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INDEX
A
Accountability, 8, 126
Act 250 (Vermont), 177
African Americans, see Black persons
Agglomeration economies, 19, 32-34, 125-126
see also Economies of scale
Agricultural land, see Rural areas
Aid, see Equalization aid;
Subsidies and aid
Air quality, 296, 304, 310-321
automobile use, 296, 299, 300, 304, 309, 314, 316-318, 319
federal regulations, 304, 310, 313-317, 319-320
funding, 304, 313
Air Pollution Control District Act (CA), 310
Air Quality Act, 310
Alabama, 60-61, 260-263
Alaska, 262-263
Alcohol use and abuse, 56, 226
Annexation, 28-29, 63, 95, 96, 203, 240, 243, 268, 276
see also Elasticity
Anti-Snob Zoning Act (MA), 158
Arizona, 262-263
Arkansas, 260
Asians, 178
children, 20
residential segregation, 27
Attitudes, 11, 127, 106-107
home ownership, 193
individualism and equal opportunity, 18
neighborhood effects, 54-55;
see also Peer influences
racial prejudice, 46, 90-91, 195, 201, 238-239, 242
residential segregation, 57
suburban residents toward inner city, 10, 52, 89, 132, 201, 271
suburban residents toward low-income housing, 29-30, 90-91, 158, 236, 238-239, 242
see also Racial discrimination
Automobiles, 6, 84, 160-161, 170, 287
gasoline taxes, 84, 299
regional transportation policy, 296, 299, 300, 304, 309, 314, 316318, 319
B
Black persons, 46, 119, 121
central cities, general, 25, 26, 57, 193-194, 230, 240
central-city/suburban disparities, 42, 69, 195, 202, 205, 207, 208, 209, 214-216
children, 20, 54
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educational attainment, 47, 49, 50, 52, 61- 62, 67, 69, 70, 195, 220-221, 229
employment, spatial mismatch hypothesis, 5-6, 52, 57, 217, 220-221, 223, 224-225, 227, 228
gender factors, 54, 214, 215
housing, 83, 90-91, 228;
see also ''segregation, residential'' infra
income, 5, 16, 20, 27, 46-50, 61, 62, 67, 120, 158, 195, 215-216;
see also "poverty" infra
local government fragmentation/consolidation, 106-107
neighborhood effects, 218, 227, 228, 240
poverty, 5-7, 16, 20, 27, 48, 54, 57, 195, 202, 205, 207, 208, 209, 214-216
segregation, educational, 26, 49
segregation, residential, 6-7, 18-19, 26, 27, 49, 56-57, 58-59, 67, 69-70, 198-199, 202, 205, 206, 228, 229, 237-238, 242
spatial distribution, general, 214-216
suburbs, 195, 213;
see also "central-city/suburban disparities" supra
Boston, Massachusetts, 57, 154, 161-162, 225
Bridges to Work, 89, 235
Building codes, 31, 130-131
Bureau of the Census, 9, 20, 117, 195
C
California, 80, 82, 94, 161, 162, 165, 255, 262-263, 279, 302, 310-311, 312-316, 317, 320
see also Los Angeles, California;
San Francisco, California
Canada, 171
Census Bureau, see Bureau of the Census
Central cities, vii, 12, 14
agglomeration economies, 32-34, 35, 125-126
black persons, general, 25, 26, 57, 193-194, 230, 240
costs of urban decline, 11, 14, 19-20, 35, 36, 71, 127, 192, 288
definition of metropolitan area, 22, 38-39(n.1), 199-206
economic competitiveness, 22, 32-34, 115
elasticity, 10, 45, 63-64, 120, 127, 193, 203, 206-207, 208, 240, 254, 269
annexation, 28-29, 63, 95, 96, 203, 240, 243, 268, 276
local government fragmentation and, 64, 65, 66
employment, 22, 33-34, 52-53, 131, 132
spatial mismatch hypothesis, 5-6, 7-8, 32, 51-52, 57, 61, 67, 216-217, 220-230 (passim)
enterprise zones, 86-87, 123, 230-233, 234
low-income housing, 53, 59, 130-131, 153
low-income minorities. isolation, 3, 5, 6-7, 10, 56-59, 201, 237
minorities, general, 25, 201, 230
place-based strategies, 87-88, 123, 230-234
political factors, 22, 36-38, 254
racial segregation, 25-26
spatial distribution, general, 24-26, 230
spatial mismatch hypothesis, 5-6, 7-8, 32, 51-52, 57, 61, 67, 216-217, 220-230 (passim)
suburbs' relation to, 4-6, 10, 11, 14, 15, 16, 19-20, 21, 24-25, 34-36;
see also Central city/suburban disparities
value of central cities, 32-38
see also Tax/service disparities
Central-city/suburban disparities
black persons, 42, 69, 195, 202, 205, 207, 208, 209, 214-216
educational attainment, 41-43, 45, 46, 58, 67-68, 194-199 (passim), 204, 273-274
educational services, 4, 17, 35
employment, 4, 5, 16, 17, 33-34, 35, 36, 41, 45, 52, 58, 62-63, 68, 69, 194-204 (passim), 214-217, 225, 281-282, 306;
see also "worker mobility strategies" infra
spatial mismatch hypothesis, 5-6, 7-8, 32, 51-52, 57, 61, 67, 216-217, 220-230 (passim);
see also "worker mobility strategies" infra
Gautreaux program (Chicago), 57-58, 90, 123, 218-219, 227-228, 238
gender factors, 214, 215
Hispanics, 195, 202, 205, 206, 207, 208, 209, 240
historical perspectives, 4, 20, 24-25, 27, 35, 41-43, 51, 63, 193, 196-197, 200, 214-215
income, 4, 16, 20, 35, 36, 41-42, 43-45, 58-59, 62-68, 120, 194-208 (passim), 215-216, 217;
see also "poverty" infra
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individuals, disparities among, 41-46
local government fragmentation/consolidation, 65, 66, 106-107
population size and density, 43-44, 192, 193, 201, 205
poverty, 4, 16, 26-27, 29, 42, 43-44, 52-53, 90-91, 97-98, 110, 194-198 (passim), 254, 267-268, 307-309
racial segregation, general, 57-58
regional factors, 43, 44-45, 120, 200-201, 203-205, 207, 208, 209
spatial mismatch hypothesis, 5-6, 7-8, 32, 51-52, 57, 61, 67, 216-217, 220-230 (passim);
see also "worker mobility strategies" infra
sprawl, 152, 158, 159, 176
taxation, general, 34, 35, 37;
see also Tax/service disparities
transportation, general, 305-306, 307
worker mobility strategies, 10, 86, 88-89, 94, 95, 123, 131, 132, 227, 235-236;
see also "spatial mismatch hypothesis" supra
see also Tax/service disparities
Centralization/decentralization policies, 3, 7-9, 10, 11, 23-24, 64-67, 96-98, 104-115, 116, 128, 160, 203, 206, 240, 242-243
black persons, attitudes toward, 106-107
central-city/suburban disparities, 65, 66, 106-107
counties, 65, 97, 98
defined, 65
demographic factors, general, 66
economies of scale, 9, 33, 65, 104-105, 106, 112, 270, 271-272, 273, 279
elasticity and, 64, 65, 66
fiscal capacity, general, 65-66
historical perspectives, 106, 110, 114, 270
income, 66-67
minority groups, general, 107-108, 238
nested government, 11, 112-113, 128-129
