opportunities that did not exist there, the SJV
has an inflow of residents due to a very high rate of immigration. However, that
immigration is characterized by relatively large numbers of poorly educated,
unskilled workers, many of whom are drawn to the area by the availability of farm
employment. Even those immigrating to the SJV from coastal areas of the state are
not necessarily bringing good jobs with them, as much as they may be seeking the
more affordable housing in the SJV. Many continue to commute significant
distances to jobs outside the SJV. Without significant opportunities for higher wage
employment, young, well-educated people will not relocate to the SJV. Rather, much
like Appalachia, an exodus of the better trained and educated may push the area into
43 Gaventa, John. Power and Powerlessness: Quiescence and Rebellion in an Appalachian
Valley. Champaign, IL: University of Illinois Press, 1982.
44 Taylor, J. Edward. and Philip L. Martin. “Central Valley evolving into patchwork of
poverty and prosperity.” California Agriculture, 54(1), January-February, 2000. See also,
Taylor, J. Edward, P.L. Martin, and M. Fix. Poverty Amid Prosperity: Immigration and the
Changing Face of Rural California Washington, DC: The Urban Institute, 1997.
a downward spiral. Business, and industries needing trained and educated workers
are reluctant to relocate to an area where such workers are scarce, and the trained and
educated workers that are there leave for opportunities elsewhere reinforcing the
area’s growth of low-skilled labor.
In this portion of the report, we provide a general empirical overview of the
Appalachian region relative to the SJV. We also provide a more focused comparison
between the SJV and a subregion of Appalachia, Central Appalachia, across a range
of socioeconomic indicators. This exercise shows socioeconomic similarities and
differences between two regions where poverty and economic distress have long been
in evidence. Data on variables of concern here for the entire 410 county Appalachian
region as defined by the ARC were, in most cases, not available at a county level.
While the Central Appalachian region is half the population size of the SJV (1.8
million versus 3.5 million people in 2003), for methodological reasons, the scale
between these two regions appears more appropriate than attempting a comparison
of the eight counties of the SJV with the 410 of the ARC defined Appalachian region.
There are counties within the 410 area that are so different across indicators from
more economically distressed Appalachian counties, as well as the SJV, that to
include them in aggregate measures could introduce a degree of bias that would
weaken the validity of the comparison.45
The Appalachian Regional Commission categorizes its 410 counties by
economic development criteria (Distressed, Transitional, Competitive and
Attainment) based on three indicators of economic viability: per capita market
income, poverty, and unemployment. Distressed Counties have poverty and
unemployment rates that are at least 150% of the national averages and per capita
market incomes that are no more than two-thirds of the national average. Counties
are also considered Distressed if they have poverty rates that are at least twice the
national average and they qualify on either the unemployment or income indicator.
Transitional Counties are those ARC counties that are neither Distressed,
Competitive, nor Attainment. Competitive Counties have poverty and unemployment
rates that are equal to or less than the national averages and they have per capita
market incomes that are equal to or greater than 80% percent, but less than 100% of
the national average. Attainment Counties have poverty rates, unemployment rates,
and per capita market incomes that are at least equal to the national rates (Figure 2).
The ARC defined Appalachian area includes large urban populations in metropolitan
counties and small, remote counties with no urban concentrations. In 2002, 60% of
the ARC residents lived in metropolitan counties, 25% in counties adjacent to
45 For example, Knoxville, Tennessee and State College, Pennsylvania are part of the ARC
defined region. Knoxville is the third largest metro area in Tennessee and home to the
Tennessee Valley Authority and the University of Tennessee. State College, Pennsylvania
is the site of Pennsylvania State University. These and other similar metro areas within the
ARC defined region could skew socioeconomic data significantly. While CRS is unable to
remove all potential sources of bias in this comparison, we did strive to match an identified
region in Appalachia that appears to most closely resemble the SJV. A list of the individual
Appalachian counties in our analysis is provided in Appendix D. The ARC’s Central
Appalachian area includes counties in Tennessee, Virginia, Kentucky, West Virginia, and
Ohio. The Central Appalachian region used in our analysis includes 68 of these counties,
but excludes all 29 counties from Appalachian Ohio (See Figure 2 above).
metropolitan counties, with the remainder in more remote rural areas. For analytical
purposes, the ARC also divides the region into three subregions: Northern
Appalachia, Central Appalachia, and Southern Appalachia. The 215-county Central
Appalachian area contains the largest proportion of rural residents of any of the
ARC’s three subregions as well as the largest number of Distressed counties.
CRS-22
Table 1. Appalachian Regional Commission County Economic Fiscal Status, 2004
Three-YearUnemployment Rate,Per CapitaPoverty Rate,
AveragePer Capita MarketaPoverty RatePercent of U.S.Market Income,Percent of U.S.
UnemploymentIncome 20002000 (%) Average Percent of U.S.Average
Rate 1999-2001(%)Average
4.3 $25,676 12.4 100 100 100
4.7 $19,736 13.6 108.3 76.9 110.2
gion
a 4.9 $19,574 16.1 113.0 76.2 130.1
4.5 $20,489 14.4 104.5 79.8 115.9
abama
iki/CRS-RL33184
g/wi a 3.9 $24,727 13.0 89.8 96.3 104.9
s.or 3.1 $23,183 9.2 71.3 90.3 74.7
leaki a
://wikie ntucky 4.7 $19,957 15.8 108.3 77.7 127.8
http 6.3 $13,154 24.4 146.5 51.2 197.4
entucky
land 3.8 $30,143 8.5 88.4 117.4 68.6
5.2 $18,381 11.7 120.7 71.6 94.1
land
5.4 $16,915 19.9 125.5 65.9 161
6.1 $15,448 19.4 141.7 60.2 156.9
4.9 $29,436 14.6 112.3 114.6 117.9
k
CRS-23
Three-YearUnemployment Rate,Per CapitaPoverty Rate,
AveragePer Capita MarketaPoverty RatePercent of U.S.Market Income,Percent of U.S.
UnemploymentIncome 20002000 (%) Average Percent of U.S.Average
Rate 1999-2001(%)Average
4.1 $23,311 12.3 95.2 90.8 99.2
3.9 $21,548 11.7 90.3 83.9 94.7
rolina
4.2 $23,974 10.6 97.4 93.4 85.6
5.7 $17,345 13.6 132.3 67.6 109.8
l va nia 4.4 $24,795 11.0 102.4 96.6 88.7
5.0 $21,418 11.4 114.9 83.4 92.1
iki/CRS-RL33184l va nia
g/w 4.6 $20,370 14.1 105.8 79.3 114.0
s.or
leak 3.6 $21,893 11.7 82.8 85.3 94.7
rolina
://wiki
httpnnessee 4.1 $21,866 13.5 95.7 85.2 108.9
4.2 $19,050 14.2 98.1 74.2 114.4
nnessee
i rginia 2.8 $28,198 9.6 65.2 109.8 77.5
5.3 $15,939 15.7 122.3 62.1 127.1
inia
i rginia 5.7 $16,772 17.9 131.1 65.3 144.6
5.7 $16,772 17.9 131.1 65.3 144.6
inia
Appalachian Regional Commission
er capita market income (PCMI) is a measure of an area’s total personal income, less government transfer payments, divided by the resident population of the area. The percent
of the U.S. average is computed by dividing the county per capita market income by the national average and multiplying by 100.
Figure 2. The Appalachian Regional Commission Area and its
Distressed Counties
Central Appalachia, as defined by the U.S. Department of Agriculture’s
Economic Research Service, is a 68 county area in parts of Virginia (7 counties),
Tennessee (9 counties), Kentucky (43 counties), and West Virginia (9 counties).
This particular subregion of Appalachia was used as a case comparison to the SJV
across several socioeconomic variables because 45 (66%) of Central Appalachia’s
68 counties are Distressed counties.46 Because the counties of this subregion are
among the most impoverished of the ARC area, we regard the comparison as a more
reliable contrast to the SJV. The data presented in this chapter are drawn from public
sources, (e.g., Bureau of Labor Statistics, Bureau of Economic Analysis, Bureau of
the Census, Census of Agriculture, and ARC). A list of sources and websites can be
found in Appendix B as well as in notes accompanying individual tables. In some
cases, the data were not available because they were not collected at the county level,
or could not be accurately aggregated across the 68-county region. In those cases, we
have used state data as a comparative point. Data for 2003 are from the American
Community Survey (ACS), which is the planned replacement for the long
questionnaire of the decennial census.
Socioeconomic Indicators in the SJV and Appalachia, 1980-
2003
A previous section provided an introduction and overview of contemporary
research on the policy issues facing the SJV. Rapid population growth, high rates of
immigration, low per capita and household income, high unemployment, low
educational achievement, weak economic diversity outside production agriculture,
and urban sprawl are among the central concerns of the SJV. While other regions in
the United States reveal similar distress, (e.g., the Rio Grande area, the Delta South,
and Native American reservations in the Great Plains), the SJV is not an area that
first comes to mind as one of concentrated poverty. This section of the report
provides a detailed examination of the socioeconomic conditions in the SJV over the
past 23 years. These indicators reveal the area as one lagging significantly behind
California, the United States, and, across many variables, the Central Appalachian
region as well. Statistics are presented in tables below based on each of the past three
decennial censuses, 1980, 1990, 2000, and, when available, for 2003-2004. Data
include indicators on labor and employment, poverty and income, disease prevalence,
educational attainment, and crime. For particular variables, geographic information
system maps of these data were created to show the graphic contrast between the SJV
counties and other California counties.
County and Regional Population Characteristics. The SJV population
is growing rapidly. In 2003, over 3.5 million people resided in the SJV, an increase
of 1.5 million since 1980, a population increase of 75.0%. Each of the SJV counties
exceeded the national rate of population growth between 1980-1990, 1990-2000, and
46 The ARC has used the distressed county designation for almost twenty years to identify
counties with the most structurally disadvantaged economies. Up to 30% of ARC’s Area
Development Funds are targeted to distressed counties through allocation of ARC grants to
distressed counties, requiring only a 20% match from the state and/or local government,
which is lower than the state/local match required from non-distressed counties. From 1983,
the inception of the distressed counties program, through 1999 the ARC provided $266
million dollars in single-county grants to distressed counties. This sum constituted 42% of
such single-county grants awarded across Appalachia. See Wood, Lawrence E. and Gregory
A. Bischak. Progress and Challenges in Reducing Economic Distress in Appalachia: An
analysis of National and Regional Trends Since 1960. Washington, DC: ARC, 2000.
growth rates than the national average, each SJV county substantially outpaced the
growth of California between 1980-2000. Madera County alone more than doubled
its population between 1980 and 2003. The adjacent counties of Mariposa and
Tuolumne also have had generally higher growth rates than either California or the
United States from 1980-2000. San Joaquin and Stanislaus counties now have
population densities considerably higher than the California average (Table 3). With
the high proportion of federal land in Mariposa and Tuolumne, these counties have
had relatively stable population densities compared to the SJV.
In marked contrast, Central Appalachia’s population declined 5.7% between
1980-1990, losing 52,000 people during that decade. The SJV grew by 34% in that
decade. Between 1990-2003, Central Appalachia grew by less than 3%, effectively
recovering about 1,000 persons more than it lost the previous decade. This rate is
considerably less than the Appalachian states as a whole, except for West Virginia,
which grew by just under 1% (Table 4).
The SJV population is projected to grow by 14.3% between 2003 and 2010
compared to projected growth rates of 10.6% for California and 6.2% for the United
States (Table 5). Projected population growth for the SJV between 2003 and 2020
is 39.0% compared to a growth rate of 15.5% for the United States and 23.6% for
California. Population growth between 2003-2020 for Mariposa and Tuolumne
counties is projected to be about the same as the national average but less than
California. Table 6 shows that Central Appalachia is projected to grow only 5.5%
between 2003 and 2020 and 2.3% between 2003-2010. If these projections prove
accurate, Central Appalachia will have a net gain of 98,000 people by 2020 and the
SJV a gain of 398,000. With the exception of West Virginia, Central Appalachia is
projected to grow between one-third and one-fourth below its respective state
population growth.
As noted earlier, immigration has been a major source of the population growth
in the SJV. As Table 7 and Table 8 show, California and the SJV’s towns and cities
have highly mobile populations, although they are not substantially different from the
United States as a whole, except for the fact that in the United States as a whole, a
much larger percent of those who moved in the previous year came from a different
state. For the 2002 through 2004 period, over 30% of the SJV metropolitan
population who moved during the previous year either lived in another California
county (16.1%), lived in a different state (8.0%), or lived abroad (6.7%). Most who
moved in the previous year, however, moved within the same county.
Nearly 20% of the SJV’s population in 2000 was foreign born (Table 9).
Almost one-quarter of the population of Merced was foreign born. In 1980, less than
14% were foreign born in that county. While these are relatively high percentages
compared to the United States percent of population that was foreign-born (11.1%),
the SJV had a lower percentage of foreign-born than California (26.2%). Mariposa
and Tuolumne counties had 2.8% and 3.2% respectively who were foreign-born.
Whether foreign-born or not, in 2000 nearly 40% of the SJV population identified
itself as Hispanic in origin, compared to 32.4% of California and 12.5% of the United
States (Table 10). I 2003, over 54% in Tulare County and 46% in Fresno County
identified themselves as Hispanic in origin. Since 1980, all the SJV counties have
increased the proportion of their population who identified themselves as Hispanic
in origin. In 1980, less than 6% of the SJV population was Mexican-born. By 2000,
13.5% were Mexican-born (Table 11). Each of the SJV counties have more than
doubled the percentage of their Mexican-born populations since 1980. This is true
of California as well. The United States more than tripled its Mexican-born
population between 1980 and 2003. Figure 3 shows the percent change in the
Mexican-born population by California county, 1990-2000.
Three additional tables show the distribution of the SJV population by race, sex,
and age, 1980-2003. From 1980-2003, the proportion of those in the SJV who
identified themselves as either Black, American Indian, or Native Alaskan have
remained small and stable (Table 12). Asian and Pacific Islanders more than
doubled from 2.9% in 1980 to 6.3% in 2000. Most of the increases in Asian and
Pacific Islanders were in Fresno, Merced, and San Joaquin counties with Fresno
County seeing the largest increase between 1980 and 2000 (63%) followed by San
Joaquin County (46%). The U.S. Census category of “Other” increased significantly
in the SJV, from 14% to over 23%. The proportion of the SJV population identifying
themselves as White declined from 77.6% in 1980 to 59.1% in 2000. Declines in the
proportion of those identifying themselves as White were evident in half of the SJV
counties between 1980 and 2000. In 2003, Fresno, Kern, San Joaquin, Stanislaus,
and Tulare counties registered increases in the proportion of the population who
identified themselves as White, as did California. Mariposa and Tuolumne counties
have the lowest proportions of their population who identify themselves as Black,
Native American Indian and Native Alaskan, Asian and Pacific Islanders, and Other.
Their population distribution by race was relatively stable between 1980 and 2000.
The distribution of the SJV population by sex in 2000 showed a slight male
bias, 50.2% versus 49.8% (Table 13). The population distribution of males and
females in California is 49.6% and 50.4% respectively. The male bias is very
pronounced in Kings county with 57.4% male and 42.6% female. Tuolumne County
also had a slight distributional bias toward males (52.6%). The sex distribution for
the United States was, like California, biased toward females, 48.9% males to 51.1%
female.
The SJV population is a relatively young population compared to many areas
of the United States, especially most rural areas. In 2000, the proportion of the U.S.
population 65 and older was 12.4%, while in California, that population stratum was
10.6% (Table 14). In the SJV, the proportion aged 65 and older was 9.9%. In Kings
County, the 65 and older accounted for just 7.5% of the population. As Table 13
showed, Kings County also has a high male proportion. That characteristic, along
with the age distribution shown in Table 14, suggest the county has a relatively high
proportion of men, especially in the prime labor cohort of 25-54 years old. The 25-
54 year old cohort in Kings County is the largest in the SJV. While the proportion
of this cohort is the largest in each SJV counties, the proportion is somewhat lower
than that of California, except for Kings County. Mariposa and Tuolumne counties,
in contrast, have very high proportions of their population 65 and older, substantially
higher than the proportions in the United States and California.
Appalachia’s Demographic Structure. In 2000, approximately 31% of
U.S. residents identified themselves as a member of a minority group. In the ARC
region, however, racial and ethnic minorities comprised only about 12% of the
population. Of the 2.8 million minority Appalachians, 66% (1.8 million) were non-
Hispanic black, with Hispanics making up another sixth (465,000).47 In the ARC-
defined Central Appalachian area, only 4% identified themselves as minorities.
Southern Appalachia, with a 19% minority population, was the most diverse region
of the ARC.
In-migration has been a key factor in the ARC’s increase in racial and ethnic
diversity. More than half of Appalachia’s Hispanic and Asian residents and one-third
of its American Indians and multiracial persons had moved since 1995-either into the
region or from another Appalachian county. Among Appalachia’s black population,
just under one-fifth had migrated from another county between 1995 and 2000-only
slightly higher than the percentage for non-Hispanic whites.48
Appalachia has a higher proportion of elderly than either the SJV or the United
States as a whole. In 2000, 14.3% of Appalachian residents were ages 65 and over,
compared with 12.4% of all U.S. residents. In the SJV, just under 10% of the
population in 2000 was age 65 or older. Northern Appalachia had the oldest
population among the ARC subregions, with 16% ages 65 and over. West Virginia,
all of which is in the ARC area, ranked third among states in 2000 in the percentage
of its population ages 65 and over; only Florida ranked higher.49 The “youth deficit”
in the Appalachian region is fairly evenly divided between the school-age and
working-age populations, both of which are slightly lower than the corresponding
national percentages.50 Given current trends, regional demographic projections show
that the ARC area will have over 5 million people ages 65 and over in 2025, nearly
20% of the total population. One of every 40 Appalachian residents will be among
the oldest old, those ages 85 and over, in 2025.51
47 Pollard, Kelvin. Appalachia at the Millennium: An Overview of Results from Census
[ ht t p: / / www.ar c.gov/ i mages/ r epor t s / c ensus2000/ over vi ew/ a ppal a chi a _census2000.pdf ]
48 Pollard, Kelvin. A “New Diversity”: Race and Ethnicity in the Appalachian Region.
Population Reference Bureau, September, 2004.
[ ht t p: / / www.ar c.gov/ i ndex.do?nodeId=2310]
49 Haaga, John. The Aging of Appalachia. Population Reference Bureau, April, 2004.
[ ht t p: / / www.ar c.gov/ i mages/ r epor t s / a gi ng/ a gi ng.pdf ]
50 Ibid., p.7.
51 Ibid., p.9.
Table 2. Population: United States, California, and Counties of
the SJV, 1980-2003
Population
(in 1000s)Percent change
1980 1990 2000 2003 1990 2000 2003
SJ V 2,048 2,744 3,303 3,583 34.0 20.4 30.6
Fresno County51566779985029.719.827.4
Kern County40354566271335.221.430.8
Kings County7410112913937.627.636.6
Madera County638812313339.639.851.5
Merced County13517821123232.618.029.8
San Joaquin County34748156463338.417.331.7
Stanislaus County26637144749239.320.632.8
Tulare County24631236839126.918.025.3
Adjacent counties
Mariposa County1114171828.819.824.5
Tuolumne County3448555742.812.517.1
California 23,668 29,758 33,872 35,484 25.7 13.8 19.2
United States226,542248,718281,422290,8109.813.116.9
Sources: U.S. Department of Commerce, U.S. Census Bureau, 2000 Census of Population and
Housing, United States Summary, PHC-3-1, Washington, U.S. Govt. Print. Off., 2004, p. 44; and U.S.
Department of Commerce, U.S. Census Bureau, American Fact Finder, available at
[ h t t p : / / www. c e n s u s . g o v ] .
Table 3. Population Density: United States, California, and
Counties of the SJV, 1980-2003
(population per square mile)
1980 1990 2000 2003
SJV75101121131
Fresno County86112134143
Kern County50678188
Kings County537393100
Madera County30415862
Merced County7092109120
San Joaquin County248343403452
Stanislaus County178248299329
Tulare County51657681
Adjacent counties
Mariposa County8101212
Tuolumne County15222425
California 151 191 217 228
United States64708082
Source: Population data are from Table 2. Land area data are from U.S. Department of Commerce,
U.S. Census Bureau, 2000 Census of Population and Housing, Summary Population and Housing
Characteristics, PHC-1-1, Washington, U.S. Govt. Print. Off., 2002, p. 11; U.S. Department of
Commerce, Bureau of the Census, 1990 Census of Population and Housing, Population and Housing
Unit Counts, United States, CPS-2-1, Washington, U.S. Govt. Print. Off., 2002, p. 116; and U.S.
Department of Commerce, Bureau of the Census, 1980 Census of the Population, Characteristics of
the Population, Number of Inhabitants, California, PC80-1-A6, Washington, U.S. Govt. Print. Off.,
1982, p. 6.8, available at [http://www2.census.gov/prod2/decennial/documents/1980a_caAB-01.pdf].
Table 4. Population: United States, Kentucky, Virginia,
Tennessee, West Virginia, and Central Appalachian Counties of
the Appalachian Regional Commission, 1980-2003
Population
(in 1000s)Percent change
1980 1990 2000 2003 1990 2000 2003
Central ARC Counties1,8371,7321,7831,785-5.73.02.9
K e ntucky 3,660 3,687 4,042 4,118 0.7 9.6 10.5
T e nnessee 4,591 4,877 5,689 5,842 6.2 16.7 16.5
V i rginia 5,347 6,189 7,079 7,386 15.8 14.4 16.2
West Virginia1,9501,7931,8081,810-8.00.80.9
United States226,54248,71281,42290,819.813.116.9
Sources: U.S. Department of Commerce, U.S. Census Bureau, 2000 Census of Population and
Housing, United States Summary, PHC-3-1, Washington, U.S. Govt. Print. Off., 2004, p. 44; and U.S.
Department of Commerce, U.S. Census Bureau, American Fact Finder, available at
[ h t t p : / / www. c e n s u s . g o v ] .
Table 5. Population Projections: United States, California, and
Counties of the SJV, to 2010 and 2020
Population
P o pul at i o n projections
(in 1000s)(in 1000s)PercentPercent
change,change,
2003-2010 2003-20202003 2010 2020
SJ V 3,583 4,097 4,981 14.3 39.0
Fresno County8509501,11511.731.1
Kern County71380995013.433.2
Kings County13915618512.833.3
Madera County13315018412.637.8
Merced County23227836119.955.8
San Joaquin County63374798918.156.4
Stanislaus County49255965413.632.8
Tulare County39144754414.539.1
Adjacent counties
Mariposa County1819214.515.8
Tuolumne County5760655.515.3
California 35,484 39,247 43,852 10.6 23.6
United States290,810308,936335,8056.215.5
Sources: Projections of U.S. population growth are from the U.S. Department of Commerce, Bureau
of the Census, U.S. Interim Projections by Age, Sex, Race, and Hispanic Origin, available at
[http://www.census.gov/population/www/projections/popproj.html]. Projections for California are
from the State of California, Department of Finance, Population Projections by Race/Ethnicity for
California and Its Counties 2000-2050, Sacramento, California, May 2004, available at
[ h t t p : / / www. d o f . c a . g o v / h t ml / d e m o g r a p / d r u _ p u b l i c a t i o n s / p r o j e c t i o n s / p 1 . h t m] .
Table 6. Population Projections: United States, Kentucky,
Virginia, Tennessee, West Virginia, and Central Counties of the
Appalachian Regional Commission, to 2010 and 2020
Population
P o pul at i o n projections
(in 1000s)(in 1000s)PercentPercent
change,change,
2003-2010 2003-20202003 2010 2020
Central ARC Counties1,7851,8261,8832.35.5
K e ntucky 4,118 4,326 4,661 5.1 13.2
T e nnessee 5,842 6,426 7,195 10.0 23.2
V i rginia 7,386 7,893 8,602 6.9 16.5
West Virginia1,8101,7691,826-2.30.9
United States290,810308,936335,8056.215.5
Sources: Projections of U.S. population growth are from the U.S. Department of Commerce, Bureau
of the Census, U.S. Interim Projections by Age, Sex, Race, and Hispanic Origin, available at
[http://www.census.gov/population/www/projections/popproj.html]. Projections for Kentucky are
from Kentucky State Data Center and Kentucky Population Research, Population Projections,
available at [ksdc.louisville.edu]. Projections for Tennessee are from Tennessee Advisory
Commission on Intergovernmental Relations and the University of Tennessee Center for Business and
Economic Research, Population Projections for the State of Tennessee, 2005-2025, available at
[cber.bus.utk.edu/census/tnpopdat.htm]. Projections for Virginia are from Virginia Employment
Commission, County/City/State Population Data, available at
[http://www.vec.virginia.gov/pdf/pop_projs.pdf].
Projections for West Virginia are from West Virginia University, Regional Research Institute,
Population Estimates and Projections, available at [http://www.rri.wvu.edu/wvpop4.htm].
Table 7. Estimated Percent of the Population That Moved
During the Previous Year: United States, California, and
Metropolitan Statistical Areas of the SJV, 1989-2004
1989-1991 1999-2001 2002-2004
SJV MSAs
Percent Who Moved20.0%19.1% a18.0%
Percent Who Lived Elsewhere in the19.2%17.6%16.7%
Percent Who Lived Abroad0.7%1.5%1.2%
California
Percent Who Moved21.6%17.0%15.5%
Percent Who Lived Elsewhere in the20.0%16.0%14.6%
Percent Who Lived Abroad1.5%1.0%0.9%
United States
Percent Who Moved17.5%15.4%14.2%
Percent Who Lived Elsewhere in the16.9%14.8%13.7%
Percent Who Lived Abroad0.6%0.6%0.5%
Source: Estimates calculated by CRS from the March Current Population Surveys (CPS) for 1989-
1991, 1999-2001, and 2002-2004.
Notes: In order to increase the sample sizes, all estimates are three-year averages. An MSA consists
of an urban center (or centers) and adjacent communities that have a high degree of economic and
social integration.
a. Data for 1998 and later years may not be comparable to data for 1988-1990. Data for 1998 and
later years include an MSA for Merced County. For 1998 and later, the Fresno MSA includes
both Fresno and Madera counties.
Table 8. Estimates of Where Persons Who Moved During the
Previous Year Lived One Year Earlier: United States, California,
and Metropolitan Statistical Areas of
the SJV, 1989-2004
1989-1991 1999-2001 2002-2004
SJV MSAs
Lived in the same county72.7%70.5% a69.1%
Lived in a different county in California18.4%13.3%16.1%
Lived in a different state5.2%8.3%8.0%
Lived abroad3.7%7.9%6.7%
California
Lived in the same county64.0%66.9%62.1%
Lived in a different county in California18.9%18.6%22.7%
Lived in a different state9.9%8.6%9.7%
Lived abroad7.2%5.9%5.5%
United States
Lived in the same county60.4%57.3%58.0%
Lived in a different county in the
same state18.7%19.8%19.7%
Lived in a different state17.4%19.0%18.9%
Lived abroad3.5%3.9%3.4%
Source: Estimates calculated by CRS from the March Current Population Surveys (CPS) for 1989-
1991, 1999-2001, and 2002-2004.
Notes: In order to increase the sample sizes, all estimates are three-year averages. An MSA consists
of an urban center (or centers) and adjacent communities that have a high degree of economic and
social integration. Details may not sum to 100% because of rounding.
a. Data for 1998 and later years may not be comparable to data for 1988-1990. Data for 1998 and
later years include an MSA for Merced County. For 1998 and later, the Fresno MSA includes
both Fresno and Madera counties.
Table 9. Percent of the Population Foreign-Born: United
States, California, and Counties of the SJV, 1980-2003
1980 1990 2000 2003
SJ V 10.4% 15.8% 19.8%
Fresno 10.6% 17.8% 21.1% 19.5%
K e rn 8.6% 12.2% 16.9% 18.1%
K i ngs 10.5% 14.1% 16.0%
Madera 9.8% 14.9% 20.1%
Merced 13.8% 19.8% 24.8%
San Joaquin10.6%16.4%19.5%21.8%
Stanislaus 10.0% 14.3% 18.3% 17.0%
T ulare 11.3% 17.6% 22.6% 23.1%
Adjacent counties
Mariposa 3.1% 2.6% 2.8%
T uolumne 3.2% 4.0% 3.2%
California 15.1% 21.7% 26.2% 26.5%
United States6.2%7.9%11.1%11.9%
Source: U.S. Department of Commerce, U.S. Census Bureau, American Fact Finder, available at
[http://www.census.gov]; U.S. Department of Commerce, Bureau of the Census, 1990 Census of
Population and Housing: Summary Social, Economic and Housing Characteristics, U.S. Govt. Print.
Off, 1992; U.S. Department of Commerce, Bureau of the Census, 1980 Census of Population: General
Social and Economic Characteristics, U.S. Govt. Print. Off., 1983.
Notes: Foreign-born persons include both naturalized U.S. citizens and non-U.S. citizens. Non-
citizens include legal permanent residents, non-immigrants who are in the United States temporarily
(e.g., on business or as students), and unauthorized aliens. Data for 2003 are from the American
Community Survey (ACS), which is the planned replacement for the long questionnaire of the
decennial census. The 2003 ACS did not cover all counties.
Table 10. Percent of Population of Hispanic Origin: United
States, California, and the Counties of
the SJV, 1980-2003
1980 1990 2000 2003
SJ V 22.9% 29.6% 39.8%
Fresno 29.2% 34.7% 44.1% 46.2%
K e rn 21.6% 27.7% 38.4% 41.8%
K i ngs NA 33.4% 43.6%
Madera 27.1% 34.2% 44.3%
Merced 25.3% 32.0% 45.4%
San Joaquin19.2%22.7%30.5%33.5%
Stanislaus 15.0% 21.6% 31.8% 36.2%
T ulare 29.8% 38.2% 50.8% 54.2%
Adjacent counties
Mariposa 4.3% 4.8% 7.5%
T uolumne 5.2% 8.0% 8.1%
California 19.2% 25.4% 32.4% 34.6%
United States6.4%8.8%12.5%13.9%
Source: U.S. Department of Commerce, U.S. Census Bureau, American Fact Finder, available at
[http://www.census.gov]; U.S. Department of Commerce, Bureau of the Census, 1980 Census of
Population: General Social and Economic Characteristics, U.S. Govt. Print. Off., 1983.
Notes: A person of Hispanic origin may be of any race. Data for 2003 are from the American
Community Survey (ACS), which is the planned replacement for the long questionnaire of the
decennial census. The 2003 ACS did not cover all counties.
Table 11. Percent of the Population Mexican-Born: United
States, California, and Counties of the SJV, 1980-2003
1980 1990 2000 2003
SJ V 5.6% 8.8% 13.5%
Fresno 6.0% 9.9% 14.0% 12.3%
K e rn 5.2% 8.1% 12.6% 11.8%
K i ngs 5.5% 9.2% 12.7%
Madera 6.4% 11.6% 17.4%
Merced 7.8% 10.9% 17.3%
San Joaquin4.0%6.0%10.0%11.2%
Stanislaus 4.3% 6.8% 11.4% 9.9%
T ulare 7.6% 12.5% 18.6% 19.2%
Adjacent counties
Mariposa 0.4% 0.2% 0.6%
T uolumne 0.5% 1.4% 0.6%
California 5.4% 8.3% 11.6% 11.4%
United States1.0%1.7%3.3%3.5%
Source: U.S. Department of Commerce, U.S. Census Bureau, American Fact Finder, available at
[http://www.census.gov]; U.S. Department of Commerce, Bureau of the Census, 1990 Census of
Population: Social and Economic Characteristics, U.S. Govt. Print. Off, 1993; U.S. Department of
Commerce, Bureau of the Census, 1980 Census of Population: General Social and Economic
Characteristics, U.S. Govt. Print. Off., 1983.
Note: Data for 2003 are from the American Community Survey (ACS), which is the planned
replacement for the long questionnaire of the decennial census. The 2003 ACS did not cover
all counties.
Figure 3. Percent Change in Mexican-Born Population by County,
Data Source: U.S. Bureau of the Census
Table 12. Distribution of Population by Race: United States,
California, and the Counties of the SJV, 1980-2003
198019902000 a2003 a
SJ V
White 77.6%69.6%59.1%
Black 4.2%4.4%4.7%
American Indian and Native Alaskan1.3%1.2%1.4%
Asian and Pacific Islander 2.9%6.8%6.3%
Other 14.0%18.0%23.3%
Two or more races 5.3%
Fresno County
White 74.8%63.5%54.1%70.9%
Black 5.0%4.9%5.1%5.1%
American Indian and Native Alaskan1.2%1.1%1.6%1.0%
Asian and Pacific Islander 3.0%8.6%8.1%8.4%
Other 16.0%21.9%26.0%10.5%
Two or more races 5.1%4.0%
Kern County
White 77.4%69.8%61.4%77.4%
Black 5.2%5.5%5.9%5.4%
American Indian and Native Alaskan1.7%1.3%1.4%1.3%
Asian and Pacific Islander 2.0%3.0%3.4%3.6%
Other 13.7%20.3%23.5%10.1%
Two or more races 4.5%2.3%
Kings County
White 75.3%63.9%53.5%
Black 4.9%8.3%8.1%
American Indian and Native AlaskanNA1.5%1.6%
Asian and Pacific Islander NA3.6%3.1%
Other 19.8%22.7%28.4%
Two or more races 5.2%
Madera County
White 75.7%72.2%62.5%
Black 3.4%2.8%3.9%
American Indian and Native Alaskan1.8%1.5%2.6%
Asian and Pacific Islander 1.1%1.4%1.5%
Other 18.0%22.0%24.3%
Two or more races 5.2%
198019902000 a2003 a
Merced County
White 77.9%67.5%55.8%
Black 5.0%4.9%3.7%
American Indian and Native Alaskan1.0%0.9%1.0%
Asian and Pacific Islander 2.4%8.3%7.1%
Other 13.7%18.3%26.2%
Two or more races 6.2%
San Joaquin County
White 76.8%73.5%57.9%68.9%
Black 5.6%5.6%6.5%7.0%
American Indian and Native Alaskan1.3%1.2%1.0%1.2%
Asian and Pacific Islander 6.3%12.4%11.9%14.4%
Other 10.1%7.2%16.5%5.8%
Two or more races 6.2%2.6%
Stanislaus County
White 88.1%80.4%69.1%80.7%
Black 1.2%1.6%2.4%2.8%
American Indian and Native Alaskan1.7%1.2%1.2%1.0%
Asian and Pacific Islander 1.7%5.1%4.5%4.8%
Other 7.2%11.7%16.9%8.2%
Two or more races 6.0%2.5%
Tulare County
White 74.4%65.9%57.9%64.3%
Black 1.5%1.5%1.7%1.5%
American Indian and Native Alaskan1.3%1.3%1.3%0.9%
Asian and Pacific Islander 2.1%4.4%3.4%3.3%
Other 20.8%27.0%31.0%27.2%
Two or more races 4.6%2.7%
Adjacent Counties
Mariposa County
White NA92.4%88.4%
Black NA1.0%0.6%
American Indian and Native AlaskanNA4.5%3.1%
Asian and Pacific Islander NA0.9%0.7%
Other NA1.2%2.9%
Two or more races 4.3%
198019902000 a2003 a
Tuolumne County
White 94.7%90.6%89.4%
Black NA3.1%2.3%
American Indian and Native Alaskan1.6%2.2%1.8%
Asian and Pacific Islander NA0.8%0.9%
Other 3.7%3.4%2.6%
Two or more races 3.0%
Califo r ni a
White 77.0%69.1%59.4%66.2%
Black 7.7%7.4%6.6%6.2%
American Indian and Native Alaskan1.0%0.8%0.9%0.8%
Asian and Pacific Islander 5.5%9.6%11.2%12.2%
Other 8.8%13.1%16.9%11.6%
Two or more races 5.0%2.9%
United States
White 83.4%80.3%75.1%76.2%
Black 11.7%12.0%12.2%12.1%
American Indian and Native Alaskan0.7%0.8%0.9%0.8%
Asian and Pacific Islander 1.6%2.9%3.7%4.3%
Other 2.5%3.9%5.5%4.8%
Two or more races 2.6%1.9%
Source: U.S. Department of Commerce, U.S. Census Bureau, American Fact Finder, available at
[http://www.census.gov]; U.S. Department of Commerce, Bureau of the Census, 1980 Census of
Population: General Social and Economic Characteristics, U.S. Govt. Print. Off., 1983.
Note: Details may not sum to 100% because of rounding. Data for 2003 are from the American
Community Survey (ACS), which is the planned replacement for the long questionnaire of the
decennial census. The 2003 ACS did not cover all counties.
Table 13. Distribution of Population by Gender: United States,
California, and the Counties of the SJV, 1980-2003
1980 1990 2000 2003
SJ V
Male49.5%50.0%50.2%
Female50.5%50.0%49.8%
Fresno County
Male49.2%49.4%49.9%49.9%
Female50.8%50.6%50.1%50.1%
Kern County
Male49.8%50.3%51.2%49.9%
Female50.2%49.7%48.8%50.1%
Kings County
Male50.5%53.7%57.4%
Female49.5%46.3%42.6%
Madera County
Male50.5%50.4%47.6%
Female49.5%49.6%52.4%
Merced County
Male50.2%50.5%49.6%
Female49.8%49.5%50.4%
San Joaquin County
Male49.4%50.6%49.8%49.5%
Female50.6%49.4%50.2%50.5%
Stanislaus County
Male48.9%49.0%49.1%49.6%
Female51.1%51.0%50.9%50.4%
Tulare County
Male49.4%49.6%49.8%50.0%
Female50.6%50.4%50.2%50.0%
Adjacent Counties
Mariposa County
Male51.0%49.2%50.7%
Female49.0%50.8%49.3%
1980 1990 2000 2003
Tuolumne County
Male50.8%53.2%52.6%
Female49.2%46.8%47.4%
Califo r ni a
Male49.3%50.0%49.7%49.6%
Female50.7%50.0%50.3%50.4%
United States
Male48.6%48.7%49.0%48.9%
Female51.4%51.3%51.0%51.1%
Source: U.S. Department of Commerce, U.S. Census Bureau, American Fact Finder, available at
[http://www.census.gov]; U.S. Department of Commerce, Bureau of the Census, 1980 Census of
Population: General Social and Economic Characteristics, U.S. Govt. Print. Off., 1983.
Note: Data for 2003 are from the American Community Survey (ACS), which is the planned
replacement for the long questionnaire of the decennial census. The 2003 ACS did not cover all
co unties.
Table 14. Distribution of Population by Age: United States,
California, and the Counties of the SJV, 1980-2003
1980 1990 2000 2003
SJ V
Less Than 58.6%9.2%8.2%
5 to 1416.3%17.7%18.4%
15-2419.0%14.6%15.5%
25-54 (prime age)36.9%41.0%40.9%
55-649.0%7.2%7.1%
65 and over10.2%10.3%9.9%
Fresno County
Less Than 58.3%9.3%8.4%8.2%
5 to 1415.8%17.6%18.4%17.5%
15-2419.7%15.3%16.3%16.6%
25-54 (prime age)37.3%40.4%40.3%40.4%
55-648.8%7.1%6.8%7.7%
65 and over10.0%10.2%9.9%9.5%
Kern County
Less Than 58.9%9.6%8.3%8.5%
5 to 1416.3%17.6%18.4%17.9%
15-2418.8%14.1%15.3%16.4%
25-54 (prime age)37.0%41.8%41.6%39.9%
55-649.2%7.2%7.0%8.1%
65 and over9.7%9.7%9.4%9.1%
Kings County
Less Than 59.8%9.3%7.9%
5 to 1417.4%17.1%16.5%
15-2420.5%16.1%16.1%
25-54 (prime age)36.4%43.7%46.1%
55-647.3%6.1%5.9%
65 and over8.6%7.7%7.5%
Madera County
Less Than 59.2%8.4%7.6%
5 to 1417.4%18.0%16.8%
15-2416.4%13.4%14.8%
25-54 (prime age)36.9%39.4%41.8%
55-649.2%8.7%8.2%
1980 1990 2000 2003
65 and over10.9%12.1%10.7%
Merced County
Less Than 59.4%10.1%8.7%
5 to 1417.2%19.2%20.2%
15-2420.4%15.3%15.7%
25-54 (prime age)36.2%39.1%39.1%
55-648.2%7.1%6.9%
65 and over8.5%9.2%9.4%
San Joaquin County
Less Than 57.8%8.6%7.8%7.7%
5 to 1415.7%16.6%18.0%17.2%
15-2418.4%14.5%15.0%15.7%
25-54 (prime age)37.1%41.7%41.2%41.7%
55-649.7%7.5%7.4%8.4%
65 and over11.2%11.1%10.6%9.4%
Stanislaus County
Less Than 58.2%9.1%7.9%8.0%
5 to 1416.1%17.2%18.2%16.7%
15-2418.4%13.8%14.7%15.7%
25-54 (prime age)37.5%41.7%41.5%42.0%
55-649.0%7.2%7.3%8.2%
65 and over10.9%10.9%10.4%9.4%
Tulare County
Less Than 59.2%9.3%8.9%9.1%
5 to 1417.5%19.0%19.3%18.3%
15-2418.5%14.7%16.2%17.0%
25-54 (prime age)35.1%39.2%39.0%38.9%
55-649.1%7.1%7.0%7.7%
65 and over10.7%10.7%9.7%9.1%
Adjacent Counties
Mariposa County
Less Than 55.3%6.3%4.8%
5 to 1413.0%12.8%13.0%
15-2416.6%9.7%11.0%
25-54 (prime age)37.4%41.9%41.3%
55-6412.3%11.4%12.9%
1980 1990 2000 2003
65 and over15.4%17.8%17.0%
Tuolumne County
Less Than 56.5%5.7%4.7%
5 to 1413.7%13.4%11.8%
15-2415.5%10.7%12.1%
25-54 (prime age)38.3%42.9%41.6%
55-6412.4%10.9%11.4%
65 and over13.7%16.5%18.5%
Califo r ni a
Less Than 57.2%8.0%7.2%7.3%
5 to 1414.6%14.2%15.8%15.4%
15-2418.9%15.0%14.1%13.9%
25-54 (prime age)39.9%44.8%44.7%44.3%
55-649.3%7.5%7.6%8.9%
65 and over10.1%10.5%10.6%10.3%
United States
Less Than 57.2%7.3%6.8%7.0%
5 to 1415.4%14.2%14.6%14.5%
15-2418.7%14.6%13.8%13.4%
25-54 (prime age)37.8%42.8%43.7%43.4%
55-649.6%8.5%8.6%9.8%
65 and over11.3%12.5%12.4%12.0%
Source: U.S. Department of Commerce, U.S. Census Bureau, American Fact Finder, available at
[http://www.census.gov]; U.S. Department of Commerce, Bureau of the Census, 1980 Census of
Population: General Social and Economic Characteristics, U.S. Govt. Print. Off., 1983. Data for
2003 are from the American Community Survey (ACS), which is the planned replacement for the long
questionnaire of the decennial census. The 2003 ACS did not cover all counties
Note: Details may not sum to 100% because of rounding. Data for 2003 are from the American
Community Survey (ACS), which is the planned replacement for the long questionnaire of
the decennial census. The 2003 ACS did not cover all counties.
