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Governance and Opportunity in Metropolitan America (1999)

Chapter: 3 Disparities in Outcomes

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Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
×

3
Disparities in Outcomes

This chapter examines the state of existing knowledge on the disparities in outcomes experienced by individuals and jurisdictions in metropolitan areas. For individuals and groups, these disparities may be grouped into three categories: income disparities (median family income levels, per capita income levels, and poverty rates); labor market disparities (employment and unemployment rates for working-age men); and educational disparities (high school and college completion rates). These simple measures do not, of course, fully capture the differences among groups in metropolitan areas. Moreover, they reflect outcomes that result from many factors, not simply from inequalities in the metropolitan opportunity structure.

We then go on to consider the extent to which these disparities are caused by differences in the metropolitan opportunity structure; we also consider the spatial components of causes less directly related to metropolitan phenomena. To give an indication of the costs to individuals and groups of these disparities, the committee reports the work of researcher Harry Holzer who calculated at our request the costs of unequal opportunity borne by those most directly affected, as well as by the entire metropolitan area.

Finally, we shift to consider disparities in fiscal capacities among local governments, in terms of taxes and services.

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
×

Disparities Among Individuals

Central-City and Suburban Residents

Analyses of intrametropolitan differences in economic and social conditions are nearly always presented in terms of central-city and suburban differences, even though there is clearly substantial variation across individual suburbs (Danielson and Wolpert, 1992). In many metropolitan areas there are inner-ring suburbs and industrial suburbs whose residents share the same environment and consequent problems as residents of the central city. However, because of the way data are presented, virtually all of the research examines only central-city and suburban differences; for that reason, most of the data and the discussion presented in this chapter focus on the central-city/suburban distinction.

In 1990, central-city residents had incomes that were considerably lower than those of suburban residents (Table 3-1). The median household income of urban residents was only 74 percent of that of their suburban counterparts, their per capita income was 84 percent of suburban per capita income, and their poverty rate was over twice as high. Disparities in employment and education were somewhat smaller, but central-city residents appear to be more deprived in these realms as well. In particular, compared with suburban communities, the unemployment rate of men of prime working age was 1.7 times higher in central cities, and the rate of young men (ages 25-34) who completed high school in central cities was only 94 percent that of the suburbs.

Perhaps more significant than the magnitude of these disparities are their trends over time. Table 3-2 shows, for selected measures, the ratios of suburban to central-city outcomes for the decades from 1960 through 1990. With the

TABLE 3-1

Comparison of Selected Outcomes for Central-City and Suburban Residents, 1990

Outcome

Central City

Non-Central City

Ratio of Central-City to Suburban Outcome

Median household income

$26,727

$36,314

.74

Per capita income

$13,839

$16,527

.84

Poverty rate, families

14.1%

6.0%

2.35

Employed men ages 25-54a

83.3%

90.0%

.93

Unemployment rate, men ages 25-54

6.8%

4.0%

1.7

High school graduates, men ages 25-34

80.7%

85.8%

.94

a Members of the armed forces are counted as employed.

Source: U.S. Bureau of the Census (1990a).

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
×

TABLE 3-2

Ratios of Selected Outcomes for Central-City and Suburban Residents, 1960-1990

 

Ratio of Central-City to Suburban Outcome

Outcome

1960

1970

1980

1990

Median family income

.89

.85

.81

.77

Per capita income

NA

.92

.88

.84

Family poverty rate

1.52

1.75

2.08

2.35

Percent employed, men age 16 and oldera

0.96

0.93

0.92

.91

Unemployment rate, men age 16 and oldera

1.37

1.33

1.34

1.59

Percent high school graduates, age 25 and older

0.85

0.86

0.9

.94

Percent college graduates, age 25 and older

0.82

0.84

0.94

.96

a For 1960, the employment and unemployment rates correspond to men at least 14 years of age.

Source: U.S. Bureau of the Census (1960, 1970, 1980, 1990a).

exception of education, every measure in the table suggests that the relative status of central-city residents has consistently declined over the last three decades. Relative to their suburban counterparts, central-city residents now have lower incomes, higher poverty rates, and lower employment rates than they did 10, 20, and 30 years ago.1

The income differences are particularly stark. In 1960, the income of central-city families was 89 percent of that of suburban families. By 1990, this ratio had fallen to 77 percent. Per capita income follows a similar pattern, with ratios falling from .92 in 1970 to .84 in 1990. Poverty is becoming increasingly concentrated in central-city areas. In 1960, poverty was 1.5 times as frequent for families living in central cities; by 1990, the ratio had risen to 2.4. Finally, in 1960 the unemployment rate in central cities was 1.5 percentage points higher than the unemployment rate in the suburbs; by 1990 it was 3 percentage points higher.

These central-city/suburban disparities have grown much more rapidly for blacks than they have for the population as a whole (Ihlanfeldt, this volume). The deepening of central-city disparities over time reflects both the selective migration of better-off people to the suburbs and the declining fortunes of lower-skilled and low-income groups remaining in the city. Their declines in fortune result from changes in the national economy, referred to earlier, that reduce the relative earning power of low-skilled workers.

As noted, education is a marked exception to the general trend of continued central-city decline. Because it is easier to increase the proportion of high school

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
×

and college graduates in a population that has fewer of them to start with, the relative fortunes of central-city residents improved as a result of overall societal progress. Between 1960 and 1990, for example, although the high school graduation rate rose by 66 percent in non-central-city areas, it rose by 79 percent in central cities.

These comparisons lump together all suburbs as a single entity, but suburbia is hardly monolithic (Orfield, 1997). Data on neighborhoods within suburban areas provide some sense of their diversity. Although, as noted above, the median household income in suburban America is significantly larger than that in central cities ($36,314 compared with $26,727), in approximately one-fifth of suburban neighborhoods, the median household income is actually less than the central-city median. (And without the commercial tax base of a central business district, these suburbs may be even worse off than their central cities.)

The story is similar with the poverty rate. Nationwide, the poverty rate is 8 percent in the suburbs and 18 percent in central cities. But approximately 10 percent of suburban census tracts had poverty rates of at least 18 percent.

How do these city-suburban disparities vary by region or by size of the metropolitan area? Table 3-3 indicates that the disparities appear to be greater in the Northeast and the Midwest and lower in the South and the West. On average, the per capita income of central-city residents in the South and the West nearly matched that of their suburban counterparts. In the average metropolitan area in the Midwest and the Northeast, by contrast, the per capita income of central-city residents was just 76 and 65 percent, respectively, of that of suburban residents.

A similar geographic pattern applies to the relative poverty rates. In the average metropolitan area in the Midwest, the central-city poverty rate was more than 4 times that of the suburban poverty rate. In the West, central-city poverty was only 1.8 times that of suburban poverty.

In larger metropolitan areas, central-city residents fare worse relative to their suburban counterparts than they do in smaller ones. Table 3-4 shows that in metropolitan areas with over 1 million residents, per capita income in central cities is an average of 80 percent of per capita income in suburban locations. In contrast, in metropolitan areas with under 250,000 residents, the per capita income in central-city and suburban areas is almost identical. Similarly, in metro-

TABLE 3-3

Mean Central-City/Suburban Disparities in 1990 by Region

Region

Per Capita Income

Poverty Rate

Northeast

.65

3.75

South

.96

2.31

Midwest

.76

4.24

West

.94

1.77

 

Source: Tabulations from U.S. Bureau of Census (1996a).