quasi-governmental organizations, 286-287
racial/income segregation, 8, 11, 66-67, 124
regional factors, 66, 107, 110-111, 113-114, 116-117, 124-125, 276;
see also Special districts
research recommendations, 120-121, 124
services, general, 8-9, 10, 65-66, 110-112
spatial opportunity structures, 64-65, 241
state policies, 109-110, 115
municipal incorporation, 8, 28-29, 31, 115, 268
subsidies and aid, 111, 114-115, 129
taxation, general, 107-108, 203
tax/service disparities, 8, 75, 116, 203, 268, 269-272
transportation, 111, 274, 296-310, 318-321
two-tier governments, 21, 95, 96, 97, 106, 268, 272-274, 287
unequal opportunity, general, 8, 65-66
zoning, 80, 81, 176-177, 180
see also Special districts
Chicago, Illinois, 17, 57-58, 62, 74, 90, 91, 198, 281
Gautreaux program, 57-58, 90, 123, 218-219, 227-228, 238
Children, 54, 56, 91, 219, 239
black, 20, 54
income segregation, 59, 117, 158, 192
minority, general, 20
peer influences, 54-55, 59, 92, 94, 117, 122, 158, 218, 219, 226, 239
tax/service disparities, 75
youth employment, 221-224
see also Education
Cities Without Suburbs, 239
Civil Rights Act, 308, 319
Classification issues
elasticity, 62-63
employment, 14, 215
high-poverty areas, 39(n.4)
metropolitan areas, 22, 38-39(n.1, n.3), 199-206
metropolitan governance, 14-15, 176
urban problems, 14, 28
Clean Air Act (federal), 310, 313, 315-317
Clean Air Acts (CA), 314, 315, 316, 320
Cleveland, Ohio, 108, 113-114, 283, 297
Coleman report, 60
Colorado, 262-263
Community development corporations/financial institutions, 87-88, 123, 232-234
Commuters and commuting, 6, 22
commuter taxes, 7, 98, 101, 123, 133, 267, 281-282
gasoline taxes, 84
reverse commuting, 10, 89, 217, 235-236
suburbanization, 28, 159, 160-161, 162, 308
tax/service disparities, 7, 98, 101, 123, 133, 253-254, 270, 281-282
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worker mobility, 10, 86, 88-89, 94, 95, 123, 131, 132, 227, 235-236
poverty and employment mobility, 10, 86, 88-89, 94, 95, 123, 131, 132, 227, 235-236
spatial mismatch hypothesis, 5-6, 32, 51-52, 56, 57, 61, 67, 89, 216-217, 220-230 (passim)
see also Mass transit
Computer applications
air quality controls, 315
employment databases, 236
Connecticut, 156
Consolidation/fragmentation, see Centralization/decentralization policies
Construction industry, see Building codes;
Housing
Counties, 15, 23, 39(n.1), 82, 243
air quality controls, 311-312
equalization aid, 101
government fragmentation/consolidation, 65, 97, 98
tax/service disparities, 255, 262-266, 270, 272, 273, 280-281
transportation policy, 297
Court cases
air quality control, 317
education, 279
mass transit, 308
zoning, 83, 154-155, 158, 165, 168, 174-175, 180-181
Crime, 9, 18, 70, 158
neighborhood effects, 6, 54, 56, 70, 226
police, 9, 19, 75-76, 83, 158, 218, 234, 267, 268, 273-274, 280, 286
segregation, general, 70
suburbs, 71, 81-82, 158, 161
tax/service disparities, 75, 267, 268, 273-274, 280, 286
Cultural factors
city institutions, 19
public choice factors, 105
residential segregation, 57
see also Neighborhood effects;
Social factors
D
Dayton, Ohio, 99-100, 285
Decentralization, see Centralization/decentralization policies
Delaware, 260
Demographic factors, 22, 201-202, 205
local government fragmentation, 66
tax/service disparities, general, 75
see also Family factors;
Gender factors;
Minority groups;
Neighborhood effects;
Population size and density;
specific minority groups
Department of Housing and Urban Development, 232
Department of Transportation, 301-302
Detroit, Michigan, 57, 69, 112, 225, 269
Discrimination, see Racial discrimination
District of Columbia, see Washington, D.C.
Drag use and abuse, 56, 226
E
Economic issues, general, 13-14
agglomeration economies, 19, 32-33, 125-126
costs of urban decline, 11, 14, 19-20, 35
globalization, 17-18, 33
speculation, 172-173
suburbanization, 28, 151, 152
see also Community development corporations;
Employment and unemployment;
Enterprise zones;
Funding;
Income;
Place-based initiatives;
Poverty;
Socioeconomic status;
Subsidies and aid;
Taxation;
Tax/service disparities
Economies of scale, 9, 33, 65, 104-105, 106, 112, 270, 271-272, 273, 279
see also Agglomeration economies
Education, 10, 60-61, 67, 107
black persons, segregation, 26, 49
central cities vs suburbs, 4, 17, 35
court cases, 279
equalization aid, 102-103, 123
expenditures, 10
Hispanics, segregation, 26
labor market skills, 86, 91-94, 133-134
life-style issues, 14
minorities, general, 26, 47, 131-132
neighborhood effects, 94, 219-220, 226, 239
poor children, 91-92, 94, 123, 131-132, 192
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Population size and density, 61-63, 120
central-city/suburban disparities, 43-44, 192, 193, 201, 205
educational attainment and, 61-62
elasticity and, 10, 45, 63-64, 269
employment and, 61
historical perspectives, 22-23, 24-25, 27, 193-194
income and, 62
metropolitan area defined, 22, 38-39(n.1, n.3)
racial disparities, 48-49, 51
spatial distribution, general, 10, 61-62
sprawl, 13, 33, 109, 151-191, 237
tax/service disparities, 75, 254, 269, 277
Portland, Oregon, 38, 81, 84, 109, 110-111, 172, 177
Poverty, vii, 3-4, 107, 192
black persons, 5-7, 16, 20, 27, 48, 54, 57, 195, 202, 205, 207, 208, 209, 214-216
central cities vs suburbs, 4, 16, 26-27, 29, 42, 43-44, 52-53, 90-91, 97-98, 110, 194-198 (passim), 254, 267-268, 307-309
classification of poverty areas, 39(n.4)
community development corporations/financial institutions, 87-88
definitional issues, 39(n.4)
educational services, 91-92, 94, 123, 131-132, 192
employment mobility, 10, 86, 88-89, 94, 95, 123, 131, 132, 227, 235-236
enterprise zones, 86-87
gender factors, 54
Hispanics, 4-5, 16, 27, 195
income segregation, 6-7, 9, 10, 16, 18-19, 21, 27, 29-31, 59-60, 65, 66-67, 70, 80, 117, 118, 124, 131, 151, 153-161, 169, 182, 192, 197-198, 199, 201-202, 229, 237
minority groups, general, 4-5, 10, 16, 53
neighborhood effects, 6, 7, 16, 17, 53-56, 59, 117-118, 197-198, 213, 217-219, 225
research recommendations, 117-118, 125
social isolation, 6, 7-8, 52-53, 89, 156, 158-159;