County and Regional Poverty Rates. Socioeconomic conditions in the
SJV as measured by a range of variables (including per capita income, poverty,
unemployment rates, median household income, Medicaid and Food Stamp
participation rates, and sources of personal income) reveal an area that falls
significantly below national and California averages. The 2000 poverty rate for the
SJV (20.5%), for example, was higher than the national rate (12.4%), California
(14.2%), and the 410 county ARC region (13.6%) (Table 15 and Table 16). While
the SJV’s poverty rate was somewhat closer both to the national and California
averages in 1980, the SJV counties saw significant increases in their poverty rates by
1990. These high rates continued to increase during the 1990s and increased between
1990 and 2000. However, in 2003, the rates declined somewhat in the 5 counties for
which there were data, as they did in California. Poverty rates in the United States,
however, rose slightly between 2000 and 2003. The two adjacent counties of
Mariposa and Tuolumne had 2000 poverty rates of 14.8% and 11.4% respectively.
Figure 4 maps county poverty rates for the SJV and other California counties.
Poverty rates for the entire 410 county ARC region, 1980-2000, were significantly
lower than those of the San Joaquin counties, although some Appalachian states had
poverty rates comparable to the SJV. ARC poverty rates were about 2.5 percentage
points higher than the United States during the decades 1980-2000, although ARC
area poverty rates did vary by state (Table 17).
Figure 4. Percent of Persons Below Poverty Level by County (2000)
Data Source: U.S. Bureau of the Census
Turning to the 68 counties of Central Appalachia, the picture is different. In
1980, Central Appalachia had a poverty rate of 23.0% compared to a rate in the SJV
of 13.9%. In 1990, poverty rates for both Central Appalachia and the SJV had risen
to 26.9% and 18.3% respectively. Central Appalachia’s poverty rate was also higher
than the rate for all the Appalachian parts of Kentucky, Tennessee, Virginia, and
West Virginia in 1980, 1990, and 2000 (Table 16 and Table 17). By 2000, Central
Appalachia’s poverty rate had fallen to 23.2% while the SJV rate had increased to
20.5%. In 2003, some counties of the SJV also had somewhat lower poverty rates
than were evident in 2000. Poverty rates also fell in the four Appalachian states
where the 68 counties are located (Table 17).
For the entire ARC defined region, the 1980 poverty rate was 14.1% (Table 16).
This ARC-wide rate was lower than the rate for all the Appalachian parts of
Kentucky, Tennessee, Virginia, and West Virginia in 1980. Kentucky’s Appalachian
region alone had a poverty rate of 26%, highest among all 13 state Appalachian
regions (Table 17). The ARC-wide rate, 1990-2000, was always higher than the
U.S. rate, showing that Appalachia today still represents a region that is more
impoverished than the United States as a whole. By 2000, the ARC-wide region’s
poverty rate declined to 13.6%, still lower than the poverty rates for all the
Appalachian parts of Kentucky, Tennessee, Virginia, and West Virginia. This
relatively low rate of the ARC-wide region suggests the possible statistical skewing
that this analysis tried to avoid by focusing predominantly on the 68 county Central
Appalachian area.
Table 15. Portion of the Population Below Poverty: United
States, California, and Counties of the SJV, 1980-2003
1980 1990 2000 2003
SJ V 13.9% 18.3% 20.5% NA
Fresno 14.5% 21.4% 22.9% 21.8%
K e rn 12.6% 16.9% 20.8% 18.1%
K i ngs 14.6% 18.2% 19.5%
Madera 15.7% 17.5% 21.4%
Merced 14.7% 19.9% 21.7%
San Joaquin13.3%15.7%17.7%14.2%
Stanislaus 11.9% 14.1% 16.0% 12.9%
T ulare 16.5% 22.6% 23.9% 22.9%
Adjacent counties
Mariposa 11.5% 12.7% 14.8%
T uolumne 11.9% 9.1% 11.4%
California 11.4% 12.5% 14.2% 13.4%
United States12.4%13.1%12.4%12.7%
Sources: U.S. Department of Commerce, U.S. Census Bureau, American Fact Finder, available at
[http://www.census.gov]; U.S. Department of Commerce, Bureau of the Census, 1980 Census of
Population: General Social and Economic Characteristics, U.S. Govt. Print. Off., 1983.
Note: Data for 2003 are from the American Community Survey (ACS), which is the planned
replacement for the long questionnaire of the decennial census. The 2003 ACS did not cover all
co unties.
Table 16. Appalachian Regional Commission Poverty Rates,
1980-2000
Persons forPersons
WhomBelowPovertyPercent of
State Y ear P overty P overty Rat e U.S.
Status isLevel Average
Determined
Totals, Appalachian Portion of the State
Alabama 1980 2,421,498 408,883 16.9 136.1
1990 2,510,095 404,533 16.1 122.9
2000 2,767,821 397,223 14.4 115.9
Georgi a 1980 1,124,481 140,896 12.5 101
1990 1,520,643 154,611 10.2 77.5
2000 2,169,854 200,543 9.2 74.7
K e ntucky 1980 1,081,384 281,333 26 209.7
1990 1,045,741 303,238 29 221
2000 1,109,411 271,113 24.4 197.4
Maryland 1980 211,771 25,296 11.9 96.3
1990 212,688 26,481 12.5 94.9
2000 220,722 25,719 11.7 94.1
Mississippi 1980 542,150 125,151 23.1 186.1
1990 551,305 129,538 23.5 179.1
2000 598,698 116,283 19.4 156.9
New York19801,031,537124,1561297
1990 1,034,063 133,032 12.9 98.1
2000 1,016,532 138,586 13.6 110.1
Nor t h 1980 1,187,272 164,175 13.8 111.5
Carolina
1990 1,270,693 158,185 12.4 94.9
2000 1,482,507 173,822 11.7 94.7
Ohio 1980 1,346,905 169,992 12.6 101.8
1990 1,334,561 232,297 17.4 132.7
Persons forPersons
WhomBelowPovertyPercent of
State Y ear P overty P overty Rat e U.S.
Status isLevel Average
Determined
Totals, Appalachian Portion of the State
Pennsyl va nia 1980 5,847,250 586,629 10 80.9
1990 5,593,189 696,729 12.5 95
2000 5,613,487 639,853 11.4 92.1
South 1980 770,339 96,995 12.6 101.5
Carolina
1990 862,416 99,634 11.6 88.1
2000 1,000,780 117,314 11.7 94.7
T e nnessee 1980 2,029,828 337,437 16.6 134
1990 2,095,424 337,709 16.1 122.9
2000 2,420,962 342,706 14.2 114.4
V i rginia 1980 637,134 99,104 15.6 125.4
1990 614,437 112,245 18.3 139.3
2000 638,257 100,438 15.7 127.1
West 1980 1,914,081 286,995 15 120.9
Virginia
1990 1,755,331 345,093 19.7 149.9
2000 1,763,866 315,794 17.9 144.6
United 1980 220,845,766 27,392,580 12.4 100
States
1990 241,997,859 31,742,864 13.1 100
2000 273,882,232 33,899,812 12.4 100
ARC Region198020,145,6302,847,04214.1113.9
1990 20,400,586 3,133,325 15.4 117.1
2000 20,212,416 3,030,896 13.6 110.2
Source: Appalachian Regional Commission
Table 17. Portion of the Population Below Poverty: United
States, Kentucky, Virginia, Tennessee, West Virginia, and
Central Counties of the ARC, 1980-2003
1980 1990 2000 2003
Central ARC Counties23.0%26.9%23.2%NA
K e ntucky 17.6% 19.0% 15.8% 17.4%
T e nnessee 16.5% 15.7% 13.5% 13.8%
V i rginia 11.8% 10.2% 9.6% 9.0%
West Virginia15.0%19.7%17.9%18.5%
United States12.4%13.1%12.4%12.7%
Sources: U.S. Department of Commerce, U.S. Census Bureau, American Fact Finder,
available at [http://www.census.gov]; U.S. Department of Commerce, Bureau of the Census,
Print. Off., 1983.
Other Poverty Measures: Food Stamps, Public Assistance Income,
Health Insurance, and Medicaid. Poverty rates provide one useful perspective
on socioeconomic well-being. Poverty rates use income thresholds weighted for
different household sizes. Other indicators of a region’s degree of poverty can
include the proportion of the population receiving food stamps, the percent of
households reporting public assistance income, the population without health
insurance, and the percent of the population enrolled in Medicaid. Medicaid, for
example, is consistent with an income maintenance program because payments are
made to households with lower income, or with medical expenses that are beyond the
household’s financial capacity. These can be imperfect regional measures, however,
because the percent of a population receiving assistance from some social welfare
program may be, and often is, lower than the percent of the population that is actually
eligible by income level to receive assistance under the particular program. For
example, immigrants may be unaware of their eligibility for particular programs, or,
if they are knowledgeable, fail to take advantage of the assistance. According to the
Appalachian Service Project in Johnson City, Tennessee, a 1992 survey of a 10-
county area in southwestern Virginia found that of 90,197 families qualified for food
stamps, only 51,649 received food stamp assistance.52 Still, these additional
indicators can serve as supporting evidence about the depth and breadth of regional
poverty.
Food Stamps. The inability to buy sufficient food is a significant indicator
of poverty. Food stamp eligibility indicates an income insufficient to purchase
adequate food. Data on the SJV’s MSAs three-year averages of food stamp use show
that the SJV has a higher percent of households receiving food stamps than either
California or the United States (Table 18). In the period 1988-1990, 12.1% of SJV
households within MSAs received food stamps, compared to 5% of households in
California and 7.2% of households in the United States. Food stamp use increased
to 13% in the period 1998-2000, while the percent of households receiving food
stamps fell in the United States to 5.6% and rose only slightly in California to 5.1%.53
Households receiving food stamps in the SJV fell in the period 2001-2003 to 8.1%,
trending in the same direction as households in the state, which fell to 3.8%. In each
of the three sampling periods, the Visalia-Tulare-Porterville MSA had the highest
proportion of households receiving food stamps. In the period 2001-2003, that MSA
had 15.6% of its households receiving food stamps, down from 19.1% in the 1998-
rising from 8.2% of households in 1988-1990 to 15.8% of households in 1998-2000.
In the period 2001-2003, however, the percent of households receiving food stamps
fell to 8.1%. The Stockton-Lodi MSA saw a steady decrease in the percent of
households receiving food stamps in the three sampling periods, declining from
10.5% to 8.3% to 3.8% respectively. The Bakersfield MSA also had a significant
decrease in the 2001-2003 period, declining to 6.1% of households in 2001-2003
from 14.0% of households in 1998-2000.
Comparable data on household food stamp participation rates across the 68
Central Appalachian counties were not available. Other data on the ARC-defined
Appalachian region in general, and Central Appalachia especially, indicate an area
where food stamps use is high. Per capita funding for food stamps in the 410 county
ARC area was $120.26 in 1990, declining 36% to a per capita expenditure of $77.34
in 2000. For the United States, per capita food stamp funding was $92.00 in 1990,
52 A 2004 Government Accountability Office (GAO) report discussed state efforts to
increase food stamp participation rates among those who are eligible. See Food Stamp
Program: Steps Have Been Taken to Increase Participation of Working Families, but Better
Tracking of Efforts Is Needed. GAO 04-236, March, 2004.
53 The 1996 Personal Responsibility and Work Opportunities Reconciliation Act limited
social welfare benefits to three months in three years for able-bodied adults aged 18-50
without dependents (ABAWD). States, however, were permitted waivers for areas of high
unemployment. California did not have an “ABAWD waiver” to help ABAWDs get
assistance and ABAWD participation fell significantly. The state legislature passed SB 68
in July, 2005 which automatically requires the state to seek a waiver for eligible counties
to the extent permitted by federal law. Given the relatively high proportion of single
farmworkers in the SJV, this measure may provide food stamps to thousands of SJV
residents in coming years.
declining to $59.06 in 2000.54 The 215 county Central Appalachian area as defined
by the ARC, which includes th 68 counties profiled in this chapter, had the highest
per capita expenditures for food stamps among the ARC’s three subareas. Per capita
funding on food stamps in the ARC’s Central Appalachian subregion was $199.26
in 1990, declining to $139.25 in 2000.
54 Black, Dan A. And Seth G. Sanders. Labor Market Performance, Poverty, and Income
Inequality in Appalachia. Report prepared by the ARC and the Population Reference
Bureau. September, 2004.
Table 18. Percent of Households Receiving Food Stamps:
United States, California, and the MSAs of the SJV, 1988-2003
1988-1990 1998-2000 2001-2003
SJV12.1%13.0% a8.1%
Bakersfield (Kern County)9.6%14.0%6.1%
Fresno (Fresno County 1989-1991;
Fresno and Madera Counties later years)14.8%13.8%9.1%
Merced (Merced County)8.2%15.8%8.9%
Modesto (Stanislaus County)NA8.2%6.7%
Stockton-Lodi (San Joaquin County)10.5%8.3%3.8%
Visalia-T ulare-Porterville
(Tulare County)16.3%19.1%15.6%
California 5.0% 5.1% 3.8%
United States7.2%5.6%5.7%
Source: Calculated by CRS from the March Current Population Surveys (CPS) for 1989-1991, 1999-
2001, and 2002-2004. The March CPS collects food stamp information for the previous year.
Notes: In order to increase the sample sizes for each Metropolitan Statistical Area all estimates are
three-year averages. An MSA consists of an urban center (or centers) and adjacent communities that
have a high degree of economic and social integration.
a. Data for 1998 and later years may not be comparable to data for 1988-1990. Data for 1998 and
later years include an MSA for Merced County. For 1998 and later, the Fresno MSA includes
both Fresno and Madera counties.
Public Assistance Income. The percentage of households in the SJV
reporting public assistance income is higher than for California and for the United
States (Table 19). Nearly 14% of households in the SJV received public assistance
income in 1980 and received higher average amounts in most of the counties than the
national or state averages. By 2000, the proportion of households receiving public
assistance income had fallen to 7.8%, down from 15.5% in 1990. Average amounts
of assistance received also fell from $6,384 to $4,808. Data from those SJV counties
reported by the U.S. Census in 2003 showed further declines in the proportion of
county households receiving public assistance income, although the average amounts
increased slightly (Note: Tulare County increased slightly from 8.6% to 8.7%).
Figure 5 maps public assistance income data for the SJV in 2000 and contrast it with
other California counties.
The percentage of households reporting public assistance income is higher in
the SJV than the percentage reporting public assistance income in Central Appalachia
(Table 20). In 1980, 12.8% of Central Appalachian households received public
assistance averaging $2,259. By 2000, only 5.9% of Central Appalachian households
were receiving public assistance income, and the average amounts were lower than
they were 20 years earlier, $2,130. In the four Appalachian states, the proportion of
households receiving public assistance income in 2003 was also lower than it was in
the eight counties of the SJV.
CRS-58
Table 19. Public Assistance Income: United States, California,
and the Counties of the SJV, 1980-2003
1980 1990 2000 2003
Percent ofPercent ofPercent ofPercent of
households withhouseholds withhouseholds withhouseholds with
public assistanceAveragepublic assistanceAveragepublic assistanceAveragepublic assistanceAverage
inco me amount inco me amount inco me amount inco me amount
13.7% $3,096 15.5% $6,384 7.8% $4,808 NA NA
r esno 13.4% $3,230 16.5% $6,636 8.5% $4,969 5.8% $5,060
ern 11.8% $2,860 13.1% $5,595 7.5% $4,471 6.8% $5,282
ings 13.8% $3,060 15.8% $5,765 7.6% $4,124
iki/CRS-RL3318414.5% $3,086 14.9% $5,505 8.0% $5,02414.0% $3,158 16.7% $6,714 9.1% $5,113
g/wan Joaquin14.1%$3,17215.6%$7,3007.2%$4,9645.4%$4,527
s.or
leaktanislaus 13.3% $2,888 14.2% $6,260 6.3% $4,699 3.7% $3,022
ulare 16.8% $3,226 18.2% $5,967 8.6% $4,819 8.7% $5,618
://wiki
httpacent counties
posa 10.6% $2,832 12.2 $5,197 5.0% $4,476
uolumne 8.0% $2,785 10.6 $5,889 4.3% $4,156
ifornia 9 .6% $3,036 9.4 $5,972 4.9% $4,819 3.6% $4,896
ted States8.0%$2,5187.5$4,0783.4%$3,0322.5%$3,084
: U.S. Department of Commerce, U.S. Census Bureau, American Fact Finder, available at [http://www.census.gov]; U.S. Department of Commerce, Bureau of the Census,
ensus of Population: General Social and Economic Characteristics, U.S. Govt. Print. Off., 1983.
Data for 2003 are from the American Community Survey (ACS), which is the planned replacement for the long questionnaire of the decennial census. The 2003 ACS did not cover
unties.
CRS-59
Table 20. Public Assistance Income: United States, Kentucky, Virginia, Tennessee, West Virginia,
and Central Counties of the ARC, 1980-2003
1980 1990 2000 2003
Percent ofPercent ofPercent ofPercent of
households withhouseholds withhouseholds withhouseholds with
public assistanceAveragepublic assistanceAveragepublic assistanceAveragepublic assistanceAverage
inco me amount inco me amount inco me amount inco me amount
tral ARC Counties12.8%$2,25913.9%$3,4995.9%$2,130NANA
tucky 9.7% $2,038 9.6% $3,282 3.8% $2,174 2.0% $2,363
nessee 9 .3% $1,905 8.4% $3,035 3.5% $1,984 2.6% $1,603
iki/CRS-RL33184
g/winia 6.6% $2,166 5.4% $3,394 2.5% $2,242 1.8% $2,528
s.or
leak
t Virginia8.7%$2,3489.7%$3,5454.0%$2,0193.1%$2,588
://wiki
httpted States8.0%$2,5187.5%$4,0783.4%$3,0322.5%$3,084
: U.S. Department of Commerce, U.S. Census Bureau, American Fact Finder, available at [http://www.census.gov]; U.S. Department of Commerce, Bureau of the Census,
ensus of Population: General Social and Economic Characteristics, U.S. Govt. Print. Off., 1983.
Figure 5. Percent of Households Receiving Public Assistance by
County (2000)
Data Source: U.S. Bureau of the Census
Health Insurance. A 2000 study by the Urban Institute found that 14%
percent of U.S. urban residents under age 65 were without health insurance.55 In
2001-2003, 15.2% of the U.S. population were uninsured and 18.7% of the
California population were uninsured. Table 21 shows that the SJV MSAs,
California, and the United States each saw a significant increase in the percent
uninsured between 1988-1990 and 2001-2003. The SJV’s share of its population
without health insurance increased from 12.9% to 20.0% during that time period.
California’s portion of its population without health insurance increased from 14.9%
to 18.7%, while the share of the United States population without health insurance
increased from 10.8% to 15.2%.
Health insurance among low-income individuals is of particular concern in the
SJV. Between 1999 and 2002, public health insurance coverage increased among
two groups of low-income U.S.-citizen children: (1) those with parents who are
native or naturalized U.S. citizens and (2) those with at least one immigrant parent
who is not a U.S. citizen (referred to as mixed-status families). The improvements
in coverage followed efforts on the part of the states and the federal government to
expand coverage of children under Medicaid and the State Children’s Health
Insurance Program (SCHIP) and the introduction of policies directed at improving
Medicaid and SCHIP access for immigrant and non-English speaking families. Still,
nearly 20% of citizen children in low-income mixed-status families remained
uninsured in 2002. This is a rate 74% percent higher than that of children with
citizen parents.56 U.S. Census data in 2003 also showed that 33% of Hispanics
nationally are without health insurance.57
While the percentage of the SJV metropolitan population without health
insurance increased only slightly in the 2001-2003 period, particular MSAs in the
SJV saw larger increases. Fresno’s percent of its population without health insurance
increased to 22.6% in 2001-2003, up from 18.7% in 1998-2000. The percentage of
Modesto residents without insurance also increased, from 15.2% in 1998-2000 to
18.6% in 2001-2003. The percentage without health insurance fell significantly in
Bakersfield, falling from 20.5% in 1998-2000 to 15.7% in 2001-2003.
Data on the percentage of residents without health insurance in the 68 largely
rural Central Appalachian counties were not available. However, rural areas
nationally have rates of uninsured significantly higher than those for urban areas. The
percentage of rural businesses that have health insurance is generally lower than the
rate in urban areas. Table 22 shows that the percentage of the population without
health insurance in each of the four Appalachian states that include the 68 counties
was lower than for both California and the SJV in each three-year sampling period,
55 Ormond, Barbara, Stephen Zuckerman, and Aparna Lhila, “Rural/Urban Differences in
Health Care Are Not Uniform Across States,” Assessing the New Federalism Brief B-11.
Washington, D.C.: Urban Institute. May, 2000.
56 Capps, Randolph, Genevieve M. Kenney, and Michael E. Fix. Health Insurance
Coverage of Children in Mixed-Status Immigrant Families. Washington D.C.: Urban
Institute. November, 2003.
57 U.S. Bureau of the Census. Income, Poverty, and Health Insurance Coverage in the
United States: 2003. August, 2004.
14.8% of its population while the SJV in that period had 20.0% of its population
without health insurance. In some cases, the proportion of uninsured in SJV
metropolitan areas was almost double the rate in some Appalachian states. Central
Appalachian counties, being poorer and more rural, likely had insurance rates lower
than for their respective states.
Medicaid. Additional detail on the extent of poverty in a region as measured
by participation in various income maintenance programs can be provided through
indicators of Medicaid enrollment (Table 23). Consistent with poverty indicators
presented earlier, the SJV has a significant proportion of its residents enrolled in
Medicaid. In the three-year sampling period, 2001-2003, the SJV had nearly 23% of
the population enrolled in Medicaid compared to 14.4% of California and 11.7% of
U.S. residents. Some MSAs in the SJV had rates over 25%. The percentage of
Visalia-Tulare-Porterville’s population enrolled in Medicaid was 34% in 2001-2003,
up from 30.4% in 1998-2000, and 21.1% in 1988-1990. With the exception of
Stockton-Lodi, which saw its percentage of Medicaid enrollment decline from 24.4%
in 1988-1990 to 17.8% in 2001-2003, each of the other SJV MSAs saw increases
during that time frame.
County data on Medicaid enrollments were not available for Central Appalachia.
The respective Appalachian states, however, each had Medicaid enrollments
significantly lower than the SJV region.
Table 21. Percent of Population Without Health Insurance:
United States, California, and the MSAs of the SJV, 1988-2003
1988-1990 1998-2000 2001-2003
SJV12.9%19.8% a20.0%
Bakersfield (Kern County)12.2%20.5%15.7%
Fresno (Fresno County 1989-1991;
Fresno and Madera Counties later years)15.6%18.7%22.6%
Merced (Merced County)NA21.4%18.3%
Modesto (Stanislaus County)8.8%15.2%18.6%
Stockton-Lodi (San Joaquin County)8.4%19.6%20.3%
Visalia-T ulare-Porterville
(Tulare County)17.4%24.6%23.6%
California 14.9% 20.3% 18.7%
United States10.8%15.3%15.2%
Sources: Calculated by CRS from the March Current Population Surveys (CPS) for 1989-1991,
1999-2001, and 2002-2004. The March CPS collects health insurance information for the previous
year.
Notes: Beginning in March 2000, the CPS asked respondents who reported that they were not covered
by a health insurance plan whether they were, in fact, uninsured. This verification question lowered
the reported number of uninsured persons. In order to increase the sample sizes for each MSA, all
estimates are three-year averages. An MSA consists of an urban center (or centers) and adjacent
communities that have a high degree of economic and social integration.
a. Data for 1998 and later years may not be comparable to data for 1988-1990. Data for 1998 and
later years include an MSA for Merced County. For 1998 and later, the Fresno MSA includes
both Fresno and Madera counties.
Table 22. Percent of Population Without Health Insurance:
United States, Kentucky, Virginia, Tennessee, West Virginia,
and Central Counties of the ARC, 1988-2003
1988-1990 1998-2000 2001-2003
Central ARC CountiesNANANA
K e ntucky 10.9% 13.8% 13.3%
T e nnessee 10.5% 11.6% 11.8%
V i rginia 10.0% 13.7% 12.5%
West Virginia10.9%16.1%14.8%
United States10.8%15.3%15.2%
Sources: Calculated by CRS from the March Current Population Surveys (CPS) for 1989-1991,
1999-2001, and 2002-2004. The March CPS collects health insurance information for the previous
year.
Notes: Beginning in March 2000, the CPS asked respondents who reported that they were not covered
by a health insurance plan whether they were, in fact, uninsured. This verification question lowered
the reported number of uninsured persons. In order to increase the sample sizes for each state, all
estimates are three-year averages.
Table 23. Percent of the Population Enrolled in Medicaid:
United States, California, and MSAs of the SJV, 1988-2003
1988-1990 1998-2000 2001-2003
SJV20.6%24.2% a22.9%
Bakersfield (Kern County)17.9%23.9%20.0%
Fresno (Fresno County 1989-1991;
Fresno and Madera Counties later years)23.5%24.0%25.1%
Merced (Merced County)25.1%25.0%
Modesto (Stanislaus County)14.9%19.9%16.2%
Stockton-Lodi (San Joaquin County)24.4%22.8%17.8%
Visalia-T ulare-Porterville
(Tulare County)21.1%30.4%34.0%
California 11.0% 13.2% 14.4%
United States8.3%10.3%11.7%
Sources: Calculated by CRS from the March Current Population Surveys (CPS) for 1989-1991,
1999-2001, and 2002-2004. The March CPS collects health insurance information for the previous
year.
Notes: The estimates from the March CPS of the number of Medicaid enrollees are lower than the
count of Medicaid enrollees from administrative records. In order to increase the sample sizes for
each MSA, all estimates are three-year averages. An MSA consists of an urban center (or centers) and
adjacent communities that have a high degree of economic and social integration.
a. Data for 1998 and later years may not be comparable to data for 1988-1990. Data for 1998 and
later years include an MSA for Merced County. For 1998 and later, the Fresno MSA includes
both Fresno and Madera counties.
Table 24. Percent of the Population Enrolled in Medicaid:
United States, Kentucky, Virginia, Tennessee, West Virginia,
and Central Counties of the ARC, 1988-2003
1988-1990 1998-2000 2001-2003
Central ARC CountiesNANANA
K e ntucky 9.0% 10.2% 12.7%
T e nnessee 11.6% 18.0% 18.0%
V i rginia 6.4% 5.1% 7.3%
West Virginia10.0%14.4%16.3%
United States8.3%10.3%11.7%
Sources: Calculated by CRS from the March Current Population Surveys (CPS) for 1989-1991,
1999-2001, and 2002-2004. The March CPS collects health insurance information for the previous
year.
Notes: The estimates from the March CPS of the number of Medicaid enrollees are lower than the
count of Medicaid enrollees from administrative records. In order to increase the sample sizes for
each state, all estimates are three-year averages.
County and Regional Employment and Income Measures. The
number of employed persons 16 and over has increased in the SJV from 813,000 in
1980 to 1.22 million in 2000 (Table 25), an increase of 49.8% and much higher than
for California during that time period (38.3%). The largest absolute increase was in
Fresno County (87,000) and San Joaquin County (83,000), followed by Kern County
(70,000) and Stanislaus County (68,000). Mariposa and Tuolumne counties saw
increased total employment during that time of 3,000 and 8,000 respectively. Those
persons counted as employed may be employed with full or part-time jobs or hold
more than one job. In the 68 Central Appalachian counties, the number of employed
persons 16 and over increased from 562,000 in 1980 to 634,000 in 2000, an increase
of 12.8%, a significantly lower rate than observed in the SJV (Table 26). Most of
that 72,000 increase in employed persons occurred between 1990 and 2000.
The labor force participation rate estimates the number of 16-and-over persons
in the labor force divided by the size of the corresponding population. The labor
force participation rate in the SJV declined from 60.5% in 1980 to 58.6% in 2000
(Table 27). The participation rate declined or increased only sightly in each SJV
county, 1980-2000. Between 1980 and 1990, California’s labor force participation
rate increased somewhat, as did the United States, but both fell between 1990 and
with Kern and San Joaquin county participation rates increasing the most in
percentage terms. Mariposa County increased from 55.0% to 57.7% between 1980
and 2000. Tuolumne County fell from a rate of 52.0% to 49.4%. In contrast to the
SJV, the Central Appalachia counties saw increases in their labor force participation
rate over the 1980-2000 period, from 47.8% to 49.2% (Table 28). The rates in each
of the respective states also increased during that time frame and from 2000-2003 as
well.
For persons 16 and over, the SJV civilian unemployment rate grew from 9.5%
1980 to 11.9% in 2000 (Table 29). The rate for California over that period increased
from 6.5% to 7.0%. In the United States, the civilian unemployment rate fell from
6.5% in 1980 to 5.8% in 2000, although the rates for both California and the United
States increased from 2000-2003. Each county within the SJV, except Stanislaus
County, saw increases in their unemployment rates between 1980-1990, and 1990-
2000. Stanislaus County saw a decline in its employment rate, from 12.7% in 1980
to 10.0% in 1990, to 11.7% in 2000. Unemployment also fell in Fresno, Kern,
Stanislaus, and Tulare counties between 2000 and 2003. In the Central Appalachian
counties, the unemployment rate fell from 10.6% in 1980 to 8.2% in 2000 (Table
although they fell between 1980 and 2000, they still had the highest rates among the
four states. Although each of the states also saw increases in their unemployment
rates since 2000, Central Appalachia had higher unemployment rates than any of the
respective states.
Table 25. Employment in the United States, California,
and the Counties of the SJV, 1980-2003
(number of persons 16 and over, in 1000s)
1980 1990 2000 2003
SJ V 813 1,082 1,218 NA
Fresno 214 270 301 340
K e rn 162 215 232 271
Kings263340
Madera243342
Merced496675
San Joaquin136196219261
Stanislaus 106 151 174 199
T ulare 95 119 134 152
Adjacent counties
Mariposa467
Tuolumne121820
California 10,640 13,996 14,719 15,638
United States97,639115,681129,722132,422
Sources: U.S. Department of Commerce, U.S. Census Bureau, American Fact Finder, available at
[http://www.census.gov];U.S. Department of Commerce, Bureau of the Census, 1980 Census of
Population: General Social and Economic Characteristics, U.S. Govt. Print. Off., 1983.
Notes: Data refer to the number of persons employed. A person may be employed full-time or part-
time or hold more than one job. The Census Bureau considers people over the age of 16 to be
employed if they are either “at work” or “with a job, but not at work.” “At work” refers to people who
did any work during the reference week as paid employees, worked in their own business or
profession, worked on their own farm, or worked 15 hours or more as unpaid workers on a family farm
or in a family business. “With a job, but not at work” includes people who did not work during the
reference week, but had jobs or businesses from which they were temporarily absent. Excluded from
the employed are people whose only activity consisted of repair work or housework around their
homes or unpaid volunteer work for religious or charitable organizations. Also excluded are people
on active duty in the U.S. Armed Forces. The reference week is the full calendar week proceeding the
date on which the respondent completed the census questionnaire. Data for 2003 are from the
American Community Survey (ACS), which is the planned replacement for the long questionnaire of
the decennial census. The 2003 ACS did not cover all counties.
Table 26. Employment in the United States, Kentucky, Virginia,
Tennessee, West Virginia, and Central Counties of the ARC,
1980-2003
(number of persons 16 and over, in 1000s)
1980 1990 2000 2003
Central ARC Counties562580634NA
K e ntucky 1,388 1,564 1,798 1,770
T e nnessee 1,915 2,251 2,652 2,715
V i rginia 2,348 3,028 3,413 3,524
West Virginia689671733723
United States97,639115,681129,722132,422
Sources: U.S. Department of Commerce, U.S. Census Bureau, American Fact Finder, available at
[http://www.census.gov];U.S. Department of Commerce, Bureau of the Census, 1980 Census of
Population: General Social and Economic Characteristics, U.S. Govt. Print. Off., 1983.
Notes: Data refer to the number of persons employed. A person may be employed full-time or part-
time or hold more than one job. The Census Bureau considers people over the age of 16 to be
employed if they are either “at work” or “with a job, but not at work.” “At work” refers to people who
did any work during the reference week as paid employees, worked in their own business or
profession, worked on their own farm, or worked 15 hours or more as unpaid workers on a family farm
or in a family business. “With a job, but not at work” includes people who did not work during the
reference week, but had jobs or businesses from which they were temporarily absent. Excluded from
the employed are people whose only activity consisted of repair work or housework around their
homes or unpaid volunteer work for religious or charitable organizations. Also excluded are people
on active duty in the U.S. Armed Forces. The reference week is the full calendar week proceeding the
date on which the respondent completed the census questionnaire.
Table 27. Labor Force Participation Rate: United States,
California, and the Counties of the SJV, 1980-2003
(persons 16 and over)
1980 1990 2000 2003
SJ V 60.5% 61.6% 58.6% NA
Fresno 61.7% 62.5% 59.8% 63.2%
K e rn 60.7% 62.0% 56.2% 63.0%
K i ngs 60.1% 53.9% 49.3%
Madera 59.0% 59.5% 53.5%
Merced 60.6% 62.2% 59.5%
San Joaquin58.5%60.9%59.8%64.9%
Stanislaus 61.7% 62.8% 61.2% 61.9%
T ulare 59.3% 61.1% 59.8% 62.6%
Adjacent counties
Mariposa 55.0% 55.5% 57.7%
T uolumne 52.0% 49.3% 49.4%
California 63.7% 66.6% 62.2% 65.2%
United States61.6%64.9%63.7%65.9%
Sources:. U.S. Department of Commerce, U.S. Census Bureau, American Fact Finder, available at
[http://www.census.gov]; U.S. Department of Commerce, Bureau of the Census, 1980 Census of
Population: General Social and Economic Characteristics, U.S. Govt. Print. Off., 1983.
Note: The labor force participation rate is the number of persons in the labor force divided by the size
of the corresponding population. The labor force includes all persons classified as being in the civilian
labor force (that is, “employed” and “unemployed” persons), plus members of the U.S. Armed Forces
— people on active duty in the Army, Air Force, Navy, Marine Corps, and Coast Guard. Data for
2003 are from the American Community Survey (ACS), which is the planned replacement for the long
questionnaire of the decennial census. The 2003 ACS did not cover all counties.
Table 28. Labor Force Participation Rate: United States,
Kentucky, Virginia, Tennessee, West Virginia, and Central
Counties of the ARC, 1980-2003
(persons 16 and over)
1980 1990 2000 2003
Central ARC Counties47.8%49.6%49.2%NA
Kentucky 56.6% 60.1% 60.7% 61.5%
T ennessee 60.2% 63.8% 63.3% 65.5%
Virginia 62.9% 67.8% 66.0% 67.9%
West Virginia51.6%52.9%54.4%55.4%
United States61.6%64.9%63.7%65.9%
Sources:. U.S. Department of Commerce, U.S. Census Bureau, American Fact Finder, available at
[http://www.census.gov]; U.S. Department of Commerce, Bureau of the Census, 1980 Census of
Population: General Social and Economic Characteristics, U.S. Govt. Print. Off., 1983.
Note: The labor force participation rate is the number of persons in the labor force divided by the size
of the corresponding population. The labor force includes all persons classified as being in the civilian
labor force (that is, “employed” and “unemployed” persons), plus members of the U.S. Armed Forces
— people on active duty in the Army, Air Force, Navy, Marine Corps, and Coast Guard. Data for
2003 are from the American Community Survey (ACS), which is the planned replacement for the long
questionnaire of the decennial census. The 2003 ACS did not cover all counties.
Table 29. Civilian Unemployment Rates: United States,
California, and the Counties of the SJV, 1980-2003
(persons 16 and over)
1980 1990 2000 2003
SJ V 9.5% 9.8% 11.9% NA
Fresno 8.9% 9.5% 11.8% 11.0%
K e rn 7.7% 9.7% 12.0% 11.0%
K i ngs 8.8% 10.7% 13.6%
Madera 10.2% 11.9% 13.2%
Merced 11.0% 10.6% 13.1%
San Joaquin10.2%8.8%10.3%10.4%
Stanislaus 12.7% 10.0% 11.7% 10.5%
T ulare 8.6% 10.7% 12.7% 10.5%
Adjacent counties
Mariposa 8.3% 6.7% 14.1%
T uolumne 12.5% 7.6% 7.7%
California 6.5% 6.6% 7.0% 8.5%
United States6.5%6.3%5.8%7.6%
Sources: U.S. Department of Commerce, U.S. Census Bureau, American Fact Finder, available at
[http://www.census.gov]; U.S. Department of Commerce, Bureau of the Census, 1980 Census of
Population: General Social and Economic Characteristics, U.S. Govt. Print. Off., 1983.
Note: Employment status is for persons 16 and over and refers to the week preceding the date the
census questionnaire was competed. The Census Bureau classifies civilians 16 years old and over as
unemployed if they (1) were not employed at a job during the reference week, and (2) were looking
for work during the last four weeks, and (3) were available to start a job. Also included as unemployed
are civilians 16 years old and over who did not work at all during the reference week, or who were
waiting to be called back to a job from which they had been laid off, or who were available for work
except for temporary illness. Data for 2003 are from the American Community Survey (ACS), which
is the planned replacement for the long questionnaire of the decennial census. The 2003 ACS did not
cover all counties.
Table 30. Civilian Unemployment Rates: United States,
Kentucky, Virginia, Tennessee, West Virginia, and Central
Counties of the ARC, 1980-2003
(persons 16 and over)
1980 1990 2000 2003
Central ARC Counties10.6%11.1%8.2%NA
K e ntucky 8.5% 7.4% 5.7% 7.5%
T e nnessee 7.4% 6.4% 5.5% 6.9%
V i rginia 5.0% 4.5% 4.2% 5.7%
West Virginia8.4%9.6%7.3%8.4%
United States6.5%6.3%5.8%7.6%
Sources: U.S. Department of Commerce, U.S. Census Bureau, American Fact Finder, available at
[http://www.census.gov]; U.S. Department of Commerce, Bureau of the Census, 1980 Census of
Population: General Social and Economic Characteristics, U.S. Govt. Print. Off., 1983.
Note: Employment status is for persons 16 and over and refers to the week preceding the date the
census questionnaire was competed. The Census Bureau classifies civilians 16 years old and over as
unemployed if they (1) were not employed at a job during the reference week, and (2) were looking
for work during the last four weeks, and (3) were available to start a job. Also included as unemployed
are civilians 16 years old and over who did not work at all during the reference week, or who were
waiting to be called back to a job from which they had been laid off, or who were available for work
except for temporary illness.