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
×

TABLE 3-4

Mean Central-City/Suburban Disparities in 1990 by Population Size of Metropolitan Statistical Area

 

Mean Ratio of Central City to Suburban Outcome in Set of Metropolitan Statistical Areas

MSA-Size Class

Per Capita Income

Poverty Rate

Employment Rate, Men 16-64

1,000,000 +

.8

3.3

.9

250,000-999,999

.91

2.6

.92

100,000-249,999

.97

2.2

.94

0-99,999

.97

2.2

.94

 

Source: Tabulations from U.S. Bureau of Census (1996a).

politan areas with over 1 million residents, the central-city poverty rate is more than 3 times larger on average than the suburban rate. In metropolitan areas with under 250,000 residents, the ratio is just over 2. In contrast to income and poverty measures, the difference in employment rates between central-city and non-central-city residents varies only modestly with population size.

Ellen (this volume) has constructed an index of disparity and ranked all metropolitan areas by their degree of city-suburban disparity.2 Significantly, she found that not all central cities are worse off than their surrounding suburbs. In 1990, central cities were actually as prosperous or more so than their surrounding suburban communities in 101 (31 percent) of metropolitan areas (see also Hill and Wolman, 1997a).

Table 3-5 presents the mean characteristics of selected variables for each of four quartiles of disadvantage. Once again, the regional pattern is pronounced.

TABLE 3-5

Regional Distribution of Central Cities, Ranked by Degree of Central-City Disadvantage (percentage)

 

Quartiles of Central-City Disadvantage

Region

Q1: Greatest Disadvantage

2nd Quartile

3rd Quartile

Q4: Least Disadvantage

Northeast

43.9

25.6

8.5

3.6

Midwest

31.7

36.6

22.0

10.8

South

20.7

22.0

45.1

60.2

West

3.7

15.9

24.4

25.3

Total

100

100

100

100

Mean Population

934,560

537,981

542,056

277,366

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
×

In the quartile with the most disadvantaged central cities, 44 percent are located in the Northeast, 32 percent in the Midwest, 21 percent in the South, and 4 percent in the West. In the quartile with the least disadvantaged central cities, by contrast, just 4 percent are in the Northeast, 11 percent are in the Midwest, 60 percent are in the South, and 25 percent are in the West. With respect to size, the metropolitan areas with greater disparities tend to have larger populations.

Variations across metropolitan areas in income disparities between cities and suburbs are substantial. Table 3-6 displays the ratios between central-city and suburban outcomes for the 15 largest metropolitan areas. The ratio of central-city to suburban per capita income ranges from a low of .56 in Detroit to a high of 1.0 in San Diego and Los Angeles.

The ratios of employment rates range from a low of .74 in Detroit to a high of .98 in San Diego, and high school completion ratios vary from .68 in Anaheim to a high of 1.03 in San Diego. Consistent with the results above, these disparities tend to be larger in the metropolitan areas located in the Northeast and the Midwest and smaller in those in the South and the West. Anaheim is the one

TABLE 3-6

Disparities Between Central-City and Suburban Residents in the 15 Largest Metropolitan Areas, 1990

 

 

Ratio of Central-City to Suburban Outcome

Metropolitan Statistical Area

Elasticitya

Per Capita Income

Employment Rate, Men 16-64

Percent High School Graduates, Men 25-34

Atlanta, GA

.139

.89

.86

.94

Riverside-San Bernadino, CA

.151

.96

.96

.97

Washington, DC

.155

.93

.90

.92

St. Louis, MO

.162

.69

.87

.91

Boston, MA

.2

.79

.91

.94

Anaheim-Santa Aria, CA

.232

.58

.95

.68

Detroit, MI

.235

.56

.74

.81

Minneapolis-St. Paul, MN

.26

.85

.92

.97

Philadelphia, PA

.326

.63

.83

.86

Dallas, TX

.394

.96

.92

.89

Los Angeles-Long Beach, CA

.442

.998

.96

.93

San Diego, CA

.445

1.00

.98

1.03

Chicago, IL

.459

.68

.85

.85

Houston, TX

.494

.89

.93

.87

New York, NY

.857

.68

.89

.90

a Elasticity is the proportion of the metropolitan area population that lives in the central-city named in the title of the Primary Metropolitan Statistical Area. (When two central cities are named in the title of the Primary Metropolitan Statistical Area, the population of both are counted as living in the primary central city.)

Source: U.S. Bureau of the Census (1990a).

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
×

notable exception, probably because of the high proportion of low-skilled, Hispanic immigrants living in its central city—nearly 50 percent of its central-city population is Hispanic.

There is also a substantial gap in educational performance between children who attend public schools in central cities and children who attend public schools elsewhere. Only 43 percent of fourth graders attending central-city schools scored at a basic or higher level on the 1994 National Assessment of Educational Progress (NAEP) reading test, compared with 63 percent for children attending public schools outside the central city. The difference was essentially the same (42 versus 66 percent) for eighth graders on the NAEP math test, and it was even greater (38 versus 65 percent) for eighth graders on the NAEP science test (Education Week, January 8, 1998).

Minorities and Whites

In the last 30 years, racial minorities have gained access to some opportunities previously closed to them. The black middle class has grown (O'Hare and Frey, 1992), racial segregation has declined (albeit modestly), and attitudes about racial prejudice appear to have softened (Farley et al., 1993; Firebaugh and Davis, 1988). Still, racial disparities remain pronounced, especially between African Americans and non-Hispanic whites (Table 3-7).

Income differences are particularly striking: The median income of black households living in a metropolitan area was just 61 percent that of the median

TABLE 3-7

Comparison of Selected Outcomes for Different Racial Groups, 1990

 

Population in Metropolitan Areas

 

 

 

Outcomes for Different Racial Groups

Ratios of Outcomes

Outcome

NHW

Black

Hispanic

Black to NHW

Hispanic to NHW

Median household Income

$34,676

$21,247

$25,009

.61

.72

Per capita income

$17,559

$9,414

$8,603

.54

.49

Poverty rate

7.7%

27.5%

24.5%

3.6

3.18

Percent employed, men 25-54

90.3%

72.5%

82.6%

.8

.91

Unemployment rate, men 25-54

3.9%

11.5%

14.1%

2.95

3.62

Percent high school graduates, men 25-34

89.4%

76.0%

55.7%

.85

.62

Note: NHW, non-Hispanic white.

Source: U.S. Bureau of the Census (1990a).

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
×

non-Hispanic white household in 1990; the median income of Hispanic households was 72 percent that of non-Hispanic white households. Racial differences in per capita income are even greater, since minority households are larger on average than white households. Finally, 3.6 times as many metropolitan-area blacks and 3.2 times as many Hispanics lived in poverty in 1990 as non-Hispanic whites.

In pan, these racial and ethnic gaps in income reflect differences in employment rates. As the table also shows, over 90 percent of prime working-age, non-Hispanic white men in metropolitan locations held jobs in 1990, compared with 83 percent of Hispanic men of prime working-age and just 73 percent of black men of similar ages. There are sharp differences in the numbers of men explicitly looking for work as well. The unemployment rate was 3 times as great for prime working-age black men as for working-age white men, and the disparity between Hispanics and non-Hispanic whites was even greater.