see also "neighborhood effects" supra
spatial distribution factors, general, 27, 119
suburbs, 3, 4, 97-98;
see also "central cities vs suburbs" supra
tax/service disparities, 73, 76, 97-98, 254, 278, 281
transportation, 305-306, 307-308;
see also Mobility (workers)
zoning discrimination, 11-12, 29;
see also Zoning (exclusionary)
see also Low-income housing;
Subsidies and aid;
Welfare
Property rights, 84-85, 152, 165, 168, 178-182
Property tax, 30, 75, 97, 99, 100-101, 102, 255, 256, 282
educational services and, 174-175
regional factors, 201
sprawl, 169, 173-175, 178
Public services, 6, 10, 30, 126
fragmented vs consolidated local government, and 8-9, 10, 65-66, 110-112
residential segregation, 57
surburbanization and, 152
unequal provision, 10, 60-61
see also Education;
Infrastructure;
Mass transit;
Police;
Special
districts;
Tax/service disparities;
Welfare
Public transportation, see Mass transit
Q
Quality of life, general, 14, 15, 129
suburban residents, 20
Quasi-governmental organizations, 286-287
R
Racial discrimination, 11-12, 18-19
antidiscrimination laws, 11-12, 94-95, 108, 131, 132, 237, 308, 319
attitudes, general, 46, 90-91, 195, 201, 238-239, 242
employment, 5-6, 10, 52, 57, 68-69, 89, 94-95, 121, 132
residential segregation, vii, 5-6, 8, 10, 25-26, 27, 31, 51, 56-59, 69-71, 118-119, 131, 158, 198-199, 201-202, 205, 213, 229, 237, 240
black persons, 6-7, 18-19, 26, 27, 49, 56-57, 58-59, 67, 69-70, 198-199, 202, 205, 206, 228, 229, 237-238, 242
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educational attainment and, 49, 69
employment, 69
household mobility strategies, 90
international studies, 118-119
local government fragmentation, 8, 11, 66-67, 124
neighborhood effects, 7, 16, 21, 53, 118, 198-199, 206, 238, 240
see also Neighborhood effects
segregation, other, 6-7, 9, 10, 18-19, 46, 57-59, 118, 124, 202, 213
Racial factors, other, see Minority groups
Regional factors, 15, 20, 21, 49, 110, 120
air quality control, 296, 304, 310-320
automobiles, regional policies, 296, 299, 300, 304, 309, 314, 316-318, 319
central cities' relations with suburbs, 35
central-city/suburban disparities, 43, 44-45, 120, 200-201, 203-205, 207, 208, 209
income, black vs white, 47-48, 49
income, central cities vs suburbs, 43, 44-45, 120
local government fragmentation/consolidation, 66, 107, 110-111, 113-114, 116-117, 124-125, 276;
see also Special districts
local government, other, 24
metropolitan planning organizations, 111-112, 114, 125, 274, 277, 302, 303-304
metropolitanization, general, 104-111
place-based initiatives, 86
political factors, 15, 36, 37, 110, 113-114, 300, 305-306, 307-309, 314
research recommendations, 124-125, 242-243
system maintenance, 15, 19
tax/service disparities, 98, 99, 133, 276
transportation policy, 111, 274, 277, 296-310, 318-321
Regression analysis, 69, 70, 76, 193, 199-200, 206-208, 242-243
Regulatory issues
automobile use, 296, 299, 300, 304, 309, 314, 316-318, 319
low-income housing, 89-90, 130-131
sprawl, federal regulations, 28, 175-176
see also Building codes;
Environmental protection;
Standards;
State
government;
Zoning
Research recommendations, 10-11, 117-127
elasticity, 241
income segregation, 58-59, 118, 124
local government fragmentation/consolidation, 120-121, 124
neighborhood effects, 117, 118, 122, 242
segregation, 49
spatial distribution factors, 117-119
spatial opportunity structures, 241-243
unequal opportunity, 9, 10, 117, 127, 129-131
Residential segregation, 6, 8, 9, 52-53, 57, 220, 242-243
black persons, 6-7, 18-19, 26, 27, 49, 56-57, 58-59, 67, 69-70, 198-199, 202, 205, 206, 228, 229, 237-238, 242
elasticity, 240
Gautreaux program (Chicago), 57-58, 90, 123, 218-219, 227-228, 238
Hispanics, 27, 58-59, 176, 205, 206, 208, 209, 237
historical perspectives, 26, 56-57, 240
immigrants, 56-57
income segregation, 6-7, 9, 10, 16, 18-19, 21, 27, 29-31, 59-60, 65, 66-67, 70, 80, 117, 118, 124, 131, 151, 153-161, 169, 182, 192, 197-198, 199, 201-202, 229, 237
children, 59, 117, 158, 192
international studies, 29, 30, 31, 118-119
neighborhood effects, 7, 16, 21, 53, 118, 198-199, 206, 238, 240
study at hand, methodology, vii
see also Racial discrimination (residential segregation);
Zoning (exclusionary)
Revenue, see Government revenues and expenditures;
Taxation
Roads, see Transportation
Rural areas
transportation policy, 298, 300
zoning, 163-164, 169, 170-171, 172, 175-176
S
Sacramento, California, 313
San Francisco, California, 162, 169-170, 304, 308, 310, 311, 312, 313, 316, 317
Seattle, Washington, 109, 111
Seoul, South Korea, 178
Services, see Public services
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Social factors, general, 9, 14, 16
family factors, 16, 54, 94, 164, 218
single parents, 58, 70, 226
life-style issues, 14, 15, 18
peer influences, 54-55, 59, 92, 94, 117, 122, 158, 218, 219, 226, 239
poverty and social isolation, 6-8, 52-53, 89, 156, 158-159;
see also Residential segregation
suburbanization, 28, 29-30
see also Demographic factors;
Minority groups;
Neighborhood effects;
Political factors;
Racial discrimination
Socioeconomic status, general
central cities' relations with suburbs, 35
classification of urban problems. 14
decentralized structures and inequality, 3
research recommendations, 117
see also Income;
Poverty;
Racial discrimination;
Residential segregation
South Carolina, 61, 264-265
South Dakota, 264-265
South Korea, 178
Spatial distribution factors, 10, 14, 21, 22, 23-28, 67-69, 192-213
black persons, general, 214-216
density of population, 10, 61-62
education, school location, 94
employment, 67-68
discrimination, 69
spatial mismatch hypothesis, 5-6, 7-8, 32, 51-52, 61, 67, 201, 216-217, 220-230 (passim)
international perspectives, 29, 30, 31, 118-119
local government, 29-32
minorities, general, 21, 119, 134, 194-195
place-based initiatives, 86-88, 123, 230-234
research recommendations, 117-119
spatial mismatch hypothesis, 5-6, 7-8, 32, 51-52, 56, 61, 67, 216-217, 220-230 (passim)
spatial opportunity structure, 10, 11, 16-17, 18, 21, 37, 40, 51, 54, 61, 79-115, 116-117, 121-122, 123-125, 127-128, 129, 133-135, 213-252