Per Capita Income. Per capita income in the SJV grew 133% between 1980
and 2000, from $6,780 to $15,798. The SJV’s per capita income rose to 73% of the
national per capita income in 2000 (Table 31). This gain was less than the per capita
income growth during that time for California (174%) and the United States (196%)
(Table 31). (Per capita income among the SJV counties for which there are data
continued to grow between 2000-2003). Kings County’s per capita income growth
was the highest in the SJV, increasing from $5,843 in 1980 to $15,848 in 2000, a
171% increase. Mariposa County’s per capita income growth was 172%, increasing
from $6,676 in 1980 to $18,190 in 2000. Tuolumne County’s growth was even
higher at 212%. According to the U.S. Bureau of Economic Analysis, Madera was
among the 10 lowest MSAs in terms of per capita personal income in 2003, rankingrd
353 out of a total of 361 MSAs. The other five MSAs in the SJV also ranked low
in per capita personal income compared to other U.S. metropolitan areas: Bakersfield
(338th), Fresno (310th), Modesto (311th), Stockton (304th), Visalia-Tulare-Porterville
(346 th). 58
For the Central Appalachian counties, per capita income grew from $5,087 in
1980 to $13,911 in 2000, almost 14% less in dollar terms than the SJV, but a total
increase of 173% compared to 133% in the SJV (Table 32). Per capita market
income in the ARC defined area, however, was $19,736 in 2000, about 77% of the
national average (Table 1).
Median Family Income. Family income is the sum of income received by
all family members in a household. In each of the SJV counties, median family
income better than doubled between 1980 and 2000, although all SJV counties, with
a range from $36,297 to $46,919, were below the 2000 national median family
income level ($50,046) and that of California ($53,025) (Table 33). The two
adjacent counties (Mariposa and Tuolumne) also had 2000 median family income
levels lower than both California and the national level. San Joaquin County had the
highest median family income in 2000 ($46,919) followed by Stanislaus County
($44,703). Between 2000-2003, San Joaquin grew to $50,922, still slightly higher
than Stanislaus County ($49,431). California’s median family income grew 146%
between 1980 and 2000, from $21,537 to $53,025. Between 2000 and 2003,
California’s median family income grew to $56,530. On average, median family
income in the SJV in 2000 was approximately $13,000 less than the median family
income of California (Figure 6).
58 U.S. Bureau of Economic Analysis, April, 2005. [http://www.bea.gov/bea/newsrel]
/ M PINe ws Re l e a s e .ht m.
Figure 6. Median Family Income By County
Data Source: U.S. Bureau of the Census
Aggregate data on median family income across the 68 Central Appalachian
counties were not available. A 2004 study of health conditions in the ARC, however,
calculated median family incomes for the 410-county Appalachian region.59 For
Appalachian counties, median family income ranged from $11,110 to $48,000 in
1990. The median family income for non-Appalachian U.S. counties ranged from
$10,903 to $65,201. The high end of median family income in the ARC was higher
than for any SJV county, California, or the United States. In 2000 the median family
income for non-Appalachian U.S. counties ranged from $14,167 to $97,225. For
Appalachian counties, median family income ranged from $18,034 to $74,003 in
2000. Given the high proportion of Distressed counties among the Central
Appalachian counties (45 of the 68), median family income is more likely to be at the
lower end of the above ranges for both 1990 and 2000. If so, median family income
in Central Appalachia was likely lower in 1990 and 2000 than it was in the SJV. In
2000, median family incomes for the four Appalachian states ranged from $36,484
to $56,169 (Table 34). For the SJV, median family income ranged from $36,297 to
$46,919 in 2000.
59 Havel, Joel. An Analysis of Disparities in Health Care Status and Access to Health Care
in the Appalachian Region. Washington, D.C.: ARC, September, 2004. Report available
at [http://www.arc.gov/index.do?nodeId=2376].
Average Family Income. Median family income measures the point where
50% of the families has a greater amount of income and 50% has a lesser amount of
income. Although a median family income value could not be calculated for the
entire 68-county Central Appalachian area or the SJV, calculating average family
income is possible. If there is high family income variance among families within
a particular geographic area, however, the average family income figure will be
biased, (i.e., a few very high income families in a region of largely poor families
portrays a higher regional family average). Less variance among family incomes will
make an average figure a more accurate portrayal of a region’s family income level.
In 2000, the average family income in the SJV was $52,854, a 144% increase
from 1980 and a 37% increase from 1990 (Table 35). At $63,541, San Joaquin
County had the highest average family income in 2003 of the counties for which data
were available. Average income in each county grew significantly between 1980 and
2000. Income between 1980 and 2000 grew 134% in Fresno County,132 % in Kern
County, 157% in Kings County, 148% in Madera County, 142% in Merced County,
165% in San Joaquin County, 151% in Stanislaus County, and 142% in Tulare
County. During the same time span, average family income grew in California by
182 %, about the same rate as that for the United States (180%) but much higher than
the SJV’s rate of 144%. By 2000, average income for the SJV was 73.4% of
California’s average family income ($52,854 vs. $71,951).
Central Appalachia’s average family income in 2000 was $39,503, about 75%
of the average family income in the SJV (Table 36). In 1980, Central Appalachia’s
average family income was 22.7 % lower than the SJV’s average, and in 1990, it was
31.6 % lower than the average in the SJV. Central Appalachia’s average income
grew 136% between 1980 and 2000, somewhat less than the growth rate for the SJV
(144%). West Virginia, with the lowest per capita income and the lowest median
family income (Table 33 and Table 34), also had the lowest average family income
in 2000 ($46,501). Average family income growth in the state between 1980 and
2000 was 136%, the same rate as the 68-county region as a whole. Kentucky, with
the second lowest growth rate, grew 172%. Virginia and Tennessee both saw rates
of average income growth greater than the United States and California (198% and
Income Sources. Total household incomes can come from multiple sources,
but wages and salaries comprise the largest source of household income. Over three-
quarters of SJV households have income from wage and salaries (Table 37). Average
wage and salary income in 1980 was $18,009 and increased to an average of $45,904
in the SJV in 2000, an increase of 155%. California had a slightly higher percentage
of its households reporting wage and salary income in 2000 than the SJV, and the
average amounts in 1980-2003 were higher than they were for the SJV. Kings
County had the highest percentage of wage and salary households (80.6%) in 2000,
although San Joaquin County had the highest average amount ($50,694). Tulare had
the smallest average amount of wage and salary income in the SJV in 2000
($41,990), although the percentage of households reporting wage and salary income
was about the same as for the SJV. Both Mariposa and Tuolumne counties had only
about 64% of households reporting income from wages and salaries, averaging
$39,877 and $43,589 respectively in 2000.
In Central Appalachia, far fewer households than in the SJV reported receiving
wage and salary income (Table 38). The percent of households with wage and salary
income fell slightly from 65.1% in 1990 to 63.4% in 2000. The average amount of
wage and salary income in Central Appalachia was $35,815 in 2000, $10,000 less
than the average in the SJV. Of the Appalachian states, only Virginia had a
proportion of households with wage and salary income greater than the United States
between 1980-2003. The four Appalachian states together had an average of $47,330
in wage and salary income compared to an average of $45,326 among the eight SJV
counties. Virginia, with a wealthy northern region lying outside Appalachia, skewed
the income distribution.
Other sources of household income include interest, dividend, or net rental
(IDR) and retirement incomes, (e.g., pensions, Individual Retirement Accounts, and
workers’ compensation). In 2000, 26.2% of SJV households reported income from
IDR (Table 39). The average amount of that income increased to $10,104 in 2000,
rising from $3,237 in 1980. The percent of households reporting IDR income fell
steadily from 1980 to 2003. The Census reported 2003 data for four SJV counties;
each had fallen to less than 20% of households reporting IDR income. The proportion
of California households and United States households reporting IDR income also
fell, although not as much as the SJV. The proportion of households in the SJV who
reported receiving retirement income rose between 1990 and 2000 (Table 40). For
all but one county (Tulare), the SJV counties for which there are 2003 data also saw
increases in the proportion of households with retirement income between 2000 and
2003. Retirement income does not include Social Security, so the sources are from
workers’ compensation, pensions, disability income, and income from an IRA or
similar plan. In 2000, the average amount of income from retirement sources in the
SJV was $15,425. Tulare County had the lowest average amount ($14,558) and San
Joaquin had the highest ($16,502). In 2003, Fresno had the highest average amount
of retirement income among those households who reported receiving retirement
income.
The percentage of SJV households reporting Social Security income remained
fairly stable from 1980-2000, with approximately 25% of households receiving
Social Security income (Table 41). The average amount received in 2000 was
$10,825 compared to $11,331 in California and $11,320 in the United States. The
proportion of California households reporting Social Security income is somewhat
less than for the SJV. The percentage of households in Mariposa and Tuolumne
receiving income from Social Security in 2000 was 37.5% and 38.5% respectively.
The proportions of households in these two counties receiving Social Security is
higher, and for Tuolumne the average amount received is about $1,500 more, than
the average amount received in the SJV. Reflecting the higher proportion of elderly
in rural counties nationally and Central Appalachian particularly, the percent of
households receiving Social Security income in Central Appalachia was nearly 36%
in 2000 (Table 42). Average amounts of Social Security income were lower than
those for the SJV. Average amounts for the four Appalachian states were, with the
exception of Virginia, lower on average than the eight SJV counties.
For those who are at least 65 years old, or blind, or disabled and are U.S.
citizens or one of certain categories of aliens, Supplemental Security Income (SSI)
provides low-income individuals with cash assistance. In 2000, 7.6% of SJV
households had SSI with an average payment of $6,704 (Table 43). This amount is
slightly less than the figure for California, and slightly more than the figure for the
United States. The proportion of households with SSI in California and the United
States is lower than the proportion of households in the SJV, 5.3% and 4.4%
respectively. In 2003, San Joaquin and Fresno counties had 9.5% and 8.2%
respectively of their households receiving SSI. This was an increase from 2000. In
Central Appalachia, the percentage of households receiving SSI in 2000 was higher
than it was in the SJV (Table 44). The proportion of households in the four
Appalachian states receiving SSI was somewhat lower than in the eight counties of
the SJV, but Central Appalachia had 11.6% of its households receiving SSI in 2000.
Average amounts received in Central Appalachia, $5,827, were also lower than the
average amounts received by SJV households.
Table 31. Per Capita Income: United States, California,
and the Counties of the SJV, 1980-2003
1980 1990 2000 2003
SJV a$6,780$11,817$15,798NA
Fresno $6,967 $11,824 $15,495 $17,377
K e rn $6,990 $12,154 $15,760 $16,845
K i ngs $5,843 $10,035 $15,848
Madera $6,361 $10,856 $14,682
Merced $6,267 $10,606 $14,257
San Joaquin$7,016$12,705$17,365$19,852
Stanislaus $7,094 $12,731 $16,913 $19,181
T ulare $6,038 $10,302 $14,006 $15,431
Adjacent counties
Mariposa $6,676 $13,074 $18,190
T uolumne $6,745 $13,224 $21,015
California $8,295 $16,409 $22,711 $24,420
United States$7,298$14,420$21,587$23,110
Sources: U.S. Department of Commerce, U.S. Census Bureau, American Fact Finder, available at
[http://www.census.gov]; U.S. Department of Commerce, Bureau of the Census, 1980 Census of
Population: General Social and Economic Characteristics, U.S. Govt. Print. Off., 1983.
Note: Data for 2003 are from the American Community Survey (ACS), which is the planned
replacement for the long questionnaire of the decennial census. The 2003 ACS did not cover all
co unties.
a. Per capita income for the SJV was calculated as follows: For each of the eight counties, per capita
income was multiplied by population. The sum of these results was divided by the total
population for the counties.
Table 32. Per Capita Income: United States, Kentucky, Virginia,
Tennessee, West Virginia, and Central Counties of the
ARC, 1980-2003
1980 1990 2000 2003
Central ARC Counties a$5,087$8,715$13,911NA
Kentucky $5,978 $11,153 $18,093 $18,587
T ennessee $6,213 $12,255 $19,393 $20,792
Virginia $7,478 $15,713 $23,975 $26,362
West Virginia$6,141$10,520$16,477$17,325
United States$7,298$14,420$21,587$23,110
Sources: U.S. Department of Commerce, U.S. Census Bureau, American Fact Finder, available at
[http://www.census.gov]; U.S. Department of Commerce, Bureau of the Census, 1980 Census of
Population: General Social and Economic Characteristics, U.S. Govt. Print. Off., 1983.
Note: Data for 2003 are from the American Community Survey (ACS), which is the planned
replacement for the long questionnaire of the decennial census. The 2003 ACS did not cover all
co unties.
a. Per capita income for the 68 counties in the central ARC was calculated as follows: For each of the
counties, per capita income was multiplied by population. The sum of these results was divided
by the total population for the counties.
Table 33. Median Family Income: United States, California,
and the Counties of the SJV, 1980-2003
1980 1990 2000 2003
SJVNANANANA
Fresno $18,396 $29,970 $38,455 $42,079
K e rn $18,780 $31,714 $39,403 $45,801
K i ngs $16,164 $27,614 $38,111
Madera $17,327 $30,246 $39,226
Merced $16,513 $28,269 $38,009
San Joaquin$19,116$34,701$46,919$50,922
Stanislaus $18,652 $32,923 $44,703 $49,431
T ulare $16,166 $26,697 $36,297 $38,464
Adjacent counties
Mariposa $15,833 $29,468 $42,655
T uolumne $16,907 $31,464 $44,327
California $21,537 $40,559 $53,025 $56,530
United States$19,917$35,225$50,046$52,273
Sources: U.S. Department of Commerce, U.S. Census Bureau, American Fact Finder, available at
[http://www.census.gov]; U.S. Department of Commerce, Bureau of the Census, 1980 Census of
Population: General Social and Economic Characteristics, U.S. Govt. Print. Off., 1983.
Note: Data for 2003 are from the American Community Survey (ACS), which is the planned
replacement for the long questionnaire of the decennial census. The 2003 ACS did not cover all
co unties.
Table 34. Median Family Income: United States, Kentucky,
Virginia, Tennessee, West Virginia, and Central Counties of the
ARC, 1980-2003
1980 1990 2000 2003
Central ARC CountiesNANANANA
K e ntucky $16,444 $27,028 $40,939 $41,898
T e nnessee $16,564 $29,546 $43,517 $46,654
V i rginia $20,018 $38,213 $54,169 $60,174
West Virginia$17,308$25,602$36,484$38,568
United States$19,917$35,225$50,046$52,273
Sources: U.S. Department of Commerce, U.S. Census Bureau, American Fact Finder, available at
[http://www.census.gov]; U.S. Department of Commerce, Bureau of the Census, 1980 Census of
Population: General Social and Economic Characteristics, U.S. Govt. Print. Off., 1983.
Table 35. Average Family Income: United States, California,
and the Counties of the SJV, 1980-2003
1980 1990 2000 2003
SJ V $21,649 $38,607 $52,854 NAa
Fresno $22,332 $38,843 $52,247 $53,639
K e rn $22,070 $38,812 $51,273 $53,271
K i ngs $19,316 $34,318 $49,728
Madera $20,642 $35,730 $51,112
Merced $20,365 $36,059 $49,349
San Joaquin$21,940$41,340$58,108$63,541
Stanislaus $22,303 $40,705 $55,910 $60,158
T ulare $20,042 $34,564 $48,595 $51,052
Adjacent counties
Mariposa $18,776 $36,197 $52,270
T uolumne $19,440 $38,551 $57,064
California $25,540 $51,198 $71,951 $73,826
United States$23,092$43,803$64,663$66,920
Source: U.S. Department of Commerce, U.S. Census Bureau, American Fact Finder, available at
[http://www.census.gov]; U.S. Department of Commerce, Bureau of the Census, 1980 Census of
Population: General Social and Economic Characteristics, U.S. Govt. Print. Off., 1983.
Notes: Income consists of money income and includes earnings, interest, dividends, retirement
income, veterans’ payments, public assistance, unemployment compensation, child support, alimony,
and other income.
Data for 2003 are from the American Community Survey (ACS), which is the planned replacement for
the long questionnaire of the decennial census. The 2003 ACS did not cover all counties.
Table 36. Average Family Income: United States, Kentucky,
Virginia, Tennessee, West Virginia, and Central Counties of the
Appalachian Regional Commission (ARC), 1980-2003
1980 1990 2000 2003
Central ARC Counties$16,737$26,403$39,503NAa
K e ntucky $19,192 $33,386 $52,124 $51,783
T e nnessee $19,616 $36,478 $56,166 $58,067
V i rginia $23,443 $46,710 $69,869 $75,763
West Virginia$19,668$31,290$46,501$48,111
United States$23,092$43,803$64,663$66,920
Source: U.S. Department of Commerce, U.S. Census Bureau, American Fact Finder, available at
[http://www.census.gov]; U.S. Department of Commerce, Bureau of the Census, 1980 Census of
Population: General Social and Economic Characteristics, U.S. Govt. Print. Off., 1983.
Notes: Income consists of money income and includes earnings, interest, dividends, retirement
income, Veterans’ payments, public assistance, unemployment compensation, child support, alimony,
and other income.
Data for 2003 are from the American Community Survey (ACS), which is the planned replacement for
the long questionnaire of the decennial census. The 2003 ACS did not cover all counties.
CRS-85
Table 37. Wage and Salary Income: United States, California, and the Counties of the SJV, 1980-2003
1980 1990 2000 2003
Percent ofPercent ofPercent ofPercent of
households withhouseholds withhouseholds withhouseholds with
wage and salaryAveragewage and salaryAveragewage and salaryAveragewage and salaryAverage
inco me amount inco me amount inco me amount inco me amount
76.3% $18,009 75.9% $33,351 77.0% $45,904 NA NA
r esno 77.6% $18,167 75.8% $32,666 77.3% $44,592 77.8% $48,379
ern 76.8% $19,004 76.9% $34,718 75.7% $45,332 76.9% $48,272
ings 79.1% $16,176 78.1% $29,727 80.6% $44,849
74.1% $17,370 72.6% $30,651 74.2% $44,790
iki/CRS-RL3318477.5% $16,317 76.4% $30,388 77.9% $42,238
g/wan Joaquin74.5%$18,50475.7%$35,94777.2%$50,69480.7%$55,551
s.ortanislaus 76.0% $18,408 76.4% $34,903 77.3% $48,124 78.1% $50,873
leak
ulare 74.5% $16,334 73.6% $29,547 76.9% $41,990 76.5% $47,151
://wiki
httpacent counties
posa 63.8% $15,242 65.3% $29,133 63.7% $39,877
uolumne 67.5% $16,272 66.0% $31,533 63.6% $43,589
ifornia 78.4% $21,283 79.2% $43,346 78.7% $61,374 77.6% $64,351
ted States77.7%$19,79677.4%$37,27177.7%$54,35877.0%$57,161
: U.S. Department of Commerce, U.S. Census Bureau, American Fact Finder, available at [http://www.census.gov]; U.S. Department of Commerce, Bureau of the Census,
ensus of Population: General Social and Economic Characteristics, U.S. Govt. Print. Off., 1983.
Data for 2003 are from the American Community Survey (ACS), which is the planned replacement for the long questionnaire of the decennial census. The 2003 ACS did not cover
unties.
CRS-86
Table 38. Wage and Salary Income: United States, Kentucky, Virginia, Tennessee, West Virginia,
and Central Counties of the ARC, 1980-2003
1980 1990 2000 2003
Percent ofPercent ofPercent ofPercent of
households withhouseholds withhouseholds withhouseholds with
wage and salaryAveragewage and salaryAveragewage and salaryAveragewage and salaryAverage
inco me amount inco me amount inco me amount inco me amount
tral ARC Counties68.8%$15,82465.1%$24,99763.4%$35,815NANA
tucky 74.6% $17,024 73.3% $29,444 73.6% $44,638 72.4% $45,604
iki/CRS-RL33184
g/w
s.ornessee 77.5% $17,096 76.5% $31,457 76.6% $46,926 76.0% $48,895
leak
://wikiinia 82.2% $19,987 81.9% $39,615 81.2% $57,889 80.0% $63,933
http
t Virginia72.5%$17,79367.5%$28,26168.2%$39,87067.1%$42,785
ted States77.7%$19,79677.4%$37,27177.7%$54,35877.0%$57,161
: U.S. Department of Commerce, U.S. Census Bureau, American Fact Finder, available at [http://www.census.gov]; U.S. Department of Commerce, Bureau of the Census,
ensus of Population: General Social and Economic Characteristics, U.S. Govt. Print. Off., 1983.
CRS-87
Table 39. Interest, Dividend, or Net Rental Income: United States, California,
and the Counties of the SJV, 1980-2003
1980 1990 2000 2003
Percent ofPercent ofPercent ofPercent of
households withhouseholds withhouseholds withhouseholds with
interest, interest, interest, interest,
dividend, or netAveragedividend, or netAveragedividend, or netAveragedividend, or netAverage
rental incomeamountrental incomeamountrental incomeamountrental incomeamount
34.3% $3,237 30.8% $6,949 26.2% $10,104
r esno 35.7% $3,242 31.7% $7,478 26.8% $10,224 17.2% $10,261
ern 34.5% $3,158 28.9% $6,072 25.0% $9,507 16.1% $6,567
ings 29.9% $2,667 26.3% $6,379 24.6% $11,004
iki/CRS-RL3318425.5% $3,202 31.7% $6,813 24.9% $11,549
g/w34.1% $3,279 30.3% $6,282 24.7% $9,757
s.or
leakan Joaquin35.4%$3,19132.7%$6,95528.1%$10,47719.8%$8,409
tanislaus 36.7% $3,198 32.2% $7,382 27.7% $9,879 18.7% $8,109
://wikiulare 30.1% $3,662 29.2% $7,225 23.6% $10,026 13.6% $12,398
http
acent counties
posa 40.7% $3,262 36.7% $7,343 35.5% $11,561
uolumne 33.9% $3,287 40.0% $7,908 40.3% $12,476
ifornia 41.2% $3,770 39.8% $9,021 35.0% $14,208 25.6% $13,654
ted States41.4%$2,99440.5%$6,94935.9%$10,67726.3%$10,184
U.S. Department of Commerce, U.S. Census Bureau, American Fact Finder, available at [http://www.census.gov]; U.S. Department of Commerce, Bureau of the Census,
ensus of Population: General Social and Economic Characteristics, U.S. Govt. Print. Off., 1983.
Data for 2003 are from the American Community Survey (ACS), which is the planned replacement for the long questionnaire of the decennial census. The 2003 ACS did not cover
unties.
CRS-88
Table 40. Retirement Income: United States, California, and the Counties of the SJV, 1980-2003
1990 2000 2003
Percent ofPercent ofPercent of
households withAveragehouseholds withAveragehouseholds withAverage
retirement incomeamountretirement incomeamountretirement incomeamount
14.7% $8,838 15.7% $15,425
r esno 13.2% $8,906 14.2% $15,414 17.1% $17,933
ern 14.7% $9,334 15.9% $15,744 16.3% $16,697
ings 14.6% $9,027 15.3% $15,607
17.8% $9,791 17.5% $15,533
15.3% $9,154 16.4% $15,703
iki/CRS-RL33184an Joaquin16.2%$8,86517.1%$16,05219.7%$15,810
g/wtanislaus 15.2% $8,109 16.3% $14,567 18.2% $17,377
s.orulare 13.5% $8,051 14.6% $14,558 14.5% $14,270
leak
://wikijacent counties
httpposa 26.0% $11,426 24.3% $19,440
uolumne 26.4% $10,329 29.1% $18,357
ifornia 14.9% $10,409 15.4% $18,826 15.3% $18,919
ited States15.6%$9,21616.7%$17,37617.0%$17,005
U.S. Department of Commerce, U.S. Census Bureau, American Fact Finder, available at [http://www.census.gov].
Retirement income includes pensions and survivor benefits; income from workers’ compensation; disability income; and regular income from an Individual Retirement Account
) or similar plan. Income from Social Security is not included. Data for 2003 are from the American Community Survey (ACS), which is the planned replacement for
questionnaire of the decennial census. The 2003 ACS did not cover all counties.
a for 2003 are from the American Community Survey (ACS), which is the planned replacement for the long questionnaire of the decennial census. The 2003 ACS did not cover all
nties.
CRS-89
Table 41. Social Security Income: United States, California, and the Counties of the SJV, 1980-2003
1980 1990 2000 2003
Percent ofPercent ofPercent ofPercent of
households withhouseholds withhouseholds withhouseholds with
social securityAveragesocial securityAveragesocial securityAveragesocial securityAverage
inco me amount inco me amount inco me amount inco me amount
25.0% $4,063 24.6% $7,586 24.6% $10,825 NA NA
r esno 23.6% $4,018 23.9% $7,548 23.6% $10,801 25.0% $11,778
ern 25.0% $4,117 23.7% $7,611 24.8% $10,877 25.1% $11,550
ings 22.5% $3,981 21.7% $7,180 22.0% $10,486
iki/CRS-RL3318426.7% $4,118 29.7% $7,709 29.0% $11,04122.8% $3,887 23.4% $7,466 24.0% $10,204
g/w
s.oran Joaquin25.9%$4,13225.3%$7,73624.6%$11,06423.2%$12,480
leaktanislaus 25.8% $4,053 24.9% $7,627 25.1% $10,960 25.1% $11,715
://wikiulare 27.3% $4,058 26.9% $7,465 25.3% $10,575 26.4% $11,516
http
acent counties
posa 35.5% $4,223 34.4% $7,556 37.5% $10,685
uolumne 32.1% $4,387 36.9% $8,404 38.5% $12,284
ifornia 22.1% $4,182 21.9% $7,957 22.3% $11,331 23.5% $12,588
ted States25.9%$4,09426.3%$7,77225.7%$11,32026.6%$12,651
: U.S. Department of Commerce, U.S. Census Bureau, American Fact Finder, available at [http://www.census.gov]; U.S. Department of Commerce, Bureau of the Census,
ensus of Population: General Social and Economic Characteristics, U.S. Govt. Print. Off., 1983.
Data for 2003 are from the American Community Survey (ACS), which is the planned replacement for the long questionnaire of the decennial census. The 2003 ACS did not cover
unties.
CRS-90
Table 42. Social Security Income: United States, Kentucky, Virginia, Tennessee, West Virginia,
and Central Counties of the ARC, 1980-2003
1980 1990 2000 2003
Percent ofPercent ofPercent ofPercent of
households withhouseholds withhouseholds withhouseholds with
social securityAveragesocial securityAveragesocial securityAveragesocial securityAverage
inco me amount inco me amount inco me amount inco me amount
tral ARC Counties32.4%$3,77933.8%$6,85835.9%$10,029NANA
tucky 28.5% $3,765 28.9% $6,985 28.5% $10,293 29.7% $11,498
iki/CRS-RL33184
g/w
s.ornessee 27.7% $3,695 27.3% $7,060 26.5% $10,655 27.8% $12,198
leak
://wikiinia 23.4% $3,836 22.8% $7,223 23.4% $10,868 24.8% $12,405
http
t Virginia32.0%$4,11434.4%$7,53333.9%$10,93135.1%$12,283
ted States25.9%$4,09426.3%$7,77225.7%$11,32026.6%$12,651
: U.S. Department of Commerce, U.S. Census Bureau, American Fact Finder, available at [http://www.census.gov]; U.S. Department of Commerce, Bureau of the Census,
ensus of Population: General Social and Economic Characteristics, U.S. Govt. Print. Off., 1983.
Table 43. Supplemental Security Income (SSI): United States,
California, and the Counties of the SJV, 2000-2003
20002003
Percent ofPercent of
househol ds househol ds
with SSIAveragewith SSIAverage
income amount income amount
SJ V 7.6% $6,704 NA NA
Fresno 7.8% $6,792 8.2% $7,310
K e rn 7.5% $6,428 4.7% $5,446
Kings7.6%$6,066
Madera 6.6% $6,540
Merced 7.7% $6,616
San Joaquin7.3%$7,0009.5%$8,435
Stanislaus 7.6% $7,061 5.8% $7,345
T ulare 7.9% $6,392 7.4% $6,549
Adjacent counties
Mariposa 5.4% $6,761
T uolumne 6.6% $6,241
California 5.3% $6,990 4.7% $7,770
United States4.4%$6,3203.9%$6,731
Source: U.S. Department of Commerce, U.S. Census Bureau, American Fact Finder, available at
[ h t t p : / / www. c e n s u s . g o v ] .
Note: Data for 2003 are from the American Community Survey (ACS), which is the planned
replacement for the long questionnaire of the decennial census. The 2003 ACS did not cover all
co unties.
Table 44. Supplemental Security Income (SSI): United States,
Kentucky, Virginia, Tennessee, West Virginia, and Central
Counties of the ARC, 2000-2003
20002003
Percent ofPercent of
househol ds househol ds
with SSIAveragewith SSIAverage
income amount income amount
Central ARC Counties11.6%$5,827NANA
K e ntucky 7.2% $5,809 6.2% $6,186
T e nnessee 5.2% $5,823 4.1% $5,992
V i rginia 3.5% $5,770 3.0% $5,984
West Virginia6.9%$5,9746.3%$6,182
United States4.4%$6,3203.9%$6,731
Source: U.S. Department of Commerce, U.S. Census Bureau, American Fact Finder, available at
[ h t t p : / / www. c e n s u s . g o v ] .
County and Regional Educational Measures. Human capital refers
generally to the level of education and training of a defined group (e.g., population
or labor force) and is important because of the direct relationship between
educational attainment and earnings.60 The demand for workers with at least some
post-secondary education has been increasing in recent decades and is projected to
rise.61 The SJV has a disproportionate share of low-skilled and poorly educated
workers, a significant percentage of whom are farmworkers. Raising the levels of
training and education is a major challenge facing the SJV. Improvements in
educational attainment and higher-level job skills are a practical necessity for the SJV
if it is to move its economy toward new competitive advantage over the coming
decades.
Table 45 shows that in 2000, 32.8% of those 18 and older in the SJV had less
than a high school education, down slightly from 34.3% in 1990. The proportion of
high school graduates without any post secondary education in 2000 was 25.1%,
higher than the proportion of high school graduates in California, but somewhat
lower than the rate in the United States (28.6%). It is the proportion of the
population with less than a high school education that is most pronounced in the SJV.
In California, 24% had less than high school educations, while most SJV counties
had rates above 30%. Figure 7 maps by county the percentage of Californians with
less than high school and shows that the SJV is overly represented by that category.
Figure 8 further maps by county the percentage of the population with a bachelor’s
or higher degree. In this category, the SJV is under-represented when compared to
California’s other counties. California had nearly 24% of its population 18 and older
with bachelors degrees in 2000. In the SJV, the proportion was less than 12.5%. In
the category of 1-3 years of college, however, the SJV at 39.8% was higher than the
national average of 28.8%. The SJV rate was somewhat lower than the state’s rate
of 1-3 years of college. For Mariposa and Tuolumne counties, the high school
graduate proportions were higher, the less than high school proportions were lower,
and the 1-3 years of college proportion and college graduates were higher than the
SJV.
In Central Appalachia, the proportion of population 18 and older with less than
high school in 2000 was higher than the rate in the SJV (Table 46) (35.4% vs.
32.8%). The proportion of high school graduates in 2000 was higher (34.9%) than
it was in the SJV (25.1%) and the United States (28.6%), but the proportion of 1-3
years of college was much lower in Central Appalachia (20.4%) than it was in the
SJV (29.8%). This may reflect the number and proximity of California institutions
of higher education compared to that of Central Appalachia. If this is a factor, it is
further seen in the proportion of Central Appalachians with a bachelor’s or advanced
degree. While the rate in 2000 in the SJV was 12.4%, in Central Appalachia the
proportion of those with bachelors or advanced degrees was 9.4%, up from 7.6% in
1990. With the exception of Virginia, the Appalachian states each had lower
proportions of their population with a bachelors or advanced degree than the United
States or the state of California.
60 See CRS Report 95-1081, Education Matters: Earnings by Educational Attainment over
Three Decades.
61 See CRS Report 97-764, The Skill (Education) Distribution of Jobs: How Is It Changing?
Table 45. Educational Attainment: United States, California,
and Counties of the SJV, 1990-2003
(persons 18 and over)
1990 2000 2003
SJ V
Less than High School34.3%32.8%NA
High School Graduate24.9%25.1%NA
1- 3 Years of College28.7%29.8%NA
Bachelor’s or Advanced Degree12.1%12.4%NA
Fresno County
Less than High School34.2%32.9%26.4%
High School Graduate21.9%21.9%27.0%
1- 3 Years of College28.9%29.9%30.9%
Bachelor’s or Advanced Degree15.0%15.3%15.8%
Kern County
Less than High School33.5%32.3%27.5%
High School Graduate25.8%26.4%29.7%
1- 3 Years of College29.0%29.5%30.4%
Bachelor’s or Advanced Degree11.8%11.8%12.3%
Kings County
Less than High School35.3%32.3%
High School Graduate29.4%29.8%
1- 3 Years of College27.7%29.0%
Bachelor’s or Advanced Degree7.6%8.9%
Madera County
Less than High School37.9%36.5%
High School Graduate24.9%25.7%
1- 3 Years of College26.8%27.3%
Bachelor’s or Advanced Degree10.4%10.5%
Merced County
Less than High School36.6%36.1%
High School Graduate24.8%25.0%
1- 3 Years of College28.1%29.3%
1990 2000 2003
Bachelor’s or Advanced Degree10.5%9.6%
San Joaquin County
Less than High School31.8%29.6%28.7%
High School Graduate26.3%25.8%30.6%
1- 3 Years of College30.2%31.7%29.2%
Bachelor’s or Advanced Degree11.7%12.9%11.4%
Stanislaus County
Less than High School32.0%29.9%24.7%
High School Graduate27.1%27.1%32.2%
1- 3 Years of College29.4%30.6%29.1%
Bachelor’s or Advanced Degree11.5%12.4%14.0%
Tulare County
Less than High School40.4%38.7%33.7%
High School Graduate23.7%23.9%27.2%
1- 3 Years of College25.7%27.4%29.0%
Bachelor’s or Advanced Degree10.3%10.0%10.1%
Adjacent counties
Mariposa County
Less than High School22.8%16.4%
High School Graduate29.1%27.3%
1- 3 Years of College32.3%37.6%
Bachelor’s or Advanced Degree15.8%18.7%
Tuolumne County
Less than High School21.3%17.5%
High School Graduate33.6%30.4%
1- 3 Years of College31.7%37.4%
Bachelor’s or Advanced Degree13.4%14.7%
Califo r ni a
Less than High School24.8%24.0%20.2%
High School Graduate23.1%21.1%23.3%
1- 3 Years of College31.3%31.0%30.2%
1990 2000 2003
Bachelor’s or Advanced Degree20.8%23.9%26.3%
United States
Less than High School24.6%20.3%17.0%
High School Graduate30.1%28.6%30.3%
1- 3 Years of College26.7%28.8%28.4%
Bachelor’s or Advanced Degree18.5%22.3%24.4%
Sources: U.S. Department of Commerce, U.S. Census Bureau, American Fact Finder, available at
[ h t t p : / / www. c e n s u s . g o v ] .
Note: Details may not sum to 100% because of rounding. Data for 2003 are from the American
Community Survey (ACS), which is the planned replacement for the long questionnaire of the
decennial census. The 2003 ACS did not cover all counties.
Figure 7. Percent of Persons with Education Less Than High School
by County (2000)
Source: U.S. Bureau of the Census
Figure 8. Percent of Persons with a Bachelors Degree or Advanced
Degree by County (2000)
Source: U.S. Bureau of the Census
Table 46. Educational Attainment: United States, Kentucky,
Virginia, Tennessee, West Virginia, and Central Counties of the
ARC, 1990-2003
(persons 18 and over)
1990 2000 2003
Central ARC Counties
Less than High School44.6%35.4%NA
High School Graduate31.6%34.9%NA
1- 3 Years of College16.1%20.4%NA
Bachelor’s or Advanced Degree7.6%9.4%NA
K e nt uc ky
Less than High School33.9%25.8%21.0%
High School Graduate32.3%33.4%35.5%
1- 3 Years of College21.4%25.2%26.4%
Bachelor’s or Advanced Degree12.4%15.6%17.1%
T e nne sse e
Less than High School1.9%24.2%19.1%
High School Graduate30.6%31.8%34.8%
1- 3 Years of College23.0%26.2%26.2%
Bachelor’s or Advanced Degree14.5%17.9%19.9%
Vir ginia
Less than High School24.2%18.8%15.8%
High School Graduate27.7%26.5%28.0%
1- 3 Years of College25.9%27.7%26.3%
Bachelor’s or Advanced Degree22.2%27.0%29.9%
West Virginia
Less than High School32.8%24.4%21.5%
High School Graduate36.5%38.8%40.1%
1- 3 Years of College19.3%23.1%22.9%
Bachelor’s or Advanced Degree11.4%13.7%15.6%
United States
Less than High School24.6%20.3%17.0%
High School Graduate30.1%28.6%30.3%
1- 3 Years of College26.7%28.8%28.4%
Bachelor’s or Advanced Degree18.5%22.3%24.4%
Sources: U.S. Department of Commerce, U.S. Census Bureau, American Fact Finder, available at
[ h t t p : / / www. c e n s u s . g o v ] .
Table 47. Per Pupil Amounts for Current Spending of Public
Elementary and Secondary School Systems: United States,
California, and Counties of the SJV,
1992-1993 and 2002-2003
1992-1993 2002-2003
SJV$4,889$7,715
Fresno County$5,193$7,772
Kern County$4,791$7,757
Kings County$4,755$7,587
Madera County$4,815$7,645
Merced County$5,068$7,687
San Joaquin County$4,669$7,345
Stanislaus County$4,603$7,698
Tulare County$5,030$8,070
Adjacent Counties
Mariposa County$5,231$8,554
Tuolumne County$4,230$8,326
Californiaa $4,845 $7,691
United States$5,177$8,019
Sources: U.S. Census Bureau, 2003 Census of Governments: Public Education Finances; U.S.
Census Bureau. 1993 Census of Governments: Public Education Finances.
Note: Data presented by counties represent averages of all school districts in each county.
a. Payments made by the California state government into the state retirement system on behalf of
school systems have been estimated for local school systems.
Table 48. Percent of Persons Who Speak a Language Other
than English at Home: United States, California, and Counties of
the SJV, 1980-2003
1980 1990 2000 2003
SJ V 23.7% 30.3% 37.3%
Fresno 27.7% 35.3% 40.8% 38.8%
K e rn 20.0% 24.6% 33.4% 35.0%
K i ngs 27.1% 31.0% 36.7%
Madera 25.7% 29.7% 37.0%
Merced 26.5% 36.0% 45.2%
San Joaquin21.1%27.9%33.7%35.6%
Stanislaus 18.0% 25.0% 32.4% 37.1%
T ulare 28.4% 35.9% 43.8% 46.5%
Adjacent counties
Mariposa 4.9% 6.6% 5.2%
T uolumne 4.7% 8.5% 5.8%
California 22.6% 31.5% 39.5% 40.8%
United States11.0%13.8%17.9%18.4%
Sources: U.S. Department of Commerce, U.S. Census Bureau, American Fact Finder, available at
[http://www.census.gov]; U.S. Department of Commerce, Bureau of the Census, 1990 Census of
Population and Housing: Summary Social, Economic and Housing Characteristics, U.S. Govt. Print.
Off, 1992; U.S. Department of Commerce, Bureau of the Census, 1980 Census of Population: General
Social and Economic Characteristics, U.S. Govt. Print. Off., 1983.
Note: Data for 2003 are from the American Community Survey (ACS), which is the planned
replacement for the long questionnaire of the decennial census. The 2003 ACS did not cover all
co unties.
While per pupil spending and rates of graduation are related, a high expenditure
is not necessarily a guarantee of a high graduation rate. Per pupil expenditures for
elementary and secondary school systems in the SJV averaged $7,715 in 2002-2003.
Each SJV county had expenditures over $7,000, with Tulare County spending over
$8,000 per pupil (Table 47). Per pupil expenditures also rose significantly from
School systems with high proportions of pupils for whom English is not their
first language may experience higher per pupil costs than other school systems.
Table 48 shows that the SJV has a high proportion of persons who speak a language
other than English at home. In 2000, over 37% in the SJV spoke a language other
than English at home. In Merced County the rate was over 45% and in Tulare
County, the rate was nearly 44%. In 2003, the rate in Tulare County was 46.5%, the
highest of the SJV counties for which there were data. In California, the rate in 2003
was nearly 41%, compared to a national rate of 18.4%. These figures suggest
significant challenges to the SJV school systems.
Per pupil spending in Central Appalachian was $777 lower than spending per
pupil in the SJV (Table 49). Tennessee and Kentucky also spent less per pupil than
the SJV average. West Virginia spends more per pupil than the other states and more
per pupil than the SJV.
Given the high rate of population growth in the SJV from immigration, CRS
sought an indicator of educational attainment of those in the labor force who reported
moving in the previous years. Table 50 shows that for those in the labor force
residing in SJV MSAs who moved, the proportion of those with less than high school
was lower than for the SJV as a whole. Of those who moved, the proportion of high
school graduates was also higher than for the SJV as a whole. For 2002-2004,
however, the proportion of high school graduates who moved in the previous year fell
from 35.9% in 1999-2001, to 28.6% in 2002-2004. These rates were still higher than
for the SJV as a whole.
Table 49. Per Pupil Amounts for Current Spending of Public
Elementary and Secondary School Systems: United States,
Kentucky, Tennessee, Virginia, West Virginia, and Central
Counties of the ARC, 1992-1993 and 2002-2003
1992-1993 2002-2003
Central ARC Counties a,b$4,391$6,938
K e ntucky $4,825 $6,647
T e nnessee $3,432 $6,201
V i rginia $5,055 $7,832
West Virginia$5,073$8,218
United States$5,177$8,019
Sources: U.S. Census Bureau, 2003 Census of Governments: Public Education Finances; U.S.