Some fraction of the income gap, as well as the employment gap itself, may be explained by significant racial and ethnic disparities in educational attainment. Among men between the ages of 25 and 34, for example, nearly 90 percent of non-Hispanic whites have at least high school diplomas. The corresponding proportions for African Americans and Hispanics are just 76 and 56 percent, respectively.

As Table 3-8 illustrates, these relationships have generally not changed much over the decade from 1980 to 1990.3 In general, blacks improved their educational attainment relative to whites, and the poverty gap closed modestly as well. Still, the gains were small, and blacks actually lost ground relative to whites with respect to their labor market success and per capita income.

Racial differences vary both by region and by metropolitan-area size. Table 3-9 illustrates that the gap between black and white per capita income is smaller

TABLE 3-8

Percentage Change in Selected Outcomes by Race, 1980-1990

 

Population in Metropolitan Areas

 

Percent Change in Outcome, 1980-1990

Outcome

Whites

Blacks

Median household income (constant dollars)

5.6

6.7

Per capita income (constant dollars)

19.4

13.4

Poverty rate

2.4

-.7

Percent employed, men ages 25-54

-.6

-4.9

Unemployment rate, men ages 25-54

.0

15.0

High school graduates, men age 25 and older

12.0

19.9

 

Source: U.S. Bureau of the Census (1980, 1990a).

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
×

TABLE 3-9

Mean Racial Disparities in Per Capita Income in Metropolitan Areas in 1990 by Region

 

Mean Ratio of Per Capita Incomes in Set of Metropolitan Statistical Areasa

Region

Black/Non-Hispanic White

Hispanic /Non-Hispanic White

Northeast

.56

.51

South

.53

.631

Midwest

.544

.602

West

.607

.501

a Ratios of black and non-Hispanic white and Hispanic and non-Hispanic white per capita income were first calculated for each individual metropolitan area. These ratios were then averaged within the region, weighted by the population of the metropolitan area.

Source: Tabulations from U.S. Bureau of Census (1996a).

in the West than in the other three regions. An examination of the poverty rate reveals a similar pattern—the poverty rate for African Americans is 1.8 times higher than the white rate in the Western region of the country, and a full 4 times greater in the Midwest (Current Population Reports, 1993). For Hispanics, the income gaps tend to be lower in the South and the Midwest and higher in the Northeast and the West. Significantly, the regional differences are considerably larger for the Hispanic-white differentials than for the black-white ones, probably because of the large differences in background between the Hispanic population groups living in different areas of the country.

The magnitude of racial disparities appears to vary with the size of a metropolitan area and to be somewhat larger in larger areas (Table 3-10). In metropolitan areas with over 1 million people, per capita income for blacks was just 55 percent of that for white households on average. In metropolitan areas with less than 100,000 residents, by contrast, black per capita income was, on average, 60 percent of white per capita income. The Hispanic-white disparities in per capita income followed a similar pattern. The per capita income of Hispanics in metropolitan areas of over 1 million people was an average of 53 percent of that for non-Hispanic whites; in metropolitan areas with less than 100,000 residents, the corresponding ratio was just 62 percent. For Hispanics, the difference may be due to the fact that recent Hispanic immigrants tend to settle in larger metropolitan areas (Bartel, 1989).

These regional and population size averages, of course, conceal considerable variation across individual metropolitan areas. In certain metropolitan areas, minority groups appear to do far better than in others, and the extent to which central-city residents fall behind their suburban counterparts varies a great deal as well. To give a sense of the range of disparities across metropolitan areas, Tables 3-11 and 3-12 display racial, ethnic, and urban-suburban disparities for the 15

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
×

TABLE 3-10

Mean Racial Disparities in Per Capita Income in Metropolitan Areas by Metropolitan Statistical Area Population Size, 1990

 

Mean Ratio of Per Capita Incomes in Set of Metropolitan Statistical Areasa

Metropolitan Statistical Area Size Class

Black to Non-Hispanic White

Hispanic to Non-Hispanic White

1,000,000 +

.545

.531

250,000-999,999

.566

.608

100,000-249,999

.577

.616

0-99,999

.603

.624

a Ratios of black and non-Hispanic white and Hispanic and non-Hispanic white per capita income were first calculated for each individual metropolitan area. These ratios were then averaged within the size-class, weighted by the population of the metropolitan area.

Source: Tabulations from U.S. Bureau of Census (1996a).

largest metropolitan areas (Nassau County, NY, is omitted since it has no central city), for three outcomes: per capita income, employment rates for men of prime working age (between 25 and 54), and high school completion for men ages 25 to 34.

In Table 3-11, comparing blacks and non-Hispanic whites, the ratio of per capita income ranges from a low of .43 in New York City to a high of .64 in Riverside. Black-white employment ratios meanwhile vary from a low of .70 in Detroit to a high of .95 in Anaheim. Black-white high school graduation rates range from a low of .78 in New York City to a high of .99 in Anaheim. As expected, these disparities generally tend to be greater in the metropolitan areas in the Northeast and the Midwest. The disparities are also larger in the metropolitan areas with larger and more segregated black populations. Indeed, the simple correlation between the segregation index for blacks (measured by the index of dissimilarity) and Ellen's index of disparity (in this volume) is -.91. More work would be useful to try to probe further into the roots of these metropolitan-area differences.

The range in disparities for these three outcomes is even greater for Hispanics and non-Hispanic whites (Table 3-12), consistent with the large cultural variation in the Hispanic population living in the United States. The Hispanic-white ratio of per capita income ranges from a low of .32 in Los Angeles to a high of .77 in St. Louis, and employment ratios range from .79 in Philadelphia to .97 in Washington, DC. High school completion ratios vary from .45 in Dallas to .89 in St. Louis. In general, the disparities are smaller in metropolitan areas, such as St.

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
×

TABLE 3-11

Disparities Between Blacks and Non-Hispanic Whites in the 15 Largest Metropolitan Areas, 1990

 

Ratio of Black to Non-Hispanic White Outcome

Metropolitan Statistical Area

Per Capita Income

Employment Rate, Men 16-64

Percent High School Graduates, Men 25-34

Anaheim, CA

.63

.95

.99

Atlanta, GA

.51

.86

.92

Boston, MA

.55

.83

.86

Chicago, IL

.45

.73

.8

Dallas, TX

.44

.83

.89

Detroit, MI

.54

.7

.81

Houston, TX

.44

.82

.86

Los Angeles, CA

.48

.8

.86

Minneapolis, MN

.5

.76

.88

New York, NY

.43

.81

.78

Philadelphia, PA

.53

.76

.81

Riverside, CA

.64

.84

.99

St. Louis, MO

.52

.77

.85

San Diego, CA

.53

.88

.95

Washington, DC

.55

.87

.88

 

Source: U.S. Bureau of the Census (1980, 1990a).

TABLE 3-12

Disparities Between Hispanics and Non-Hispanic Whites in the 15 Largest Metropolitan Areas, 1990

 

Ratio of Hispanic to Non-Hispanic White Outcome

Metropolitan Statistical Area

Per Capita Income

Employment Rate, Men 16-64.