tax/service disparities, 268-269
see also Elasticity;
Land use;
Neighborhood effects;
Residential
segregation;
Special districts;
Sprawl;
Zoning
Special districts, 23, 98, 112, 125, 129, 269, 272-274, 277
air quality control, 296, 304, 310-321
metropolitan planning organizations, 111-112, 114, 125, 274, 277, 302, 303-304
Speculation, 172-173
Sprawl, 13, 33, 84, 109, 151-191, 237
central-city/suburban disparities, 152, 158, 159, 176
environmental impacts, 175-176, 177-178
immigrants, 177-178
international perspectives, 151, 153, 162-163, 165, 168, 170
opportunity costs, 176
property rights, 84-85, 152, 165, 168, 178-182
property tax, 169, 173-175, 178
see also Elasticity
Stable Neighborhood Initiatives Program, 238, 239
Standards
building codes, 31, 130-131
educational, 131, 132
State government, 3-4, 8, 11, 18, 21, 115, 129-130
air quality controls, 310-315
annexation, 28-29
commuter taxes, 123
education, 102-103, 104
employment, 177
enterprise zones, 86-87, 123, 230-233, 234
equalization aid, 7, 10, 72, 101-103, 123, 125, 133, 268, 278-280, 284;
see also Place-based initiatives
housing, 8, 80-81, 236-237
land use policies, 8, 11, 80-81, 82-84, 119, 130, 154-155, 168, 177, 180-181, 236-237
local governments and, 8, 11, 18, 21, 76, 98, 99, 101, 102-103, 104, 260-267, 277, 278, 280-281
metropolitan consolidation policies, 109-110, 115, 128-130
municipal incorporation policies, 8, 28-29, 31, 115, 268
tax/service disparities, 76, 98, 99, 101, 102-103, 104, 260-267, 277, 278, 280-285
metropolitan governance, general, 11, 109-110, 115
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municipal incorporation policies, 8, 28-29, 115
political factors, 11, 28, 37, 177, 181, 280
rural property tax, 175
subsidies and aid, 74
tax policies, general, 8, 175, 255
tax revenues by state and/or type, tables, 256-257
tax/service disparities, 76, 98, 99, 101, 102-103, 104, 260-267, 277, 278, 280-285;
see also Equalization aid
transportation policies, 298, 299-300, 306
unequal opportunity, 18, 129-130
see also Court cases;
Legislation, specific state;
specific states
Statistical analyses
agglomeration economies, 34
central cities' relations with suburbs, 35-36
local government fragmentation effects, 66
municipal incorporation factors, 31
racial disparities, 49
see also Regression analysis
St. Louis, Missouri, 108
Subsidies and aid
community development corporations/financial institutions, 87-88, 123, 232-234
enterprise zones, 86-87, 123, 230-231, 234
Europe, 162-163, 165, 167
federal government, 74, 101-102, 111, 114-115, 298-303, 304, 306-307
growth controls, 84
housing, 90, 154-155
metropolitan consolidation, 111, 114-115, 129
sprawl, 171-172
tax/service disparities, 72, 74, 267;
see also Equalization aid
transportation, 298-303, 304, 306-308
zoning and, 30, 82-84, 85, 171-172, 179
see also Vouchers;
Welfare
Suburbs and suburban residents, 4-5, 15, 16, 21, 192
agglomeration economies, 33, 34
attitudes toward inner city, 10, 52, 89, 132, 201, 271
attitudes toward low-income housing, 29-30, 90-91, 158, 236, 238-239, 242
causes of, 10, 28-29, 30, 118, 151-191, 281-282
federal government role, 28, 175-176
political factors, 28-29, 158, 163, 164-165, 176-178, 254
transportation factors, 28, 159, 160-161
costs of urban decline, 11, 14, 19-20, 35, 36, 71, 127, 192, 288
crime, 71, 81-82, 158, 161
employment, 22, 33-34, 132, 163-164
discrimination, 5-6, 10, 19, 57, 95, 132
spatial mismatch hypothesis, 5-6, 7-8, 32, 51-52, 57, 61, 67, 216-217, 220-230 (passim)
see also Mobility (workers)
Hispanics, 195, 202, 205, 208
historical perspectives, 24, 28, 153, 154, 157, 158, 159-161, 175, 193, 195, 196
household mobility strategies, 86, 89-91
income segregation/stratification, 7-8, 151, 152, 153-159
inner-ring, 3, 4, 41, 76, 162-163, 170, 192
international perspectives, 29, 118, 151, 153, 162-163, 165, 168, 170, 171
low-income housing, 81-82, 84-85, 89-91, 107, 110, 130
attitudes toward, 29-30, 90-91, 158, 236, 238-239, 242
sprawl and, 151-152, 153, 154-158, 171-172, 176
minorities, 3, 25, 26, 28, 130
poverty, 3, 4, 97-98
property rights, 84-85, 152, 165, 168, 178-182
research recommendations, 118
spatial mismatch hypothesis, 5-6, 7-8, 32, 51-52, 57, 61, 67, 216-217, 220-230 (passim)
spatial opportunity structures, 17, 117
sprawl, 13, 33, 84, 109, 151-191
white flight, 237-238
zoning, 151-191
exclusionary, 8, 11, 12, 16, 21, 29, 30-32, 38, 61, 79-80, 81-82, 89-90, 104, 130, 131, 152, 153-159, 168-169, 175-182, 201, 236-237
inclusionary, 10, 38, 78, 81, 82-84, 130, 176, 177
see also Central-city/suburban disparities;
Commuters and commuting;
Tax/service disparities
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T
Taxation, 9
classification of urban problems, 14
central cities' relations with suburbs, 34, 35, 37
commuter taxes, 7, 98, 101, 123, 133, 267, 281-282
enterprise zones, 86-87, 123, 230-233, 234
gasoline taxes, 84, 299
historical perspectives, 101, 256-267, 282, 288
home owners, advantages, 171-172
income taxes, 34, 77, 101, 133, 172, 173, 255, 256, 260-261, 266, 267, 282, 283-284, 295
local government fragmentation/consolidation, 107-108, 203
local revenues by state and/or type, 256-267
property taxes, 30, 75, 97, 99, 100-101, 102, 169, 173-175, 307
public choice factors, 105
racial/economic segregation, 7
residential segregation, 7, 57
sales taxes, 74, 75, 76, 255, 256, 258, 260, 262-267, 307
speculation and, 173
state policies, general, 8, 175, 255
transportation, 84, 299, 307, 309, 313;
see also "commuter taxes" supra
zoning and, 30, 169;
see also "enterprise zones" supra
Tax/service disparities, 7, 8, 10, 29, 30, 32, 72-77, 95-104, 107, 116, 119-120, 122-123, 132-133, 203, 253-295
children, 75;
see also "education" infra
commuter taxes, 7, 98, 101, 123, 133, 267, 281-282
counties, 255, 262-266, 270, 272, 273, 280-281
crime, 75, 267, 268, 273-274, 280, 286
education, 7, 75, 122, 174-175, 255, 267, 278, 279, 280
equalization aid, 101-103, 123, 125, 133, 268, 278-280, 284;
see also Place-based initiatives
export taxes, 98, 100-101, 266, 283-284;
see also "commuter taxes" supra