Census Bureau. 1993 Census of Governments: Public Education Finances.
Note: Data presented for Central ARC counties represents the average of all school districts in the
Central ARC counties.
a. Payments made by the Kentucky state government into the state teachers’ retirement system and
for health and life insurance on behalf of Kentucky school systems have been estimated for local
school systems.
b. Payments made by the West Virginia state government into the state teachers’ and public
employees’ retirement funds on behalf of West Virginia school systems have been estimated for
local school systems.
Table 50. Educational Attainment of Persons in the Labor Force
Who Moved During the Previous Year: United States, California,
and MSAs of the SJV, 1989-2004
1989-1991 1999-2001 2002-2004
SJV MSAs
Less than high school 29.1%23.4% a25.1%
High school graduate 32.5%35.9%28.6%
Bachelor’s or advanced degree11.5%11.8%13.6%
California
Less than high school 22.0%16.6%16.1%
High school graduate 25.9%24.2%22.8%
Bachelor’s or advanced degree24.5%28.2%29.0%
United States
Less than high school 17.4%14.7%14.4%
High school graduate 33.6%30.8%29.4%
Bachelor’s or advanced degree23.1%25.7%27.4%
Source: Calculated by CRS from the March Current Population Surveys (CPS) for 1989-1991, 1999-
2001, and 2002-2004.
Notes: In order to increase the sample sizes, all estimates are three-year averages. An MSA consists
of an urban center (or centers) and adjacent communities that have a high degree of economic and
social integration. Details may not sum to 100% because of rounding.
a. Data for 1998 and later years may not be comparable to data for 1988-1990. Data for 1998 and
later years include an MSA for Merced County. For 1998 and later, the Fresno MSA includes
both Fresno and Madera counties.
Health and Disease Rates in the SJV. Disease prevalence, availability
of health professionals, and other health indicators may reveal particular impediments
to human capital development, and, by extension, to economic development.
Disparities in health create significant burdens on health care providers and on
society. The costs to provide health care to a population are directly related to the
general health of the resident population. Poverty is a also a reliable indicator of
health. As we discuss in a later section, the SJV plans to make health care and
related industries a major growth sector for the future. High costs for health care,
large proportions of the regional population without insurance, and high percentages
of Medicaid recipients may be important factors in the eventual success of an
expanding healthcare center in the SJV. The variables examined in this section
characterize some of the challenges the SJV might confront in the coming decade.
Comparable data for the ARC are not available for many of the health variables
presented below.
Physicians per 1,000 Population. The number of doctors per 1,000
population is one indicator of the availability of health care in a region. For the
United States in 2001, there were 2.3 doctors engaged in patient care per 1,000
population. Total active doctors in the United States was 2.6 per 1,000 population.
The latter figure includes physicians engaged in teaching, research, and
administration as well as patient care physicians. In the SJV, there were 1.3
physicians engaged in patient care per 1,000 population and 1.4 active doctors per
1,000 population in 2001 (Tables 51 and 52). Fresno County had 1.7 doctors
engaged in patient care per 1,000 population and 1.9 per 1,000 total. Kings County
and Madera County had fewer than 1.0 physicians engaged in patient care per 1,000
and fewer than 1.0 total active doctors per 1,000 in 2001. California in 2001 had 2.2
doctors engaged in patient care per 1,000 population and 2.5 per 1,000 population
total.
Central Appalachia looked very similar to the SJV in 2001 in distribution of
physicians per 1,000 (Tables 53 and 54). The 68 Central Appalachian counties had
and 1.3 total active doctors per 1,000 population, one-tenth of a percent fewer than
the SJV. Kentucky and West Virginia each had physician rates lower than the United
States; Tennessee and Virginia had rates equal to or slightly greater than the United
States.
Teen Birth Rates. Birth rates for teenagers aged 15-19 fell significantly
between 1980 and 2003 in the SJV counties (Table 55). Rates in 2003 ranged from
a low of 45.3 teen births per 1,000 population in Stanislaus County to a high of 69.2
per 1,000 in Madera. These rates were down considerably from their high point in
1990 when most of the SJV counties had rates of over 100 per 1,000 population, but
were still significantly higher than the rates for California and the United States. Teen
birth rates in the SJV grew from 1980 to 1990 and then fell in the decade 1990-2000.
Mariposa and Tuolumne counties had rates below California, the United States, and
the counties of the SJV.
Latinas have the highest teen birth rates of any race/ethnic group in California.62
A 2003 report by the California Public Health Institute estimated that the annual net
costs to U.S. taxpayers of births to teenagers in California amounted to
approximately $1.5 billion based on 2000 data. The analysis disaggregated the data
by counties in the various assembly districts in California. For assembly District 17
which included the counties of Merced, San Joaquin, and Stanislaus, the estimated
annual cost to taxpayers associated with births to teenagers was $31 million; for
62 Johnson, Hans B. 2003. Maternity Before Maturity: Teen Birth Rates in California.
California Counts: Population Trends and Profiles, Volume 4(3). Public Policy Institute
of California, San Francisco, February.
assembly District 29 which included the counties of Fresno and Madera, the
estimated annual cost was $23 million; for assembly District 30, which included the
counties of Fresno, Kern, Kings, and Tulare, the annual cost was $39 million; and for
assembly District 31 which included the counties of Fresno and Tulare, the annual
cost to taxpayers was $44 million.63
Infant Mortality Rates. Deaths of infants less than one year of age per 1,000
live births ranged from 12.9 in Kern County in 1980 to a low of 4.9 in Merced
County in 2000. Infant mortality rates rose in five of the eight SJV counties in 2002
(Table 56). Rates were somewhat lower in the SJV compared to the United States
and California in 1980. With the exception of Stanislaus County, rates in 2002 were
lower than the United States, but much higher than the rates for California. A 2002
report presented infant mortality data for 38 of California’s 58 counties, with the
other counties not having enough live births and infant deaths to calculate reliable
mortality rates.64 The 38 California counties accounted for nearly 99% of
California’s live births and infant deaths in 2002. If the 38 counties are ranked from
lowest (best) to highest (worst) for infant mortality rates, 16 counties rank better than
the average for the state and 22 counties rank worse than the average. The eight
counties of the SJV all rank worse than the state average, ranging from Tulare
County at 20th to Stanislaus County at 35th. Two of the eight SJV counties, San
Joaquin County and Stanislaus County, also had worse rates than the U.S. rate of 7.0
per 1,000 live births. The rates and the rankings may vary considerably from one
year to another.
Age-Adjusted Obesity and Healthy Weight.65 Interest in and data
collection on obesity in specific communities is a relatively recent phenomenon. The
California county data presented in Table 57 are taken from the California Health
Interview Survey (CHIS), which was first conducted in 2001. CHIS is a
population-based telephone survey conducted every two years, with more than
55,000 households participating in 2001. For 2003, CHIS surveyed 42,000
households; these data are now being processed and are not yet available. CHIS 2005
is currently being planned.
The survey shows that SJV counties have higher incidences of obesity than California
or the United States.
63 Constantine, Norman A. and Carmen R. Nevarez. No Time for Complacency: Teen Births
in California. California Public Health Institute. March, 2003, pp. 4-5, 28.
64 Ficenec, Sandy. California’s Infant Mortality Rate, 2002. California Department of
Health Services, Center for Health Statistics, Data Summary No. DS04-02000, February
65 The age-adjusted rate is the hypothetical rate if the population of the county or state were
distributed by age in the same proportion as the 2000 U.S. population. It permits
comparisons between counties without regard for the influence of the actual age distribution
in the various counties.
Age-Adjusted Death Rates from Heart Disease. Heart disease has been
the leading cause of death in the United States for well over 50 years.66 In general,
the age-adjusted death rate for heart disease has decreased significantly and steadily
since 1980 for the United States as a whole and for California (Table 58).
Experience in the counties of the SJV has been more mixed, with some counties
showing a steady decline in the rate (Fresno, Kings, and Tulare), while others have
seen their rates decline and either stabilize or increase again (Kern, Madera, Merced,
San Joaquin, and Stanislaus). In 1980, 5 of the 8 counties of the SJV had
age-adjusted death rates for heart disease that were higher than the average for the
state, but none had rates higher than the U.S. average. In 2002, in contrast, all 8
counties had heart disease death rates higher than the California average, and 7 of the
8 had rates higher than the U.S. average (Kings County was the only exception). The
heart disease death rate for Kern County has been consistently the highest among the
Age-Adjusted Death Rates from Cancers. In California and in the U.S.,
cancer has long been the second leading cause of death, after heart disease. The
age-adjusted death rate for cancer peaked in California in 1984 (at 209.3 per 100,000
population) and in the U.S. as a whole in 1990 (at 216.0 per 100,000 population), and
both rates have slowly decreased since then (Table 59). The rates for California have
been consistently lower than those for the U.S., with the discrepancy increasing in
recent years. The rates for the counties of the SJV have been more variable, but with
two exceptions, Madera and Merced counties, they have not kept pace with the
decline for California as a whole. In 1980, six of the eight SJV counties had
age-adjusted death rates for cancer that were lower than the state and U.S. rates,
while two of the eight, Kern and Merced counties, had rates higher than the U.S.
average. In 2002, only Kings and Madera counties had rates lower than the state
average, while three of the counties (Kern, San Joaquin, and Stanislaus) had rates
higher than the U.S. rate, and the other three had intermediate rates, which were
higher than the state average, but lower than the U.S. average.
Age-adjusted Death Rates from Stroke. Stroke is the third leading cause
of death in the United States, after heart disease and cancer. In general, the death rate
for cerebrovascular disease has decreased steadily since 1980 for the United States
as a whole and for California (Table 60). Experience in the counties of the SJV has
been more mixed, with some counties showing a fairly steady decline in the rate
(Kings, San Joaquin, Stanislaus, and Tulare), while others have seen their rates
decline and then increase again (Fresno, Kern, Madera, and Merced). In 2002, six
of the eight SJV counties had age-adjusted death rates for cerebrovascular disease
that were higher than the averages for both California and for the U.S.
Age-Adjusted Death Rates from All Causes. Age-adjusted death rates
per 100,000 population from all causes fell in the SJV counties between 1980 and
2000 (Table 61). Between 1980 and 1990, only San Joaquin saw an increase in the
age-adjusted death rate per 100,000 from all causes (757.9 vs 861.5). Between 2000
and 2002, however, five of the SJV counties had increases in their age-adjusted death
66 Centers for Disease Control and Prevention. Health, United States, 2004, Table 29, p.
rates (Fresno, Kern, Merced, San Joaquin, and Stanislaus). In 2002, all eight of the
SJV counties had age-adjusted death rates higher than the average for the state, and
five of the eight had rates higher than the U.S. average
Age-Adjusted Prevalence of Diabetes in Adults. Estimates of the
age-adjusted prevalence of diagnosed diabetes among adults in the United States
come from the annual National Health Interview Survey conducted by the National
Center for Health Statistics (NCHS) of the Centers for Disease Control and
Prevention (CDC). Among the eight SJV counties, only Stanislaus in 2003 had a
diabetes prevalence rate lower than the state rate (Table 62). All the other counties
had rates higher than the state and U.S. rates in both 2001 and 2003. Consistent with
the state and U.S. rates, rates for six of the eight counties also increased between
Age-Adjusted Deaths from Diabetes. In 2002, all eight of the SJV
counties had age-adjusted death rates for diabetes that were higher than the average
for the state, and they also had rates higher than the U.S. average (Table 63). The
diabetes death rate for Kings County was markedly higher than other counties in both
Health and Disease Profile of Appalachia. Compiling comparable
health data for the 68-county Central Appalachian area was beyond the scope of this
report. A 2004 ARC report, An Analysis of Disparities in Health Status and Access
to Medical Care, however, provides a detailed picture of the health disparities that
are present in the ARC region. Results from that study show that the Appalachian
region, much as the SJV area, suffers from an excess in mortality from leading causes
of death when compared to the non-Appalachian United States. Data in the
Appalachian study also reveal a high degree of variation within the region, with
adverse health outcomes correlating geographically with the poorest and most
isolated areas.67 The low rate of physician access in Central Appalachia noted in
Table 53 and Table 54 below is an important factor in health outcomes and one
shared by the SJV. Major conclusions of the study show:
!While there is significant variation by geography, gender, ethnicity,
and age, Appalachia has higher mortality rates from many of the
major causes of disease relative to the non-Appalachian United
States. The ARC region suffers an excess of premature deaths
(among persons 35-64) from heart disease, all cancers combined,
lung cancer, colorectal cancer, chronic obstructive pulmonary
disease, diabetes, and motor vehicle accidents;
!High rates of hospitalization, a valid indicator of morbidity, are
concentrated in the Central Appalachian counties of Eastern
Kentucky, Southwest Virginia, and Western Virginia.
67 Halverson, Joel. An Analysis of Disparities in Health Status and Access to Health Care
in the Appalachian Region. Washington, D.C.: ARC, September, 2004.
Table 51. Total Active Doctors Per 1,000 Population: United
States, California, and the Counties of the SJV, 1995-2001
19952001
SJV1.41.4
Fresno County1.91.9
Kern County1.31.4
Kings County0.80.8
Madera County0.70.9
Merced County1.11.0
San Joaquin County1.41.4
Stanislaus County1.51.5
Tulare County1.11.1
Adjacent counties
Mariposa County0.90.5
Tuolumne County1.61.8
California 2.5 2.5
United States2.42.6
Source: Calculated by CRS from the Area Resource File (ARF), available from the U.S. Department
of Health and Human Services, Health Resources and Services Administration, Bureau of Health
Professions, February 2003.
Notes: Data are for total active medical doctors, which includes physicians engaged in patient care
as well as teaching, research, and administrative doctors.
Table 52. Doctors Engaged in Patient Care Per 1,000
Population: United States, California, and the Counties of
the SJV, 1995-2001
19952001
SJV1.31.3
Fresno County1.81.7
Kern County1.31.3
Kings County0.80.7
Madera County0.60.9
Merced County1.11.0
San Joaquin County1.31.3
Stanislaus County1.51.4
Tulare County1.01.1
Adjacent counties
Mariposa County0.80.5
Tuolumne County1.51.7
California 2.2 2.2
United States2.22.3
Source: Calculated by CRS from the Area Resource File (ARF), available from the U.S. Department
of Health and Human Services, Health Resources and Services Administration, Bureau of Health
Professions, February 2003.
Notes: Data are for medical doctors engaged in patient care. Teaching, research, and administrative
doctors are not included.
Table 53. Total Active Doctors Per 1,000 Population: United
States, Kentucky, Tennessee, Virginia, West Virginia, and the
Central Counties of the ARC, 1995-2001
19952001
Central ARC Counties1.21.3
Kentucky2.02.2
Tennessee2.32.5
Virginia2.42.6
West Virginia2.02.3
United States2.42.6
Source: Calculated by CRS from the Area Resource File (ARF), available from the U.S. Department
of Health and Human Services, Health Resources and Services Administration, Bureau of Health
Professions, February 2003.
Notes: Data are for total active medical doctors, which includes physicians engaged in patient care
as well as teaching, research, and administrative doctors.
Table 54. Doctors Engaged in Patient Care Per 1,000
Population: United States, Kentucky, Tennessee, Virginia, West
Virginia, and the Central Counties of the Appalachian Regional
Commission (ARC), 1995-2001
19952001
Central ARC Counties1.11.3
Kentucky1.82.0
Tennessee2.12.3
Virginia2.22.4
West Virginia1.82.1
United States2.22.3
Source: Calculated by CRS from the Area Resource File (ARF), available from the U.S. Department
of Health and Human Services, Health Resources and Services Administration, Bureau of Health
Professions, February 2003.
Notes: Data are for medical doctors engaged in patient care. Teaching, research, and administrative
doctors are not included.
Table 55. Teen Birth Rates: United States, California, and
Counties of the SJV, 1980-2003
(per 1,000 population)
1980 1990 2000 2003
Teen birth rateTeen birth rateTeen birth rateTeen birth rate
(ages 15-19)(ages 15-19)(ages 15-19)(ages 15-19)
SJV
Fresno 71.1 102.9 70.4 58.1
K e rn 89.1 101.9 74.0 64.0
K i ngs 94.0 114.6 78.3 67.0
Madera 88.6 101.0 71.8 69.2
Merced 78.4 102.5 66.2 53.4
San Joaquin68.488.461.148.7
Stanislaus 72.0 89.0 54.9 45.3
T ulare 90.6 105.9 78.5 67.5
Adjacent counties
Mariposa 27.0 58.7 44.3 NA
T uolumne 38.7 38.6 25.9 23.8
California 52.7 70.6 47.0 38.9
United States53.059.947.741.7
Sources: Birth data for 1980 were obtained by telephone from the California Department of Health
Services. The population data are from U.S. Department of Commerce, Bureau of the Census, 1980
Census of the Population, General Population Characteristics, California, tables 19 and 45. The 1980
birth rates were calculated by the Congressional Research Service. Birth rate data for 1990 are from
the California Department of Health Services, Maternal and Child Health, Epidemiology Section,
prepared by D. Taylor, October 12, 2000, available at [http://www.mch.dhs.ca.gov/documents/pdf/
teenbirthratebycounty1990-98.pdf]. Birth rate data for 2000 are from Hans P. Johnson, “Maternity
Before Maturity: Teen Birth Rates in California,” California Counts — Population Trends and
Profiles, Public Policy Institute of California, vol. 4, no. 3, Feb. 2003, pp. 16-17. Data for 2003 are
from the California Department of Health and Human Services, Center for Health Statistics, Natality:
County Data, Number 18, available at [http://www.dhs.ca.gov/hisp/chs/OHIR/vssdata/
2003data/2003NCountyPDF.htm]. See also: California Health Care Chartbook: Key Trends and
Data (Henry J. Kaiser Family Foundation and the University of California, Berkeley, Center for Health
and Public Policy Studies), August 2004, p. 9, exhibit 1.3c, available at
[ h t t p : / / www. k f f . o r g / s t a t e p o l i c y / 7086/lo ader.cfm? url=/commo nspot/security/getfile.cfm&P ageID=4
4213]. See also: Table 2.2, General Fertility Rates, Total Fertility Rates, and Birth Rates by Age of
Mother, California, 1970, 1975, 1980, 1985, 1990-2003, available at
[ h t t p : / / www. d h s . c a . g o v / h i s p / c h s / O H I R / V S S d a t a / 2001data/01Ch2 Ex/2_02_2001.xls].
Table 56. Infant Mortality Rates: United States, California, and
Counties of the SJV, 1980-2002
1980 1990 2000 2002
Deaths under one year of age per 1,000 live births
SJV
Fresno 11.1 8.5 7.2 6.9
K e rn 12.9 10.3 7.4 6.2
K i ngs 10.2 12.3 6.0 6.5
Madera 10.8 3.3 5.7 6.1
Merced 8.4 7.6 4.9 6.9
San Joaquin11.38.76.97.3
Stanislaus 7.6 8.1 7.0 7.8
T ulare 11.5 7.7 6.6 5.7
Adjacent counties
Mariposa NA NA NA NA
T uolumne NA NA NA NA
California 11.1 7.9 5.4 5.4
United States12.69.26.9 7.0
NA - Infant mortality rates were not presented for counties with fewer than the 1,000 live
births and fewer than five infant deaths needed to calculate reliable mortality rates.
Sources: Rates for the United States come from: Kochanek, KD, et al. Deaths: Final Data for 2002.
National Vital Statistics Reports, vol. 53, no. 5, Oct. 12, 2004. Table 30, p. 94. Hyattsville, MD:
National Center for Health Statistics. Available at
[ h t t p : / / www. c d c . g o v / n c h s / d a t a / n v s r / n v s r 5 3 / n v s r 53_05.pdf].
Rates for California and California counties come from a series of reports on California’s infant
mortality rate published by the California Department of Health Services, Center for Health Statistics.
Reports for 1998 and later are available at
[http://www.dhs.ca.gov/hisp/chs/OHIR/Publication/OtherReports/InfantDeath.htm]. The report for
1990 was obtained from the Department of Health Services.
Rates for 1980 and 1990 come from: Oreglia, Anthony. California’s Infant Death Rate, 1990.
California Department of Health Services, Health Data and Statistics Branch, Data Summary 92-
01002, January 1992. Rates for 2000 and 2002 come from: Ficenec, Sandy. California’s Infant
Mortality Rate, 2002. California Department of Health Services, Center for Health Statistics, Data
Summary No. DS04-02000, February 2004.
Table 57. Age-Adjusted Prevalence of Obesity and Healthy
Weight: United States, California, and Counties of the
SJV, 1992-2002
(per 100 adults)
199220012002
Healthy
Area Obesity O besity w eight Obesity
SJV
Fresno NA 26.6 33.1 NA
K e rn NA 25.6 37.3 NA
K i ngs NA 27.5 35.0 NA
Madera NA 24.4 34.6 NA
Merced NA 29.9 30.6 NA
San JoaquinNA25.232.7NA
Stanislaus NA 25.2 36.2 NA
T ulare NA 24.3 30.0 NA
Adjacent counties combined:
T uolumne/Calaveras/
Anador/Inyo/Mariposa/
Mono/Alpine NA 16.6 43.2 NA
California12 a19.143.019 a
United States13 a23 bNA22 a
U.S. Health Objectives 2010(15)(60)
Sources unless otherwise noted: California. Department of Health. Center for Health Statistics.
Prevalence of obesity and healthy weight in California counties, 2001. Prepared by Laura Lund,
Sharon Sugerman and Susan Forster. June 2004. (Adults defined as age 20 and above).
Notes: The data provided in this table are from three different sources because the interest in and data
collection on obesity is only relatively recent in terms of specific communities. While national data
have been collected for years, state-by-state data have only been collected over the past 20 years.
Within state data are even more recent as a result of the recognition that obesity prevention is largely
a health problem needing local solutions.
The California counties data presented in this table is taken from the California Health Interview
Survey (CHIS), which was first conducted in 2001. CHIS is a population-based telephone survey
conducted every two years with more than 55,000 households participating in 2001. CHIS 2003
surveyed 42,000 households; the data are now being processed and are not yet available. CHIS 2005
is currently being planned.
Obesity occurs when individuals consistently consume more calories than they expend in physical
activity. According to the CHIS survey report, obesity is roughly equivalent to an average of 30
pounds overweight. While the table provides data on the self-reported prevalence of obesity and
healthy weight in the selected counties, no information is available on the prevalence of overweight
and underweight in the individuals surveyed.
U.S. Health Objectives are public health goals that have been set every decade since the 1970s. They
are designed as goals for health professionals to work toward in terms of improving the overall health
status of the U.S. population. According to Health People 2010, adults with a body mass index greater
than or equal to 18.5 and less than 25 have a healthy weight, while adults with a body mass index
greater than or equal to 30 are obese.
a. U.S. Department of Health and Human Services. Centers for Disease Control and Prevention.
Behavioral Risk Factor Surveillance System. Trends Data, 1992-2002.(Adults defined as age
18 and above).
b. U.S. Department of Health and Human Services. Centers for Disease Control and Prevention.
National Health and Nutrition Examination Survey. Prevalence of Overweight and Obesity
Among Adults: United States, 1999-2002. (Adults defined as age 20 and above).
Table 58. Age-Adjusted Death Rates from Heart Disease: United
States, California, and Counties of the SJV, 1980-2002
1980 1990 2000 2002
Age-adjusted deaths per 100,000 population
SJV
Fresno 349.6 309.4 252.4 248.7
K e rn 410.2 381.3 313.1 317.7
K i ngs 380.0 375.1 292.8 238.4
Madera 335.5 295.1 251.3 252.7
Merced 400.7 275.8 222.2 253.2
San Joaquin378.7311.2252.8256.8
Stanislaus 349.8 253.4 301.3 303.1
T ulare 376.3 350.0 258.0 253.0
Adjacent counties
Mariposa 312.1 273.9 161.9 232.6
T uolumne 375.2 299.7 286.1 223.6
California 374.6 303.2 239.9 225.9
United States412.1321.8257.6240.8
Source: Centers for Disease Control and Prevention (CDC), National Center for Health Statistics.
Compressed Mortality File, a database containing mortality and population counts for all U.S.
counties, searchable by cause of death, state, county, age, race, sex, and year. It is available for
queries covering 1979-2002 via the CDC WONDER On-line Database at [http://wonder.cdc.gov].
Underlying cause of death is classified in accordance with the International Classification of Disease.
Deaths for 1979-98 are classified using the Ninth Revision (ICD-9). Deaths for 1999 and beyond are
classified using the Tenth Revision (ICD-10). In this table, heart disease is defined as ICD-9 Codes
390-398, 402, 404, and 410-429 (Compressed Mortality File Groups GR028-GR036), and ICD-10
Codes I00-I09, I11, I13, and I20-I51 (Compressed Mortality File Groups GR049-GR059).
Note: The age-adjusted death rate is the hypothetical rate if the population of the county or state were
distributed by age in the same proportion as the 2000 United States population. It allows comparisons
between counties without regard to the influence of the actual age distribution in the various counties.
The crude death rate (not shown) represents the actual risk of dying in that county or state for the given
year (number of deaths divided by the population of the county or state).
Table 59. Cancer Deaths: Age-Adjusted Death Rates from
Cancers: United States, California, and Counties of the SJV,
1980-2002
1980 1990 2000 2002
Age-adjusted deaths per 100,000 population
SJV
Fresno 190.6 200.9 177.6 176.1
K e rn 210.1 217.7 181.9 196.0
K i ngs 183.3 159.6 162.0 174.5
Madera 192.8 193.0 178.6 151.0
Merced 239.3 227.1 185.4 176.9
San Joaquin204.8200.0193.9204.1
Stanislaus 200.2 191.0 198.4 197.1
T ulare 193.4 207.1 182.0 180.6
Adjacent counties
Mariposa 173.4* 145.5 290.0 185.1
T uolumne 222.5 215.8 185.6 218.5
California 204.8 203.5 182.1 175.1
United States207.9216.0199.6193.5
Source: Centers for Disease Control and Prevention (CDC), National Center for Health Statistics.
Compressed Mortality File, a database containing mortality and population counts for all U.S.
counties, searchable by cause of death, state, county, age, race, sex, and year. It is available for
queries covering 1979-2002 via the CDC WONDER On-line Database at [http://wonder.cdc.gov].
Underlying cause of death is classified in accordance with the International Classification of Disease.
Deaths for 1979-98 are classified using the Ninth Revision (ICD-9). Deaths for 1999 and beyond are
classified using the Tenth Revision (ICD-10). In this table, malignant neoplasms (cancer) includes
ICD-9 Codes 140-208.9 and ICD-10 Codes C00-C97.
Note: The age-adjusted death rate is the hypothetical rate if the population of the county or state were
distributed by age in the same proportion as the 2000 United States population. It allows comparisons
between counties without regard to the influence of the actual age distribution in the various counties.
The crude death rate (not shown) represents the actual risk of dying in that county or state for the given
year (number of deaths divided by the population of the county or state).
* Statistically unreliable rate, because it is based on a death count of 20 or fewer deaths in the county.
Table 60. Age-Adjusted Death Rates from Stroke: United States,
California, and Counties of the SJV, 1980-2002
1980 1990 2000 2002
Age-adjusted deaths per 100,000 population
SJV
Fresno 101.7 56.5 66.8 65.3
K e rn 81.6 60.1 75.0 65.6
K i ngs 119.3 85.1 65.2 43.5
Madera 141.2 47.7 47.7 55.2
Merced 92.1 53.7 58.5 65.1
San Joaquin92.881.075.874.4
Stanislaus 109.4 73.9 66.7 59.5
T ulare 114.2 72.9 72.7 68.3
Adjacent counties
Mariposa 58.3* 64.9* 46.1* 40.2*
T uolumne 82.5 61.6 47.7 53.6
California 99.4 71.0 64.0 58.1
United States96.465.560.856.2
Source: Centers for Disease Control and Prevention (CDC), National Center for Health Statistics.
Compressed Mortality File, a database containing mortality and population counts for all U.S.
counties, searchable by cause of death, state, county, age, race, sex, and year. It is available for
queries covering 1979-2002 via the CDC WONDER On-line Database at [http://wonder.cdc.gov].
Underlying cause of death is classified in accordance with the International Classification of Disease.
Deaths for 1979-98 are classified using the Ninth Revision (ICD-9). Deaths for 1999 and beyond are
classified using the Tenth Revision (ICD-10). In this table, cerebrovascular disease includes ICD-9
Codes 430-438 and ICD-10 Codes I60-I69.8.
Notes: The age-adjusted death rate is the hypothetical rate if the population of the county or state were
distributed by age in the same proportion as the 2000 United States population. It allows comparisons
between counties without regard to the influence of the actual age distribution in the various counties.
The crude death rate (not shown) represents the actual risk of dying in that county or state for the given
year (number of deaths divided by the population of the county or state).
Stroke is the third leading cause of death in the United States, after heart disease and cancer. In
general, the death rate for cerebrovascular disease has decreased significantly and steadily since 1980
for the United States as a whole and for California. Experience in the counties of the SJV has been
more mixed, with some counties showing a fairly steady decline in the rate (Kings, San Joaquin,
Stanislaus, and Tulare), while others have seen their rates decline and then increase again (Fresno,
Kern, Madera, and Merced). In 2002, 6 of the 8 SJV counties had age-adjusted death rates for
cerebrovascular disease that were higher than the averages for both California and for the United
States.
*Statistically unreliable rate, because it is based on a death count of 20 or fewer deaths in the county.
Table 61. Age-Adjusted Death Rates from All Causes of Death:
United States, California, and Counties of the SJV, 1980-2002
1980 1990 2000 2002
Age-adjusted deaths per 100,000 population
SJV
Fresno 1,002.7 919.0 829.6 843.6
K e rn 1,103.5 1,019.0 931.8 962.4
K i ngs 1,044.3 987.3 870.6 832.9
Madera 1,003.8 890.4 843.7 788.1
Merced 1,090.6 898.4 829.0 864.5
San Joaquin1,050.4757.9861.5877.8
Stanislaus 991.2 909.2 895.5 917.8
T ulare 1,053.1 997.9 898.7 886.6
Adjacent counties
Mariposa 901.2 817.0 719.2 779.9
T uolumne 1,088.1 916.3 833.9 817.3
California 995.6 904.3 787.2 758.1
United States1,038.7938.0868.3845.3
Source: Centers for Disease Control and Prevention (CDC), National Center for Health Statistics.
Compressed Mortality File, a database containing mortality and population counts for all U.S.
counties, searchable by cause of death, state, county, age, race, sex, and year. It is available for
queries covering 1979-2002 via the CDC WONDER On-line Database at [http://wonder.cdc.gov].
Note: The age-adjusted death rate is the hypothetical rate if the population of the county or state were
distributed by age in the same proportion as the 2000 United States population. It allows comparisons
between counties without regard to the influence of the actual age distribution in the various counties.
The crude death rate (not shown) represents the actual risk of dying in that county or state for the given
year (number of deaths divided by the population of the county or state).
Table 62. Age-Adjusted Prevalence of Diagnosed Diabetes in
Adults: United States, California, and Counties of the SJV, 2000-
2003
2000 2001 2002 2003
Age-adjusted rate per 100 adults (age 18 and over)
SJV
Fresno NA 7.8 NA 8.1
KernNA7.1NA7.4
KingsNA8.8NA9.1
Madera NA 6.6 NA 9.2
Merced NA 7.9 NA 10.5
San JoaquinNA7.7NA7.8
Stanislaus NA 6.3 NA 5.7
T ulare NA 10.5 NA 9.4
Adjacent counties
T uolumne/Calaveras/
Amador/Inyo/Mariposa/
Mono/Alpine NA 5.1 NA 5.6
California NA 6.1 NA 6.6
United States6.06.46.56.5
Sources: Estimates of the age-adjusted prevalence of diagnosed diabetes among adults in California
and California counties have been available since 2001 through the California Health Interview Survey
(CHIS). CHIS 2001 and CHIS 2003 are population-based household telephone surveys of a sampling
of California adults, providing county-specific data on various health measures, including diabetes.
The survey is planned again for 2005. See Laura E. Lund and Gary He, Prevalence of Diabetes in
California Counties, 2001, California Department of Health Services, Center for Health Statistics,
County Health Facts No. 04-01, January 2004. Also Laura E. Lund, Prevalence of Diabetes in
California Counties: 2003 Update, County Health Facts Update No. 05-A, February 2005. Both are
available at [http://www.dhs.ca.gov/hisp/chs/OHIR/reports/].
Before CHIS, diabetes prevalence for California counties was estimated by extrapolation from state
rates determined by the California Behavioral Risk Factor Survey. The rates are not comparable to
those derived from CHIS. See, for example, the January 2000 report, The Burden of Diabetes in
California Counties, published by the Diabetes Control Program of the California Department of
Health Services. The report is available at [http://www.caldiabetes.org] (click on Data).
Estimates of the age-adjusted prevalence of diagnosed diabetes among adults in the United States
come from the annual National Health Interview Survey conducted by the National Center for Health
Statistics (NCHS) of the Centers for Disease Control and Prevention (CDC). They are published
annually in Summary Health Statistics for U.S. Adults: National Health Interview Survey, [year] (see
Table 8), which is a publication in the Vital and Health Statistics Series 10. The most recent
compilation of prevalence rates for diagnosed diabetes, covering 1997-2004, may be found at
[http://www.cdc.gov/nchs/about/major/nhis/released200503.htm] in the Early Release of Selected
Estimates Based on Data From the January-September 2004 National Health Interview Survey.
Note: Among the 8 SJV counties, only Stanislaus in 2003 had a diabetes prevalence rate lower than
the state rate. All the other counties had rates higher than the state and U.S. rates in both 2001 and
2003. In company with the state and U.S. rates, rates for 6 of the 8 counties increased between 2001
and 2003.
Table 63. Diabetes Deaths — Age-Adjusted Death Rates for
Diabetes Mellitus: United States, California, and Counties of the
SJV, 1980-2002
1980 1990 2000 2002
Age-adjusted deaths per 100,000 population
SJV
Fresno 15.6 18.3 28.3 27.9
K e rn 20.2 15.1 28.4 31.9
K i ngs 13.3* 29.5* 44.6 65.6
Madera 20.0* 29.0 32.6 30.7
Merced 26.2 23.3 32.9 35.4
San Joaquin18.220.725.431.9
Stanislaus 17.3 10.3 24.2 29.2
T ulare 14.4 21.1 31.4 32.0
Adjacent counties
Mariposa 15.5* Suppressed Suppressed Suppressed
T uolumne 2.1* 17.4* 9.5* 16.7*
California 13.8 14.2 21.3 22.2
United States18.120.725.025.4
Source: Centers for Disease Control and Prevention (CDC), National Center for Health Statistics.
Compressed Mortality File, a database containing mortality and population counts for all U.S.
counties, searchable by cause of death, state, county, age, race, sex, and year. It is available for
queries covering 1979-2002 via the CDC WONDER On-line Database at [http://wonder.cdc.gov].
Underlying cause of death is classified in accordance with the International Classification of Disease.
Deaths for 1979-98 are classified using the Ninth Revision (ICD-9). Deaths for 1999 and beyond are
classified using the Tenth Revision (ICD-10). In this table, diabetes is defined as ICD-9 Codes 250-
250.9 and ICD-10 Codes E10-E14.9.
Notes: The age-adjusted death rate is the hypothetical rate if the population of the county or state were
distributed by age in the same proportion as the 2000 United States population. It allows comparisons
between counties without regard to the influence of the actual age distribution in the various counties.
The crude death rate (not shown) represents the actual risk of dying in that county or state for the given
year (number of deaths divided by the population of the county or state).
For 1989 and later, some death rates are marked “Suppressed” due to confidentiality constraints and
concern for protecting personal privacy in the case of small counties (year 2000 population less than
100,000) with few deaths (5 or fewer deaths from the condition.)
*Statistically unreliable rate, because it is based on a death count of 20 or fewer deaths in the county.
Medicare Enrollment in the SJV and Appalachia. In 2001-2003, 9.8%
of the SJV population was covered by Medicare (Table 64). The proportion of the
region’s population covered by Medicare has been relatively stable and was less than
the rate in California (10.9%) and the United States (13.5%). Data are not available
for Central Appalachia, but the four states containing the 68 counties had higher
proportions of their population covered by Medicare (Table 65). In 2001-2003,
Kentucky had 15.8% of its population covered by Medicare, 13.5% in Tennessee,
13.1% in Virginia, and 20.2% in West Virginia. These rates reflect the fact that
Appalachia’s population has a much higher proportion of elderly. Rural areas in the
United States generally have higher proportions of those 65 and older than the United
States as whole.
In 1988-1990, the Metropolitan Statistical Areas of Modesto and Stockton-Lodi
had greater rates of Medicare coverage than California. Modesto’s proportion was
also greater than that of the United States. In 1998-2000, Stockton-Lodi also has had
the highest proportion of its population covered by Medicare, although the rate
(10.1%) was lower than that of California (10.9%). All other SJV metropolitan areas
had lower Medicare rates than California. In the 2001-2003 period, Modesto’s rate
of Medicare coverage grew to 13.4%, up from 9.1% in 1998-2000. Only Modesto
had higher proportions of its population under Medicare than California.
Table 66 and Table 67 provide data on per capita monthly Medicare
expenditures for aged beneficiaries in traditional medicine for the SJV and Central
Appalachian counties respectively.
Per capita monthly expenditures for aged beneficiaries on traditional medicine in the
SJV was $527 in 2003 (Table 66). This was less than monthly expenditures in
California ($620) and nearly the same as for the United States ($534). The adjacent
counties of Mariposa and Tuolumne had lower monthly expenditures than the SJV.
Monthly expenditures grew by 44% between 1990 and 2003 and 16.5% between
2000 and 2003. Monthly expenditures were highest in Stanislaus County ($680) and
lowest in Fresno County ($459).
In 2003, per capita monthly expenditures for aged beneficiaries on traditional
medicine in the Central Appalachia was $541, slightly higher than the per capita
expenditure rate in the SJV, and generally higher than the monthly rate for most of
the individual SJV counties (Table 67). The monthly per capita rate in Cental
Appalachia was higher than the rate in each of the four states and the United States.
Monthly per capita rates increased by 52.5% between 1990 and 2003 and by 17.6%
between 2000 and 2003.
Table 64. Percent of the Population Covered by Medicare:
United States, California, and MSAs of the SJV, 1988-2003
1988-1990 1998-2000 2001-2003
SJV9.8%9.1% a9.8%
Bakersfield (Kern County)10.7%8.9%7.2%
Fresno (Fresno County 1989-1991;
Fresno and Madera Counties later years)6.6%9.3%10.7%
Merced (Merced County)8.2%7.9%
Modesto (Stanislaus County)14.0%9.1%13.4%
Stockton-Lodi (San Joaquin County)11.4%10.1%9.6%
Visalia-T ulare-Porterville
(Tulare County)8.3%8.2%9.9%
California 10.9% 10.9% 10.9%
United States12.8%13.3%13.5%
Sources: Calculated by CRS from the March Current Population Surveys (CPS) for 1989-1991,
1999-2001, and 2002-2004. The March CPS collects health insurance information for the previous
year.
Notes: In order to increase the sample sizes for each MSA, all estimates are three-year averages. An
MSA consists of an urban center (or centers) and adjacent communities that have a high degree of
economic and social integration.
a. Data for 1998 and later years may not be comparable to data for 1988-1990. Data for 1998 and
later years include an MSA for Merced County. For 1998 and later, the Fresno MSA includes
both Fresno and Madera counties.
Table 65. Percent of the Population Covered by Medicare:
United States, Kentucky, Virginia, Tennessee, West Virginia,
and Central Counties of the ARC, 1988-2003
1988-1990 1998-2000 2001-2003
Central ARC Counties NANANA
K e ntucky 14.1% 14.0% 15.8%
T e nnessee 14.4% 12.6% 13.5%
V i rginia 11.2% 13.2% 13.1%
West Virginia15.8%19.5%20.2%
United States12.8%13.3%13.5%
Sources: Calculated by CRS from the March Current Population Surveys (CPS) for 1989-1991,
1999-2001, and 2002-2004. The March CPS collects health insurance information for the previous
year.
Note: In order to increase the sample sizes for each state, all estimates are three-year averages.
Table 66. Per Capita Monthly Medicare Expenditures for Aged
Beneficiaries in Traditional Medicare: United States, California,
and Counties of the SJV, 1990-2003
199020002003
SJV$295 $440 $527
Fresno$260 $391 $459
Kern$337 $490 $563
Kings$246 $413 $449
Madera$266 $409 $474
Merced$308 $419 $512
San Joaquin$313 $451 $526
Stanislaus$293 $501 $680
Tulare$288 $390 $464
Adjacent counties
Mariposa$265 $372 $431
Tuolumne$283 $368 $486
California$366 $526 $620
United States$298 $441 $534
Source: Table created by CRS based on data from the Centers for Medicare and Medicaid Services.
Note: Amounts are based on three-year averages ending in the years shown and are weighted by
beneficiary demographics and count.