Percent High School Graduates, Men 25-34

Anaheim, CA

.38

.95

.48

Atlanta, GA

.66

.95

.71

Boston, MA

.46

.85

.71

Chicago, IL

.4

.94

.55

Dallas, TX

.39

.94

.45

Detroit, MI

.64

.89

.82

Houston, TX

.38

.95

.47

Los Angeles, CA

.32

.95

.47

Minneapolis, MN

.52

.92

.86

New York, NY

.34

.86

.67

Philadelphia, PA

.43

.79

.66

Riverside, CA

.51

.95

.6

St. Louis, MO

.77

.94

.89

San Diego, CA

.43

.93

.63

Washington, DC

.51

.97

.65

 

Source: U.S. Bureau of the Census (1980, 1990a).

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
×

Louis, that have smaller, more middle-class Hispanic populations. The simple correlation between the standardized mean of these disparities and the index of Hispanic residential segregation is -.91, and the correlation between the mean disparity and the proportion Hispanic in the metropolitan area is -.57.

In summary, large disparities in social and economic outcomes persist between central-city and suburban residents and between minorities and whites. In general, the magnitude of the racial and ethnic disparities has remained fairly constant between 1980 and 1990, and the city-suburban and skills differentials have grown significantly. Nonetheless, there is substantial variation across individual metropolitan areas.

Accounting for the Causes of Outcome Disparities

This section examines the causes of the disparities in outcomes between central-city and suburban residents and between whites and minorities in metropolitan areas. The focus is on factors that relate specifically to metropolitan phenomena and, in particular, to the metropolitan spatial opportunity structure. We consider the ways in which the physical and institutional structure of metropolitan areas affects these disparities. And we distinguish causes of outcome disparities that are metropolitan in nature from causes that are national and are manifested in metropolitan areas simply because these areas constitute such a large share of the U.S. population.

Metropolitan-Related Causes
Spatial Mismatch

The spatial mismatch hypothesis states that there is a disjuncture between the location of jobs (which are increasingly found in the suburbs) and the location of potential qualified workers (who are constrained to live, as a result of low income or housing segregation patterns or both, in central-city neighborhoods). As evidence, proponents of the spatial mismatch hypothesis point to high unemployment rates in many central cities at the same time that metropolitan labor markets are tight and jobs are apparently available in suburbs. Spatial mismatch is thought to reduce the well-being of central-city residents and contribute to city-suburban disparities by making it more difficult for central-city residents to find work, by reducing wage rates in the central city relative to the suburbs, and by increasing the commuting costs of central-city residents (Ihlanfeldt, this volume).

There are several reasons related to distance and metropolitan structure that explain how such a mismatch could exist. The most straightforward of these is that low-income central-city residents lack physical access to suburban jobs as a consequence of low rates of car ownership and poor public transportation services. Another possibility is that information atrophies with distance, and that

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
×

central-city residents know little about job opportunities in outlying suburban areas. A third related hypothesis is that minorities are apprehensive of hostility in distant suburbs with which they have little experience, whether or not such hostility exists. But reasons unrelated to distance may also play a role. Suburban employers may, in fact, discriminate against minority workers, or against central-city workers regardless of race. And central-city workers may have poor access to information about job opportunities, regardless of distance from their residence, if they are isolated from job information networks.

Earlier research suggested that it was not distance (job accessibility) but race that explained racial differences in youth employment rates (Ellwood, 1986). However, reviewing the recent evidence on the spatial mismatch hypothesis, Ihlanfeldt (this volume) found that distance does matter in explaining the large difference in employment rates of black and white youth in metropolitan areas. In a recent review of the literature, Mayer (1996:38) is somewhat less definite but concludes that ''commuting times appear to be an important factor in explaining reduced employment for black and Hispanic youth.''

Little of the spatial mismatch research has focused on smaller metropolitan areas, where the distance component of spatial mismatch should be reduced. Ihlanfeldt reports (this volume) that, although racial differences in youth employment rates are only modestly lower in smaller than in larger metropolitan areas, the importance of job accessibility as a determinant of these racial employment gaps is directly proportional to metropolitan size and is unimportant for metropolitan areas of less than 1 to 1.5 million people. This, by inference, casts doubt on the importance of the distance factor in larger metropolitan areas as well and suggests that dynamics other than distance, such as lack of connection to job information networks and social isolation, may be important factors at work in explaining employment disparities between black and white youth.

Ihlanfeldt also reports on research that he and colleagues have done on the relative importance of specific barriers that prevent blacks from shifting their labor supply to suburban areas in response to spatial mismatch. This research is of particular importance in terms of its relevance for policy responses. It concludes that a combination of barriers prevents central-city blacks and less-educated whites from obtaining suburban jobs, including an absence of information on suburban job opportunities, greater hiring discrimination against blacks in suburban areas (reflecting both consumer and employer prejudice), and the inability to commute from the inner city to suburban employment centers via public transportation.

Concentrated Poverty, Social Isolation, and Neighborhood Effects

Other possible reasons why central-city residents have low employment rates relative to suburban residents are not necessarily related to distance but may nonetheless be related to location and metropolitan structure. One such possible

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
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set of reasons relates to the social isolation of poor people, particularly blacks, in high-poverty neighborhoods. Residence in such areas, it is argued, imposes "neighborhood effects" on inhabitants, external costs that would not be present if the individual lived elsewhere.

Some concentrated-poverty neighborhoods are inevitable and functional parts of every large metropolitan area (Downs, 1997). This is both because poverty exists and such neighborhoods provide low-cost housing for the poor and because newly arriving immigrants tend to concentrate in a small number of specific neighborhoods with low-cost housing in which previous arrivals from their ethnic group have congregated. However, in many American cities, the degree of concentrated poverty, as well as its racial dimensions, make it unusual and clearly dysfunctional.

The extent of concentrated poverty in metropolitan areas—defined as the percentage of the metropolitan-area population living in census tracts with 40 percent or more of the households with income below the poverty level—is largely the result of metropolitan-wide processes of income generation and neighborhood sorting (Jargowsky, 1997). Variation in the level of black neighborhood poverty is related significantly to mean metropolitan household income (the lower the mean income, the greater the neighborhood poverty rate), to income inequality (the higher the degree of income inequality, the greater the neighborhood poverty rate), and to the ratio of black mean household income to metropolitan mean household income in metropolitan areas (the higher the ratio of black mean household income to metropolitan-area mean household income, the lower the neighborhood poverty rate) (Jargowsky, 1997). But it is also positively related to what Jargowsky calls "neighborhood sorting processes" as measured by indices of racial and economic segregation.

The critical question is whether such neighborhoods are simply staging grounds for people who move outward and upward after an initial period of residence, or whether they are permanent ghettos for those who live there, from which movement out is unlikely. If these areas are actually "sinkholes," then the adverse effects of living in them constitute a part of the metropolitan opportunity structure that may contribute to inequity and the disparities we have discussed.

There are very substantial rates of emigration from high-poverty areas. In any one year, 25 percent of all poor white adults leave such areas for other areas. However, only 10 percent of poor black adults do so (Gramlich et al., 1992). Gramlich and colleagues note (1992:246): "This is still a high enough rate of exit to shed doubt on the entrapment hypothesis, but the fact that it is so much lower [for blacks] than for similarly situated whites means that perhaps poor whites and blacks are not similarly situated after all." They also found that the overwhelming majority of leavers from poor areas do not return, although others from nonpoor areas take their place.