federal government, 98, 253, 254, 268, 278, 281, 287-288
fragmentation/consolidation of metropolitan government, 8, 75, 116, 203, 268, 269-272
international perspectives, 287
metropolitan governance, general, 96-98, 99, 107, 254, 277, 278
minority groups, general, 97
political factors, 95-98, 100, 105, 268-269, 270, 271, 272-273, 276-278, 280, 284-285, 288
population size/density, 75, 254, 269, 277
poverty, 73, 76, 97-98, 254, 278, 281
public choice factors, 105-106
regional factors, general, 98, 99, 133, 276
spatial distribution, general, 268-269
state policy, 76, 98, 99, 101, 102-103, 104, 260-267, 277, 278, 280-285;
see also "equalization aid" supra
subsidies and aid, 72, 74, 267;
see also Equalization aid
suburbs, 74-75, 76, 270-271, 281-282, 285;
see also Commuters and commuting
tax-base sharing. 99-100, 268, 274-276, 284;
see also "equalization aid" supra
transportation, 254, 286;
see also Commuters and commuting
welfare, 76-77, 254
Telecommunications, 33
Interact, 180
Tennessee, 264-265
Texas, 264-265, 268
Transportation, 19, 230
automobiles, 6, 84, 160-161, 170, 287, 296, 299, 300, 304, 309, 314, 316-318, 319
central-city/suburban disparities, general, 305-306, 307
equity, general, 307-309
federal government, 298-303, 304, 306-307
funding, 298-303, 304, 306-308
gasoline taxes, 84, 299
historical perspectives, 296-304, 309
housing and, 309
Intermodal Surface Transportation Efficiency Act, 111, 274, 288, 304
land use policy, general, 309-310
local government fragmentation/consolidation, 111, 274, 296-310, 318-321
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mass transit, 51, 111, 170, 235, 286, 288, 300-306, 307-309
political factors, 300, 305-306, 307-309
poverty, 305-306, 307-308;
see also Mobility (workers)
regional, 111, 274, 277, 296-310, 318-321
rural areas, 298, 300
special-purpose districts, 274
state policy, 298, 299-300, 306
study at hand, methodology, vii, 13
suburbanization, causes of, 28, 159, 160-161
taxation, 84, 299, 307, 309, 313;
see also Commuters and commuting (commuter tax)
tax/service disparities, 254, 286
worker mobility, 10, 86, 88-89, 94, 95, 123, 131, 132, 227, 235-236
poverty and employment mobility, 10, 86, 88-89, 94, 95, 123, 131, 132, 227, 235-236
spatial mismatch hypothesis, 5-6, 32, 51-52, 56, 57, 61, 67, 89, 216-217, 220-230 (passim)
see also Commuters and commuting
Two-tier governments, 21, 95, 96, 97, 106, 268, 272-274, 287
U
Unemployment, see Employment and unemployment
Unequal opportunity, general, 16-17, 19, 20, 27, 40-78, 69-71, 85-95, 116, 121, 127
exclusionary zoning, 8, 11, 12, 16, 21, 29, 30-32, 38, 61, 79-80, 81-82, 89-90, 104, 130, 131, 201, 236-237
sprawl and, 152, 153-159, 168-169, 175-182
globalization, 18
individualism and equal opportunity, 18
local government fragmentation/consolidation, 8, 65-66
metropolitan governance, 114
national policy, 18
policy options, 79-115
public services, 10, 60-61
research recommendations, 9, 10, 117, 127, 129-131
spatial opportunity structures, 21, 79-115, 116, 117, 127, 213-252
state policy, 18, 129-130
unemployment, underemployment and low-income, 9, 18, 19
see also Central-city/suburban disparities;
Neighborhood effects;
Poverty;
Racial discrimination;
Residential segregation;
Spatial
distribution factors;
Tax/service disparities
Urban Change and Poverty, vii
Urban Mass Transportation Act, 301
Urbanization economies, 32
Utah, 264-265
V
Vermont, 80, 177
Virginia, 115, 162, 260, 266-267
Voting Rights Act, 108
Vouchers
educational, 92-94, 104, 132
housing, 10, 58, 90, 123, 131, 227, 237
W
Washington, D.C., 17, 82, 97-98, 162, 198, 282
Washington State, 266-267, 311
Welfare, 237
neighborhood effects, 54
political factors, 18, 181-182
tax/service disparities, 76-77, 254
see also Low-income housing
Wisconsin, 266-267
Milwaukee, Wisconsin, 74-75, 98
Working Class Suburb, 195
World Wide Web, see Internet
Wyoming, 266-267
Z
Zoning, 11, 107
community development corporations, 88
court cases, 83, 154-155, 158, 165, 168, 174-175, 180-181
discriminatory, 11-12, 29;
see also "exclusionary" infra
enterprise zones, 86-87, 123, 230-233, 234
exclusionary, 8, 11, 12, 16, 21, 29, 30-32,
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38, 61, 79-80, 81-82, 89-90, 104, 130, 131, 201, 236-237
sprawl and, 152, 153-159, 168-169, 175-182
historical perspectives, 153, 154
local government fragmentation/consolidation, 80, 81, 176-177, 180
inclusionary, 10, 38, 78, 81, 82-84, 130, 176, 177
political factors, 158, 163, 164-165, 176-178, 181, 236
property rights, 84-85, 152, 165, 168, 178-182
rural areas, 163-164, 169, 170-171, 172, 175-176
sprawl and, 151-191
subsidies and aid, 30, 82-84, 85, 171-172, 179;
see also "enterprisezones" supra
1 Metropolitan statistical areas (MSAs) are defined as follows: "Each MSA must include at least: (a) one city with 50,000 or more inhabitants, or (b) a Census Bureau-defined urbanized area (of at least 50,000 inhabitants) and a total population of at least 100,000 (75,000 in New England). Under the standards the county (or counties) that contains the largest city becomes the central county
(counties), along with any adjacent counties that have at least 50 percent of their population in the urbanized area surrounding the largest city. Additional 'outlying counties' are included in the MSA if they meet specified requirements of commuting to the central counties and other selected requirements of metropolitan character (such as population density and percent urban) (U.S. Bureau of the Cencus, 1996a:937). An urbanized area is "an area consisting of a central place(s) and adjacent urban fringe that together have a minimum residential population of at least 50,000 people and generally an overall population density of at least 1,000 people per square mile of land area" (U.S. Bureau of the Census, 1994:G-54). Unlike metropolitan areas, which must contain entire counties, urbanized areas are defined with reference to density.
2 Holding 1960 metropolitan-area boundaries constant, the proportion of the U.S. population living in these areas actually fell slightly, from 63 percent in 1960 to 62 percent in 1990.