Table 67. Per Capita Monthly Medicare Expenditures for Aged
Beneficiaries in Traditional Medicare: United States, Kentucky,
Virginia, Tennessee, West Virginia, and Central Counties of
the ARC, 1990-2003
199020002003
Central ARC Counties $257$446$541
K e ntucky $244 $399 $493
T e nnessee $258 $407 $488
V i rginia $258 $342 $419
West Virginia$275$387$471
United States$298 $441 $534
Source: Table created by CRS based on data from the Centers for Medicare and Medicaid Services.
Note: Amounts are based on three-year averages ending in the years shown and are weighted by
beneficiary demographics and count.
Crimes and Crime Rates in the SJV and Appalachia. Although the
crime rate per 100,000 population in the SJV declined from 7,692 in 1980 to 6,812
in 1990, the total number of crimes increased between 1980 and 1990 from 157,530
to 186,889 (Table 68).68 Violent crimes, which include murder and non-negligent
manslaughter, forcible rape, robbery, and aggravated assault, increased from 14,852
incidents in 1980 to 22,391 in 1990. Property crime also increased between 1980 and
1990. The crime rate per 100,000 population in the SJV was slightly less than the
rate for California in 1980 and somewhat higher than California’s rate in 1990.
Madera, Merced, Stanislaus, and Tulare counties had rates lower in 1980 than both
California and the SJV rate. Fresno, Kern, Kings, and San Joaquin counties had
rates per 100,000 higher than California and the SJV rate in 1980. Data were not
available for Mariposa County, but Tuolumne County had a crime rate of 3,979 per
100,000 population in 1980, almost half the rate of California and the SJV, and for
SJV and California’s crime rates declined between 1980 and 1990. Kings
County saw its rate decline from 5,221 per 100,000 population to 3,805 per 100,000,
although the total number of crimes remained about the same. Kings, Madera, and
Merced counties had roughly the same number of total crimes in 1990 as they did in
1980. Kern County’s total number of crimes decreased from 36,144 in 1980 to
34,931 in 1990. San Joaquin County, on the other hand, had a total of 40,006 crimes
in 1990, up from 29,929 in 1980. Tuolumne County had a total of 1,258 crimes in
Between 1990 and 2000, the total number of crimes in the SJV decreased from
California’s rate fell as well, to 3,740. With the exception of Kings and Madera
counties, in 2000 the SJV counties each had crime rates per 100,000 population
higher than California. Tuolumne County’s rate fell to 1,644 per 100,000 in 2000.
In 2003, however, the total number of crimes in the SJV increased by over 14,000
crimes and the rate per 100,000 population increased slightly to 4,872. Most of the
increase was attributable to increases in property crimes.
Crime rates and total number of crimes were not calculated for the 68 counties
of Central Appalachia. The rates per 100,000 for the four Appalachian states,
however, were each significantly lower than the rates for the SJV (Table 69). In
some years, the total number of crimes committed in Kentucky and West Virginia
was less than for the eight counties of the SJV. With the exception of Tennessee in
2000 and 2003, the crime rate of the SJV exceeded the rate per 100,000 population
in each Appalachian state (Table 69). Total property crimes in the SJV were almost
as high as the combined property crime total for Kentucky and West Virginia in
68 Crime data were reported for MSA’s that were contiguous with single counties or the sum
of offences reported by city, county and state law enforcement agencies for the county.
Table 68. Number of Crimes and Crime Rate: United States,
California, and Counties of the SJV, 1980-2003
Total
Crimes:
TotalNumber of Number of Rate Per
number ofviolentapropertyb100,000
crimescrimes crimes Population
1980
SJ V 157,530 14,852 142,678 7,692
Fresno County43,4244,68838,7368,438
Kern County36,1443,28632,8588,967
Kings County3,8504923,3585,221
Madera County2,9203722,5484,626
Merced County8,0325877,4455,969
San Joaquin County29,9292,56727,3628,617
Stanislaus County20,2361,51418,7227,610
Tulare County12,9951,34611,6495,288
Adjacent counties
Mariposa CountyNA
Tuolumne County1,3501751,1753,979
California 1,843,332 210,290 1,633,042 7,788
United States13,408,3001,344,52012,063,7005,919
1990
SJ V 186,889 22,391 164,498 6,812
Fresno County55,0366,79948,2378,245
Kern County34,9314,64630,2856,410
Kings County3,8614573,4043,805
Madera County3,8314583,3734,349
Merced County c8,2668667,4004,633
San Joaquin County40,0063,93736,0698,324
Stanislaus County24,2022,96221,2406,532
Tulare County c16,7562,26614,4905,372
Total
Crimes:
TotalNumber of Number of Rate Per
number ofviolentapropertyb100,000
crimescrimes crimes Population
Adjacent counties
Mariposa CountyNA
Tuolumne County1,258701,1882,596
California 1,965,237 311,051 1,654,186 6,604
United States14,475,6131,820,12712,655,4865,820
2000
SJ V 160,093 21,804 138,289 4,847
Fresno County c48,2526,04242,2106,036
Kern County25,5603,24022,3203,863
Kings County3,1313532,7782,418
Madera County4,5958033,7923,732
Merced County8,9931,3077,6864,271
San Joaquin County29,6334,59425,0395,258
Stanislaus County23,8403,08820,7525,333
Tulare County16,0892,37713,7124,372
Adjacent counties
Mariposa CountyNA
Tuolumne County896968001,644
California 1,266,714 210,531 1,056,183 3,740
United States11,608,0701,425,48610,182,5844,125
2003
SJ V 174,538 22,755 151,783 4,872
Fresno County c 47,5205,05542,4655,588
Kern County33,1253,74229,3834,645
Kings County c3,9174343,4832,827
Total
Crimes:
TotalNumber of Number of Rate Per
number ofviolentapropertyb100,000
crimescrimes crimes Population
Madera County c5,0228644,1583,763
Merced County11,5331,6039,9304,980
San Joaquin County40,7815,38135,4006,445
Stanislaus County30,0743,11026,9646,110
Tulare County2,5662,566NANA
Adjacent counties
Mariposa CountyNA
Tuolumne County1,6402041,4362,890
California 1,420,637 205,551 1,215,086 4,004
United States11,816,7821,381,25910,435,5234,063
Sources: U.S. Department of Justice, Federal Bureau of Investigation, Crime Statistics in the United
States, various issues. The population estimates used to calculate crime rates are from Table 2 above.
Notes: Data are for (a) metropolitan statistical areas (MSAs) that are contiguous with single counties
or (b) the sum of offenses reported by city, county, and state law enforcement agencies for the county.
Data for cities are for cities and towns with populations of 10,000 or more.
a. Violent crimes include murder and non-negligent manslaughter, forcible rape, robbery, and
aggravated assault.
b. Property crimes include burglary, larceny theft, and motor vehicle theft.
c. Because of changes in reporting procedures (e.g., a new or separate MSA), data may not be
comparable to data for previous years.
Table 69. Number of Crimes and Crime Rate: United States,
Kentucky, Virginia, Tennessee, West Virginia, and Central
Counties of the ARC, 1980-2003
Total
Number of Number of Crimes: Rate
Total numberviolentapropertybPer 100,000
of crimescrimes crimes Population
1980
Central ARC CountiesNA
K e ntucky 125,039 9,711 115,328 3,416
T e nnessee 204,456 20,824 183,632 4,453
V i rginia 245,942 16,355 229,587 4,600
West Virginia49,2663,54745,7192,526
United States13,408,3001,344,52012,063,7005,919
1990
Central ARC CountiesNA
K e ntucky 121,594 14,386 107,208 3,298
T e nnessee 246,346 32,698 213,648 5,051
V i rginia 274,757 21,694 253,063 4,439
West Virginia44,8913,03641,8552,503
United States14,475,6131,820,12712,655,4865,820
2000
Central ARC CountiesNA
K e ntucky 119,626 11,903 107,723 2,960
Total
Number of Number of Crimes: Rate
Total numberviolentapropertybPer 100,000
of crimescrimes crimes Population
T e nnessee 278,218 40,233 237,985 4,890
V i rginia 214,348 19,943 194,405 3,028
West Virginia47,0675,72341,3442,603
United States11,608,0701,425,48610,182,5844,125
2003
Central ARC CountiesNA
K e ntucky 121,195 10,777 110,418 2,943
T e nnessee 296,010 40,177 255,833 5,067
V i rginia 220,106 20,375 199,731 2,980
West Virginia47,3754,66142,7142,617
United States11,816,7821,381,25910,435,5234,063
Sources: U.S. Department of Justice, Federal Bureau of Investigation, Crime Statistics in the United
States, various issues. The population estimates used to calculate crime rates are from Table 2 above.
a. Violent crimes include murder and non-negligent manslaughter, forcible rape, robbery, and
aggravated assault.
b. Property crimes include burglary, larceny theft, and motor vehicle theft.
Chapter 3 — Federal Direct Expenditures in the San
Joaquin Valley and the Appalachian Regional
Commission Area
Scope. This chapter describes the functional categories and funding levels of
federal direct expenditures and obligations going to the San Joaquin Valley and
compares it to the 410-county ARC area and to Central Appalachia, a 68-county
subregion of the Appalachian Regional Commission area comprised of particular
counties in Kentucky, Tennessee, Virginia, and West Virginia. Comparative federal
funds data for FY2003 are also provided for another distinctive economic
development area, the Tennessee Valley Authority, a 186 county area in Alabama,
Georgia, Kentucky, Mississippi, North Carolina, Tennessee, and Virginia (See
Appendix E for a list of the counties). Data on total direct federal expenditures in
the SJV and Appalachia are provided for the two most recent fiscal years available,
FY2002 and FY2003. Related, but not directly comparable, data on six functional
categories developed by the USDA’s Economic Research Service are provided for
the 68-county Central Appalachia area and for the SJV. A rough gauge of the
importance of federal programs locally can be obtained by computing total federal
funds received in a particular county divided by the county’s population (federal
funds per capita). Per capita data on federal expenditures are also provided in the
tables below. Two non-metro counties adjacent to the SJV, Mariposa and
Tuolumne, are also profiled and compared to the eight county SJV.
Federal expenditures are the obligations made by various federal agencies to
state, county, and subcounty areas of the United States, including the District of
Columbia and U.S. outlying areas. Total federal assistance is larger than total federal
payments. For FY2002, reported amounts for nationwide direct expenditures or
obligations (i.e., payments) totaled $2.1 trillion. However, there was an additional
$966 billion in other federal assistance in FY2002 for direct and guaranteed loans and
insurance programs. These latter programs, while part of federal benefits, are
considered “contingent liabilities” of the federal government. Loans are expected to
be repaid and insurance payments occur only when an insured event occurs, (e.g.,
crop damage or flooding). If a loan is in default or a payment made for insured
damages, only then is there a federal obligation, i.e., a payment. When that happens,
the payment is included in the category of direct expenditures and obligations.
No single data source consistently reports accurate and complete figures on the
geographic distribution of federal funds. The federal government currently has five
major sources that present geographical distribution of federal domestic grants, loans,
salaries and wages, direct payment to individuals, and federal procurement activity.
These five sources are (1) Federal Aid to States, (2) the Consolidated Federal Funds
Report, both published annually by the U.S. Bureau of the Census; (3) the Office of
Management and Budget Circular A-133 audits; (4) the Federal Procurement
Report; and (5) the Analytical Perspectives volume of the U.S. budget documents.69
For comparative purposes, CRS chose the Consolidated Federal Funds Report
because it has the broadest county level coverage. Federal Aid to the States provides
69 See CRS Report 98-79, Federal Funds: Tracking Their Geographic Distribution.
a relatively comprehensive picture of individual federal agencies and functional areas
within those agencies, and the aggregate figures are included in the broad categories
of the Consolidated Federal Funds Report. Readers are encouraged to examine the
data sources for additional perspective on federal funding to particular geographic
areas.
The Consolidated Federal Funds Report.70 Federal funds data reported
below were compiled from the Consolidated Federal Funds Report, State and
County Area (CFFR), an annual compilation of federal expenditures disaggregated
into various categories of funding obligations and outlays to counties and states. The
CFFR is published by the Department of Commerce, Bureau of the Census,
Government Division and covers federal government expenditures or obligations.
Generally, federal grants and procurement data represent obligated funds. Direct
payments (e.g., retirement and disability) and salaries and wages represent actual
expenditures or outlays. Data in the CFFR are developed by aggregating available
statistics on federal expenditures and obligations. Primary data sources for the CFFR
are:
!Federal Assistance Awards Data System,
!Federal Procurement Data System,
!Office of Personnel Management,
!Department of Defense,
!U.S. Postal System
For FY2003, the most recent data available, total direct federal expenditures and
obligations to all states and territories presented in the CFFR totaled $2.1 trillion.
This amount, however, excludes expenditures that could not be geographically
distributed, all international and foreign payments, and federal outlay categories not71
covered by any of the reporting systems serving as data sources for the CFFR. For
some agencies, data for selected object categories could not be obtained. These
include the procurement actions of the judicial and legislative branches of the federal
government. Expenditures other than salaries and wages are not available for the
Federal Deposit Insurance Corporation, National Credit Union Administration , and
the Federal Savings and Loan Insurance Corporation.
Many agency grant programs make direct payments to state governments who
administer the programs and then “pass through” the funds to local government (e.g.,
block grants, transportation funds, and other assistance programs). To the extent
possible, data on sub-state grants are provided in the CFFR at the county or county-
equivalent area. Outlays for sub-state programs include the following:
70 Information presented in the section is taken from the Introduction to the Consolidated
Federal Funds Report, 2004 (pp. v-xviii).
71 The largest unreported items were net interest on federal debt (estimated at $153 million
for FY2003) and FY2003 outlays for the international affairs budget (estimated at $21
billion). Expenditures for the Central Intelligence Agency, the Defense Intelligence Agency,
and the National Security Agency are excluded from coverage.
!Food Stamps
!National School Lunch Program
!Special Supplemental Food Program for Women, Infants, and
Children (WIC)
!Handicapped Education-State Grants
!Rehabilitation Services - Basic Support
!Low-Income Home Energy Assistance
!Social Services Block Grant
!Block Grants for Prevention and Treatment of Substance Abuse.
The CFFR contains detailed methodological information on the availability,
reliability, and coding of federal funds data. Readers are encouraged to review the
CFFR for greater detail on the compiling of federal data for the CFFR for better
understanding of the data presented here. Certain categories of spending are
intentionally excluded in the CFFR, e.g., interest paid on the federal debt,
international payments, and foreign aid, and some agencies do not submit data to any
of the federal statistical reporting systems, (e.g., Central Intelligence Agency,
Defense Intelligence Agency, and National Security Agency). Individual federal
agency expenditures are also provided in CFFR tables. The agency data, however,
are reported only at the state level. As noted above, some of these funds do go to
individual counties and are, to the extent possible, accounted for in the CFFR direct
expenditure data on the counties.
The CFFR also provides state-level data on direct loans, guaranteed loans, and
insurance. These data are, with some exceptions, compiled from the Federal
Assistance Award Data System (FAADS). Data on direct loans, guaranteed loans,
and insurance are reported in the FAADS by state and county area, but are not
disaggregated to the county level in the CFFR. For this report, CRS has not
attempted to reconstruct FAADS and aggregate county level data on individual loan
and insurance programs for the SJV or for Central Appalachia. Nonetheless, federal
funding support for these functions may properly be regarded as part of “total federal
assistance” going to the respective regions. Only data on direct federal expenditures
and obligations are reported in the following tables in this chapter. Appendix F,
however, provides federal direct expenditures and obligation for individual programs
by SJV county. Appendix F also provides funding data for other federal assistance,
(i.e., direct and guaranteed loans and insurance programs).
In the related comparison between the 68 Central Appalachian counties and the
SJV counties also presented here, USDA’s Economic Research Service (ERS) did
compile data on some direct loans, guaranteed loans, and insurance and include that
in the total figures. However, ERS data exclude programs for which most or all of
their funding is reported only at the state or national level. For example, most of the
large block grant program related to social services, employment, and training were
excluded. Thus, these exclusions tend to understate the actual level of federal
funding received by counties, particularly for the category of Human Resources. For
these reasons, we recognize that the ERS data are not directly comparable to the
CFFR data for the two regions in the following tables, even though the CFFR is the
source for all the tables presented in this chapter.
Comparing FY2002 Federal Expenditures in the San Joaquin, the
United States, and California. Table 70 provides total and per capita amounts
of federal direct expenditures and obligations in FY2002 for the SJV, individual
counties in the SJV, and the two adjacent counties of Mariposa and Tuolumne.
(Table 71) provide data for the ARC region). Table 72 presents total and per capita
federal expenditures in the SJV for FY2003, the most recent available. Analysis of
federal direct expenditures data and various socioeconomic variables reveal several
patterns.
According to a 2002 report, California residents paid over $58 billion more in
federal taxes than the state received back in federal spending.72 There are two
primary reasons why Californians are net tax exporters. First, California’s
above-average income creates above-average federal income tax receipts. Second,
the fastest growing portion of the federal budget is in Social Security and Medicare
payments. California’s population is significantly younger than the U.S. average, and
thus has fewer recipients of payments from these programs. In contrast to
Appalachia, with its higher proportion of those 65 and over, California’s wealth and
youthfulness may constitute positive attributes. A negative balance of payments
could be viewed as one cost of these demographic advantages.73
In FY2002, the SJV received $15.64 billion dollars in federal direct
expenditures and obligations. This was a per capita rate of $4,472. Total amounts
to individual counties ranged from highs of $3.7 billion each in Fresno and Kern
counties to a low of $500.4 million to Madera County. Per capita rates ranged from
a high of $5,403 in Kern County to a low of $3,841 in Madera County. The per
capita rate for the SJV was $2,178 less than the $6,650 per capita federal expenditure
rate for the United States, and $1,406 less than the per capita rate for California
($5,878). The data further showed that each SJV county had a lower per capita rate
of federal expenditure than either the United States or California. Most SJV counties
were substantially below the national per capita rate of $6,650, ranging between
$1,247 to $2,809 per capita lower. Individual SJV counties ranged from $2,037
(Madera) to $475 (Kern) less per capita than the rate for California in FY2002.
In every federal expenditure category (retirement and disability, other direct
payments to individuals and others, grants, procurement contracts, and salaries and
wages), the SJV had a lower per capita federal expenditure and obligation rate than
the per capita rates for the United States and California. With a few exceptions, the
SJV counties had per capita federal expenditure levels below the national per capita
rate and state rates. In the category of retirement and disability spending, several SJV
counties had rates near or slightly above the state average. For wage and salary
expenditures, Kings and Kern counties had higher per capita rates than California or
the United States.
72 See California Institute for Federal Policy Research. Special Report: California’s
Balance of Payments with the Federal Treasury, Fiscal Years 1981-2002. Washington, DC.
73 Ibid.
Of the total $15.64 billion in federal expenditures going to the SJV in FY2002,
$5.71 billion was for retirement and disability payments. Retirement and disability
programs include federal employee retirement and disability payments benefits,
Social Security payments of all types, selected Veterans Administration programs,
and selected other federal programs. The per capita rate for retirement and disability
payments in the United States in FY2002 was $2,126. In the SJV, it was $1,632 per
capita, with the rate ranging from a high of $1,732 in San Joaquin County to a low
of $1,375 in Kings County. Direct payments to individuals other than for retirement
and disability amounted to $3.41 billion in FY2002 for a per capita rate of $976 for
the region. Other direct payments to individuals include such programs as crop
insurance indemnity payments, legal services, Postal Service operations, food
stamps, Federal Employee Workers Compensation, Unemployment Compensation
Trust Fund payments, and Medicare payments. For the SJV, per capita payment for
these other direct payment programs at $976 were lower than the rate for the United
States ($1,464) and for California ($1,286).
Grants are the second largest category of federal expenditures in the SJV after
retirement and disability. Grant expenditures to the SJV amounted to $3.87 billion
in FY2002 for a per capita rate on $1,107. This rate is 22.5 % less than the rate for
the United States ($1,430) and nearly 20% less than the rate for California ($1,369).
As with virtually all of the CFFR categories, no individual SJV county had a per
capita grant rate that was as high as the grant rate for either the United States or for
California.
Contract procurement expenditures in the United States were $940 per capita.
The per capita rate for the SJV was $260, over 72% less than the U.S. rate, and
ranged from $593 per capita in Kern County to $26 per capita in Madera County.
California has a slightly higher per capita rate for receiving federal contract
expenditures than the United States, $990 per capita in FY2002. Federal salary and
wage expenditures totaled $1.74 billion in the SJV, a per capita rate of $497, lower
than the per capita rate for the United States ($690) and for California ($545). At
$1,574, Kings County was distinctive in the SJV with its per capita rate for federal
wage and salaries being nearly three times the SJV and California rates and more
than double that of the United States.
Adjacent County Comparison. Mariposa especially and Tuolumne to a
lesser extent had higher per capita rates of direct federal expenditure than the SJV.
Mariposa’s per capita rate across all the CFFR categories was $6,123, which was
lower than the United States rate but higher than California’s. Tuolumne’s per capita
rate was $5,317, higher than most SJV counties, but lower than the per capita rates
for the United States and California. Retirement and disability and other direct
payments were the two largest expenditure categories respectively. Federal wages
and salaries are also a federal expenditure in Mariposa, with a per capita rate of
$1,361, nearly twice the national rate and over twice the SJV rate.74 The per capita
74 Mariposa and Tuolumne are, respectively, “government-dependent” and “service-
dependent” counties and are also characterized by large proportions of federal lands.
Government dependent and service dependent counties are two USDA Economic Research
(continued...)
rates for retirement and disability in Mariposa County ($2,823) and Tuolumne
County ($2,998) were also significantly higher than the rates for the SJV, the United
States, and California.
Metropolitan and Non-Metropolitan areas.75 With the exception of Kings
County, the eight counties comprising the SJV are metro counties as defined by the
U.S. Bureau of the Census. Metro counties in the United States, on average, receive
higher per capita federal expenditure rates than the national rate. This was not the
case in the SJV. Kern County had the highest per capita rate of federal direct
expenditures ($5,403) followed by Kings County ($5,321), a nonmetro county. Kern
County had the second largest 2002 population after Fresno County, while Kings
County had the second lowest population in the SJV.
Federal Funding in the SJV and the TVA for FY2003. Table 72
presents the most recent CFFR data available for the SJV and Table 73 presents the
same CFFR data for the TVA. These data are directly comparable to the FY2002
data in Table 70.
Population in the SJV grew by nearly 65,000 residents between July 2002 and
July 2003, a 1.8% increase. Total federal expenditures and obligations in the SJV
grew by $908.1 million to $16.55 billion. The per capita rate for FY2003 increased
to $4,619 from $4,472 in FY2002, a $147 increase (3.2%). Individual county per
capita rates rose unevenly, ranging from $5 in Kern County to $284 in Kings County.
Per capita rates rose for each CFFR category except for “other direct payments,”
which fell from $976 in FY2002 to $948 in FY2003. Retirement and disability
payments increased from $1,632 per capita to $1,665.
Grant spending per capita increased for 2003 in Fresno County to $1,340, up
from $1,180 in FY2002. Most expenditure categories rose slightly in each county.
Salary and wages in Kings County increased from $1,574 in FY2002 to $2,051 in
FY2003. Stanislaus County saw a drop of $10 per capita in federal wages and
salaries between FY2002 and FY2003 and Kern County saw a $31 drop in per capita
74 (...continued)
Service designations of non-metro counties based on a county’s dominant economic activity.
A government-dependent county receives at least 25% or more of its income from
government. Service-dependent counties are non-metro counties where at least 50% or more
of total income is from service sector employment (e.g., retail, business and professional,
education, finance, insurance, and real estate).
75 Rural areas are defined in the U.S. Bureau of the Census as places of less than 2,500
people, including rural portions of extended cities and areas outside incorporated places.
Metro and non-metro areas are defined by OMB’s Metropolitan Statistical Areas and
Micropolitan Statistical Areas and are collectively referred to as Core Based Statistical
Areas (CBSAs). Metro areas consist of (1) central counties with one or more urbanized
areas and (2) outlying counties that are economically tied to the core counties as measured
by worker commuting data. Outlying counties are included if 25% of workers living there
commute to the core counties, or if 25% of the employment in the county consists of
workers coming from the central counties. Non-metro counties are outside the boundaries
of metro areas and are further subdivided into micropolitan areas centered on urban clusters
of 10,000-50,000 residents, and all remaining “non-core” counties.
funding for contract procurement. In the category “other direct payments”, Fresno
County’s per capita rate fell by $42, although its rate increased by $268 across all
categories.
Per capita federal expenditure rates for the United States in 2003 across each
CFFR category were substantially higher than the rates in the SJV. The per capita
federal expenditure rate for the United States increased to $7,089 in FY2003 from
$6,650 in FY2002, a 6.6% increase. The gap between per capita federal expenditure
rates for the SJV and the United States increased by $292 over the FY2002
difference. The gap between the SJV per capita rate and the California rate also
increased by $167. While population growth alone does not necessarily mean an
increase in federal dollars going to a region, the population in California grew by 1%
compared to population growth of 1.8% in the SJV between 2002 and 2003.
Per capita federal direct expenditure for FY2003 in the TVA was $7,505 (Table
73). This was $2,886 more per capita more than the SJV, $1,474 per capita more
than the ARC area in FY2002, and $398 more per capita than the United States. In
every CFFR expenditure category, federal funding in FY2003 for the TVA exceeded
that of the SJV. With the exceptions of Alabama and Kentucky, however, the TVA
areas had lower per capita rates of federal direct obligations than their respective
states. Tennessee, all of whose counties are in the TVA, had a lower per capita rate
of federal expenditure that the United States ($206 per capita less).
The 7 TVA states have counties that are also within the ARC area (in some
states, TVA counties and ARC counties overlap). Comparing a state’s ARC region
to its TVA region in FY2002 shows that in all but two states (Mississippi and
Tennessee) the TVA region’s per capita expenditure exceeded the state’s ARC
region.
Comparing Federal Funding in the Appalachian Regional
Commission Area to Federal Funding in the SJV. In FY2002, federal direct
expenditures and obligations in the ARC area amounted to $138.07 billion compared
to the SJV’s total federal expenditure of $15.64 billion (Table 70 and Table 71).
The SJV received $2,342 per capita less (34.3%) than the ARC region in direct
federal expenditures and obligations in FY2002. The ARC region received $783 per
capita less than the national per capita rate in FY2002, while the SJV received $2,178
less than the national per capita rate.76 Only six of the 13 ARC state Appalachian
regions, however, matched or exceeded the ARC region’s (Alabama, Kentucky,
76 The ARC data presented here relied on April 2000 state and county population estimates
in calculating per capita rates for 2002 federal funds data. The data on the SJV in Table 70
used July, 2002 population estimates. If population growth was high in the ARC 2000-2002,
the per capita figures in Table 71 would be lower. Population growth in the ARC region,
however, grew only 9.1% between 1990 and 2000. In the SJV, the population grew 5.6%
between April 2000 and July 2002. Using 2000 population estimates for the San Joaquin
would introduce a significant degree of bias by inflating the actual per capita rates. For
example, using 2000 population estimates raises the per capita rate for federal funding in
the San Joaquin from $4,472 to $4,736. With population growth generally slow in the ARC
region, we judged that whatever bias may occur from using the 2000 estimates is likely to
be relatively insignificant.
Pennsylvania, Tennessee, Virginia, and West Virginia) per capita rate. Individual
ARC counties within the 13 states that comprise the ARC region may also receive
lower per capita rates than their respective state rates, and some states with few
Appalachian counties may receive disproportionate funding.77 In only one state’s
ARC counties (Georgia) was the per capita rate of direct federal expenditures lower
than that of the SJV.
Direct payments to individuals for retirement and disability is the largest
category of federal spending in the ARC region followed by grants and other direct
payments to individuals and direct payments other than to individuals.78 Per capita
payments in the SJV for retirement and disability averaged $1,632 in FY2002. In the
ARC region, the per capita payment was $6,031, $883 less than the per capita rate
nationally but $1,559 more than the per capita rate in the SJV. The ARC region’s
history of coal mining as well as the age of the ARC population, help explain the
high per capita disability and retirement rates for the ARC relative to the SJV. The
Black Lung Disability Trust fund, for example, is an important source of disability
payments in Appalachia. Per capita grant funding in the ARC area for FY2002 was
$1,229, which is $122 more than the SJV.
While there is significant variation among the Appalachian parts of the 13 states
that comprise the ARC region, in FY2002, per capita federal payments in the ARC
region as a whole ($6,031) exceeded the per capita rate of federal expenditure for
every SJV county. The per capita rates in the ARC region for all CFFR categories
of federal expenditure and obligation also exceeded those of the SJV, most by
substantial amounts. Other patterns in federal funding in the ARC may be seen with
procurement contracts. With the exception of Tennessee and Alabama, federal
spending on procurement contracts is generally low and similar to the SJV. While
the ARC region’s per capita payment for procurement contracts is $644 compared to
$260 in the SJV, Anderson County, Tennessee and Madison County, Alabama are
home to the U.S. Department of Energy’s Oak Ridge National Laboratory and
Marshall Space Center respectively, skewing this category. Without Tennessee and
Alabama’s relatively high per capita rates for federal procurement dollars ($1,626
and $1,757 per capita respectively), the ARC’s per capita rate for that category would
decline, although it would still be higher than the level of the SJV. As discussed
above, the potential for a few counties to skew overall regional per capita payments
77 An Ohio newspaper, the Columbus Dispatch, conducted a review of 22,169 grants
awarded from FY1966-FY1998 and found that none of the five counties receiving the most
funds had ever been considered a Distressed county, the ARC designation for the poorest
of Appalachian counties. Five poverty-stricken counties in Kentucky and West Virginia
finish near the bottom of the study, receiving less than $1.3 million each. Aid to Maryland,
New York, Pennsylvania, and South Carolina, states with few if any Distressed counties,
totaled nearly $4.6 billion, more than a fourth of all ARC non-highway spending. See
Ferenchik, Mark and Jill Riepenhoff. “Mountain money: Federal tax dollars miss the mark
in core Appalachia.” Columbus Dispatch, September 26, 1999.
[http://www.sullivan-county.com/ nf0/dispatch/moun_money.htm]
78 The ARC data disaggregated non-retirement direct payments to individuals and “direct
payments other than for individuals.” For the SJV, these two categories were combined into
“Other Direct Payments.”
is increased when examining the entire 410 county ARC region. Below, we examine
a relatively more homogenous group of Appalachian counties.
CRS-142
Table 70. Federal Direct Expenditures and Obligations in the SJV, FY2002
(thousands of dollars)
Total Federal
n JoaquinPopulationDirectExpendituresPeraRetirement andOther Direct PaymentsGrantsProcurementSalaries and Wages
unties(July, 2002)andCapita Disability
Obligations
TotalPerCapitaaTotal PerCapitaaTotalPerCapitaaTotalPerCapitaaTotalPerCapitaa
3 ,497,911 15,641,645 4,472 5,708,730 1,632 3,413,141 976 3,872,383 1,107 907,841 260 1,738,552 497
sno 834,632 3,775,225 4,523 1,319,908 1,581 791,021 948 985,257 1,180 184,064 221 494,975 593
rn 694,059 3,749,816 5,403 1,196,532 1,724 766,061 1,104 714,633 1,030 411,451 593 661,139 953
s 135,043 718,549 5,321 185,731 1,375 158,826 1,176 135,212 1,001 26,168 194 212,612 1,574
iki/CRS-RL33184ra 130,265 500,411 3,841 219,150 1,682 138,267 1,061 124,143 953 3,402 26 14,450 111
g/wrced 225,398 891,366 3,955 364,412 1,617 206,402 916 251,889 1,118 30,047 133 38,615 171
s.or
leakn Joaquin614,3022,557,6014,1631,064,2421,732538,645877654,3511,065127,490208172,874281
laus 482,440 1,889,937 3,917 805,704 1,670 426,606 884 473,185 981 105,400 218 79,042 164
://wikilare 381,772 1,558,740 4,083 553,051 1,449 387,313 1,015 533,713 1,398 19,819 51 64,845 170
httpAdjacent Counties
iposa 17,195 105,292 6,123 48,353 2,812 19,802 1,152 10,368 603 3,352 195 23,416 1,362
olumne 55,850 296,938 5,317 163,387 2,925 64,652 1,158 34,849 624 13,509 242 20,540 368
United States and California
. 288,368,698 1,917,637,403 6,650 612,995,927 2,126 422,239,079 1,464 412,371,161 1,430 270,965,430 940 199,065,805 690
iforn ia 35,116,033 206,401,495 5,878 59,256,019 1,687 45,165,873 1,286 48,083,694 1,369 34,752,544 990 19,143,365 545
Consolidated Federal Funds Report, FY 2003.
er capita amounts are reported in actual dollars.
CRS-143
Table 71. Federal Direct Expenditures and Obligations in the Appalachian Regional Commission, FY2002
(thousands of dollars)
Total Federal
DirectPerRetirement and
n Joaquin CountiesPopulation(April, 2000)ExpendituresandCapitaa DisabilitybOther Direct PaymentsGrantsProcurementSalaries and Wages
Obligations
TotalPerCapitaaTotal PerCapitaaTotalPerCapitaaTotalPerCapitaaTotalPerCapitaa
achian Region22,894,017138,071,0006,03157,864,0002,52728,104,0001,22828,128,0001,22914,749,0006449,227,000403
achian Alabama2,837,22420,989,0007,3987,363,0002,5953,532,0001,2453,122,0001,1004,985,0001,7571,988,000701
achian Georgia2,207,5317,232,0003,2763,684,0001,6691,474,0006681,328,000602302,000137444,000201
achian Kentucky1,141,5117,223,0006,3283,230,0002,8301,358,0001,1902,242,0001,96488,00077304,000266
achian Maryland236,6991,163,0004,913605,0002,556303,0001,280116,00049066,00027973,000308
iki/CRS-RL33184achian 615,452 3,450,000 5,606 1,433,000 2,328 793,000 1,288 861,000 1,399 153,000 249 210,000 341
g/wssi ssi p p i
s.orachian New York1,072,7866,219,0005,7972,530,0002,3581,118,0001,0421,634,0001,523653,000609283,000264
leakachian North1,526,2077,585,0004,9703,790,0002,4831,480,0009701,713,0001,122233,000153368,000241
olina
://wikiachian Ohio1,455,3137,106,0004,8833,268,0002,2461,568,0001,0771,794,0001,233181,000124296,000203
http
achian 5,819,800 37,124,000 6,379 15,848,000 2,723 9,041,000 1,553 7,266,000 1,248 2,652,000 456 2,317,000 398
ylvania
achian South1,028,6564,450,0004,3262,327,0002,262852,000828851,000827217,00051203,000197
olina
achian Tennessee2,479,31717,808,0007,1836,427,0002,5923,008,0001,2133,012,0001,2154,031,0001,6261,331,000537
achian Virginia665,1774,362,0006,5581,900,0002,856796,0001,197890,0001,338587,000882189,000284
st Virginia1,808,34413,361,0007,3895,460,0003,0192,780,0001,5373,298,0001,824602,0003331,221,000675
. 281,421,906 1,917,637,000 6,814 612,996,00 2,178 422,239,000 1,500 412,371,000 1,465 270,965,000 963 199,066,000 707
0
rce: U.S. Department of Commerce, Census Bureau, Consolidated Federal Funds Report, 2002 (downloaded from [http://www.census.gov/govs/www/cffr.html] on October
er capita amounts are reported in actual dollars.
tegory includes Black Lung Benefits Program payments
CRS-144
Table 72. Federal Direct Expenditures or Obligations in the San Joaquin Valley, FY2003
(thousands of dollars)
SanPopulationTotal Federal DirectPeraRetirement andOther Direct PaymentsGrantsProcurement ContractsSalaries and Wages
oaquin(July, 2003)Expenditures andCapita Disability
untiesObligations
TotalPeraTotal PeraTotalPeraTotalPer CapitaaTotalPera
Capita Capita Capita Capita
n 3,582,797 16,549,751 4,619 5,966,870 1,665 3,397,805 948 4,319,021 1,205 957,296 267 1,908,759 533
lley
sno 850,325 4,074,176 4,791 1,372,950 1,615 770,666 906 1,139,360 1,340 251,682 296 539,518 634
rn 713,087 3,856,033 5,408 1,249,312 1,752 736,277 1,033 768,614 1,078 401,096 562 700,733 983
s 138,564 776,751 5,606 199,699 1,441 121,100 874 144,740 1,045 26,959 195 284,254 2,051
iki/CRS-RL33184ra 133,463 522,284 3,913 232,627 1,743 128,968 966 138,528 1,038 6,653 50 15,508 116
g/wrced 231,574 964,503 4,165 386,083 1,667 219,077 946 290,309 1,254 22,694 98 46,339 200
s.orn 632,760 2,675,054 4,228 1,104,466 1,745 568,137 898 730,493 1,154 94,811 150 177,147 280
leak
://wikilaus 492,233 2,046,853 4,158 841,226 1,709 470,565 956 549,591 1,117 109,581 223 75,890 154
httplare 390,791 1,634,097 4,182 580,507 1,485 383,015 980 557,386 1,426 43,820 112 69,370 178
Adjacent Counties
iposa 17,803 134,623 7,562 50,207 2,820 23,120 1,299 15,258 857 19,592 1,100 26,446 1,485
olumne 56,755 332,012 5,850 169,574 2,988 70,706 1,246 58,149 1,025 11,408 201 22,174 391
United States and California
. 290,809,777 2,061,485,972 7,089 636,238,733 2,188 446,119,217 1,534 441,037,633 1,517 327,413,076 1,126 210,677,312 724
iforn ia 35,484,453 219,705,707 6,192 61,235,997 1,726 49,480,339 1,394 51,328,805 1,447 37,049,547 1,044 20,611,019 581
Consolidated Federal Funds Report, FY2003 (September 2004).
Some figures in this table were revised in December 2006 from the amounts originally published in December 2005. An error in the SJV July 2003 population figure resulted
htly higher per capita federal expenditure rates. Rather than an SJV per capita rate for federal expenditures of $4,645, as originally reported, the revised population figure results
per capita rate of $4,619. Total county expenditures were lower than originally reported for Kings and Merced counties, resulting in higher total county per capita rates in the
inal figures (e.g., $5,613 vs. $5,606 in Kings County). I am very grateful to Dr. Martha Jones of the California Research Bureau, California State Library, for bringing these errors
y attention.
er capita amounts are reported in actual dollars.
CRS-145
Table 73. Federal Direct Expenditures and Obligations in the Tennessee Valley Authority Area FY2003
(thousands of dollars)
Total Federal
ennesseePopulationDirectPerRetirement and
Valleyrity(July, 2003)ExpendituresandCapitaaDisabilityOther Direct PaymentsGrantsProcurementSalaries and Wages
Obligations
TotalPerCapitaaTotal PerCapitaaTotalPerCapitaaTotalPerCapitaaTotalPerCapitaa
ssee 40,721,886 305,611,715 7,505 94,163,755 2,312 53,831,196 1,322 54,483,644 1,338 62,626,877 1,538 40,533,244 995
rity
a 4 ,500,752 30,870,869 6,859 12,232,032 2,718 7,698,399 1,710 6,649,139 1,477 7,067,435 1,570 3,223,864 716
a TVA1,008,69911,073,24310,9782,753,6962,7301,128,2821,119979,3449715,098,2905,0541,113,6321,104
rgia 8 ,684,715 51,910,196 5,977 16,665,866 1,919 11,426,056 1,316 10,561,235 1,216 5,242,532 604 8,014,506 923
iki/CRS-RL33184rgia TVA388,3111,582,2154,075833,6732,147373,533962299,70977226,2106749,089126
g/w4,117,827 31,153,085 7,565 10,168,614 2,469 6,118,924 1,486 6,634,063 1,611 5,119,069 1,243 3,112,416 756
s.or
leak TVA631,0715,984,8469,4841,557,1922,468819,7071,299748,5661,1861,638,7792,5971,220,6021,934
://wikisissippi 2,881,281 21,740,611 7,545 6,922,911 2,403 4,903,648 1,702 5,318,478 1,846 2,625,647 911 1,969,926 684
httpssi p p iA 1,073,213 5,673,189 5,286 2,371,279 2,210 1,251,956 1,167 1,451,994 1,353 266,808 249 331,152 309
th Carolina8,407,24851,766,3626,15718,805,7412,23711,012,2831,31011,613,2141,3813,794,4554516,540,669778
h Carolina184,501947,1435,134428,7822,324180,863980183,547995155,17684125,775140
A
sseeb 5,841,748 40,311,139 6,901 13,743,588 2,353 7,039,653 1,205 8,648,710 1,481 7,521,940c 1,288 3,357,249 575
A
ginia 7,386,330 82,453,984 11,163 19,553,290 2,647 9,420,394 1,275 7,885,964 1,068 30,838,710 4,175 14,755,627 1,998
ginia TVA116,9421,015,7028,686359,1233,071155,8971,333158,8201,358299,2612,55942,601364
d States290,080,9772,061,485,9727,107636,238,7332,193446,119,2171,538441,037,6331,520327,413,07651210,677,312726
Consolidated Federal Funds Report, FY 2003.
er capita amounts are reported in actual dollars.
ll Tennessee counties are within the Tennessee Valley Authority.
rement figures for Tennessee are based on FY2000 data. TVA has not reported procurement data since FY2000.