These data do not tell us what proportion of the population of high-poverty areas are long-time residents; it is possible that it is substantial. Nor do they

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
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provide information on who is moving into these areas (other than information on the areas from which they have come). Weicher (1990:91-92) analyzed movement into and out of poverty neighborhoods (neighborhoods with 20 percent or more of the households below the poverty line) and found most of those moving into these neighborhoods during this period came from elsewhere in the same city.

The impact of living in areas of concentrated poverty may have serious adverse consequences for metropolitan opportunity structures. These effects may vary with stage in the life-cycle, having relatively small impacts on small children, but increasingly more on older children and youth (Ellen and Turner, 1997). Some of these effects may be intergenerational in nature. Corcoran and colleagues (1992:589) found, for example, that the sons of families who lived in neighborhoods with a high proportion of welfare recipients when the son was growing up do significantly worse, for a range of labor market outcomes, than do sons of similarly situated families who lived in areas with a low proportion of welfare recipients. However, the little research that has been done on intergenerational links has, except for the finding just cited, not shown relationships between neighborhood characteristics and economic outcomes. Corcoran et al. (1992) found that other community characteristics—area median income, unemployment rate, and percentage of families that are female headed with children—were unrelated to the economic outcomes of sons, and neighborhood poverty rates were related to future economic outcomes of white men, but not of black men or white women (Corcoran and Adams, 1997). Haveman and Wolfe (1994:250-251) found that the relationship between growing up from ages 6 to 15 in a "bad neighborhood" and economic inactivity at age 24, although positive, was not statistically significant.4

Neighborhood effects, broadly construed, are the effects imposed on individuals as a result of living in a specific neighborhood that the same individual (or household) would not experience if living in a different neighborhood. With respect to neighborhoods of high poverty concentration, these effects are overwhelmingly adverse.

Some neighborhood effects are simply the result of features highly associated with poverty. Since crime and poverty are related, individuals living in high-poverty neighborhoods are more likely to be the victims of crime than would be the case if they were living in a nonpoverty neighborhood. Some effects have to do with the level of public services and amenities in high-poverty neighborhoods, which tend to be worse than would be the case in other neighborhoods.

Some effects, however, have to do with more subtle influences of residents of the neighborhood on the behavior of each other. Since behaviors considered socially undesirable according to dominant norms are more prevalent in poor neighborhoods, individuals living there are more likely to be influenced to engage in self-destructive or antisocial behavior themselves (Ihlanfeldt, this volume). Thus, peer effects could result in greater rates of school dropout and poor

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
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performance in school (if education is not valued or if high grades are seen as acting "white") or higher rates of teenage pregnancy than would be the case for similarly situated individuals living in nonpoverty areas. Research going back to the original Coleman report on equal opportunity in education has pointed to the importance of peer effects in the classroom on student performance (Coleman et al., 1966).

Some neighborhood effects may be related directly to employment prospects. Youth growing up in neighborhoods of concentrated poverty may be cut off from mainstream values and may adopt a set of peer group "oppositional" values that are not well related to workplace success. The lack of adults in the area with steady employment may also affect the employment prospects of others in the area. Also, young people living in a neighborhood of concentrated poverty may know very few people who work. This provides two forms of disadvantage: they are not linked into word of-mouth job networks through which many jobs are filled, and they are not exposed to modeling about appropriate job behavior.

The theoretical and conceptual literature concerned with neighborhood effects suggests that these effects are nonlinear—that is, that there is some threshold of neighborhood poverty at which negative external effects appear, whereas previously they did not. Thus, an increase in the percentage of poverty households in a neighborhood from 10 to 20 percent might be unlikely to have any of the hypothesized adverse neighborhood effects, whereas an increase from 20 to 40 percent (the conventionally used indicator of high-poverty neighborhoods) might do so (see Quercia and Galster, 1997). Unfortunately, there seems to be no theoretical or empirically derived reason for selecting 40 percent as the threshold above which such effects are likely to occur.

Although there is a growing amount of research on such neighborhood effects, much of it is problematic because of the difficulty in accounting for the possibility of endogenous effects. It is possible, for example, that people who behave in ways society deems undesirable choose to live in neighborhoods of concentrated poverty because they prefer the social environment or other characteristics of such a neighborhood over that of other neighborhoods in which low-income housing might be available, or they are forced to live in such neighborhoods because housing they can afford is unavailable elsewhere. As Ihlanfeldt observes (this volume), "There is always the concern that effects that are attributable to neighborhoods may simply reflect unmeasureable characteristics of individuals or families who end up living in the poorest neighborhoods."

An oft-cited earlier review of the literature by Jencks and Mayer (1990:174) was skeptical of the existence of neighborhood effects. They concluded that "there is no general pattern of neighborhood or school effects that recurs across all outcomes." However, recent research has tended to provide more support for the hypothesis. Ihlanfeldt notes that a study by Case and Katz (1991) is the most convincing, since they explicitly modeled the possibility of endogenous residential location. Case and Katz modeled a variety of behavior for 17- to 24-year-

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
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olds, including criminal activity, illegal drug use, alcohol use, church attendance, idleness (neither working nor in school), friendship with gang members, and parenthood outside marriage. For all but the last two behaviors, they found that a youth's involvement is dependent on the extent to which other youth in the same neighborhood engage in the same behavior.

Likewise, three recent reviews found indications of convergence in results with respect to the existence of neighborhood effects (Galster and Killen, 1995; Mayer, 1996; Ellen and Turner, 1997). Galster and Killen observe, for example (1995:35): "Much statistical evidence supports the influence of neighborhood social networks and economic conditions on youth's intellectual development, educational attainment, marriage and fertility, labor market participation and earnings and, to a lesser extent, criminal behavior and drug use. We believe that this evidence is sufficiently convincing that neighborhood effects should be adopted as a working hypothesis."

Ellen and Turner (1997) conclude that the bulk of the empirical studies found that neighborhood effects do exist. Nonetheless, they are more cautious, observing that neighborhood effects tend to be small relative to the importance of family characteristics. Furthermore, they emphasize what we do not know (1997:834-835): "the existing evidence is inconclusive when it comes to determining which neighborhood conditions matter most, how neighborhood characteristics influence individual behavior and well-being, or how neighborhood effects may differ for families with different characteristics."

A few recent studies have tried to sort out the relative impact of spatial mismatch (job accessibility) and neighborhood effects on labor market outcomes. Cutler and Glaeser (1995) and O'Regan and Quigley (1996) found that both are important but that the strength of the neighborhood effects variables is dominant. Ihlanfeldt (this volume), however, criticizes the measure of job accessibility used in both studies as likely to have underestimated the true effect of this variable.

Finally, Quercia and Galster (1997:11) note that "virtually none" of the literature on neighborhood effects has tested for threshold effects, which, as they note, may differ for different kinds of outcomes and population subgroups.