3 Metropolitan areas are divided into primary metropolitan statistical areas (PMSAs) and consolidated metropolitan statistical areas (CMSAs). CMSAs consist of two or more contiguous and closely related PMSAs. As of June 1995, there were 271 metropolitan areas, consisting of 253 PMSAs and 18 CMSAs. The 18 CMSAs contained within them a total of 73 PMSAs. The total number of PMSAs was therefore 326.
4 Increases in the proportion of the population living in high-poverty areas may result from an increasing number of census tracts being classified as high-poverty areas as nonpoor households move out, from an increasing incidence of poverty, or from an increasing propensity of the poor to move into such areas.
1 Data from the Current Population Survey presented in Ihlanfeldt (this volume) suggest that the city-suburban disparity in family income continued to rise between 1989 and 1995.
2 The index is calculated from three ratios of central-city to suburban outcomes: per capita income, employment rate for men between 16 and 64, and the proportion of persons 25 or older who have at least a high school diploma. In order that each of the three measures is weighted equally, they are each standardized to a scale of 0-100, and the standardized ratios are then averaged to create an overall index of disparity. The higher the number, the better off the central city relative to its suburban counterparts. In order to give equal weight to each of the three ratios, they were each standardized to a scale of 0-100 before being averaged. The minimum value was assigned as zero and the maximum value 100. The ratios in between are assigned values between 0 and 100 according to the following formula: y = (x-xmin)/(xmax - xmin).
3 The figures here compare all whites and all blacks, since separate non-Hispanic white estimates were not available for 1980.
4 A "bad neighborhood" is defined as a neighborhood in which more than 40 percent of teenagers are high school dropouts, more than 40 percent of families are headed by single females, and less than 10 percent of employed persons hold professional or managerial jobs.
5 Hanushek (1996:59) does not argue that schools or school inputs do not matter. He argues, instead, that, although commonly measured input characteristics, such as class size and teacher education and experience, do not make a difference, there are other unmeasured characteristics of schools and teachers that do.
6 In particular, they were able to utilize a "value added" approach to track changes in educational performance over time for individual students, to isolate instructional spending from total educational spending, and to utilize measures of actual class size rather than school or district averages of teacher-pupil ratios.
7 In metropolitan areas in which there is more than one central city, they included the largest central city, but included smaller central cities only if their population was over 100,000.
8 Blair et al. (1996) examine the effect of elasticity on both city and metropolitan-area growth in population, employment, per capita income, and poverty in 117 metropolitan areas between 1980 and 1990. They found that elasticity is related significantly to growth in all of the variables for central cities (positively for the first three and negatively for poverty). It is significantly related to growth in population and employment, but not for per capita income or poverty for metropolitan areas. However, the only variable controlled for in the analysis was the state change (net of the
metropolitan area) in each of the dependent variables examined. These findings do not address the question of the impact of elasticity on central-city/suburban disparities.
9 The finding that more fragmented systems of government lead to lower per capita spending does not necessarily mean they are more efficient, since it is virtually impossible in these studies to separate out expenditure differences that reflect efficiency from those that reflect differences in the quantity or quality of services provided. Indeed, we would expect the demand for services to vary with different sizes of government over which demand is aggregated and with different spillover effects associated with different sizes of government.
10 The most commonly used operational measures is the number of local governments in a metropolitan area or number of local governments per capita. But it is not clear that this is a valid measure of the concept. Should all local governments be counted in fragmentation research? To the extent the research is concerned with coordination difficulties, then perhaps the most commonly used measures are reasonable: the greater the number of local governments (or local governments per capita), the greater the difficulties in arranging coordinated activity across the area. But, if the concern is the "sorting" consequences of fragmentation, as discussed above, perhaps only those local governments that have an important effect on the sorting process, i.e., those with local land use powers (primarily general-purpose units of local government rather than special districts) should be counted. However, it might well be argued that local school districts, although a special district and without land use powers, play such a significant role in the sorting process that they should be included as well.
11 Lewis' measure of fragmentation differs dramatically from previously utilized measures. He constructs a fragmentation index that is equal to TE(1-SSP), in which TE is total expenditures per capita in the metropolitan area and SSP is the sum of the squared percentages of total expenditures accounted for by each local government. The greater the number of governments, each with a lower share of total government expenditure, the greater will be the fragmentation index.
12 Bald (1994:297) reports on tax/service differences in 35 metropolitan areas between central cities and suburbs in the aggregate. On average in these 35 areas, central cities spent $1.51 per capita for every $1.00 per capita spent by the area's suburbs. (The difference was due to the much higher level of spending by cities on noneducational expenditures; suburban governments spent more per capita on education than did cities.) However, taxes as a percentage of family income (tax burden) were an average of 44 percent higher in the central cities, and Bahl notes (1994:297) that the tax burden disparity is increasing over time.
13 Oakland (1994:7-8) argues, however, that fiscal disparities are not necessarily undesirable and that efforts to reduce or eliminate them could have perverse efficiency consequences.
14 Pagano observes (this volume) that, on the basis of the Ladd and Yinger measures, the cities with the greatest actual revenue-raising capacity are in Ohio, which permits the most progressive earnings taxes on commuters; Cleveland's revenue-raising capacity was 41 percent higher than the average U.S. city and Dayton's 59 percent higher, both substantially above their standardized revenue-raising capacity.
1 We do not consider income transfer programs, since these do not address the causes of unequal opportunities and disparities.
2 Fiscal capacity is defined as the per capita equalized market value of all real property in a jurisdiction.
3 Despite these findings, evidence from citizen satisfaction surveys has frequently indicated strong black support for the results of metropolitan reform (see, for example, Stowers, 1996, in reference to Dade County and Lyons et al., 1992, who find greater satisfaction with services among blacks living in a neighborhood in the consolidated government of Lexington than among blacks living in a socially and economically similar black suburb in the fragmented Louisville metropolitan area).
4 Only fragmentary evidence exists on whether such redistribution does indeed occur. One study (Hawkins and Hendrick, 1994) found fiscal redistribution between suburban areas and central cities through the tax and expenditure behavior of the overlapping county government in the Milwaukee area; another (Banovetz, 1965) found mixed evidence in the Twin Cities area.
1 In fact, despite their overrepresentation in central cities, the share of blacks who live in suburban areas has been increasing. In 1960, for instance, just 20 percent of blacks lived in suburban communities, compared with 26 percent in 1990.
2 Data from the Current Population Survey presented in Ihlanfeldt (this volume) suggest that the city-suburban disparity in family income continued to rise between 1989 and 1995.
3 Calculated from Massey and Denton (1993:Table 8.1).
4 The minimum value is assigned 0, the maximum value is assigned 1, and the values in between are standardized according to the following formula: Z = (X-Xmin)/(Xmax-Xmin).
5 Hill and Wolman (1997) examine the impact of tight labor market conditions on central-city/suburban differences and find, contrary to conventional wisdom, that economic growth may actually exacerbate disparities.
6 Several researchers have found the age of the metropolitan area to be correlated with greater central-city/suburban inequality (see Bollens, 1986; Hill, 1974; Logan and Schneider, 1982; Schnore, 1965).