Federal Funding in Appalachia and the San Joaquin: The Economic
Research Service Data. The data for the SJV and the ARC discussed above are
comparable and reveal significant variation both within each region and between the
two regions. In this section, we examine FY2000 federal funding data in the eight-
county SJV region and Appalachia based on data generated by researchers at the U.S.
Department of Agriculture’s Economic Research Service (ERS). ERS has studied
federal funding distribution in several regions of the United States using functional
categories developed from the CFFR object codes.79 Appalachia, as ERS has defined
it, is a 246 county area in 12 states, as opposed to the ARC area of 410 counties in
13 states (ERS excluded South Carolina). Central Appalachia as defined by ERS is
a 68-county, largely rural region in Kentucky, Tennessee, Virginia, and West Virginia
(for a list of the counties, see Appendix D).80 This area comprises the counties for
which certain socioeconomic data are provided in Chapter 2.
Central Appalachia contains some of the poorest counties in the entire ARC
region with 45 of its 68 counties defined by the ARC as Distressed counties (see
description of ARC county categories in Chapter 2). As the data in Chapter 2
demonstrate, there are socioeconomic parallels between the SJV and Central
Appalachia in terms of poverty and unemployment. The area is also heavily
dependent on low-wage, low-skilled service sector employment. Like the SJV,
Central Appalachia has long seen many of its better educated residents leave for more
attractive economic opportunities elsewhere.
79 See Bagi, Faqir S., Richard Reeder, and Samuel Calhoun. “Federal funding’s unique role
in Appalachia.” Rural Development Perspectives, 14(1), May, 1999; Reeder, Richard, Faqir
Bagi, and Samuel Calhoun. Which federal programs are most important for the Great
Plains?” Rural Development Perspectives, 113(1), June, 1998.
80 The Economic Research Service’s Central Appalachian region is smaller by 164 counties
than Appalachia as defined by the ARC (410 counties) and 147 counties smaller than the
ARC defined region of Central Appalachia. ERS defined Appalachia following a modified
version of the counties identified in Donald J. Bogue and Calvin L. Beale’s, Economic Areas
of the United States (Free Press, 1961). The ARC region includes the entire State of West
Virginia, and part of 11 other States (from north to south): New York, Pennsylvania, Ohio,
Maryland, Virginia, Kentucky, Tennessee, North Carolina, Georgia, Alabama, and
Mississippi. One county in Kentucky and two in Virginia were dropped from the list
identified by Bogue and Beale because these counties are not under ARC’s jurisdiction.
Appalachia is further subdivided into subregions. Northern Appalachia includes 2 counties
in Maryland, 23 in Ohio, 37 in Pennsylvania, and 46 in West Virginia. Of these, 34 are
metro (urban) and 74 non-metro (rural) counties. In other words, almost one-third (32
percent) of counties in this region are urban counties, a nd thus this subregion is the most
urbanized of the three subregions. Central Appalachia includes 43 counties in Kentucky,
9 in Tennessee, 7 in Virginia, and 9 in West Virginia. Of these, only 6 (9%) counties are
metro, and the remaining 62 are non-metro (rural). Thus, Central Appalachia is more rural
than the rest of Appalachia. Southern Appalachia includes 10 counties in Georgia, 16 in
North Carolina, 28 in Tennessee, and 16 in Virginia. Almost one out of every four (24%)
counties in this subregion is urban (metro). So, while southern Appalachia is also
predominantly rural, it is much more urbanized than central Appalachia. See Bagi, Faqir,
Richard Reeder, and Samuel Calhoun. “Federal Funding in Appalachia and its Three
Subregions.” Rural America, Volume 17 (4). Winter 2002.
ERS combined various CFFR categories into 6 broad functional categories of
different types of federal funding. ERS data, however, provide a somewhat different
picture of federal funding because they categorize the data differently. The data for
FY2000 covered 1,165 programs, but the data were not reliable at the county level
for every federal program. ERS excluded federal programs for which 25% or more
of their funding went to state capitals, because the states may redistribute these funds
to some or all counties and Census data do not reveal the amount of this
redistribution. ERS analysts also excluded programs for which most or all of the
funding is reported only at the state or national level. Thus, most of the large block
grant programs related to social services, employment, and training were excluded
from their analyses. Relative to Table 74 and Table 75 below, these exclusions
understate the amount of federal funding received, particularly for human resource
programs. For FY2000, ERS determined that the data were reliable at the county
level for 703 federal programs. These programs, accounted for $1.79 trillion
natiowide, or about 92% percent of the total federal funds reported by the Bureau of
the Census for FY2000.
In the remainder of this chapter, we present data on the SJV and Central
Appalachia based on ERS’s functional categories. Also provided are 10 maps
(Figures 9-18) based on these ERS data. It should be emphasized that Tables 74 and
Table 75 cannot be directly compared to Tables 70 and 71. They provide a different
perspective on similar, but not identical, data. For example, unlike data in Tables
70 and 71, the ERS data exclude large block grant programs. Interpretations of any
of these tables should be made with caution because federal funds data are only as
good as the information each agency supplies to the U.S. Bureau of the Census. In
some cases, as with Medicaid, the data are based not on actual outlays that go to
places, but on estimates based on other information, which may involve errors. In
other cases, like procurement, expenditures may be reported only at the location of
prime contractors or primary subcontractors and ignore further subcontracting that
disperses the impact of expenditures. For example, defense procurement, which
primarily benefitted Appalachian metro areas and government-dependent nonmetro
areas, may involve subcontracting that disperses the benefits broadly to some other
areas.
The ERS functional categories for federal programs include:
!Agriculture and Natural Resources including agricultural assistance,
agricultural research and services, forest and land management, and
water/recreation resources.
!Community Resources include business assistance, community
facilities, community and regional development, environmental
protection, housing, Native American programs, and transportation;
!Defense and Space including aeronautics and space, defense
contracts, and payroll/administration;
!Human Resources including elementary and secondary education,
food and nutrition, health services, social services, training, and
employment;
!Income Security including medical and hospital benefits, public
assistance and unemployment compensation, retirement, and
disability — including Social Security; and
!National Functions including criminal justice and law enforcement,
energy, higher education and research, and all other programs
excluding insurance.
The ERS data show that the SJV received a total of $16.33 billion in federal
expenditures in FY2000 with a per capita rate of $4,944 (Table 74). Income Security
programs represent the largest category of expenditure ($9.48 billion) with a per
capita rate of $2,870. Per capita rates varied slightly in this category, with San
Joaquin County receiving the highest per capita rate in the SJV ($3,093). San
Joaquin County also had a higher per capita rate of Community Resources
expenditure ($1,018) than did the SJV ($862). Human Resources programs received
the lowest level of federal expenditure in the SJV ($600.8 million) with a per capita
rate of $182.
The size of the agricultural sector in the SJV is reflected in federal expenditures
in the SJV. In FY2000, the SJV received $782.4 million in the category of
Agriculture and Natural Resources with a per capita rate of $237. Kern at $420,
Kings at $316, and Fresno at $313 had the highest per capita rates in this category of
expenditure. San Joaquin County and Stanislaus County had the lowest per capita
rates, $64 and $57 respectively.
Defense and Space expenditures were highly localized in Kern and Kings
counties. These two counties received all but $169.6 million of the $1.24 billion
going to the SJV for this category, and thus skew the distribution. The per capita
rate in Kern and Kings counties was $1,189 and $2,196 respectively. The average
per capita rate of expenditure for Defense and Space in the other six SJV counties
was $51. Procurement contracts and wages and salaries associated with Edwards Air
Force Base and the Naval Petroleum Reserve in Kern County and Lenmoore Naval
Air Station in Kings County are the significant factors in these high rates for Kern
and Kings counties. (Figure 14).
Per capita rates of federal expenditure among the six categories were somewhat
lower in the SJV than the per capita rates for California (Table 74). California had
a per capita rate of federal expenditure of $5,340 compared to the SJV’s rate of
$4,944. Income Security per capita in the state and SJV were nearly the same.
Defense and Space payments per capita were over twice as high in California as the
SJV. Agriculture and Natural Resources expenditures per capita were nearly six
times greater in the SJV as the state. Community Resources rate per capita were
nearly the same in the SJV as the state while National Functions were $300 more per
capita in the state than in the SJV.
The per capita federal expenditure rate in Mariposa County was $748 more than
the SJV. Per capita rates in Mariposa County for Income Security and National
Functions were also higher than the rates for the SJV. Income Security per capita in
Mariposa County was nearly $1,000 higher than the SJV and National Functions
brought Mariposa’s per capita rate in that category to $1,505, over three times the
rate in the SJV. The map in Figure 14 shows the federally owned land in Mariposa
and Tuolumne counties which contributes to high federal expenditures for National
Functions in Mariposa. The per capita expenditure rate in Tuolumne County was
$116 higher than the SJV’s rate. Like Mariposa County, Tuolumne County had a
per capita rate of $4,057 for Income Security, which was significantly higher than
that of the SJV. Among other factors, this reflects the higher proportion of those
over 65 in both counties’ population.
Per capita data for Appalachia show distinct differences from those for the SJV
(Table 75). Data are provided for three subregions of Appalachia: North, South, and
Central. These data also reveal distinctive patterns among the three subregions. The
per capita rate for federal expenditure in the smaller Appalachian region that ERS
delimited was $6,044 in FY2002. The 57 metropolitan counties within this region
had a per capita rate of federal expenditure of $6,562 and the 189 non-metropolitan
counties had a per capita rate of $5,416. This is consistent with national patterns of
federal expenditure, which also show generally higher per capita rates in metro areas
as opposed to non-metro areas. Metro, non-metro, and Appalachia as a whole each
had per capita expenditure rates higher than the rate for the SJV ($4,944). By a
significant margin, the highest per capita rate of federal expenditure among the three
Appalachian subregions was in Central Appalachia. Per capita expenditure in that
region was $7,730. Per capita rates in North Appalachia and South Appalachia were
$5,951 and $5,305 respectively. The high rate of Central Appalachia’s metro
counties accounts for the high rate overall. Central Appalachia’s metro rate per
capita was $15,455 compared to its non-metro rate of $6,292. This non-metro rate,
however, is the highest among the three subregions, and is $876 more per capita than
the rate for the Appalachian region as a whole.
As was the case for the United States, Appalachia and each of its subregions had
the highest federal expenditures for Income Security programs. The per capita rate
for Income Security expenditures in Appalachia was $4,239 compared to a rate of
$3,276 in the United States. In the SJV, the Income Security per capita rate was
$2,870. Central Appalachia’s non-metro counties had the highest rate per capita rate
of the three regions for this category, $5,135, substantially higher than the non-metro
rates in the other two regions, as well as the region-wide rate of $4,239.
National Functions, located largely in Central Appalachia’s metro-counties,
account for the disproportionate per capita rate for that subregion. The per capita rate
for National Functions in Central Appalachia was $7,097 compared to a region-wide
per capita rate of $865, a higher rate than that of the United States ($822). If Central
Appalachia’s high rate is discounted, Appalachia’s National Function per capita rate
would fall to $784. West Virginia’s universities and the 1995 completion of a
Federal Bureau of Investigation research center in Clarksburg were major factors in
Central Appalachia’s high metro per capita rate in this category. The 17 metro
counties in South Appalachia also had a per capita rate of expenditures for National
Functions, $1,225. The per capita rate for National Functions in the SJV was $417.
Per capita rates for Human Resources, Defense and Space, and Community
Resources in the SJV were higher than the rates for these categories in Appalachia,
although the rates are significantly different within Appalachia’s metro and non-
metro areas and vary across the three subregions. The per capita federal expenditure
rate for Human Resources was $119 in Appalachia, the same as for the United States.
For the SJV, per capita expenditure was $182 for this category. For Community
Resources, Appalachia had a per capita expenditure rate of $504 compared to the
SJV’s rate of $862. As noted above, just two counties (Kern and Kings) account for
high rates of Defense and Space expenditures in the SJV. The map in Figure 14
shows the sources of federal expenditure for this category. In Appalachia, the rate
for this category is $282 compared to $376 in the SJV. Again, the rate in Central
Appalachia’s metro counties skews the regional rate. Central Appalachia’s 62 non-
metro counties had a Defense and Space expenditure rate per capita of $103. Its 6
metro counties had a per capita rate of $3,655.
Per capita expenditures for Agriculture and Natural Resources are very low
compared to the SJV, although South Appalachia’s per capita rate for this category
was $56 compared to Stanislaus County’s per capita rate of $57. For the
Appalachian region as a whole, the per capita rate for Agriculture and Natural
Resources expenditures was $36 compared to a per capita rate of $237 in the SJV.
CRS-151
Table 74. Per Capita Federal Funds By ERS Function for the SJV, FY2000
(thousands of $)
unty /Area Population2000 All Federal fundsPerCapita* Agriculture and natural resources Community resources Defense and space Human resources Income security National functions
Total PerCapita*Total PerCapita*Total PerCapita*TotalPerCapita*Total PerCapita*Total PerCapita*
3 ,302,792 16,328,050 4,944 782,449 237 2,848,419 862 1,240,550 376 600,761 182 9,478,591 2,870 1,377,275 417
sno 799,407 3,844,718 4,809 250,047 313 630,637 789 61,910 77 172,929 216 2,186,739 2,735 542,455 679
n 661,645 4,059,857 6,136 277,768 420 647,644 979 786,600 1,189 118,831 180 1,937,870 2,929 291,142 440
s 129,461 729,061 5,632 40,875 316 61,494 475 284,262 2,196 23,508 182 299,322 2,312 19,599 151
dera 123,109 495,802 4,027 26,959 219 83,715 680 1,461 12 16,698 136 350,601 2,848 16,367 133
iki/CRS-RL33184rced 210,554 956,131 4,541 55,937 266 166,465 791 8,992 43 44,129 210 599,921 2,849 80,686 383
g/wo aquin 563,598 2,697,883 4,787 36,257 64 573,484 1,018 90,602 161 86,303 153 1,743,340 3,093 167,897 298
s.orn islaus 446,997 1,968,630 4,404 25,547 57 395,539 885 4,172 9 65,329 146 1,321,930 2,957 156,113 349
leak
re 368,021 1,575,968 4,282 69,059 188 289,441 786 2,551 7 73,034 198 1,038,868 2,823 103,016 280
://wikiAdjacent Counties
http
riposa 17,130 97,502 5,692 67 4 3 ,107 181 310 18 1,783 104 66,456 3,880 25,778 1,505
ne 54,501 281,308 5,162 101 2 27,144 498 600 11 3,565 65 221,115 4,057 28,783 528
California
ornia 33,871,648 180,871,138 5,340 1,468,879 43 28,008,452 827 25,518,476 753 4,619,704 136 96,975,231 2,863 24,280,397 717
U.S. Department of Agriculture, Economic Research Service calculations of federal funds data from the U.S. Census Consolidated Federal Funds Report, FY2000.
r capita funds reported in actual dollars
CRS-152
Table 75. Per Capita Federal Funds for Appalachia by ERS Function and Region, FY2000
Appalachia and itsTotal FederalAgricultureCommunityDefense andHumanIncomeNational
Subregions funds perand NaturalResourcesSpaceResourcesSecurityFunctions
(# of counties)capitaResources
5,690 116 680 678 119 3,276 822
5,743 39 728 771 113 3,182 910
etro 5,481 427 486 303 143 3,656 467
6,044 36 504 282 119 4,239 865
6,562 32 571 432 104 4,251 1,172
iki/CRS-RL33184etro (189)5,41640423991384,224491
g/w
s.or 5,951 26 546 276 109 4,270 724
leak
6,325 16 592 370 104 4,445 798
://wikietro (74)5,24845460991183,942585
http
5,305 56 467 81 102 3,754 845
5,742 70 540 68 102 3,736 1,225
etro (53)4,80740383971033,773411
7,730 37 401 661 193 4,974 1,465
15,455 56 413 3,655 128 4,105 7,097
etro (62)6,292333991032065,135416
U.S. Department of Agriculture, Economic Research Service calculations of federal funds data from the U.S. Bureau of the Census’s Consolidated Federal Funds Report,
Geographical Information System Mapping of Federal Funds
Data
Figures 9-18 below map the federal funds data for each of the six ERS
categories in Table 75. Also presented are maps for total federal funds by county
and per capita federal funds by county (Figure 10 and Figure 11). Each map also
provides an inset of the same data to contrast the SJV with California’s other 58
counties. Figure 15 is a map showing federal lands and military installations and
Figure 17 provides a proportional county map for the ERS categories across all
counties in the state.
Figure 9. Total Federal Assistance by County, FY2000
Data Source: U.S. Department of Agriculture, Economic Research Service calculations of federal
funds data from the U.S. Census Consolidated Federal Funds Report, FY2000.
Figure 10. Total Federal Assistance Per Capita, FY2000
Data Source: U.S. Department of Agriculture, Economic Research Service calculations of federal
funds data from the U.S. Census Consolidated Federal Funds Report, FY2000.
Figure 11. Federal Assistance per Capita for Agriculture and Natural
Resources by County, FY2000
Data Source: U.S. Department of Agriculture, Economic Research Service calculations of federal
funds data from the U.S. Census Consolidated Federal Funds Report, FY2000
Figure 12. Federal Assistance Per Capita for Community Resources
Data Source: U.S. Department of Agriculture, Economic Research Service calculations of federal
funds data from the U.S. Census Consolidated Federal Funds Report, FY2000
Figure 13. Federal Assistance Per Capita for Defense and Space by
County, FY2000
Data Source: U.S. Department of Agriculture, Economic Research Service calculations of federal
funds data from the U.S. Census Consolidated Federal Funds Report, FY2000
Figure 14. Federally Owned Land in the SJV
Data Source: U.S. Geological Survey
Figure 15. Federal Assistance Per Capita for Human Resource by
County, FY2000
Data Source: U.S. Department of Agriculture, Economic Research Service calculations of federal
funds data from the U.S. Census Consolidated Federal Funds Report, FY2000
Figure 16. Federal Assistance per Capita for Income Security by
County, FY2000
Data Source: U.S. Department of Agriculture, Economic Research Service calculations of federal
funds data from the U.S. Census Consolidated Federal Funds Report, FY2000
Figure 17. Federal Assistance per Capita for National Functions by
County, FY2000
Data Source: U.S. Department of Agriculture, Economic Research Service calculations of federal
funds data from the U.S. Census Consolidated Federal Funds Report, FY2000
Figure 18. Allocation of Federal Assistance by ERS Category in
California and the SJV, FY2000
Data Source: U.S. Department of Agriculture, Economic Research Service calculations of federal
funds data from the U.S. Census Consolidated Federal Funds Report, FY2000
Chapter 4 — The Economic Structure of the San
Joaquin Valley
Introduction. Identifying the forces that will influence future economic
growth in the SJV is a formidable challenge to policy makers and residents of the
SJV. Projections of population growth presented earlier show the SJV as one of
California’s fastest growing regions. Migration from the coast is a factor in this
growth, yet many of these residents continue to commute to jobs in Los Angeles and
the Bay Area. International migration from Asia and Latin America is also a
significant factor in the population growth. Although agriculture employment as a
proportion of the California economy continues to shrink, wage and salary farm
production employment in the state has grown between 1990 and 2002, from 172,307
jobs in 1990 to 244,525 jobs in 2002. Agricultural service employment and
agricultural processing and marketing employment have also grown between 1990
and 2000, although these categories decreased by approximately 29,000 jobs between81
Agriculture remains the SJV’s dominant economic sector, although hired farm
labor has declined from 377,853 workers in 1992 to 243,079 workers in 200282
(35.6%). Between 1997 and 2002, only Kings and Tulare counties saw small
increases in number of hired farm workers. Yet, agricultural development in the SJV
may produce different effects in the SJV from the changes in commodity production
seen in other parts of the United States, (e.g., the Northern Great Plains and
Midwest). As we discuss below, the dynamic agricultural economy of the SJV is
becoming increasingly specialized, vertically integrated, and export-oriented in a
globalized agro-food production system. Although these changes are occurring
throughout large-scale commercial agriculture, their scale and the existence of
agricultural manufacturing and processing sectors in the SJV suggest that the model
of integration is perhaps at its leading edge in the SJV. Agriculture, unlike other
economic sectors, is also vulnerable to changes in water supply and the conversion
of prime farmland to urban uses. Change in availability or cost of these inputs could
significantly alter the role of agriculture in the SJV for the future.
For all its importance to the SJV today, agricultural production will likely exist
alongside an increasing diversification in the Valley’s economy. While no new
economic sector has developed to the point that analysts might credibly point to it as
a main economic engine of the region’s future, information and electronics,
biomedical/health, computers and data processing, in addition to agriculture, have
81 These data were compiled by USDA’s Economic Research Service and are based on the
1997 North American Industry Classification System (NAICS). Most industry estimates
were developed from an enhanced file of the County Business Patterns, U.S. Bureau of the
Census. Farm proprietors and farm wage and salary workers are from the Bureau of
Economic Analysis, U.S. Department of Commerce.
[ h t t p : / / www.e r s .us da .gov/ Da t a / Fa r ma ndRe l a t e d E mp l o y me n t / V i e w D a t a . a s p ? Ge o Ar e a P i c
k= ST ACA_California&YearPick=2002&B1=Submit]
82 National Agricultural Statistical Service. U.S. Census of Agriculture, 1992, 1997, and
2002. It should be noted that these Census of Agriculture data did not include the number
of workers brought to farms by farm labor contractors until the 2002 Census of Agriculture.
been identified as emerging economic “clusters” within the Central Valley during the
1990s.83 In the SJV, computers and data processing services grew strongly in the
early 1990s. This sector, which includes back-office data processing functions,
however, is increasingly vulnerable to off-shoring to sites where labor costs are
lower. The SJV also revealed a nascent biomedical “cluster” which included a
growing medical instrument and supply sector.84 In addition to profiling the
economic structure of the SJV, we also discuss below the potential of an expanding
biomedical and health care industry in the SJV.
Unlike agriculture, which depends in large measure on a less skilled labor pool,
the more technologically advanced production “clusters” will require increased
numbers of more highly skilled workers. A more technologically sophisticated
agricultural industry in the SJV will likely also demand a better trained workforce in
the future. Human capital development in the SJV, (i.e., life-long education and
training, may become a central consideration in the diversification of the Valley
economy into higher wage, higher skilled sectors). The SJV’s capacity to develop
and sustain high quality educational programs and worker training opportunities will
be critical to creating a labor force able to take advantage of new sources of
economic growth over the next two decades.
Agriculture in the SJV
Trends in the Structure of SJV Agriculture. Agriculture defines the
socioeconomic structure of the SJV. The Central Valley, of which the San Joaquin
is part, is the most productive agricultural region in the United States. The SJV
generates half of the state’s gross value of agricultural production and ranks fourth
in the United States in the number of people involved in farming, forestry, and
fishing. Policy issues such as labor, immigration, the environment, water supply, and
land use each affect and are affected by the structure of agriculture in the Valley.
While economic diversification is a goal shared by many citizens of the Valley,
agriculture production and its related industries will likely remain a central pillar of85
the economy for the foreseeable future. Agriculture in the future, however, will
likely have different characteristics from the agriculture of today. Increasing
technological integration, fewer farm jobs, greater economic scales of production in
some sectors, and more specialization and integration are significant trends that will
shape SJV agriculture in the years ahead.
83 Bradshaw, Ted K. “How will the Central Valley grow?” California Agriculture, 54(1),
January-February, 2000. Industrial “clusters” are agglomerations of interrelated regional
industries that gain advantages because they are co-located and can share supply networks,
research and development, and post-production specialization, e.g., marketing, shipping.
See National Governors Association. A Governor’s Guide to Cluster-Based Economic
Development. Washington, D.C., July, 2002.
[http://www.nga.org/ cda/ files/AM02CLUST ER.pdf]
84 Ibid.
85 Great Valley Center. The State of the Great Valley Central Valley of California:
Assessing the regional Via Indicators: The Economy, 1999-2004. Modesto: Great Valley
Center, 2005.
The long-standing trend toward fewer, larger, and more specialized commercial
farms and ranches in the U.S. (horizontal integration) is well documented.
Agriculture in the SJV is arguably the model of large-scale, industrial agriculture
today. Not only have these trends been observed for many years, recent data suggest
they may be accelerating as pressures increase from global competitors and as new
agricultural technologies continue to reinforce the substitution of capital for labor to
create even greater scale efficiencies.86 Rapid and increasing consolidation and
coordination (vertical integration) in agriculture are indicators of a more fundamental
restructuring occurring in the food and fiber system today. A growing share of
commodity producers, mostly within animal production currently, are joining “supply
chains.”87 A supply chain is a tightly organized production, processing, and
marketing system formed by agribusiness firms that, in its most coordinated form,
could potentially link each step of food production from proprietary genetic material
to the grocery shelf.
Like previous agricultural changes, technology will play a key role in the
evolution of supply chains. Technology has been a major force in driving the shift
of farm activities off the farm and into the input industries. Advances in agricultural
biotechnology can be expected to do the same, but with a distinct variation. Initial
biotechnology development in agriculture focused on changes in bulk commodities,
(e.g., herbicide resistant soybeans and pesticide resistant corn). Much current
research in biotechnology is focused on the characteristics of farm products, not just
how the products are produced. Proprietary products lend themselves to the structure
of supply chains as the contractor firms target new bio-engineered products to
particular market niches. Some farmers in some regions may choose to continue
producing bulk commodities; other farmers may choose to contract with an
agribusiness firm to produce a value-added bio-engineered product.
Some contract producers might find themselves with decreasing power to
negotiate the terms of their contracts as the relative power of large processors to
determine the conditions of production increases.88 Although some states, (e.g.,
Minnesota), have adopted measures to protect contract producers, some observers
believe that because producers negotiate individually with a processor, often with
contract confidentiality clauses, individual producers can be at a disadvantage.89
86 Approximately half of California’s agricultural sales is in the labor-intensive fruit,
vegetable, and horticultural sub-sector. These farms are heavily reliant on hired labor for
most of the farm’s seasonal work requirements.
87 Drabenstott, Mark. “Rural America in a new century.” Main Street Economist, Federal
Reserve Bank of Kansas City, October, 1999.
88 Some economists have suggested that rapid expansion of consolidation in agriculture has
also exposed agribusiness firms to increased financial pressures. Such stress could leave
producers who are dependent on contracts or marketing agreements with large agribusiness
firms vulnerable. See Kohl, David. “Reflections and perspectives” Ag Lender, June 21,
89 Etka, Steve. “Contract agriculture: serfdom in our time.” National Campaign for
Sustainable Agriculture, Update, June, 2001.
What is of particular significance, if still poorly understood, are the implications
for areas such as the SJV where agriculture plays such a central role in the region’s
economy. Historically, agricultural production was relatively widely distributed
across the landscape. Supply chains appear to be redrawing the landscape of
dispersed agricultural production. Poultry production and swine production were
once widely dispersed across the country. Today, broiler production, which is almost
exclusively done under producer contracts, is found mostly in the South and
Southeastern U.S. and upper Midwest. Poultry processing plants are even more
concentrated within those regions. Similarly, beef production, with large feed lots
and nearby meat packing plants, suggests a very different agricultural geography, one
with potentially significant social and environmental effects in regions where such
production occurs. Given the SJV’s strong production in dairy, fruits, and
vegetables, the evolution of supply chain production in those sectors is likely to hold
significant implications for agriculture in the Valley.
Agriculture and SJV Communities. Some research has suggested that
farm scale and other management characteristics are associated with certain
community characteristics. This research has been controversial since Walter
Goldschmidt’s pioneering 1944 research on two San Joaquin farming communities
conducted for the USDA’s Bureau of Agricultural Economics.90 A substantial body
of evidence has shown that communities characterized by large-scale, especially
industrial, farm structures are often associated with adverse community
socioeconomic conditions, e.g., lower community standards of living, less economic
diversity, fewer community services, less vibrant retail trade, etc., than communities91
with other types of farming enterprises. The direction of that statistical association,
however, remains unclear as does the strength of the relationship and, even more
important, the processes that underlie it.
Research conducted as part of the Office of Technology Assessment’s (OTA)
1986 report, Technology, Public Policy, and the Changing Structure of American
Agriculture, supported the relationship reported by Goldschmidt between industrial
farming and community quality of life in its analysis of Florida and several Western92
states. Farms dominated by manager-worker relations and dependent on large,
mostly unskilled labor forces can be associated with adverse socioeconomic effects.93
Because a significant portion of SJV agriculture does exhibit some of the
characteristics of industrialized agricultural, the relation between agriculture and
90 Walter F. Goldschmidt. As You Sow: Three Studies in the Social Consequences of
Agribusiness. Montclair, NJ: Allanheld, Osmun and Co., 1978.
91 Counties with the most industrialized agriculture are found in California, Arizona, Texas,
and Florida. Of these, California and Texas are among the top 10 states with the most
agricultural workers.
92 MacCannell, Dean and Edward Dolber-Smith. “Report on the Structure of Agriculture and
Impacts of New Technologies on Rural Communities in Arizona, California, Florida, and
Texas. Report prepared for the U.S. Office of Technology Assessment, 1985.
93 California has more farm workers than any other state. The Central Valley of California,
the richest agricultural area in the world, however, has an unemployment rate three times
the national average (New York Times, June 18, 2001, A1, A14).
community demonstrated by Goldschmidt is arguably a factor in the current
socioeconomic structure of the SJV. However, large-scale, owner-operated farms,
which also characterize farming in the San Joaquin, generally show positive effects.
As these observations might suggest, any association between farm organization and
various community characteristics appears to be mediated by the size and economic
diversity of the community, the region, the kinds of agricultural commodities
produced, and a rural area’s proximity to urban-suburban areas.
The social organization of the local and regional non-farm economy also exerts
important effects on the surrounding area suggesting that newly created opportunities
in the non-farm economy may have significant impact on the farm economy and the
rural economy more generally. As supply chains and other forms of vertical
integration and coordination come to characterize various production sectors, the
kinds and degree of impact in the SJV may vary considerably depending on the
broader characteristics of the regional economy and on the existence of local
capacities for generating innovative alternatives or complements to these forms of
production.
Agricultural Land Conversion. Given the population growth projected for
the SJV, pressures to convert productive agricultural acreage to housing and other
urban needs will become increasingly important issues for planners and economic
development officials.94 The conflict between agriculture and the need to manage the
tremendous population growth that the SJV will experience over the next 20 years
indicate significant planning challenges to the region.95 From 1990-2002, 283,277
acres of irrigated farmland in the Central Valley were converted, mostly to urban
uses. The SJV experienced the greatest amount of farmland loss.96 An analysis of
the Central Valley by the American Farmland Trust (AFT) estimated that low-density
urban sprawl would consume over 1 million acres of farmland by 2040,
approximately 60% of which would be prime farmland and farmland of state
importance.97 In addition, growth pressures on agricultural land within a one-third
mile zone around urban areas would involve another 2.5 million acres. While the
AFT report recognized that a “no-growth” future was unrealistic, the loss of prime
farmland, reduced agricultural production, and related income loss over the next 35
years could be attenuated by more compact growth scenarios as opposed to low-
density sprawl. The AFT report estimated that a compact pattern of urban growth
could also result in saving Central Valley agriculture about $72 billion between
94 Great Valley Center. Can City and Farm Coexist? The Agricultural Buffer Experience
in California. January, 2002.
95 Great Valley Center. Agriculture and New Housing. January, 2001.
96 Great Valley Center. The State of the Great Valley Central Valley of California: Assessing
the regional Via Indicators: The Economy, 1999-2004. Modesto: Great Valley Center,
January, 2005, p. 33.
97 American Farmland Trust. Alternatives for Future Urban Growth in California’s Central
Valley: The Bottom Line for Agriculture and Taxpayers. Washington, D.C. October, 1995.
Figure 19. SJV Land Use/Land Cover
Data Source: U.S. Geological Survey
SJV Farm Characteristics. Table 76 shows SJV county farms by size. The
Valley as a whole has nearly 10 million acres of farmland and over 28,000 farms.
Fresno and Tulare Counties have the largest number of farms while Kern County has
the largest acreage in farmland. Kern and Fresno Counties also have the largest
number of farms of 1,000 acres or more, although the average size farm in the Valley
is 436 acres. This is approximately the average size farm in the United States, but
somewhat larger than the average size California farm. While Mariposa and
Tuolumne Counties also have large average sized farms, they have significantly
fewer farms and less acreage in farmland than the eight counties of the SJV.
Value of Products. California produces a significant proportion of higher-
valued agricultural products, (e.g., fruits, vegetables, tree crops, dairy). The average
market value of agricultural product sales per farm in 2002 in the United States and
California was $94,245 and $323,205 respectively according to data from the most
recent Census of Agriculture (Table 77). For the SJV, the average agricultural
market value per farm of the eight counties was $494,892, with over 9,000 farms
producing sales of $100,000 or more. The total market value of crops in the SJV was
$8.1 billion and the total market value of livestock was $4.4 billion. Over 42% of the
market value of crops and 67% of the market value of livestock in California come
from the SJV. As Figure 20 shows, the SJV is in the top quartile of average sales
per farm for the state.
Table 78 provides more detailed data from California’s County Agricultural
Commissioners’ Reports on the gross value of the SJV’s leading commodities.
Again, the data in Table 78 show that Mariposa and Tuolumne counties stand in
marked contrast to the agricultural character of the SJV with very little agricultural
production in comparison. Table 79 shows the 5 leading counties by commodity
rank and the percentage of California’s total gross value of agricultural production
for that commodity. With the exception of nursery products, flowers and foliage, and
strawberries, at least one SJV county is within the top 5 among California’s 10
highest value commodities.
Irrigation. Much of SJV agricultural production is based on irrigation. Of the
total 28,357 farms in the SJV, over 80% (23,482) have some portion of their farm
under irrigation (Table 80). Of the 1.44 million acres of total farm land on which
some portion is irrigated, 76% of that acreage is irrigated. Over 10% of the farms
that irrigate are 500 to 2,000 acres or more. Fresno and Tulare counties have the
largest amounts of irrigated acreage, 1.1 million and 652,000 respectively. Mariposa
and Tuolumne counties have only about 5,200 acres in irrigated land between them,
while the SJV counties have a total of 4.73 million acres of irrigated farmland. The
eight SJV counties represent about 54% of California’s total irrigated acreage (See
Figure 21 and Figure 22). Of that amount, 72% is located on farms of 500-2,000
acres or more.
Direct Subsidies to Agriculture. Another characteristic of U.S. agriculture
is federal subsidies to certain crops. Grains, cotton, rice, soybeans, peanuts, and
barley are subsidized by direct federal payments to the farmers who grow these crops.
The SJV, with its high production in unsupported fruits and vegetables, does not
receive commodity support payments per farm to the same extent as other parts of the
United States where production of supported crops is much higher. In 2000, direct
government payments to California amounted to $667 million out of total federal
direct agricultural payments of $22.9 billion, about 3% of all direct federal payments
for agriculture.98 In contrast, Iowa received about 10% of U.S. payments and Texas
received about 7%.99
The federal farm payments received in SJV are mostly for cotton, rice, wheat
and feed grains. Table 81 provides 2002 data on federal farm payments showing
that, while the number of farms growing supported crops is small relative to the total
number of farms in the SJV, the average subsidy per farm is substantially higher than
for the United States as a whole (See Figure 23) Approximately 33% of U.S. farms
and 9% of California farms receive federal subsidies. Led by Kings, Fresno, and
Kern Counties, the average federal agricultural support payment to farms receiving
payments in the SJV was nearly $29,000 compared to a national average of $9,251
and a California average of $23,340. Mariposa County received about one-fourth the
average of federal farm payments ($7,333) that SJV farms received, while Tuolumne
County’s farms received much less on average ($3,727). Total federal payments to
the SJV in 2002 were $85.3 million, slightly more than 1% of the total for the United
States, but 51% of the total for California.
Agricultural Labor. Farmworkers are a marginalized population, often
isolated from the communities in which they live and work. One consequence of this
isolation is the lack of reliable information on farmworker demographics and
economic conditions. Although there are no current reliable statistics for the total
number of farmworkers, the National Agricultural Workers Survey, conducted by the
U.S. Department of Labor, estimated that in 1995, there were approximately 1.6
million agricultural workers in the United States.
Hired Farm Labor. Hired labor is an important characteristic in the structure
of large-scale agricultural production. While smaller-scale family-run operations
may also regularly hire farm labor, the scale and intensity of agricultural production
in the SJV make hired farm labor a dominant feature of production, especially on the
largest farms. There were 243,079 hired farm workers in the SJV in 2002 accounting
for about 8% of the hired farm workers in the United States and 45% of California’s
hired farmworkers (Table 82). Of the total 28,357 farms in the SJV, 50% rely to
some extent on hired farm labor (14,135 farms).100 Of those farms employing hired
labor, one-third have 10 or more hired workers with an average of 45 hired workers
on those farms employing 10 or more workers. Table 82 shows that farms with 5-9
hired workers employed an average of 6.5 in 2002. Mariposa and Tuolumne also had
a few farms (17) with 10 or more hired workers, averaging between 25-30 workers
per farm.
Hired farm labor in the SJV had a $1.68 billion payroll in 2002. This amounts
to an average worker wage of approximately $6,900. This wage may or may not
represent full-time farm labor over the course of a year. This average wage, however,
98 Johnston, Warren E. and Alex F. McCalla. Whither California Agriculture: Up, Down,
or Out? Some Thoughts about the Future. Giannini Foundation Special Report 04-1,
August 2004.
99 Ibid., p. 62.
100 The category of hired farm labor includes paid family members of farm owners.
reflects some variation among individual counties, suggesting that labor on different
farms is paid differently and/or that the wages reflect differing total days worked.
The average county wages for hired farm labor ranged from a high of $9,492 in Kern
County to a low of $5,058 in Fresno county.
Two additional tables (Table 83 and Table 84 ) provide a more detailed look
at the labor structure of SJV farms. Generally, hired farm workers are concentrated
on larger farms that are more dependent on hired labor, (i.e., those with 10 or more
hired workers). Table 83 shows that of the total 28,357 farms in the SJV, 37.7%
(10,677) employed hired labor for 150 days or fewer per year in 2002. Fresno and
Tulare counties have the highest number of hired farm workers working 150 days or
fewer. In Fresno County, nearly 90% of hired farm workers working 150 days or
fewer did so on farms with 10 or more hired workers. Fresno County farms with 10
or more hired workers working 150 days or fewer had an average of about 38
workers per farm. In the other SJV counties, most of the hired workers working
fewer than 150 days per year also worked on farms with 10 or more hired workers.
For the SJV, 86% of the workers working 150 days or fewer worked on farms with
10 or more hired workers. The average number of hired workers in the SJV working
on farms with more than 10 hired workers was 42 workers. For the United States as
a whole, 54% of hired farm workers working 150 days or fewer worked on farms
with 10 or more hired workers. In California, that figure was 83% in 2002 with an
average of 41 workers per farm. Mariposa and Tuolumne counties had very small
numbers of hired farm labor compared to the SJV.
Table 84 provides data on farms where labor is retained over longer periods.
While most farms in the SJV employing hired workers retain these workers for 150
days or fewer, about 30% of SJV farms (8,665) employ hired farm workers for 150
days or more. In 2002, there were 77,683 hired workers who worked 150 days or
more. Fresno and Tulare counties also had the most hired workers working 150 days
or more. As was the case with workers who worked 150 days or fewer, most workers
working 150 days or more worked on farms with more than 10 workers. The average
number of workers per farm, however, was somewhat less than for farms with hired
labor working 150 days or fewer (34 versus 42 workers per farm respectively). For
those farms that hire few workers on average, those with fewer than nine workers,
the average was approximately four workers per farm. The data show that the
majority of hired farm labor in the SJV works on a relatively concentrated group of
larger, more industrially managed operations within each of the SJV counties.
Migrant Farm Labor. A particular class of hired farm labor is migrant labor.
In a case study of farmworkers in Kern County, the Housing Assistance Council
noted that migrant and resident farmworkers constitute distinct populations, each101
with its own special needs. Information on U.S. farm migrant labor, however, was
collected for the first time in the 2002 Census of Agriculture. To gauge the extent
to which SJV farms were reliant on migrant labor, farm operators were asked
whether any hired or contract workers were migrant workers, defined as a farm
worker whose employment required travel that prevented the migrant worker from
101 Housing Assistance Council. Taking Stock: Rural People, Poverty, and Housing at the
Turn of the 21st Century. Washington, D.C. 2002.
returning to his/her permanent place of residence the same day. Table 85 provides
2002 data on farm migrant labor. Of the 243,079 hired farm workers, 3,994 were
officially counted as migrant workers. This official tally categorizes 1.6% of all SJV
hired farm labor as migrant labor. An additional 820 migrant farmworkers worked
on SJV farms as contract labor. Based on these 2002 Census of Agriculture data,
45% of California’s migrant farm labor force and 54% of migrant contract labor work
on farms in the SJV. These data further show that approximately 10% of U.S.
migrant farm labor and 12% of U.S. migrant contract labor work on farming
operations in the SJV.