Racial Segregation

Chapter 2 described the high extent of racial segregation in U.S. metropolitan areas. There is little question that some portion of the residential segregation of blacks is voluntary, representing the tendency for ethnic groups of all types to prefer living in close proximity to those similar to others like themselves. However, in a review of the segregation literature, Massey and Denton (1993), citing the very high dissimilarity indices for blacks compared with those for European-origin ethnic groups, conclude that voluntary segregation can explain very little of the high degree of racial segregation of blacks in urban areas. They note (1993:57) that "not only was the segregation of European ethnic groups lower, it

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
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was also temporary. Whereas Europeans' isolation indices began to drop shortly after 1920, the spatial isolation characteristic of blacks had become a permanent feature of the residential structure of large American cities by 1940."

Indeed, a recent survey of the residential preferences of blacks in Atlanta, Boston, Detroit, and Los Angeles (Farley et al., 1997) found that more than half preferred living in a neighborhood that was 50 percent white (although only 8 percent preferred living in a neighborhood that was more than 85 percent white). More than one-third of the blacks interviewed said that they would be willing to be the first black family to move into an all-white neighborhood with attractive and affordable housing (1997:794).

What is the purported relationship of racial segregation to disparities in outcomes? If racial segregation promotes concentrations of poverty among low-income blacks, then it will adversely affect outcomes through the various mechanisms discussed above. Indeed, racial segregation does seem to be linked to concentrations of poverty among low-income blacks; in 1990, 34 percent of poor blacks, but only 6 percent of poor whites, lived in areas of highly concentrated poverty (Jargowsky, 1997). Similarly, to the extent that racial segregation is involuntary and disproportionately confines blacks to central-city residence, then the negative effects of spatial mismatch will contribute to black-white disparities.

In addition, racial segregation, when combined with incomes that are lower for blacks than for whites, may mean that blacks (including middle-income blacks) are more likely than whites to reside in communities with lower tax bases and thus a lower ability to finance public services from their own resources. As a consequence, segregation would contribute to disparities in public service levels and to disparities in labor market and other outcomes, to the extent that inferior education and other public services contribute to such disparities.

Galster (1993:1431) argues that segregation can contribute to intergroup disparities in outcomes between minorities and whites in four ways:

First, separate informal networks and formal institutions serving the minority community, because they have a narrower scope and base of support, will have fewer financial, informational, and human resources upon which to draw; therefore, they will offer inferior options for the development of human capital and the discovery of alternative employment possibilities. Second, isolation can encourage and permit the development of distinct subcultural attitudes, behaviors, and speech patterns that may impede success in the mainstream world of work, either because they are counterproductive in some objective sense or because they are perceived to be so by prospective white employers. Third, an identifiable, spatial labor market may be formed in the minority community and attract employers offering only irregular, low-paying, dead-end jobs. Fourth, inter-racial competition and suspicions are abetted, encouraging the formation of discriminatory barriers in many markets.

Ihlanfeldt (this volume) cites research on the Gautreaux program in the Chicago area as providing the strongest support that racial segregation adversely

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
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affects outcomes for minority groups and contributes to unequal opportunities and disparities. In this program, put in place as a result of a court decision, families residing in public housing in the city of Chicago were given the opportunity of receiving certificates to rent market-rate housing in "revitalized" neighborhoods throughout the Chicago area. Because most participants accepted the first unit offered to them, whether in the city or in suburban areas, this created a quasi-experimental design. A comparison of the results for those who moved to predominantly black, low-income areas in the city of Chicago with those who moved to predominantly white, middle-income neighborhoods in the suburbs found that adult employment was higher for suburban compared with central-city movers, although earnings and hours worked were not. For children, suburban movers were more likely, compared with city movers, to graduate from high school, attend college, and attend a four-year college. For the children of movers who did not attend college, suburban movers were more likely to receive higher wages and better job-related benefits (Rosenbaum, 1995).

Econometric work has also supported the adverse impact of racial segregation on black outcomes. Cutler and Glaeser (1997) examined the level of segregation at the metropolitan level and asked whether it was related to outcomes for blacks throughout the region. They related the level of racial segregation as measured by the dissimilarity index to a variety of outcomes for young people, controlling for other possible determinants of those outcomes, in 204 metropolitan areas for 1990. They conclude that (1997:28-29): "blacks are significantly worse off in segregated communities than they are in non-segregated communities. If we measure success by high school graduation rates, not being idle, earnings, or not becoming a single mother, then integration is intimately associated with success. Our estimates suggest that a one standard deviation reduction in segregation (13 percent) would eliminate one-third of the gap between white and blacks in most of our outcomes."

Jargowsky (1997:Ch. 6) also found that racial segregation is significantly related to level of neighborhood poverty for blacks in both 1980 and 1990 and to the change in levels of neighborhood poverty for blacks between 1980 and 1990. It is thus implicated indirectly in terms of the adverse effects that concentrated poverty has on unequal opportunities and disparities. Galster and Keeney (1988:104-105) found that residential segregation was related to black-white income differentials in metropolitan areas, although only for metropolitan areas that were characterized by governmental fragmentation.

As mentioned earlier, Ellen (this volume) investigated the link between the extent of racial segregation in metropolitan areas and the extent of central-city suburban disparities as measured by a city-suburban index of disparities. Controlling for region, population size, percentage of blacks and Hispanics in the metropolitan-area population, and poverty rate, she found that both black-white segregation and Hispanic-white segregation are positively related to disparities;

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
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the greater the degree of segregation in a metropolitan area, the greater the disparities between central city and suburb.

Economic Segregation

Residential segregation by income—economic segregation—is also a characteristic of U.S. metropolitan areas, facilitated, as discussed earlier, by the existence of large numbers of local governments in most metropolitan areas, each with control of land use powers. As Downs (1994) notes, although there is some heterogeneity in all communities, in general, neighborhoods in metropolitan areas are sorted out by income level, with the poor living in low-prestige areas with poor housing, because that is all they can afford.

As a result of the migration of middle- and high-income groups to the suburbs and racial segregation, the central city typically (but not always) becomes increasingly low-income. The results of this process in terms of the disparity in income between central cities and suburbs have been described.

The extent to which such segregation by income is inevitable, either at the jurisdictional or at the neighborhood level, is debatable. Fischel (this volume) argues that economic segregation by neighborhood will occur "under any mechanism that operates without a severe dose of coercion" (although, he contends, economic segregation by jurisdiction is not inevitable). However, indices of metropolitan-area economic segregation do show substantial variation among metropolitan areas (see Abramson et al., 1995:50-53). In addition, the degree of economic mixing in many European urban areas is widely thought to be substantially greater than is the case in the United States (Berry, 1973; Danielson, 1976:1; Weir, 1995:217; Sellars, 1998).

The logic of the relationship between economic segregation and disparities in outcomes operates in much the same manner as that for race. If there are adverse impacts resulting from the tendency of lower-income individuals to associate in their neighborhood environment primarily with other low-income individuals rather than mixing with those from higher socioeconomic backgrounds, then economic segregation will contribute to them. Of particular concern are the peer effects for children. Similarly, when economic stratification occurs by jurisdiction, as between the typical central city and its middle- and higher-income suburbs, residents of the lower-income jurisdictions will be faced with lower levels of service, or higher tax burdens, or both. Disparities in public service, such as education and public health, may be translated into disparities in outcomes among residents of jurisdictions in terms of future income and employment.

What empirical evidence exists that economic segregation, either by neighborhood or by jurisdiction, does have an adverse impact? At the neighborhood level, we have already reviewed the adverse effects on outcomes caused by areas of highly concentrated poverty. But there is little or no research on the effect on

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
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outcomes of the degree of economic stratification among neighborhoods or jurisdictions across the metropolitan area.