7 The official Census Bureau definition of central city is used here to construct a measure of elasticity. As Hill and Wolman (1997) point out, the Census Bureau uses a very broad definition of central city, which encompasses more than merely the largest municipality in the metropolitan area and may include as well cities that might be better described as ''edge cities.'' Thus, using the Census definition of central city may not be ideal for constructing a measure of elasticity. Nonetheless, it is consistent with the other data used here, which also rely on the official Census definition for central city. The results remain the same when using a more restrictive definition of central city (at least for the 152 metropolitan statistical areas for which the more restrictive measure of elasticity is available).
8 Note that this measure of elasticity differs from the more complicated index used by Rusk, but it captures the essence of his concept (see Hill and Wolman, 1997).
9 Significantly, the quartiles are defined so that each includes an equal number of metropolitan areas, rather than residents. It turns out that the metropolitan areas in which central cities fare worse
are far more populous. Thus, for example, the quartile with the most relatively disadvantaged cities houses a full 41 percent of the total metropolitan population.
10 The natural logarithm is used to smooth the distribution of metropolitan population.
11 Specifically, the regression includes a variable that is equal to the difference between the elasticity and .45 when elasticity is above .45 and takes on the value of 0 when the elasticity is below .45. For more information, Greene includes an excellent discussion of spline regressions (see Greene, 1993:234-238.)
12 Hill and Wolman (1997) find no connection between elasticity and the disparity in per capita income between central cities and suburbs. Their analysis differs in three ways, however. First, they include city-suburban human capital differences as an independent variable, which means that their regression model attempts to explain city-suburban differences in returns to education, rather than overall disparities. Second, most of their estimated models also include the level of disparity existing in 1980 as an independent variable, which means that they test whether elasticity has any effect on the change in disparity between 1980 and 1990. Finally, they do not include a spline variable. (When the spline variable is not included here, the elasticity remains significant, but its magnitude is far smaller.)
1 Evidence on segregation in metropolitan housing markets, on one hand, indicates that racial segregation has declined over time but remains at a high level (Farley and Frey, 1994). Evidence on income segregation indicates that it has been increasing but is not nearly as high as racial segregation (Abramson et al., 1995; Massey and Eggers, 1993; Jargowsky, 1996). The increase in income segregation has occurred in the white, black, and Hispanic groups, but the largest increases were for minorities during the 1980s (Jargowsky, 1996).
2 Wilson (1987:8) defines the underclass as the heterogenous grouping of families and individuals who lack training and skills and either experience long-term unemployment or are not part of the labor force, individuals who engage in street criminal activity and other aberrant behavior, and families who experience long-term spells of poverty and/or welfare dependency.
3 In fact, if low-skilled whites can easily shift their labor supply to the suburbs in response to job decentralization, then spatial mismatch is unlikely to be much of a problem, since this may represent enough supply adjustment to eliminate the disequilibrium.
4 The dependence of long-run effects on short-run events has been labeled "hysteresis," a term
5 This fact is explained by the standard urban model if the income elasticity of housing demand exceeds the income elasticity of commuting cost. Alternatively stated, higher-income people may have longer commutes because they wish to consume more units of housing at a lower price. This explanation assumes that housing prices on average decline as distances to employment centers increase, which considerable empirical evidence suggests is the case (see, for example, Jackson, 1979). Other models suggest that higher-income workers travel farther to get to work because they are willing to trade commuting costs for either environmental amenities or better government services.
6 Kasarda and Ting find that their measure of job access—commute time of city residents for each racial group—has no effect on their outcome variables for black males, which unlike the rest of their results is inconsistent with the spatial mismatch hypothesis. However, all of their results may be underestimates of true effects, due to the crudeness of their access measure (which they acknowledge) and their failure to address the simultaneity between their endogenous variables and residential location.
7 To quote Ellwood's often repeated aphorism, "The problem isn't space. It's race."
8 In comparison to adults, youth are less likely to have access to an automobile for commuting to work, they may place a higher value on their commuting time due to their school responsibilities, and have less information on distant jobs because of a greater reliance on informal sources of job information.
9 The results of Holzer et al. (1994) are also suggestive of information limitations. They find that black and white central-city youth do not offset greater job decentralization with greater distances traveled, for either search or work.
10 It should be noted that both of the regression studies use questionable measures of job accessibility. Both use variants of neighborhood mean commute times based on the reasonable assumption that a youth has better job access if he or she lives in a neighborhood where residents have to make only a short commute to get to work. However, neither study standardizes travel times for transportation mode and both use travel times to all jobs in computing means. Since there is considerable variation in travel times between public and private carriers and the spatial distribution of youth jobs differs from that of all jobs, the findings of Cutler and Glaeser and O'Regan and Quigley may understate the true effects of job access by a considerable amount.
11 The Gautreaux program does not admit families with more than four children, large debts, or unacceptable housekeeping.
12 More recent research by Bartik (1994) provides further support for this conclusion. He finds that metropolitan-area employment growth increases the income of households in the poorest income quintile by five times as much as the increase experienced by households in the richest quintile.
13 A fourth category of policies includes educational reforms, such as site-based management, charter schools, vouchers, and school choice. These reforms are not discussed here, since adequately covering them would extend this paper to unmanageable length. For a recent review of current issues in public urban education, see Picus, Lawrence O. 1996. Current Issues in Public Urban Education. Housing Policy Debate 7(4):715-730.
14 In fact, the dispersal (category three) versus development (category one) debate has been simmering and at times raging for over 25 years. Early participants in this debate include Kain and Persky (1969), Downs (1968), Edel (1972), and Harrison (1974).
15 Apparently, the problem with tax credits for targeted jobs is that they have a stigmatizing effect on members of the targeted group in the eyes of employers (Burtless, 1985; Bishop and Kang, 1991).
16 Other place-based initiatives that could be listed are business retention and expansion programs focused on areas in central cities where jobs are most needed. Although a number of cities have such programs, no evidence could be located on their effectiveness. Nevertheless, their low cost in comparison to tax incentives and other types of programs designed to attract new firms makes these programs an attractive option. Downs (1994) recommends that city governments survey employers to see what problems they have and what can be done to solve them.
17 This approach is complicated by the heterogeneity of community development corporation employment programs. They may fare more or less well relative to urban enterprise zones depending on the specifics of their programs.
18 There was a series of reverse-commuting demonstration projects funded by the federal government in the 1960s. These projects produced at best only meager benefits. But these results may not be applicable today, since there have been major changes in the spatial distributions of jobs and people in metropolitan areas over the past 30 years.
19 Between 1915 and 1920 jitneys, which were private vehicles (mostly Ford Model Ts), profitably operated in many metropolitan areas throughout the United States (Eckert and Hilton, 1972). They had flexible destinations and carried multiple passengers, generally going to different but nearby locations. Their life in America was cut short by regulations passed by municipalities that made their costs of doing business prohibitive. Jitneys were put down in order to preserve streetcars, which were favored because, unlike jitneys, they were an important source of tax revenue for local governments. It was also believed that competition between streetcars and jitneys would make it impossible for streetcars to subsidize their longer routes from revenues generated by their shorter routes, which were rapidly losing patronage in favor of the faster, more convenient service provided by the jitneys.
20 Even with white flight, residential mobility policies will improve the job accessibility of minorities. Although retailing and personal services will follow whites to more distant suburbs, the immobility of capital will keep manufacturing jobs in those areas that undergo racial transition.