A 1997 U.S. Department of Labor report based on 1994-1995 data from the
National Agricultural Workers Survey, showed that 94% of all U.S. foreign born102
farm workers were Mexican. Nearly 56% of the farmworkers surveyed were
migrants. While migrant workers are a sub-category of farmworkers, the conclusions
of the Department of Labor report are significant for the SJV:
!Over time the farmworker population has become increasingly male
(currently 80%).
!Over time the population has become increasingly foreign born
(currently70%).
!Farmworkers are generally young (66% are younger than 35) and
almost 20% are in their first year of U.S. farm work.
!Most adult foreign farmworkers are married and have children.
!Most foreign-born farm workers with families live and work
separately from their spouses and children.
!Most foreign farmworkers live with non-relatives.
!Most (60%) farmworkers are poor; and the proportion seems to be
increasing over time.
!Despite their poverty, few use social services, although Food
Stamps, Medicaid, and to a lesser extent the WIC programs were
used.
!The proportion of unauthorized farm workers rose quickly as
citizens and the newly legalized population left farm work. In the
1994-1995 period, 37% of farmworkers were unauthorized, up from
102 U.S. Department of Labor. 1997. A Profile of U.S. Farm Workers: Demographics,
Household Composition, Income, and Use of Services. Report prepared for the Commission
on Immigration Reform. Washington, D.C.
CRS-173
Table 76. Farms by Size, 2002
Land inAverageFarms by size
SJV CountiesFarms(Number)farmssize of farm10 to 4950 to 179180 to 499500 to 9991,000 acres
(Acres)(Acres)1 to 9 acresacresacresacresacresor more
6,281 1,928,865 307 965 2,682 1,360 552 359 363
e rn 2,147 2,731,341 1,272 345 437 443 346 220 356
i ngs 1,154 645,598 559 198 364 237 139 100 116
1,780 682,486 383 208 596 460 279 107 130
2,964 1,006,127 339 333 1,150 757 370 160 194
iki/CRS-RL33184oaquin 4,026 812,629 202 876 1,644 781 396 153 176
g/w
s.or4,267 789,853 185 949 1,883 777 399 125 134
leaklare 5,738 1,393,456 243 1,218 2,295 1,178 566 243 238
://wiki28,357 9,990,355 436 5,092 11,051 5,993 3,047 1,467 1,707
httpAdjacent Counties
284 219,133 772 22 86 73 44 23 36
ne 358 149,767 418 89 117 63 35 20 34
California and the United States
79,631 27,589,027 346 21,827 27,307 14,356 7,741 3,604 4,796
2,128,982 938,279,056 441 179,346 563,772 658,705 388,617 161,552 176,990
2002 Census of Agriculture, USDA, National Agricultural Statistics Service
CRS-174
Table 77. Market Value of Agricultural Product Sales, 2002
Market valueAverageMarketMarket valueNumber of Farms by value of sales
SJVof agriculturalMarketvalue ofof Livestock Less$5,000$25,000$50,000
Countiesproducts soldValueCrops($1,000)than$2,500 toto$10,000 tototo$100,000 or
($1,000) ($1,000) $2,500 $4,999 $9,999 $24,999 $49,999 $99,999 mo r e
esno 2,759,421 439,328 2,150,938 608,483 1,063 280 424 786 749 922 2,057
rn 2,058,705 958,875 1,783,418 275,288 617 122 101 121 121 138 927
ngs 793,061 687,228 394,674 398,387 250 74 71 108 91 69 491
710,433 399,120 505,071 205,363 400 100 91 150 178 211 650
1,409,254 475,457 597,577 811,677 560 131 193 365 326 322 1,067
iki/CRS-RL33184n Joaquin1,222,454303,640907,837314,6179422273224614433981,233
g/w
s.oranislaus 1,228,607 287,932 567,965 660,643 1,075 271 395 624 457 394 1,051
leaklare 2,338,577 407,560 1,194,237 1,144,340 1,068 312 405 683 653 684 1,933
://wikital SJV12,520,5123,959,1408,101,7174,418,7985,9751,5172,0023,2983,0183,1389,409
httpunt ies
Adjacent Counties
posa 6 ,285 22,130 470 5,815 144 28 38 40 11 9 1 4
olumne 23,569 65,836 1,134 22,435 198 42 47 19 28 10 14
California and the United States
ited States200,646,35594,24595,151,954105,494,401826,558213,326223,168256,157157,906140,479311,388
lifornia 25,737,173 323,205 19,152,722 6,584,451 23,362 6,038 7,262 9,455 7,131 6,798 19,585
2002 Census of Agriculture, USDA, National Agricultural Statistics Service
Figure 20. Average Sales per Farm by County (2000)
Source: 2002 Census of Agriculture, USDA, National Agricultural Statistics Service
Table 78. Leading Commodities for Gross Value of Agricultural
Production by SJV and Adjacent Counties, 2003
Fresno $1,000Kern$1,000
Grapes $400,842 Grapes $402,80
Tomatoes$384,290Almonds and By-Products$280,50
Cotton $341,666 Citrus $278,01
Cattle and Calves$263,510Carrots$269,13
Poultry $246,520 Milk $230,30
Milk$221,199Cotton and Cottonseed$176,68
Oranges$215,349Alfalfa Hay$115,69
Almonds$201,596Nursery Crops$100,70
Onions $164,766 Potatoes $83,241
Peaches$158,470Cattle and Calves$67,868
Kings $1,000 Madera $1,000
Milk, All$325,412Almonds$154,98
Cotton, All$200,071Milk, Market$126,95
Cattle and Calves$103,683Grapes, Wine$87,991
Alfalfa Hay$45,807Cattle, Replacement$47,025
Pistachios$37,744Grapes, Table$34,158
T urkeys $30,117 Pistachios $31,891
Tomatoes, Processing$26,495Alfalfa Hay$29,409
Corn Silage$26,460Cattle and Calves$29,185
Wheat$22,525Grapes, Raisin$26,111
Peaches, All$22,121Poultry$22,125
Mariposa $1,000 Merced $1,000
Cattle and Calves$9,736Milk, Market$552,61
Pasture, Range$7,058Chicken$230,06
Livestock and Poultry$1,236Almonds$211,86
Poultry, All$974Cattle and Calves$168,66
Forest Products$644Potatoes, Sweet$89,186
Fruit and Nut Crops$451Tomatoes, Fresh Market$81,298
Honey$213Alfalfa Hay$68,986
Sheep and Lambs$189Cotton, Lint$68,218
Nursery Stock$160Eggs, Chicken$48,484
Livestock, Misc.$119Turkeys$48,436
San Joaquin$1,000Stanislaus$1,000
Milk, All$256,633Milk, Market$424,98
Grapes, All$175,156Almonds$239,90
Almond Meats$125,977Chickens$104,55
Tomatoes, All$118,380Nursery, Fruit, Vine, Nuts$71,282
Cherries, All$109,869English Walnuts$59,046
English Walnuts$96,386Cattle, Fed Heifers and$42,235
Nursery, Woody$59,585Peaches, All$39,477
Apples$53,550Corn Silage$38,312
Eggs, Chicken$51,558Alfalfa Hay$36,410
All hay$50,467Chicks$31,672
Tulare $1,000Tuolumne$1,000
Milk $1,067,797 Live stock $11,958
Oranges, Navel and$442,504Cattle and Calves$5,594
Grapes$378,511Pasture, Range$2,030
Cattle and Calves$372,863Forest Products, Firewood$1,041
Plums$85,500Apiary Products$367
Alfalfa Hay and Silage$84,019Pasture, Irrigated$209
Peaches, Cling and$70,092Fruit and Nut Crops $170
Walnuts$68,970Other Hay$1,133
Nectarines$66,474Sheep and Lambs$92
Corn Grain and Silage$66,008Livestock Products$85
Source: Summary of County Agricultural Commissioners’ Reports: Gross Values by Commodity
Groups — California 2002-2003. September, 2004.
CRS-178
Table 79. SJV Commodity Rank and Leading Counties by Gross Value of Agricultural Production, 2003
Five Leading Counties by Rank and Percentage of State Total
CommodityValue
State Rank$00012345
and Cream1 $4,112,479TulareMercedStanislausSan BernardinoKings
2 $3,022,439KernFresnoNapaTulareSonoma
Products3 $2,654,394San DiegoOrangeRiversideMontereyLos Angeles
iki/CRS-RL33184 19.1% 8.0% 7.7% 7.5% 6.6%
g/wttle and Calves4 $1,996,552TulareFresnoImperialMercedKings
s.or 18.7% 13.2% 11.9% 8.4% 5.2%
leak
5 $1,634,171MontereyFresnoImperialSanta BarbaraSan Benito
://wiki63.2%10.3% 8.9%5.8%4.3%
http
onds6 $1,501,592KernStanislausMercedFresnoMadera
7 $973,233VenturaMontereySanta BarbaraSanta CruzOrange
es8 $949,358TulareKernFresnoVenturaSan Bernardino
9 $782,186KernImperialTulareMercedFresno
e10$778,087San DiegoSanta BarbaraSan Luis ObispoVenturaMonterey
CRS-179
Five Leading Counties by Rank and Percentage of State Total
CommodityValue
State Rank$00012345
11 $774,208FresnoKingsKernMercedTulare
12 $638,046ColusaSutterButteGlennYuba
13 $592,357MontereySanta BarbaraFresnoSan Luis ObispoImperial
matoes, Processing14 $571,113FresnoYoloSan JoaquinColusaMerced
iki/CRS-RL33184 47.6% 10.7% 10.1% 5.7% 5.2%
g/w
s.or15 $440,817MontereyImperial — — —
leak 99.3% 0.7%
://wikilish Walnuts16 $433,800San JoaquinTulareStanislausButteTehama
http 22.2% 15.9% 13.6% 11.0% 6.5%
17 $416,165FresnoTulareStanislausSutterKings
ocados18 $402,160San DiegoVenturaRiverside Santa BarbaraOrange
ens19 $379,399MercedStanislausSan BernardinoSan JoaquinSan Diego
e20 $325,852TulareMercedStanislausKernKings
21 $306,095FresnoImperialLos AngelesKernSan Joaquin
CRS-180
Five Leading Counties by Rank and Percentage of State Total
CommodityValue
State Rank$00012345
matoes, Fresh Market22 $305,546FresnoMercedSan JoaquinSan DiegoStanislaus
gs, Chicken23 $302,524RiversideSan JoaquinSan DiegoMercedSan Bernardino
ons24 $278,081VenturaKernRiversideTulareSan Diego
25$270,041VenturaMontereySanta BarbaraSan Luis ObispoSan Benito
iki/CRS-RL33184 42.0% 39.1% 12.5% 3.2% 1.8%
g/w
s.or Summary of County Agricultural Commissioners’ Reports: Gross Values by Commodity Groups — California 2002-2003. September, 2004.
leak
://wiki
http
CRS-181
Table 80. SJV Irrigated Land, 2002
Irrigated acres by size of farm
IrrigatedTotal land inIrrigated1 to 69 acres70 to 179 acres180 to 499 acres500 to 2,000 acres or
V Countieslandirrigatedland (acres)more
(farms)farms (acres)
Farms Acres Farms Acres Farms Acres Farms Acres
esno 5,405 1,442,088 1,098,941 3,455 72,535 830 78,961 489 125,712 631 821,733
rn 1,408 1,543,013 811,672 470 8,003 271 28,389 245 65,700 422 709,580
ngs 909 482,753 407,031 430 7,666 156 15,085 132 34,383 191 349,897
1,260 503,402 317,241 618 15,632 266 25,184 209 54,200 167 222,225
iki/CRS-RL33184
g/w2,569 803,965 518,538 1,459 32,995 477 45,873 325 79,216 308 360,454
s.orn Joaquin3,428749,595520,1722,26039,74347945,54037794,424312340,465
leak
://wikianislaus 3,764 702,692 401,439 2,672 46,135 484 45,480 376 87,818 232 222,006
httplare 4,739 1,036,279 652,385 3,108 59,090 727 69,538 511 134,554 393 389,203
tal SJV23,4827,263,7874,727,41914,472281,7993,690354,0502,664676,0072,6563,415,563
unt ies
Adjacent Counties
posa 6 0 42,196 1,541 30 123 15 440 2 0 13 531
olumne 142 59,628 3,738 86 502 22 567 13 125 21 2,495
California and the United States
lifornia 55,596 17,587,694 8,709,353 36,220 517,570 7,620 633,966 5,833 1,295,449 5,923 6,262,368
ited States299,583243,442,39655,311,236146,8941,594,89041,2182,278,77439,3675,802,40772,10445,635,165
2002 Census of Agriculture, USDA, National Agricultural Statistics Service
Figure 21. Irrigated Farm Acreage by County (2000)
Data Source: 2002 Census of Agriculture, USDA, National Agricultural Statistics Service
Figure 22. Irrigated Land in Acres by County (2002)
Source: 2002 Census of Agriculture, USDA, National Agricultural Statistics Service
CRS-184
Table 81. SJV Federal Farm Payments, 2002
SJV CountiesNumber of FarmsNumber of Farms ReceivingPayments in 2002Government payments($1,000)Average Payment perfarm
al SJV Counties28,3572,958$85,346.0$28,852
534$18,898.0$35,390
ern 2,147362$13,248.0$36,597
ings 1,154290$10,038.0$34,614
127$3,160.0$24,882
iki/CRS-RL33184 454$11,479.0$25,284
g/woaquin 4,026333$7,118.0$21,375
s.or
leak 331$8,589.0$25,949
://wikilare 5,738527$12,816.0$24,319
http
Adjacent Counties
9$66.0$7,333
ne 358 11 $41.0 $3,727
California and the United States
79,631 7,228 $168,698 $23,340
2,128,982 707,596 $6,545,678 $9,251
2002 Census of Agriculture, USDA, National Agricultural Statistics Service
Figure 23. Average Federal Farm Payments per Farm by County
(2002)
Source: 2002 Census of Agriculture, USDA, National Agricultural Statistics Service
CRS-186
Table 82. SJV Hired Farm Labor, 2002
# ofFarms with 1Farms with 2Farms with 3 or 4Farms with 5 to 9Farms with 10
Farms# of HiredPayroll ofworkerworkersworkersworkersworkers or more
SJ V with farm Hired
untiesHiredlaborer farm labor
farm($1,000)FarmsWorkersFarms WorkersFarmsWorkersFarmsWorkersFarmsWorkers
labor
esno 3,413 69,991 354,051 443 443 378 756 437 1,533 693 4,428 1,462 62,831
rn 1,183 31,521 299,204 199 199 248 496 231 845 167 1,049 338 28,932
ngs 573 10,269 86,254 44 44 74 148 99 335 128 903 228 8,839
925 19,131 97,123 179 179 92 184 106 354 156 1,078 392 17,336
iki/CRS-RL331841,495 19,727 178,581 244 244 224 448 270 916 376 2,589 381 15,530
g/w1,761 30,957 209,676 252 252 289 578 292 1,009 349 2,302 579 26,816
s.orquin
leakanislaus 1,795 19,293 167,804 528 528 273 546 287 972 312 1,993 395 15,254
://wikilare 2,990 42,190 286,657 845 845 354 708 491 1,720 366 2,453 934 36,464
httptal SJV14,135243,0791,679,3502,7342,7341,9323,8642,2137,6842,54716,7954,709212,002
unt ies
Adjacent Counties
posa 3 5 193 549 0 0 14 28 7 2 8 1 1 6 5 3 72
olumne 72 582 1,831 19 19 5 1 0 2 2 7 5 1 2 8 1 1 4 397
United States and California
lifornia 34,342 535,256 4,317,078 8,012 8,012 4,988 9,976 5,632 19,421 5,723 37,166 9,987 460,681
ited 554,434 3,036,470 18,568,446 208,224 208,224 112,722 225,444 104,232 354,400 73,825 467,084 55,431 1,781,318
2002 Census of Agriculture, USDA, National Agricultural Statistics Service
CRS-187
Table 83. SJV Farm Workers by Days Worked — Less than 150 days, 2002
# of Farms# of
withWorkersFarms with 1 workerFarms with 2Farms with 3 or 4Farms with 5 to 9Farms with 10
WorkersWhoworkersworkersworkersworkers or more
SJVWhoWorked
untiesWorkedLess than
Less than150 daysFarmsWorkersFarms WorkersFarmsWorkersFarmsWorkersFarmsWorkers
150 days(workers)
(farms)
esno 2,870 51,240 375 375 312 624 411 1,409 568 3,500 1,204 45,332
rn 810 18,338 185 185 176 352 151 517 107 661 191 16,623
ngs 391 6,013 53 53 77 154 49 161 90 615 122 5,030
iki/CRS-RL33184739 15,139 145 145 71 142 66 208 138 903 319 13,741
g/w
s.or1,087 12,044 242 242 88 176 270 879 248 1,495 239 9,252
leakn Joaquin1,37022,6342162162104202338142871,87742419,307
://wikianislaus 1,296 12,073 403 403 251 502 225 746 182 1,158 235 9,264
httplare 2,114 27,915 614 614 236 472 355 1,219 278 1,742 631 23,868
tal SJV10,677165,3962,2332,2331,4212,8421,7605,9531,89811,9513,365142,417
unt ies
Adjacent Counties
posa 2 1 103 0 0 8 (D) 0 0 12 74 1 (D)
olumne 70 520 21 21 4 8 22 75 9 54 14 362
California and the United States
lifornia 25,984 333,404 6,925 6,925 3,829 7,658 4,292 14,574 4,112 26,068 6,826 278,179
ited 455,669 2,108,762 193,688 193,688 92,695 185,390 79,961 269,149 51,000 319,676 38,325 1,140,859
ithheld to avoid disclosing data for individual farms.
2002 Census of Agriculture, USDA, National Agricultural Statistics Service
CRS-188
Table 84. SJV Farm Workers by Days Worked — 150 Days or More, 2002
# of# ofWorkersFarms with 3 or 4Farms with 5 to 9Farms with 10
WorkersWhoFarms with 1 workerFarms with 2 workersworkersworkersworkers or more
SJVWhoWorked Worked
Counties150 daysWorkers
or more150 daysor moreFarmsWorkersFarms WorkersFarmsWorkersFarmsWorkersFarmsWorkers
(farms) (w orkers)
esno 1,849 18,751 585 585 250 500 311 1,065 316 1,981 387 14,620
rn 844 13,183 181 181 217 434 125 430 92 629 229 11,509
ngs 441 4,256 51 51 109 218 88 301 89 603 104 3,083
iki/CRS-RL33184555 3,992 195 195 113 226 89 297 84 527 74 2,747
g/w1,061 7,683 291 291 171 342 230 821 199 1,272 170 4,957
s.or
leakn Joaquin1,0578,3232782781783562347991911,2361765,654
://wikianislaus 1,016 7,220 313 313 158 316 185 617 183 1,159 177 4,815
httplare 1,842 14,275 643 643 303 606 276 912 239 1,523 381 10,591
tal SJV8,66577,6832,5372,5371,4992,9981,5385,2421,3938,9301,69857,976
unt ies
Adjacent Counties
posa 1 6 9 0 0 0 7 (D) 7 28 0 0 2 (D)
olumne 10 62 5 (D) 1 (D) 0 0 3 2 0 1 (D)
California and the United States
lifornia 19,950 201,852 5,757 5,757 3,456 6,912 3,535 11,937 3,261 20,650 3,941 156,596
ited States214,631927,70898,12898,12842,99285,98436,422122,82821,463133,99315,626486,775
ithheld to avoid disclosing data for individual farms.
2002 Census of Agriculture, USDA, National Agricultural Statistics Service
Table 85. SJV Migrant Farm Labor Valley, 2002
SJV CountiesMigrant farm labor on farmswith hired labor Migrant farm labor on farmsreporting only contract labor
Fresno1,382206
Kern30246
Kings5230
Madera37935
Merced34862
San Joaquin525118
Stanislaus31181
Tulare695242
Total SJV3,994820
Counties
Adjacent Counties
Mariposa80
Tuolumne70
California and the United States
California 8,787 1,521
United States40,8486,536
Source: 2002 Census of Agriculture, USDA, National Agricultural Statistics Service
Notes: Information on migrant workers was collected for the first time in the 2002 census. Operators
were asked whether any hired or contract workers were migrant workers, defined as a farm worker
whose employment required travel that prevented the migrant worker from returning to his/her
permanent place of residence the same day.
Figure 24. Number of Migrant Workers on Farms with Hired Labor by
County, (2002)
Data Source: 2002 Census of Agriculture, USDA, National Agricultural Statistics Service
Agriculture’s Future in the San Joaquin. As an economic driver in the
regional economy and as a factor in the socioeconomic structure of the SJV,
agriculture will likely continue to play a decisive role as it adapts to changing market,
technological, and regulatory forces.103 Increased public concerns about clean water,
pesticide use, groundwater contamination, air quality, food safety, and long-term
impacts on ecosystems will likely increasingly shape the future role of agriculture in
the SJV. Intensification of production in fruits and nuts and vegetables and
movement away from field crop acreage is likely to continue in coming years. In
1980, field crops used 72% of cropland in California, but accounted for only 43% of
the value. Fruits and nuts and vegetables grown on 28% of the acreage contributed
risk crops accounted for 78% of the value from cropland, but used only 45% of the
103 Johnston, Warren E. and Alex F. McCalla. Whither California Agriculture: Up, Down,
or Out? Some Thoughts about the Future. Giannini Foundation Special Report 04-1,
August 2004.
104 Johnston, Warren E. And Harold Carter. “Structural adjustment, resources, global
economy to challenge California agriculture.” California Agriculture, 54(4), July-August
acreage. Such specialization of production and related processing and marketing are
likely to become even more important to agriculture in the SJV in the future.
However, this will likely occur with the continuing decline in the number of farms
and the increasing size of those that remain. As the discussion above on supply
chains indicated, structural changes in agriculture will likely make the sector more
technological, managerial, and information intensive.
Research sponsored by the Great Valley Center and the California Trade and
Commerce Agency has pointed to the dynamics underlying this changing agro-food
system and their implications for the SJV.105 This study identified five major forces
that are driving change in SJV agriculture:
!(1) the segmentation of mass markets;
!(2) consolidation of the food distribution chain;
!(3) globalization of markets;
!(4) technology;
!(5) environmental challenges.
Mass market segmentation can open new niche markets responding to new
products, new uses for products, health/nutrition, and convenience. Supply chains
will likely further consolidate the agro-food system creating a dual system of fewer
but larger buyers and sellers and smaller niche actors. New global production and
marketing strategies and partnerships can open new growth opportunities as well as
new competitors. An increasing technologically driven market place (e.g., Internet
sales) will likely require advanced telecommunication infrastructure.106 Farm-to-
retailer partnerships supported by the Internet may create new opportunities both for
the smaller, niche oriented producer as well as for the largest producers and retailers.
In the area of environmental challenges, water-related drainage and issues and non-
point pollution concerns will likely become more important to producers and
residents of the SJV alike. Precision agricultural technologies could become an
essential part of SJV agriculture in the future.107 This suite of technologies holds
105 Great Valley Center. Producing a Competitive Advantage: Agri-Tech in the SJV.
Modesto, California. December 2000.
106 The Great Valley Center has published a series of studies on the importance of advanced
telecommunications to the future of the SJV. In early 2000, the Center published individual
assessments of each county in the SJV identifying strengths and weaknesses in each
county’s capacity for building greater connectivity to advanced telecommunications. See
Connecting (County): Assessing Our Readiness for the Networked World. See also two
other Center reports that examine the SJV’s advanced telecommunication capacity: Bridging
the Digital Divide in the SJV: The Digital Divide Education Project of New Valley
Connexions. January 2000, and Connecting to Compete in the New Economy. May 2000.
107 The expansion of precision irrigation technologies beyond agricultural production has
been identified as a potential growth area that might be exploited as a driver for new
economic opportunities in the SJV. See Great Valley Center. The Economic Future of the
SJV: Growing a Prosperous Economy that Benefits People and Place. January, 2000.
(continued...)
considerable promise for lessening the environmental impact of agricultural
production. 108
Other observers see the structure of California agriculture as a major factor in
the SJV’s continuing poverty and lack of new economic opportunity. During the
1980s, an analysis using the Urban Institute Underclass Database found that 100
additional farm jobs contributed to an increase of 136 immigrants, 139 poor
residents, and 79 welfare recipients.109 The newly arrived immigrants were not
welfare recipients, but their presence helped to depress wages. This perspective on
SJV agriculture might be seen as falling in the stream of research discussed earlier
about the relation between community well-being and the presence of large,
industrially managed farming operations. Mexican immigrants comprise the largest
proportion of U.S. farmworkers (77%), and San Joaquin agriculture creates a steady
demand for low-wage, low-skilled employment. Opportunities remain limited in the
SJV to move out of agricultural labor and into other sectors. The steady demand for
jobs encourages immigration and the absence of alternatives reinforces the expansion
of agriculture. Efforts to raise farmworker incomes and educational levels can be
hindered when there is a ready supply of new immigrant labor. If the SJV is unable
to create new opportunities for resident immigrants, the poverty that so many
Mexican immigrants are fleeing in their own county may be reproduced within the
SJ V.110
The Non-Agricultural Economy of the San Joaquin
Overview. Although farm jobs accounted for 17% of the employment in the
Central Valley in 2000, other economic sectors, particularly the service sector, are
growing. The service sector accounted for about 77% of the jobs in the Central111
Valley in 2003. Agricultural employment actually declined in the Central Valley
by 10,000 jobs between 1994-2003, with 85% of these jobs losses occurring in112
Fresno, Kern, Kings, Madera, and Tulare counties. The three leading sectors of
employment in the eight-county SJV are government, agriculture, and health services.
The SJV led the greater Central Valley in retail sales from 1998-2002, averaging
nearly $24 billion per year. Growth in retail sales suggests that such expenditures are
likely benefitting the SJV, with spending occurring within the region rather than
leaking outside to other areas. While this increased spending is indicative of
107 (...continued)
Modesto, California.
108 See CRS Report RL30630, Precision Agriculture and Site-Specific Management: Current
Status and Emerging Policy Issues.
109 Immigration and the Changing Face of Rural California and Rural America. Urban
Institute Conference, March 24, 1998.
110 Kasler, Dale. “Central Valley mired in grinding poverty.” Sacramento Bee, January 24,
111 Great Valley Center. Assessing the Region via Indicators: The Economy, 1999-2004.
Modesto, California, January 2005.
112 Ibid., p.22.
economic vitality, retail service jobs generally pay lower wages relative to other jobs
in the service sector.
Throughout the 1990s, job growth in the Central Valley as a whole generally
lagged behind growth in the size of the available labor force. Between 1988-1997,
the labor force grew 21% in the Central Valley versus 13% in the state.113 Between
versus 10.5% respectively. Between 1991-1997, new business formation remained
unchanged in the SJV, although the region led in the number of corporate
headquarters (18) with 400 or more employees. Of the three subregions of the
Central Valley (North Valley, Sacramento, and the SJV), the SJV consistently had
the highest unemployment rate. Five of the ten highest annual U.S. unemployment
rates for MSAs in 2003 were in the SJV .
As noted in Chapter 1, the FJI aims to create 30,000 net new jobs paying at least
$30,000 each annually. The Initiative would aim to reduce Fresno county’s
unemployment rate to the statewide average by creating jobs in health care, advanced
manufacturing, and distribution. Despite high unemployment rates, some SJV
employers report shortages of workers. Hospitals, for example, say they cannot find
Registered Nurses despite offering entry-level salaries of $45,000 to $55,000 a
year.114 Many residents are poorly educated. A third of SJV adults do not have a
high-school diploma. As with many rural areas in the United States, SJV cities have
also sought prisons as an economic stimulus. New prison jobs, however, do not
necessarily go to local residents. Some observers believe that prisons, instead of
creating jobs, may discourage investors from moving to the SJV.
SJV County Employment Profiles. Tables 86-97 provide data from the
U.S. Bureau of Labor Statistics’ Quarterly Census of Employment and Wages on the
annual employment and pay of the 20 largest industries in each of the San Joaquin
counties, Mariposa and Tuolumne counties, and California and the United States115
from 1990-2003.
For comparative purposes, we have also included the same data for the four
Appalachian states containing the 68-county Central Appalachian area: Kentucky,
Tennessee, Virginia, and West Virginia. While the Appalachian state data are not
comparable to Central Appalachia or the individual SJV counties, a comparative
113 Great Valley Center. Assessing the Region via Indicators. Modesto, California, July
114 Rural Migration News. “California: SJV, Refugees.” Rural Migration News, 10(3), July
115 There are many sources for employment numbers. Those from the decennial census count
the number of people with jobs at the time of enumeration. The Bureau of Labor Statistics
(BLS) estimates people working (employed) or looking for work (unemployed) and
estimates the number of jobs by industry based on covered employment. The Bureau of
Economic Analysis estimates the number of jobs by industry (by place of work) and also
includes sole proprietors (which BLS does not). Caution is urged when “mixing” sources,
since each agency uses different estimation methods and therefore have somewhat different
numbers.
view may offer some insight into California and the SJV’s relative standing within
the same employment categories and average annual pay.
Fresno County. Average annual pay grew 54% from $19,603 in 1990 to
$30,196 in 2003. The total employment increased by over 45,000 jobs. In 1990,
crop production was the largest source of employment, accounting for just under
Crop production was followed by support activities for agriculture (8.5%),
educational services (8.2%), food services and drinking establishments (5.1%), and
food manufacturing (3.4%). Of these employment sectors, food manufacturing paid
the highest annual wages ($23,009) in 1990 followed by educational services
($21,353). Reflecting the generally low wage rate in most food service employment,
annual wages in that sector were $7,780. By 2003, educational services had the
largest proportion of county jobs (9.3%) followed by support services for agriculture
(8.2%), food services (5.7%), crop production (5.3%), and hospitals (3.8%). Of these
top 5 employers, hospitals paid the average highest wages ($43,683) in 2003, up from
$25,456 in 1990. In addition to hospital employment, ambulatory health care
services also rose from 12th highest employer in 1990 to 9th in 2003.
Kern County. The average annual pay in Kern County increased by 44%
between 1990-2003 compared to 60% for the United States and 62.8% for California.
As with the United States as a whole and California, educational services was the
largest employer category in Kern County in both 1990 and 2003, although in 2000,
support services for agriculture was the leading employer. Total employment grew
by about 45,000 jobs 1990-2003. Crop production fell from second place in 1990
to third in 2003, while food services were the third largest employment category in
1990 and 2003. Total county employment increased from 202,355 workers in 1990
to 247,760 workers in 2003. Educational services at 10% of county employment in
2003 was followed by support activities for agriculture (9.5%), crop production
(6.9%), food services and drinking establishments (5.8%), and administrative and
support services (3.6%). Of these employment sectors, educational services paid the
highest annual wages ($36,044) in 2003 followed by administrative and support
services ($21,247). With the presence of military bases in the county (Edwards Air
Force Base and the Naval Petroleum Reserve), national security and international
affairs employed over 6,000 persons at an annual wage of $68,324, which along with
mining support activities ($51,312), were the highest paying employers in Kern
County. Food services and agricultural support were the lowest paying jobs in the
county. Ambulatory health care services in Kern County rose from 12th highestth
employer in 1990 to 6 in 2003.
Kings County. Average annual pay was $28,559 for Kern County compared
to $42,592 for California and $37,765 for the United States. Crop production and
support activities for agriculture and forestry were the leading employers in 1990,
2000, and 2003. Total employment in the county in 2003 was 38,112, up from
30,460 in 1990. Kings County, along with Madera and Merced counties, had the
lowest annual employment numbers. In 2003, agricultural support activities, food
manufacturing, and crop production were the top three employers and together
accounted for 21.6% of total county employment. Average annual pay grew 36.2%
from 1990 to 2003 ($20,967 and $28,559 respectively) compared to 62.8% for
California as a whole and 60% for the United States. Total employment increased in
the county by just under 8,000 jobs. Food services and ambulatory health care
services ranked fourth and fifth respectively in employment. Ambulatory services,
with 952 employees, has an average annual wage of $40,481, the third highest annual
pay after heavy and civil engineering construction ($49,516) and national security
and international affairs ($45,263). The latter category likely reflects the presence of
Lemoore Naval Air Station. In 2003, nursing and residential care facilities employed
592 persons, ranking 10th in employment. In 1990, that category was not among the
Madera County. Average annual pay in Madera County increased from
$23,961 in 2000 to $27,877 in 2003, a 16.3% increase. Between 1990 and 2003,
average annual pay increased 54.5% compared to California’s 62.8%. With a total
of 40,465 employees in the county in 2003, crop production and agricultural support
activities accounted for 18.1% of county employment and paid an average of about
$15,000 annually. Crop production and agricultural support activities were also the
top two employers in 1990, paying an average of about $10,500. In 2000 and 2003,
justice, public order, and safety activities became the third largest employer with
slightly over 1,900 jobs. No such employers were among the top 20 employers in
1990 and likely reflect the operation of two prisons in Madera County. Jobs in this
sector paid an average of $41,432, third in ranking after non-metallic mineral productth
manufacturing ($58,535) and telecommunications ($51,007). Ranking 20 among
employers in Madera County, telecommunications employed 434 persons in 2003.
Madera County was the only SJV county where telecommunications ranked among
the top 20 employers.
Merced County. Average annual wages increased 13.5% between 2000 and
2003 and 58.7% between 1990 and 2003. Food manufacturing and crop production
are ranked first and second respectively in Merced County, the same as 1990,
accounting for 17.1% of total employment in 2003. Total employment in the county
grew by nearly 10,000 jobs 1990-2003. Employment growth in food manufacturing
grew by 847 jobs between 1990 and 2003, while annual wages in the sector increased
by 38.5%. Crop production employment, however, fell by over 1000 jobs between
1990 and 2003, although average pay for crop production jobs increased 53.5% in the
county, somewhat lower than the average growth in pay for all job categories
(58.7%). In 1990 and 2000, animal production was ranked fourth in total
employment. By 2003, that category had disappeared from the top 20 employers and
was replaced by agricultural support activities. Specialty trade contractors and
ambulatory health care services were ranked fifth and sixth respectively.
Management of companies and enterprises was also among the top 20 employers in
2003, accounting for over 1,000 workers and paying the highest average annual
wages in the county ($49,873). This was not a top 20 category in 1990.
San Joaquin County. In 2003, San Joaquin County employees had the
highest average annual pay of any of the 8 counties in the SJV ($32,956), increasing
by 12.2% between 2000 and 2003. It also has a relatively diverse employment base
with significant employment in hospitals, ambulatory health care services,
professional, scientific, and technical services, and merchant wholesalers In 1990,
crop production was the leading employment category in the county, accounting for
losing 1,776 jobs. Food services became the leading employment category in 2003
with over 13,000 employees and accounting for 6.1% of the total county employment
of 211,582. Crop production jobs in 2003, however, paid an annual average of
$20,775 compared to $12,454 for food service jobs. This low annual wage is
consistent with many jobs in the expanding service sector. While many service
sector jobs are among the highest paying, these tend to be in business and
professional services. Administrative and support services were ranked second after
food services. These jobs tend to pay better wages than food service employment,
but they are also low relative to manufacturing and fabrication employment.
Warehousing and storage employment provided 4,187 jobs in 2003, ranking 15th in
the county and paying an average annual wage of $43,254. This category was not
among the top 20 in 1990.
Stanislaus County. Average annual pay in Stanislaus County increased
from $28,160 in 2000 to $31,926 in 2003, a 13.4% increase. Like San Joaquin
County in 2003, the food service industry was the largest employer in Stanislaus
County. In 1990 and 2000, food manufacturing was the leading sector in the county,
accounting for 14,475 jobs, 10.5% of the total of 138,212 jobs. Food manufacturing
employment fell by nearly 5,000 jobs between 1990 and 2003. This sector paid
average annual wages of $37,047 in 2003 while food service employment paid
$11,602 on average annually. Support services for agriculture ranked fifth in county
employment and paid slightly more than food service employment. Ambulatory
health care services and hospitals ranked sixth and seventh respectively and were the
two highest annual paying categories. Average annual wages across the top 20
employers in the county increased 57.9% between 1990 and 2003, somewhat lower
than California’s growth rate (62.8%) and that of the average income growth
nationally (60%). Stanislaus County had the third highest average annual pay
($31,926) after San Joaquin and Fresno counties.
Tulare County. Tulare County in 2003 had the lowest average annual pay
among the 8 SJV counties ($26,637). Average annual pay, however, increased
11.9% between 2000 and 2003 and 52.2% between 1990 and 2003. Support
activities for agriculture and forestry is the leading employment category with
average annual pay of $15,250. Support activities for agriculture was also the
leading sector in 1990. Educational services ranked second in 2003. In 1990, crop
production ranked second with 10,574 workers; in 2003, crop production ranked
third, having lost about 125 jobs over that time. By 2003, food services had
increased employment by about 2,500 workers over that of 1990, but the category
was still ranked the second largest employer. Hospital employment accounted for
6,243 workers in 2003 and ranked fifth in the county. In 1990, hospital employment
was not among the top 20 employers and ranked only 14th in 2000. Total
employment in the county rose from 111,085 in 1990 to 135,547, an increase of 18%.
Animal production rose from 11th place in 1990 to 7th place in 2003, more than
doubling employment in that area.
Mariposa County. Mariposa County’s average annual pay in 2003, at
$25,653, was lower than any SJV county, about $1,000 less than Tulare County.
Annual pay also increased only 3.9% between 2000 and 2003 and 52.8% between
1990 and 2003. Reflecting the tourist destination that it is, the leading employment
sector in 2003 was in hotels/motels and similar accommodations. This sector
accounted for 30.8% of employment, 1,551 jobs out of a county total of 5,027.
While accommodations also ranked first in 1990, the sector has lost about 400 jobs
since 1990. Museums, historical sites, and similar institutions rank second in the
county, the same as 1990. This sector grew by about 100 jobs between 1990 and
2003 to 627 jobs. Aside from 146 jobs in ambulatory health care services, most of
the other 17 sectors each had fewer than 60 jobs each.
Tuolumne County. Annual pay across the county’s top 20 categories
averaged $29,535 in 2003, an increase of 15.9% over 2000 and a 50.2% increase
between 1990 and 2003. Tuolumne County also had about three times the total
employment of Mariposa County (17,510) in 2003. Food services was the leading
employment category, paying an average annual wage in of $10,522. The sector
added fewer than 100 jobs between 1990 and 2003. Average pay in the sector
increased by 41.7 % between 1990 and 2003. The second largest employment
category was justice, public order, and safety activities with somewhat under 1,200
jobs. The highest average paying categories were ambulatory health care services
($44,906) and professional, scientific, and technical workers ($43,253).
CRS-198
Table 86. Annual Employment and Average Annual Pay of the 20 Largest Industries, United States, 1990-2003
1990 2000 2003
Averag e Averag e
A nnual Averag e A nnual annual A nnual annual
kIndustryemploymentannual payIndustryemploymentpayIndustryemploymentpay
All 108,603,565$23,605All129,879,584$35,331All127,795,827$37,765
1Educational Services 8,491,193$23,223Educational Services10,554,237$31,957Educational Services 11,293,097$35,009
2Food Services and Drinking Places6,321,450$8,371Food Services and Drinking Places 8,179,177$11,882Food Services and Drinking Places8,593,004$12,726
Professional, Scientific, andAdministrative and SupportAdministrative and Support
3Technical Services 4,991,097$34,892Services7,760,581$22,413Services 7,287,734$25,356
Professional, Scientific, andProfessional, Scientific, and
4Hospitals 4,592,588$24,130Technical Services6,919,298$57,955Technical Services 6,744,928$59,869
Administrative and Support
5Services 4,304,726$15,336Hospitals5,070,038$34,754Hospitals 5,393,226$40,410
6Ambulatory Health Care Services3,045,160$32,275Ambulatory Health Care Services4,397,005$41,068Ambulatory Health Care Services4,875,481$44,491
7Specialty Trade Contractors3,027,590$25,065Specialty Trade Contractors4,170,355$35,117Specialty Trade Contractors 4,216,229$36,913
Merchant Wholesalers, DurableExecutive, Legislative, and Other
8Food and Beverage Stores2,712,706$13,760Goods 3,135,258$50,116General Government Support3,098,922$37,363
iki/CRS-RL331849Executive, Legislative, and OtherGeneral Government Support2,646,022$23,276Food and Beverage Stores 2,990,519$17,907Nursing and Residential CareFacilities2,991,712$23,044
g/wExecutive, Legislative, and OtherMerchant Wholesalers, Durable
s.orGeneral Merchandise Stores 2,633,741$12,329General Government Support2,947,306$33,452Goods2,929,332$51,713
leakMerchant Wholesalers, Durable
Goods2,599,521$31,780General Merchandise Stores2,862,087$16,259Food and Beverage Stores 2,864,053$19,812
://wikiCredit Intermediation and RelatedActivities2,548,473$25,737Nursing and Residential CareFacilities2,794,034$20,781General Merchandise Stores 2,852,423$18,457
httpTransportation EquipmentCredit Intermediation and RelatedCredit Intermediation and Related
Manufacturing2,251,045$34,771Activities 2,551,316$43,134Activities2,791,388$52,341
Nursing and Residential CareInsurance Carriers and Related
Facilities2,141,231$13,865Activities 2,102,099$48,448Social Assistance2,173,977$20,807
Insurance Carriers and RelatedTransportation EquipmentInsurance Carriers and Related
Activities 1 ,949,731 $30,503 Manufacturing 2 ,083,748 $49,812 Activities 2 ,147,820 $55,419
Computer and Electronic ProductMerchant Wholesalers,Merchant Wholesalers,
Manufacturing1,891,514$34,986Nondurable Goods2,006,512$42,373Nondurable Goods1,998,438$46,800
Merchant Wholesalers,
Nondurable Goods1,702,214$27,976Social Assistance1,972,690$18,835Motor Vehicle and Parts Dealers 1,878,753$38,138
Accommodation1,625,572$12,940Accommodation 1,875,478$19,914Accommodation1,804,429$21,580
Fabricated Metal ProductTransportation Equipment
Manufacturing1,615,042$26,747Motor Vehicle and Parts Dealers1,851,378$35,379Manufacturing1,784,938$55,968
Computer and Electronic ProductJustice, Public Order, and Safety
Motor Vehicle and Parts Dealers 1,537,525$23,842Manufacturing1,806,140$71,168Activities1,722,726$47,563
U.S. Department of Labor, Bureau of Labor Statistics, Quarterly Census of Employment and Wages (QCEW), available at [http://www.bls.gov/cew/home.htm].