Unequal Provision of Public Services

Metropolitan areas are characterized by substantial variations in public service levels. These variations flow from the very structure of U.S. metropolitan areas: a large number of service-providing local districts, stratified by income and race, each primarily dependent on its own local tax base for the ability to finance and provide public services. Since most public services can be considered to a large extent consumption goods, lower levels of public services (or the necessity of accepting a higher tax burden in order to receive equivalent levels) in themselves represent a disparity resulting from metropolitan-area structure that adversely affects the well-being of those who live in jurisdictions with inadequate fiscal capacity.

Although a case can be made for the effects of a variety of public services on human capital development, education is the most obvious area and the one that has received the most attention. The view commonly expressed through the press and by most of the public is that variations in the level of school resources will result in associated variations in the quality of education provided as measured by student performance and other outcomes. However, at least until recently, conventional wisdom, based on social science research dating back to the Coleman report (Coleman et al., 1966), was skeptical. The Coleman study found that differences in a variety of school input measures that reflect increased spending, including class size and teacher quality, had little impact on student achievement, as measured by performance on standardized test scores. A recent review of 377 studies of education production functions counted the number that found significant relationships, as opposed to no relationships or relationships in the unexpected direction, and concluded there was no systematic relationship between teacher-pupil ratios or teacher education on student performance (Hanushek, 1996:54).5

However, the conclusion that school inputs are unrelated to outputs is not universally accepted by researchers. Using formal meta-analysis techniques, Hedges and colleagues (1994) and Hedges and Greenwald (1996) reexamined the same set of studies Hanushek examined and found evidence that both teacher-student ratios and teacher education are positively and significantly related to student achievement. In addition, other recent studies have begun to cast doubt on the earlier conclusions and to provide support for the relationship between expenditure differences and variation in student performance. Ferguson (1991) and Ferguson and Ladd (1996) engaged in carefully structured studies that overcome many of the methodological differences of other education production function studies.6 In their study of Alabama schools, they found that class size, teachers' test scores, and teachers' education all affect student performance and

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
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concluded that, since these "all cost money," money matters and money spent for instructional purposes particularly matters (Ferguson and Ladd, 1996).

Card and Krueger (1996) argue that, whatever their effect on test scores, school resources positively affect long-term outcomes such as educational attainment and earnings. They conducted a natural experiment involving two states that spent substantially different amounts on the per pupil education of black children and white children between 1900 and 1960. During that period, North Carolina systematically provided more resources per black students and fewer for white students than did South Carolina. In the state with higher spending on black children (North Carolina), the future wages of blacks were higher than those of blacks educated in South Carolina. In the state with higher spending on white students (South Carolina), the future wages of whites was higher than those of whites educated in North Carolina.

Size and Density

The effects of physical features of metropolitan areas, such as population size, land area, and density (or sprawl), on metropolitan-area opportunity structures and outcome disparities is a question of great interest and controversy, and the empirical evidence is sparse and contradictory.

On one hand, larger metropolitan areas may affect the spatial mismatch problem by increasing distances between the central city and suburban workplaces; they may also intensify the impact of social isolation, since information on labor market opportunities may be more readily available in smaller areas. On the other hand, larger metropolitan areas may provide more opportunity and greater and more complex information linkages, thus increasing the chances that connections will be made to labor market opportunities.

Low-density areas may lead to unequal opportunity by increasing the distance between central-city residents and suburban job opportunities, thereby contributing to spatial mismatch. Low-density development, particularly if supported by exclusionary zoning practices, may also increase the land cost of housing, thus making it more difficult for low- and moderate-income households to reside in suburban areas near areas of growing job opportunity.

Ihlanfeldt observes that the difference in youth employment rates for blacks and whites is only slightly less in metropolitan areas with low population than in those with high population, suggesting that size of area is unlikely to have much effect. However, he cites his own research (1992) as the only work that provides separate estimates for different size metropolitan areas of the impact of job access on both youth job probability and racial employment gaps. He found that the impact of job access measures on these outcomes was directly proportional to metropolitan size, with no importance found for job access measures in metropolitan areas of less than 1 to 1.5 million people.

Cutler and Glaeser (1997) found that metropolitan-area population size is

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
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related to differences in college graduation rates between blacks and whites: the larger the metropolitan area, the lower the college graduation rate for blacks relative to whites. However, they also found that large metropolitan areas are associated with higher black earnings relative to whites (suggesting that the negative relationship between relative black earnings and metropolitan-area size presented in Table 3-10 above is reversed in the context of a multivariate analysis in which other variables are controlled for). The rate of single motherhood is also lower for blacks relative to whites in larger metropolitan areas.

Hill and Wolman (1997c) include the log of metropolitan-area population size in a model designed to explain per capita income differentials between suburbs and the central city in metropolitan areas for all metropolitan areas whose central-city population exceeded 250,000. Controlling for region, elasticity, employment structure, and other variables, they found that these differentials were inversely and significantly related to metropolitan-area population size: the larger the metropolitan-area population, the smaller the per capita income difference between suburbs and the central city. However, Ellen (this volume) estimates a multivariate model and found that metropolitan-area population size is not significantly related to an index of city-suburban disparities.

Persky and Wiewel (1998) attempted to calculate the costs and benefits of placing a new electrical equipment plant with 1,000 workers in a ''greenfield'' [field of undeveloped suburban land] site in the outer suburbs of Chicago rather than a site in the central city. They found low-income groups and city residents to be the biggest losers from locating the plant in the suburbs; their calculations, although based on controversial methodological assumptions, also indicate that there is essentially no difference in efficiency in terms of whether the firm locates in the city or the outer suburbs.

Economic and Population Growth

Conventional wisdom suggests that growth and increased labor market tightness should narrow city-suburban income disparities. The reasoning is straightforward. Since highly skilled labor is likely to be employed throughout the business cycle and tends to reside in suburbs, growth should disproportionately attract lower-skilled individuals into the labor market. Disproportionate numbers of these lower-skilled individuals are likely to live in central cities.

However, examining data for the period 1980-1990, Hill and Wolman (1997b) found that increasing labor market tightness, as measured by either declines in the unemployment rate or by increases in the ratio of employment to the working-age population, was positively correlated with city-suburban disparities: as labor markets tightened, disparities increased.

They then examined central-city/suburban per capita income disparities in a cross-sectional multivariate model, using employment as a percentage of working-age population as a variable to measure labor market tightness and control-

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
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ling for a variety of variables. They found a nonlinear relationship between tightening of labor markets and city-suburban income disparities. Increasing labor market tightness at first leads to greater disparities in city-suburban per capita income, but finally reaches a point (when the ratio of employment to working-age population is 71.9 percent, slightly below the mean of 72 percent for all of the metropolitan areas in the sample) above which further increases begin to reduce disparities. Hill and Wolman note, however, that (1997b:573) "these spatial income gaps do not disappear even in very tight local markets."

They explain their results by observing that employers seeking additional labor in tight labor markets tended to be located disproportionately in the suburbs. This demand was met in the first instance primarily through increases in the suburban labor force as secondary workers—spouses, teenagers, and elders—entered the labor market. Only after this additional source of labor was utilized did employers turn to lower-skilled central-city workers. Hill and Wolman conclude (1997b:577) that "economic growth, bringing about tighter labor markets, is clearly desirable, but it is not a cure for inner-city poverty and will not narrow gaps between central-city and suburban incomes in and of itself."