21 Other provisions include race-conscious counseling; housing centers that disseminate information on neighborhood change, provide counseling, and prevent the spread of rumors; and bonuses for metro-based organizations that work with several integrated communities.
22 Some additional evidence that whites' aversion to black neighbors in not based on pure racial prejudice is provided by Harris (1997). He estimates hedonic housing price equations and finds that the racial composition of the neighborhood is not a statistical significant explanatory variable, after controlling for nonracial characteristics of the neighborhood (e.g., percentage poor and percent affluent).
23 There is the possibility that Ellen's results reflect, at least in part, differences in prejudice between owners and renters and families with and without children. To the extent that this is true, policies to arrest structural decline will be less effective in achieving racially stable neighborhoods.
24 Cutler and Glaeser (1995) have also suggested that political fragmentation may impose an added cost on blacks trying to change neighborhoods because a different neighborhood may have different public goods and perhaps even public goods designed to discourage racial integration. Their examples of the latter are racist police officers and schooling designed particularly for white suburban residents.
25 Jargowsky studies the factors that determine what percentage of a metropolitan area's blacks will live in high-poverty census tracts. The latter are defined as tracts that have a poverty rate of 40 percent or higher and are commonly believed to contain the worst neighborhood effects. His regression model includes metropolitan-area mean household income, mean black income relative to overall mean income, measures of income inequality, and dissimilarity indexes to measure economic and racial segregation. The latter variable is found to have a strong and highly statistically significant effect on the percentage of blacks living in concentrated poverty.
26 For example, the Multi-City Study of Urban Inequality data identify respondents' home census tracts. Under special arrangements, tract identifiers can also be appended to the individual
27 The success of this program caused Congress in 1992 to fund a Gautreaux-type program, called Moving to Opportunity, which was initiated in five cities in 1994. The program encountered severe opposition in the suburbs of Baltimore, one of the five cities selected. This was all the fodder needed by opponents in Congress to kill the program after its first year.
28 Evidence suggests that white flight from inner to outer suburban areas during the 1980s was as virulent as the white flight from central cities to inner suburban areas during the 1960s and 1970s (Ihlanfeldt, 1994).
29 See Farley and Frey (1992), who report the 1980 and 1990 index of dissimilarity for each of 318 U.S. metropolitan areas.
1 Gyourko and Summers (1997) note that large cities (over 300,000 population) spend 30 percent of their own-source revenues on health, hospitals, and public welfare, compared with only 9.1 percent for smaller cities (under 75,000 population) Pack (1995) found that on average cities spend 3.5 percent of their own-some revenues on unreimbursed ''poverty'' programs (excluding hospitals), but that Philadelphia spent 7.6 percent in 1995 (see also Salins, 1993).
2 For an opposing view, see Hill and Wolman (1995).
3 Much research has centered on the efficient production of local government services, which certainly needs to be factored into any discussion about tax burden. Productivity has received popular attention with the publication of Osborne and Gaebler's Reinventing Government (1992).
4 It should be noted that some special districts, such as sewer and water authorities, mass transit districts, and gas and electric utilities, are usually denied access to any general tax, but rather are restricted to a user charge for revenue generation.
5 Ladd and Yinger's measures are presented because they are more accurate measures than others. The representative tax structure, developed by the U.S. Advisory Commission on Intergovernmental Relations, is premised on measuring fiscal capacity as equal tax rates, ignoring tax burden (defined as taxes as a percentage of wealth). For a review of other budgetary and economic measures of fiscal health, see Bahl et al. (1992a:420-432 and 1992b:49-66).
6 This variation in service responsibilities was an important factor in Fuchs's finding that New York City's fiscal condition suffered more than Chicago's (see Fuchs, 1992).
7 Addressing issues of intrametropolitan disparities, according to some analysts, cannot and should not be left to the local governments in question. Nongovernmental organizations, such as the Atlanta Project, the Providence Plan, and many others, may be more successful in addressing
intrametropolitan inequities than are either formal regional governments or ad hoc interlocal (voluntary) agreements.
The Atlanta Project (TAP) was begun by former President Jimmy Carter and funded primarily from industry and foundations for the purpose of "accomplishing social goals associated with poverty, including teen pregnancy, childhood immunization, school dropout rates, and crime and violence" (Wallis, 1994:304). It provides services to 20 neighborhood clusters in 3 counties in the Atlanta metropolitan region. Each neighborhood cluster has a corporate sponsor and designs programs to address poverty-related problems (e.g., teen pregnancy, violence, school dropout). Rich argues that the solution to municipal social problems, such as Atlanta's, ought to shift from being a responsibility solely of city hall to one that includes the nonprofit sector (see Rich, 1993; Giles, 1993). Nonprofits, unlike municipalities, are usually not constrained by the political boundaries of the municipal corporations. Consequently, they can reach out beyond the central city to the broader metropolis. Moreover, he argues that, in an environment in which the likelihood of substantial federal or state support is remote, partnerships between local governments and nonprofits not only fill the breach, but also, because they spring from local concerns, are more likely to be tailored to local problems. Programs such as the Atlanta Project have spread and have been supported by a number of large foundations, such as the Annie P. Casey Foundation, the Rockefeller Foundation, the Pew Charitable Trusts, among others, and have been implemented in cities and metropolitan regions across the country.
8 Under the state's Municipal Annexation Act, cities over 100,000 population are allowed territorial dominance for five miles beyond the corporate limits. In this extraterritorial jurisdictions, cities "can impose subdivision regulations, approve the creation of MUDs [municipal utility districts], designate tax exempt 'industrial districts,' and prohibit new incorporations" (Thomas, 1993:289).
9 Correspondence with Dan Durning, Carl Vinson Institute of Government, University of Georgia, January 31, 1997 (updated to include two referenda defeated in November 1996). In testimony before the Senate Committee on Intergovernmental Relations, El Paso, Texas, April 1, 1996, Terrell Blodgett, Professor of Urban Management at the University of Texas School of Public Affairs, counted four likely elections for city-county consolidation and eight studies under way in 1996.
10 Testimony of Terrell Blodgett, p. 6 (see note 9).
11 Yet on the basis of their own data of residents' subjective ratings of services, the only substantial discrepancy in ratings is in the education function, which is only one of two services rated (the other was police). One might just as easily speculate that consolidation has reduced the disparity in perception between residents of the pre-Unigov city and the other residents over how well schools were performing because the data are not longitudinal ratings of satisfaction.
12 Bell (1994) argues the purpose is also to rationalize land use planning, an issue not discussed here.
13 In a similar vein, Fischel contends that the Serrano decision in California may have actually caused the tax revolt (Proposition 13) by forcing wealthy school districts to raise their own property tax rates even while state equalization grants in response to Serrano were redistributing more aid to poorer school districts (see Fischel, 1989).
14 Pennsylvania also allows an income tax, but nonresidents cannot be taxed at more than 1 percent regardless of the city's income tax (excluding Philadelphia).
15 This is an admittedly very tenuous conclusion because no comprehensive study of the effect of Ohio's municipal income tax on intrametropolitan disparities has been conducted.
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