: Data refer to the average pay of employers to workers. An individual worker may work for more than one employer during the year or hold more than one job at the same time.
CRS-199
Table 87. Annual Employment and Pay of the 20 Largest Industries, California, 1990-2003
1990 2000 2003
Averag e Averag e Annua l Av eragea nnua l
A nnual annual A nnual annual
k I ndus t r y e mpl oy me nt pay I ndus t r y e mpl oy me nt pay I ndus t r y employment pa y
All 13,262,696 $26,162 All 14,905,055 $41,263 All 14,807,656 $42,592
1Educational Services988,983$24,283Educational Services1,222,682$34,850Educational Services1,302,061$39,360
Administrative and Support
2Food Services and Drinking Places 770,684$9,392Services964,186$24,539Food Services and Drinking Places 971,410$14,420
Professional, Scientific, andProfessional, Scientific, andProfessional, Scientific, and
3Technical Services758,264$37,125Technical Services959,261$69,577Technical Services935,474$67,814
Administrative and SupportAdministrative and Support
4Services 627,830$16,890Food Services and Drinking Places 922,592$13,139Services 898,902$27,261
Computer and Electronic Product
5Manufacturing 471,439$40,526Specialty Trade Contractors479,027$37,557Specialty Trade Contractors518,395$38,119
6Hospitals437,507$28,274Ambulatory Health Care Services 465,532$42,327Hospitals497,947$48,417
7Specialty Trade Contractors419,729$27,028Hospitals 450,210$39,883Ambulatory Health Care Services495,932$45,563
iki/CRS-RL331848Ambulatory Health Care Services378,291$35,821Computer and Electronic ProductManufacturing430,785$104,900Merchant Wholesalers, DurableGoods 343,121$54,899
g/wMerchant Wholesalers, DurableMerchant Wholesalers, DurableComputer and Electronic Product
s.or9Goods 342,919$34,049Goods366,793$52,027Manufacturing 324,545$87,273
leakCredit Intermediation and RelatedManagement of Companies and
Activities 334,124$28,409Enterprises 331,180$68,091Food and Beverage Stores321,053$26,374
://wikiFood and Beverage Stores300,204$19,452Food and Beverage Stores301,074$25,478Credit Intermediation and RelatedActivities 294,116$63,535
httpTransportation EquipmentJustice, Public Order, and SafetyJustice, Public Order, and Safety
Manufacturing282,031$38,743Activities257,511$52,071Activities 277,213$58,825
General Merchandise Stores280,067$14,715General Merchandise Stores246,584$18,085General Merchandise Stores264,868$20,212
Insurance Carriers and RelatedCredit Intermediation and RelatedManagement of Companies and
Activities 216,425$33,967Activities236,432$48,742Enterprises255,557$65,005
Merchant Wholesalers,Merchant Wholesalers,
Crop Production 202,659$13,469Nondurable Goods 223,880$42,507Nondurable Goods231,025$47,079
Justice, Public Order, and SafetyNursing and Residential CareNursing and Residential Care
Activities 202,086$38,278Facilities 208,601$21,192Facilities226,691$24,084
Insurance Carriers and RelatedInsurance Carriers and Related
Accommodation 201,437$13,744Activities201,969$51,294Activities 220,886$62,339
Merchant Wholesalers,Amusement, Gambling, and
Nondurable Goods192,398$30,163Motor Vehicle and Parts Dealers200,181$39,913Recreation Industries217,196$21,598
Executive, Legislative, and OtherExecutive, Legislative, and Other
General Government Support186,540$29,730Crop Production 198,087$19,226General Government Support209,625$48,655
Food Manufacturing184,942$23,738Accommodation197,772$20,745Motor Vehicle and Parts Dealers206,425$42,794
U.S. Department of Labor, Bureau of Labor Statistics, Quarterly Census of Employment and Wages (QCEW), available at [http://www.bls.gov/cew/home.htm].
: Data refer to the average pay of employers to workers. An individual worker may work for more than one employer during the year or hold more than one job at the same time.
CRS-200
Table 88. Annual Employment and Pay of the 20 Largest Industries, Fresno County, 1990-2003
1990 2000 2003
Averag e Averag e Av erage
A nnual annual A nnual annual Annua l a nnua l
k I ndus t r y e mpl oy me nt pay I ndus t r y e mpl oy me nt pay I ndus t r y employment pa y
All 283,020 $19,603 All 324,397 $26,169 All 328,131 $30,196
Support Activities for Agriculture
1Crop Production 26,529$10,199and Forestry34,536$12,052Educational Services30,621$34,195
Support Activities for AgricultureSupport Activities for Agriculture
2and Forestry24,206$10,554Educational Services29,415$31,169and Forestry26,986$15,774
3Educational Services 23,173$21,353Crop Production19,666$16,205Food Services and Drinking Places 18,678$11,552
4Food Services and Drinking Places14,667$7,880Food Services and Drinking Places 19,281$10,006Crop Production17,286$17,449
Administrative and Support
5Food Manufacturing9,563$23,009Services 12,112$18,608Hospitals12,730$43,683
6Specialty Trade Contractors 9,484$22,606Food Manufacturing11,277$26,728Food Manufacturing12,368$28,383
7Hospitals 8,708$25,456Ambulatory Health Care Services10,006$44,429Specialty Trade Contractors11,806$32,181
iki/CRS-RL331848Food and Beverage Stores8,186$17,027Hospitals9,920$35,357Administrative and SupportServices 11,552$22,097
g/wExecutive, Legislative, and Other
s.or9General Government Support8,012$21,153Specialty Trade Contractors9,886$29,562Ambulatory Health Care Services10,373$47,917
leakProfessional, Scientific, andProfessional, Scientific, andProfessional, Scientific, and
Technical Services7,334$28,525Technical Services 8,160$36,810Technical Services 9,162$39,247
://wikiAdministrative and SupportExecutive, Legislative, and Other Executive, Legislative, and Other
httpServices7,298$13,626General Government Support7,842$33,816General Government Support8,670$38,440Ambulatory Health Care Services 7,265$35,460General Merchandise Stores6,164$15,772General Merchandise Stores6,832$18,014
General Merchandise Stores 6,376$12,941Food and Beverage Stores6,053$22,503Food and Beverage Stores6,474$23,899
Merchant Wholesalers, DurableMerchant Wholesalers, DurableNursing and Residential Care
Goods6,151$25,265Goods 5,965$34,752Facilities6,096$21,299
Merchant Wholesalers,Nursing and Residential CareMerchant Wholesalers, Durable
Nondurable Goods4,927$28,098Facilities5,891$18,390Goods 5,918$38,676
Credit Intermediation and Related
Activities4,877$22,665Private Households5,261$9,850Motor Vehicle and Parts Dealers5,373$36,259
Merchant Wholesalers,Merchant Wholesalers,
Motor Vehicle and Parts Dealers 4,200$25,925Nondurable Goods5,230$39,812Nondurable Goods5,310$40,927
Insurance Carriers and RelatedManagement of Companies and
Activities4,038$28,555Motor Vehicle and Parts Dealers5,039$33,439Enterprises4,575$39,699
Insurance Carriers and RelatedCredit Intermediation and Related
Construction of Buildings3,855$24,429Activities 4,974$38,782Activities 4,422$43,522
Management of Companies and
Truck Transportation3,760$23,468Enterprises4,290$36,095Construction of Buildings 4,334$40,154
U.S. Department of Labor, Bureau of Labor Statistics, Quarterly Census of Employment and Wages (QCEW), available at [http://www.bls.gov/cew/home.htm].
Data refer to the average pay of employers to workers. An individual worker may work for more than one employer during the year or hold more than one job at the same time.
CRS-201
Table 89. Annual Employment and Pay of the 20 Largest Industries, Kern County, 1990-2003
1990 2000 2003
Averag e Averag e Annua l Av eragea nnua l
A nnual annual A nnual annual
k I ndus t r y e mpl oy me nt pay I ndus t r y e mpl oy me nt pay I ndus t r y employment pa y
All 202,355 $22,481 All 239,696 $28,410 All 247,760 $32,352
Support Activities for Agriculture
1Educational Services17,470$23,742and Forestry25,056$11,748Educational Services25,198$36,044
Support Activities for Agriculture
2Crop Production14,954$14,884Educational Services23,491$32,660and Forestry23,649$13,818
Support Activities for Agriculture
3and Forestry14,228$10,796Crop Production17,443$18,777Crop Production17,187$21,781
4Food Services and Drinking Places 10,710$7,743Food Services and Drinking Places 13,519$10,182Food Services and Drinking Places 14,288$11,665
National Security and InternationalAdministrative and SupportAdministrative and Support
5Affairs8,224$35,035Services 9,629$19,642Services 8,989$21,247
Professional, Scientific, and
6Technical Services7,891$29,645Ambulatory Health Care Services7,710$38,014Ambulatory Health Care Services8,767$42,034
Professional, Scientific, and
iki/CRS-RL331847Specialty Trade Contractors7,670$27,194Technical Services6,940$38,867Specialty Trade Contractors8,299$31,810
g/wAdministrative and SupportProfessional, Scientific, and
s.or8Services 6,642$15,221Specialty Trade Contractors6,892$30,356Technical Services8,218$42,729National Security and International
leak9Oil and Gas Extraction5,981$44,190Affairs6,032$59,354Hospitals6,610$42,726
://wikiSupport Activities for Mining5,572$32,133Hospitals 5,351$31,388National Security and InternationalAffairs 6,332$68,324
httpFood and Beverage Stores5,528$17,269Food and Beverage Stores5,196$24,123Food and Beverage Stores5,333$22,665
Management of Companies andJustice, Public Order, and Safety
Ambulatory Health Care Services5,248$30,439Enterprises5,061$35,344Activities 5,142$39,012
Hospitals 4,716$22,807General Merchandise Stores4,895$15,313General Merchandise Stores4,868$17,305
General Merchandise Stores4,398$11,618Support Activities for Mining4,543$43,968Food Manufacturing4,655$32,229
Heavy and Civil EngineeringJustice, Public Order, and Safety
Construction3,254$29,771Activities 4,490$35,100Support Activities for Mining4,144$51,312
Executive, Legislative, and Other
General Government Support3,121$26,860Motor Vehicle and Parts Dealers3,729$31,759Motor Vehicle and Parts Dealers4,066$34,475
Credit Intermediation and RelatedExecutive, Legislative, and Other
Activities 3,024$23,592Food Manufacturing3,434$29,291General Government Support3,513$38,956
Merchant Wholesalers, DurableNursing and Residential Care
Goods 2,987$26,538Truck Transportation 3,421$32,054Facilities3,473$19,519
Executive, Legislative, and OtherMerchant Wholesalers, Durable
Motor Vehicle and Parts Dealers2,882$23,449General Government Support3,336$35,360Goods 3,308$40,319
Nursing and Residential Care
Truck Transportation 2,724$24,323Facilities3,285$17,311Truck Transportation 3,193$36,016
U.S. Department of Labor, Bureau of Labor Statistics, Quarterly Census of Employment and Wages (QCEW), available at [http://www.bls.gov/cew/home.htm].
Data refer to the average pay of employers to workers. An individual worker may work for more than one employer during the year or hold more than one job at the same time.
CRS-202
Table 90. Annual Employment and Pay of the 20 Largest Industries, Kings County, 1990-2003
1990 2000 2003
Averag e Averag e Annua l Av eragea nnua l
A nnual annual A nnual annual
k I ndus t r y e mpl oy me nt pay I ndus t r y e mpl oy me nt pay I ndus t r y employment pa y
All 30,460 $20,967 All 36,464 $25,436 All 38,112 $28,559
Support Activities for AgricultureSupport Activities for Agriculture
1Crop Production3,273$14,282and Forestry3,988$12,774and Forestry2,922$17,842
2Food Services and Drinking Places1,633$11,298Crop Production 2,642$20,942Food Manufacturing 2,675$35,460
Support Activities for Agriculture
3and Forestry 1,510$11,509Food Manufacturing 2,140$29,916Crop Production 2,646$22,552
4Food Manufacturing 1,375$22,608Food Services and Drinking Places1,962$9,701Food Services and Drinking Places2,132$10,827
National Security and International
5Affairs1,004$19,360General Merchandise Stores971$13,966Ambulatory Health Care Services 952$40,481
6Ambulatory Health Care Services801$28,832Ambulatory Health Care Services 918$36,673General Merchandise Stores881$15,781
National Security and International
7Food and Beverage Stores648$14,621Affairs 749$40,427Specialty Trade Contractors795$25,936
iki/CRS-RL331848General Merchandise Stores 626$12,253Food and Beverage Stores 668$18,287Food and Beverage Stores 754$21,873National Security and International
g/w9Specialty Trade Contractors462$17,435Specialty Trade Contractors588$23,909Affairs 741$45,263
s.orExecutive, Legislative, and OtherExecutive, Legislative, and OtherNursing and Residential Care
leakGeneral Government Support429$24,275General Government Support549$31,696Facilities592$18,510
Merchant Wholesalers,Nursing and Residential CareExecutive, Legislative, and Other
://wikiNondurable Goods 423$41,592Facilities485$18,464General Government Support577$30,565
httpMotor Vehicle and Parts Dealers 406$21,047Motor Vehicle and Parts Dealers 440$28,983Rental and Leasing Services500$18,791Credit Intermediation and RelatedProfessional, Scientific, and
Activities390$16,696Gasoline Stations 394$32,994Technical Services482$35,117
Professional, Scientific, andProfessional, Scientific, andMerchant Wholesalers,
Technical Services344$21,991Technical Services391$33,484Nondurable Goods414$26,383
Credit Intermediation and Related
Educational Services332$10,116Truck Transportation346$29,794Activities384$39,247
Merchant Wholesalers,
Construction of Buildings 289$21,574Nondurable Goods346$33,918Motor Vehicle and Parts Dealers 376$32,997
Building Material and GardenHeavy and Civil EngineeringBuilding Material and Garden
Equipment and Supplies Dealers 286$17,392Construction 336$44,922Equipment and Supplies Dealers 372$21,049
Truck Transportation283$20,547Rental and Leasing Services331$19,270Truck Transportation353$25,876
Clothing and Clothing AccessoriesCredit Intermediation and RelatedHeavy and Civil Engineering
Stores 227$10,137Activities327$26,705Construction 300$49,516
Religious, Grantmaking, Civic,
Professional, and SimilarBuilding Material and Garden
Organizations226$10,340Equipment and Supplies Dealers 248$21,069Repair and Maintenance282$26,280
U.S. Department of Labor, Bureau of Labor Statistics, Quarterly Census of Employment and Wages (QCEW), available at [http://www.bls.gov/cew/home.htm].
Data refer to the average pay of employers to workers. An individual worker may work for more than one employer during the year or hold more than one job at the same time.
CRS-203
Table 91. Annual Employment and Pay of the 20 Largest Industries, Madera County, 1990-2003
1990 2000 2003
Averag e Averag e Annua l Av eragea nnua l
A nnual annual A nnual annual
k I ndus t r y e mpl oy me nt pay I ndus t r y e mpl oy me nt pay I ndus t r y employment pa y
All 26,559 $18,048 All 39,016 $23,961 All 40,465 $27,877
Support Activities for AgricultureSupport Activities for Agriculture
1Crop Production 4,234$10,443and Forestry6,147$10,833and Forestry3,806$13,555
Support Activities for Agriculture
2and Forestry2,370$9,688Crop Production4,778$15,993Crop Production3,511$16,529
Justice, Public Order, and SafetyJustice, Public Order, and Safety
3Food Services and Drinking Places1,437$7,014Activities 1,904$37,185Activities 1,926$41,432
4Food Manufacturing 968$20,050Food Services and Drinking Places 1,746$9,943Food Services and Drinking Places 1,677$11,370
Nonmetallic Mineral Product
5Manufacturing 727$34,172Ambulatory Health Care Services948$44,688Specialty Trade Contractors1,350$27,342
Professional, Scientific, and
6Food and Beverage Stores 713$16,906Specialty Trade Contractors845$28,864Technical Services1,343$16,166
7Machinery Manufacturing679$31,370Food and Beverage Stores 815$21,273Ambulatory Health Care Services1,063$48,608
iki/CRS-RL33184Nursing and Residential Care
g/w8Specialty Trade Contractors635$21,277Facilities746$17,665Food and Beverage Stores 988$24,498
s.orBeverage and Tobacco ProductNonmetallic Mineral Product
leak9Manufacturing609$32,539Manufacturing657$47,753Animal Production 850$22,867Administrative and Support
://wikiAmbulatory Health Care Services 552$27,376Machinery Manufacturing 635$41,484Services 724$18,071Nursing and Residential Care
httpConstruction of Buildings546$21,245Animal Production592$20,820Facilities718$22,042
Administrative and SupportNonmetallic Mineral Product
Motor Vehicle and Parts Dealers 489$21,086Services 514$13,280Manufacturing 663$58,535
Animal Production 446$15,400Accommodation 503$14,591Machinery Manufacturing 652$41,136
Executive, Legislative, and Other
General Government Support410$22,229General Merchandise Stores492$13,559Construction of Buildings 613$28,155
Building Material and GardenExecutive, Legislative, and Other
Equipment and Supplies Dealers 372$20,482Construction of Buildings 452$25,258General Government Support548$37,747
Nursing and Residential Care
Facilities304$12,955Motor Vehicle and Parts Dealers436$24,375Accommodation 544$15,774
Credit Intermediation and RelatedExecutive, Legislative, and Other
Activities275$18,554General Government Support435$35,072General Merchandise Stores531$16,820
Repair and Maintenance258$19,063Private Households385$9,386Food Manufacturing514$30,478
Administrative and Support
Services 253$12,298Telecommunications381$41,159Motor Vehicle and Parts Dealers470$27,146
Accommodation251$12,075Food Manufacturing353$29,772Telecommunications434$51,007
U.S. Department of Labor, Bureau of Labor Statistics, Quarterly Census of Employment and Wages (QCEW), available at [http://www.bls.gov/cew/home.htm].
Data refer to the average pay of employers to workers. An individual worker may work for more than one employer during the year or hold more than one job at the same time.
CRS-204
Table 92. Annual Employment and Pay of the 20 Largest Industries, Merced County, 1990-2003
1990 2000 2003
Averag e Averag e Annua l Av eragea nnua l
A nnual annual A nnual annual
k I ndus t r y e mpl oy me nt pay I ndus t r y e mpl oy me nt pay I ndus t r y employment pa y
All 56,613 $17,731 All 64,611 $24,796 All 66,250 $28,152
1Food Manufacturing5,993$21,352Crop Production 5,682$17,034Food Manufacturing6,840$29,570
2Crop Production5,624$12,892Food Manufacturing5,511$26,875Crop Production 4,560$19,791
3Food Services and Drinking Places 3,000$7,654Food Services and Drinking Places3,609$9,637Food Services and Drinking Places3,782$11,202
Support Activities for Agriculture
4Animal Production 2,200$15,220Animal Production2,595$21,808and Forestry3,187$15,535
Insurance Carriers and RelatedExecutive, Legislative, and Other
5Activities1,404$23,296General Government Support1,815$30,786Specialty Trade Contractors 2,016$27,034
6Food and Beverage Stores 1,345$16,886Ambulatory Health Care Services1,712$35,206Ambulatory Health Care Services1,940$38,542
Executive, Legislative, and Other
7Ambulatory Health Care Services1,340$28,926General Merchandise Stores1,615$15,791General Government Support1,715$39,124
8General Merchandise Stores 1,203$11,014Food and Beverage Stores1,488$21,564General Merchandise Stores1,643$17,791
iki/CRS-RL331849Specialty Trade Contractors1,164$17,664Administrative and SupportServices 1,471$14,997Food and Beverage Stores1,534$22,030
g/wAdministrative and Support
s.orServices 1,122$11,252Specialty Trade Contractors 1,429$23,083Hospitals1,519$44,854
leakExecutive, Legislative, and OtherAdministrative and Support
General Government Support1,092$23,063Motor Vehicle and Parts Dealers 1,246$27,084Services1,443$17,601
://wikiNursing and Residential Care
httpTruck Transportation 1,072$22,968Facilities1,073$16,112Truck Transportation1,249$31,850Fabricated Metal ProductProfessional, Scientific, andNursing and Residential Care
Manufacturing944$16,216Technical Services978$32,791Facilities1,234$19,749
Management of Companies andMerchant Wholesalers,
Motor Vehicle and Parts Dealers859$21,466Enterprises924$71,835Nondurable Goods1,065$39,657
Nursing and Residential CareInsurance Carriers and Related
Facilities847$11,904Activities923$36,455Motor Vehicle and Parts Dealers 1,059$31,074
Merchant Wholesalers,Merchant Wholesalers,
Nondurable Goods837$22,269Nondurable Goods898$30,567Private Households1,010$9,764
Professional, Scientific, andManagement of Companies and
Technical Services 789$24,108Truck Transportation708$28,349Enterprises1,006$49,873
Credit Intermediation and RelatedProfessional, Scientific, and
Activities 654$18,067Repair and Maintenance 668$25,586Technical Services904$39,326
Construction of Buildings 579$18,282Private Households609$9,688Construction of Buildings765$31,764
Building Material and GardenBuilding Material and Garden
Gasoline Stations564$11,769Equipment and Supplies Dealers597$27,655Equipment and Supplies Dealers761$23,605
U.S. Department of Labor, Bureau of Labor Statistics, Quarterly Census of Employment and Wages (QCEW), available at [http://www.bls.gov/cew/home.htm].
Data refer to the average pay of employers to workers. An individual worker may work for more than one employer during the year or hold more than one job at the same time.
CRS-205
Table 93. Annual Employment and Pay of the 20 Largest Industries, San Joaquin County, 1990-2003
1990 2000 2003
Averag e Averag e Annua l Av eragea nnua l
A nnual annual A nnual annual
k I ndus t r y e mpl oy me nt pay I ndus t r y e mpl oy me nt pay I ndus t r y employment pa y
All 169,650 $21,576 All 200,996 $29,355 All 211,582 $32,926
1Crop Production9,531$11,778Food Services and Drinking Places11,497$10,369Food Services and Drinking Places13,004$12,454
Administrative and SupportAdministrative and Support
2Food Services and Drinking Places9,432$8,269Services10,510$18,321Services9,811$21,431
3Food Manufacturing8,526$25,538Crop Production9,498$18,993Specialty Trade Contractors9,519$34,719
Administrative and Support
4Services5,719$17,658Specialty Trade Contractors7,490$32,505Crop Production7,755$20,775
Support Activities for AgricultureSupport Activities for Agriculture
5and Forestry 5,563$7,531Food Manufacturing6,932$34,886and Forestry 6,811$16,495
Support Activities for Agriculture
6Specialty Trade Contractors5,435$23,205and Forestry 6,506$15,598Hospitals6,527$45,123
7Ambulatory Health Care Services 4,813$32,816Ambulatory Health Care Services 5,739$40,359Ambulatory Health Care Services 6,009$41,434
iki/CRS-RL331848Credit Intermediation and RelatedActivities4,456$26,335Truck Transportation 5,563$35,109Justice, Public Order, and SafetyActivities5,665$47,722
g/w9Hospitals4,250$24,796Food and Beverage Stores 5,530$25,096Food and Beverage Stores 5,628$25,076
s.orJustice, Public Order, and Safety
leakFood and Beverage Stores 3,784$18,464Activities 5,498$42,300Truck Transportation5,345$37,312
Justice, Public Order, and Safety
://wikiActivities 3,759$36,459Hospitals 5,214$34,758General Merchandise Stores5,220$18,380
httpTruck Transportation3,707$24,726General Merchandise Stores4,662$17,355Food Manufacturing 5,148$37,675Nursing and Residential CareNursing and Residential CareProfessional, Scientific, and
Facilities 3,498$12,843Facilities 4,655$19,272Technical Services5,043$49,468
Professional, Scientific, andNursing and Residential Care
General Merchandise Stores3,267$11,770Technical Services3,610$38,867Facilities 4,553$22,101
Professional, Scientific, andFabricated Metal Product
Technical Services3,227$25,319Manufacturing3,583$37,478Warehousing and Storage 4,187$43,254
Merchant Wholesalers, Durable
Motor Vehicle and Parts Dealers 3,077$22,861Warehousing and Storage 3,552$36,446Goods3,859$41,457
Merchant Wholesalers, DurableMerchant Wholesalers, Durable
Goods3,018$26,955Goods3,243$38,611Motor Vehicle and Parts Dealers 3,845$38,447
Credit Intermediation and Related
Construction of Buildings2,966$26,034Motor Vehicle and Parts Dealers 3,232$35,515Activities 3,817$42,371
Merchant Wholesalers,
Nondurable Goods2,617$30,490Educational Services3,087$21,666Educational Services3,499$22,577
National Security and InternationalMerchant Wholesalers,
Affairs2,527$25,860Social Assistance2,981$19,518Nondurable Goods3,344$43,202
U.S. Department of Labor, Bureau of Labor Statistics, Quarterly Census of Employment and Wages (QCEW), available at [http://www.bls.gov/cew/home.htm].
Data refer to the average pay of employers to workers. An individual worker may work for more than one employer during the year or hold more than one job at the same time.
CRS-206
Table 94. Annual Employment and Pay of the 20 Largest Industries, Stanislaus County, 1990-2003
1990 2000 2003
Averag e Averag e Annua l Av eragea nnua l
A nnual annual A nnual annual
k I ndus t r y e mpl oy me nt pay I ndus t r y e mpl oy me nt pay I ndus t r y employment pa y
All 138,212 $20,222 All 162,674 $28,160 All 166,988 $31,926
1Food Manufacturing14,475$22,390Food Manufacturing 11,772$32,817Food Services and Drinking Places11,779$11,602
2Food Services and Drinking Places 7,797$7,875Food Services and Drinking Places10,481$9,933Food Manufacturing 9,688$37,047
Administrative and Support
3Specialty Trade Contractors6,092$24,203Services8,460$18,554Specialty Trade Contractors8,526$32,184
Support Activities for AgricultureAdministrative and Support
4Crop Production5,614$13,151and Forestry7,815$9,842Services6,978$22,205
Support Activities for AgricultureSupport Activities for Agriculture
5and Forestry5,608$8,488Specialty Trade Contractors7,051$29,751and Forestry6,489$13,714
6Ambulatory Health Care Services4,227$32,892Ambulatory Health Care Services 6,017$38,348Ambulatory Health Care Services 6,460$44,421
7Hospitals4,166$24,763Crop Production 5,192$18,656Hospitals 6,076$46,820
Management of Companies and
iki/CRS-RL331848Food and Beverage Stores 3,776$18,403Enterprises4,916$59,510Food and Beverage Stores 4,706$25,793Professional, Scientific, and
g/w9General Merchandise Stores 3,493$11,463Food and Beverage Stores 4,661$24,351Technical Services4,591$36,024
s.orAnimal Production3,413$16,986Hospitals4,320$35,765Crop Production 4,565$20,065
leakProfessional, Scientific, and
Technical Services 2,974$25,307General Merchandise Stores4,209$15,480General Merchandise Stores4,418$18,057
://wikiAdministrative and SupportNursing and Residential CareMerchant Wholesalers,
httpServices 2,830$13,287Facilities3,924$19,375Nondurable Goods3,725$39,269Executive, Legislative, and OtherProfessional, Scientific, andExecutive, Legislative, and Other
General Government Support2,796$26,021Technical Services3,851$33,536General Government Support3,549$43,171
Executive, Legislative, and OtherNursing and Residential Care
Truck Transportation 2,209$23,661General Government Support3,243$38,096Facilities3,323$23,627
Merchant Wholesalers,
Nondurable Goods2,141$26,704Motor Vehicle and Parts Dealers 2,921$35,135Motor Vehicle and Parts Dealers 3,242$38,816
Motor Vehicle and Parts Dealers2,090$24,815Animal Production 2,824$21,602Animal Production 2,934$22,858
Fabricated Metal ProductMerchant Wholesalers,Building Material and Garden
Manufacturing2,046$30,999Nondurable Goods2,819$35,132Equipment and Supplies Dealers 2,363$28,851
Fabricated Metal ProductFabricated Metal Product
Construction of Buildings 2,012$24,539Manufacturing2,552$40,130Manufacturing2,239$44,244
Nursing and Residential CareMerchant Wholesalers, Durable
Facilities1,956$13,168Goods 2,336$38,401Truck Transportation2,218$36,237
Credit Intermediation and RelatedBuilding Material and GardenCredit Intermediation and Related
Activities 1,943$20,953Equipment and Supplies Dealers 2,057$24,442Activities2,192$49,067
U.S. Department of Labor, Bureau of Labor Statistics, Quarterly Census of Employment and Wages (QCEW), available at [http://www.bls.gov/cew/home.htm].
Data refer to the average pay of employers to workers. An individual worker may work for more than one employer during the year or hold more than one job at the same time.
CRS-207
Table 95. Annual Employment and Pay of the 20 Largest Industries, Tulare County, 1990-2003
1990 2000 2003
Averag e Averag e Averag e
A nnual annual A nnual annual A nnual annual
k I ndus t r y e mpl oy me nt pay I ndus t r y e mpl oy me nt pay I ndus t r y e mpl oy me nt pay
All 111,085 $17,506 All 132,816 $23,799 All 135,547 $26,637
Support Activities for AgricultureSupport Activities for AgricultureSupport Activities for Agriculture
1and Forestry17,750$9,712and Forestry18,905$13,178and Forestry17,511$15,250
2Crop Production10,574$11,867Educational Services12,926$33,082Educational Services13,729$36,221
3Educational Services9,897$24,112Crop Production11,589$16,490Crop Production10,423$17,187
4Food Services and Drinking Places 4,682$7,121Food Services and Drinking Places 5,891$10,568Food Services and Drinking Places 6,362$11,036
Administrative and Support
5Food Manufacturing4,332$22,192Services 5,280$15,179Hospitals6,243$34,536
Administrative and Support
6Food and Beverage Stores 3,041$15,471Animal Production 4,304$21,936Services 5,070$17,515
7Specialty Trade Contractors2,677$19,818Food Manufacturing4,003$36,229Animal Production 4,877$23,981
8Ambulatory Health Care Services2,495$29,799General Merchandise Stores 3,214$18,998Food Manufacturing4,511$40,515
iki/CRS-RL331849Administrative and SupportServices 2,145$12,337Ambulatory Health Care Services3,190$36,023Specialty Trade Contractors3,853$29,462
g/wExecutive, Legislative, and Other
s.orGeneral Government Support2,126$21,862Specialty Trade Contractors 3,118$27,548Ambulatory Health Care Services3,752$40,427
leakExecutive, Legislative, and OtherExecutive, Legislative, and Other
Animal Production2,032$16,154General Government Support3,061$30,189General Government Support3,074$36,825
://wikiGeneral Merchandise Stores1,996$11,123Food and Beverage Stores2,679$20,445General Merchandise Stores2,878$17,680
httpTruck Transportation 1,954$21,720Nursing and Residential CareFacilities2,268$17,251Food and Beverage Stores2,832$21,328
Merchant Wholesalers, NondurableNursing and Residential Care
Goods1,899$23,344Hospitals 1,888$27,699Facilities2,586$18,822
Professional, Scientific, andProfessional, Scientific, andProfessional, Scientific, and
Technical Services 1,806$22,338Technical Services 1,859$30,459Technical Services 2,142$33,173
Printing and Related Support
Activities1,719$24,538Truck Transportation 1,858$28,546Warehousing and Storage 1,961$32,179
Merchant Wholesalers,Insurance Carriers and Related
Motor Vehicle and Parts Dealers1,679$20,768Nondurable Goods1,857$33,934Activities 1,852$35,917
Merchant Wholesalers,
Hospitals 1,529$29,829Motor Vehicle and Parts Dealers1,816$29,112Nondurable Goods1,786$38,050
Nursing and Residential Care
Facilities1,468$11,082Warehousing and Storage 1,683$24,679Motor Vehicle and Parts Dealers1,781$32,393
Insurance Carriers and RelatedInsurance Carriers and Related
Activities 1,401$21,857Activities 1,523$31,591Truck Transportation 1,714$31,340
U.S. Department of Labor, Bureau of Labor Statistics, Quarterly Census of Employment and Wages (QCEW), available at [http://www.bls.gov/cew/home.htm].
: Data refer to the average pay of employers to workers. An individual worker may work for more than one employer during the year or hold more than one job at the same time.
CRS-208
Table 96. Annual Employment and Pay of the 20 Largest Industries, Mariposa County, 1990-2003
1990 2000 2003
Averag e Averag e Averag e
A nnual annua A nnual annual A nnual annual
kIndustryemployment payIndustryemploymentpayIndustryemploymentpay
All 5 ,504 $16,787 All 4 ,815 $24,694 All 5 ,027 $25,653
1Accommodation 1,907$12,603Accommodation 1,547$20,376Accommodation 1,551$21,716
Museums, Historical Sites, andMuseums, Historical Sites, andMuseums, Historical Sites, and
2Similar Institutions 524$24,592Similar Institutions 551$41,836Similar Institutions 627$34,901
3Food and Beverage Stores139$10,467Ambulatory Health Care Services108$24,564Ambulatory Health Care Services146$27,407
4Construction of Buildings 132$18,046Food and Beverage Stores105$17,497Private Households 108$12,865
5Ambulatory Health Care Services61$15,318Private Households 67$11,065Construction of Buildings 90$21,695
Justice, Public Order, and SafetyJustice, Public Order, and Safety
6Activities 60$41,770Activities 63$37,569Food and Beverage Stores67$20,002
7Gasoline Stations50$12,761Miscellaneous Store Retailers49$16,328Specialty Trade Contractors64$23,880
Justice, Public Order, and Safety
8Miscellaneous Store Retailers36$12,894Gasoline Stations43$11,445Activities 61$33,912
Building Material and GardenPublishing Industries (except
iki/CRS-RL331849Equipment and Supplies Dealers30$12,508Construction of Buildings 35$25,812Internet) 48$23,033Building Material and GardenBuilding Material and Garden
g/wPostal Service26$26,205Equipment and Supplies Dealers 33$18,434Equipment and Supplies Dealers 42$17,722
s.orReligious, Grantmaking, Civic,
leakProfessional, and SimilarHeavy and Civil Engineering
Organizations21$7,927Social Assistance 29$13,553Construction 41$30,617
://wikiSocial Assistance 16$9,821Postal Service25$34,371Gasoline Stations 40$12,446Administration of EnvironmentalAdministration of Environmental
httpQuality Programs12$22,569Quality Programs20$30,126Health and Personal Care Stores 32$21,698
Religious, Grantmaking, Civic,
Professional, and Similar
Organizations18$11,609Social Assistance 29$15,464
Administration of EconomicAdministration of Environmental
Programs16$21,243Quality Programs24$46,559
Postal Service22$37,370
Religious, Grantmaking, Civic,
Professional, and Similar
Organizations 20 $16,144
Motor Vehicle and Parts Dealers 17$14,278
Repair and Maintenance 16$22,178
Insurance Carriers and Related
Activities 16$44,124
U.S. Department of Labor, Bureau of Labor Statistics, Quarterly Census of Employment and Wages (QCEW), available at [http://www.bls.gov/cew/home.htm].
: Data refer to the average pay of employers to workers. An individual worker may work for more than one employer during the year or hold more than one job at the same time.
CRS-209
Table 97. Annual Employment and Pay of the 20 Largest Industries, Tuolumne County, 1990-2003
1990 2000 2003
Averag e Averag e Averag e
A nnual annual A nnual annual A nnual annual
k I ndus t r y e mpl oy me nt pay I ndus t r y e mpl oy me nt pay I ndus t r y e mpl oy me nt pay
All 13,812 $19,669 All 15,514 $25,490 All 17,510 $29,535
1Food Services and Drinking Places1,220$7,424Food Services and Drinking Places1,313$8,830Food Services and Drinking Places1,308$10,522
Justice, Public Order, and SafetyJustice, Public Order, and Safety
2Food and Beverage Stores555$18,159Activities 828$37,327Activities 1,181$40,522
3Construction of Buildings 530$17,231Food and Beverage Stores556$21,557Ambulatory Health Care Services749$44,906
4Specialty Trade Contractors463$17,955Ambulatory Health Care Services554$44,210General Merchandise Stores 549$17,079
Administrative and SupportProfessional, Scientific, and
5Services 453$12,646General Merchandise Stores 550$14,253Technical Services534$43,253
Justice, Public Order, and SafetyAmusement, Gambling, and
6Activities 444$44,916Recreation Industries 514$12,260Food and Beverage Stores525$24,514
Professional, Scientific, andAmusement, Gambling, and
7Accommodation 441$8,376Technical Services427$31,823Recreation Industries 485$15,837
Administrative and Support
iki/CRS-RL331848Ambulatory Health Care Services431$27,638Services 409$17,908Specialty Trade Contractors479$27,310Administration of Environmental
g/w9Quality Programs414$25,233Specialty Trade Contractors409$22,079Construction of Buildings 439$26,716
s.orAmusement, Gambling, andAdministrative and Support
leakRecreation Industries 357$10,865Construction of Buildings 383$22,552Services373$19,897
Professional, Scientific, and
://wikiTechnical Services328$19,661Accommodation 359$10,423Accommodation 371$11,951Religious, Grantmaking, Civic,Religious, Grantmaking, Civic,
httpCredit Intermediation and RelatedProfessional, and SimilarProfessional, and Similar
Activities 321 $17,105 Organizations 295 $16,702 Organizations 339 $19,119
Insurance Carriers and RelatedExecutive, Legislative, and Other
Activities 265$20,772Machinery Manufacturing262$38,352General Government Support325$37,720
Religious, Grantmaking, Civic,
Professional, and SimilarExecutive, Legislative, and Other
Organizations242$11,683General Government Support254$33,072Miscellaneous Store Retailers271$13,162
Executive, Legislative, and OtherAdministration of Environmental
General Government Support223$21,743Repair and Maintenance247$22,702Quality Programs242$44,719
Building Material and Garden
Equipment and Supplies Dealers220$19,123Miscellaneous Store Retailers211$11,811Repair and Maintenance235$25,574
Nursing and Residential Care
General Merchandise Stores193$11,877Real Estate208$19,599Facilities234$22,663
Nursing and Residential CareBuilding Material and Garden
Repair and Maintenance181$18,280Facilities206$18,843Equipment and Supplies Dealers232$24,399
Administration of Environmental
Forestry and Logging171$31,194Quality Programs191$39,274Motor Vehicle and Parts Dealers215$29,804
Motor Vehicle and Parts Dealers163$23,187Gasoline Stations189$12,877Real Estate207$24,187
U.S. Department of Labor, Bureau of Labor Statistics, Quarterly Census of Employment and Wages (QCEW), available at [http://www.bls.gov/cew/home.htm].
: Data refer to the average pay of employers to workers. An individual worker may work for more than one employer during the year or hold more than one job at the same time.
Appalachian State Employment Profiles. Similar data are not provided
on each of the 68 Central Appalachian counties. Data on the four Appalachia states
where the 68 counties are located reveal some similarities and differences with the
San Joaquin. Like the United States and California, the largest industry in Kentucky,
Tennessee, Virginia, and West Virginia in 2003 was educational services. Education
services was also the largest industry in 1990 and 2000 for each state, with the
exception of professional, scientific and technical services in Virginia in 1990. In
2003, educational services was also the largest industry in Fresno and Kern counties
and the second largest industry in Tulare County. Food services, hospitals, and
ambulatory health care services were also among the top six to eight industrial
sectors in each of the states. Were the SJV not so heavily represented in crop
production and agricultural services in their top five sectors, the SJV counties would
look somewhat similar to West Virginia in terms of sectoral ranking. Average annual
wages in West Virginia for all 20 sectors in 2003 was $29,284. The average annual
wage for all 20 industrial categories for Fresno, Kern, San Joaquin, and Stanislaus
counties was higher in 2003 than that of West Virginia. For Kings, Madera, Merced,
and Tulare counties, the average wage was lower. In hospitals, ambulatory health
care, professional, scientific, and technical services, food services, an