In related research, Pastor and colleagues (1997:Ch. 3) examined the relationship between metropolitan growth (in per capita income) and poverty between 1980 and 1990, using a simultaneous equation approach. They found no significant relationship between metropolitan growth and change in the city to suburban poverty ratio and conclude (1997:3-13) that "growth itself will not necessarily 'trickle down' to help the central city more than the suburbs."

Danielson and Wolpert (1992, 1994) found evidence that growth widened disparities. Studying the effect of population and employment growth on per capita income disparities among 365 contiguous municipalities in northern New Jersey, they concluded (1992:513): "Our test case of rapid growth in a highly fragmented metropolitan area demonstrates that disparities between richest and poorest communities widened significantly, especially when growth accelerated during the 1980s. Development and jobs shifted to the outer suburbs and rural fringe and bypassed the low-income and minority cities in the region."

Elasticity

It has been argued that fewer city-suburban disparities are found in metropolitan areas with more elastic cities—which are cities that can expand their population either by developing vacant land within existing borders or by annexing areas outside their borders (Rusk, 1993). The explanation, according to Rusk, is the greater control that elastic central cities have over their environment.

The concept of elasticity has proven difficult to operationalize in a satisfying manner. Rusk himself provides a definition that is complex and not clearly related to the concept. He operationalizes it as a variable (1993:53) by multiplying the ranking of a city's density (population per square mile) in 1950 by its

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
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ranking for the percentage by which it expanded its boundaries between 1950 and 1990. A seemingly more direct approach would operationalize elasticity by taking central-city population as a percentage of metropolitan-area population.

Using his operational definition described above, Rusk shows that elastic cities comprise a higher proportion of metropolitan-area population than do inelastic cities. He also found (1993:75-82) that city-suburban income gaps are wider in metropolitan areas with inelastic cities than in those with elastic cities. However, this finding is simply a bivariate relationship without any controls.

Contrary evidence is provided by Hill and Wolman (1997c). They use the alternative definition of elasticity described above7 in a model designed to account for differences in the central-city/suburban per capita income gap across metropolitan areas. Controlling for a variety of factors, including region, metropolitan-area economic structure, tightness of metropolitan-area labor markets, and human capital differences between city and suburban residents, they found no statistically significant effect (at the .05 level or below) for elasticity on city-suburban per capita income differentials.8

Ellen (this volume) tested for the effect of elasticity (defined as the population of central cities in a metropolitan statistical area, MSA, as a percentage of MSA population) on her index of city-suburban disparities in a multivariate model that includes region, various metropolitan demographic characteristics, and government structure. She found a nonlinear, "kinked" relationship. When elasticity is below .45 (i.e., when the central-city population is less than 45 percent of the metropolitan-area population), elasticity is negatively and significantly related to the disparity index; as elasticity increases up to the .45 level, central-city/suburban disparities decrease. Above an elasticity level of .45, increases in elasticity have essentially no effect on city-suburban disparities.

Metropolitan Government Structure

Another possible contributor to the degree of disparities among residents within metropolitan areas, both by place and by group, is the nature of the government structure in these areas, particularly the number of local governments and the degree of fragmentation. We consider in what ways political fragmentation might contribute to a spatially determined opportunity structure.

We begin with the basic fact that local governments in the United States finance their services primarily from their own tax base. General-purpose local governments also control local land use decisions. As a consequence, local governments have both the incentives and the means to differentiate themselves with respect to the income, tastes, and tax and service preferences of their residents, and residents have the ability to make choices among local governments based on these same characteristics. Political boundaries thus facilitate sorting, and the more jurisdictions there are, the more effective the sorting process is likely to be (Lewis, 1995).

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
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The logic of this argument is that greater fragmentation will lead to a more differentiated spatial opportunity structure, with more fragmented metropolitan areas experiencing greater disparities among individuals in important outcomes and greater tax/service disparities among local governments. It is not clear whether central-city/suburban differences should be greater in more fragmented areas. Since fragmentation increases the potential for choice and thus sorting, we would also expect fragmentation to be positively related to income segregation in metropolitan areas (Bradford and Oates, 1974; Mills and Oates, 1975) and, since race and income are correlated, to racial segregation.

The concept of fragmentation needs to be distinguished carefully from the concept of elasticity, as discussed above. Elasticity refers to the central city's ability to exercise influence and control over the metropolitan area, and it is best measured by the percentage of metropolitan-area population living in the main central city. Fragmentation, as we define it, relates to the ability of the local government system to engage in sorting behavior through offering a multitude of choices (local governments) with the effective ability to exclude. It should be measured by the number of relevant local governments per capita in a metropolitan area. A relatively elastic metropolitan area may still be fragmented if the remainder of the area is divided into a large number of local governments. Similarly, a relatively inelastic metropolitan area may have little fragmentation if the remainder of the area has few other local jurisdictions with the ability to engage in sorting behavior. This would be the case where the basic unit of local government with land use powers is the county government, as in Maryland and Virginia.

Most of the research effort with respect to fragmentation has been directed toward the impact of fragmentation on size of government, as measured by expenditures per capita or on service delivery and efficiency (see Wagner and Weber, 1975; Sjoquist, 1982; Chicoine and Walzer, 1985; Schneider, 1986, 1989; Dolan, 1990; U.S. Advisory Commission on Intergovernmental Relations, 1991; Boyne, 1992a, 1992b; Foster, 1997:Ch. 3). Boyne (1992b) reviews more than 20 studies of the impact of fragmentation on local government spending. He found that fragmentation leads to lower per capita spending for the system of multipurpose government units (i.e., typically municipalities) within metropolitan areas, but higher per capita spending for single-purpose units. He explains the difference by noting that fiscal migration is a much more potent threat to multipurpose governments (thus acting as a restraint on spending) than to single-purpose governments and also that many single-purpose governments provide services that are capital-intensive and thus incorporate economies of scale.9 In another review of the literature, Dowding and colleagues (1994) also conclude that local government fragmentation leads to reduced expenditure. However, they agree that existing research is unable to sort out whether this effect is due to competition or to other causes related to the smaller size of government in fragmented areas, such as fewer opportunities to redistribute among income classes.

The body of literature directed at disparities and inequality is smaller and

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
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less compelling, and it is particularly so given the difficulties in constructing a convincing operational measure of fragmentation.10 The variation in measures of fragmentation and the nature of the dependent variables and methodologies used make it difficult to come to overall conclusions. The seminal research was conducted by Hill (1974), who attempted to account for income inequality among municipalities in 63 metropolitan areas (rather than among all households in metropolitan areas). His dependent variable as a measure of intrametropolitan income inequality was the standard deviation in the distribution of median family income among municipalities. In a multivariate analysis, he found that political fragmentation, measured as the number of municipalities per capita, was positively related to his measure of municipal income inequality (but that fragmentation, as measured by the total number of municipal governments, was not).

Ostrom (1983:98) criticizes Hill's methodology, contending that "comparing means or medians of different-sized units can lead to false conclusions about the extent of heterogeneity in a population." Ostrom, however, does not attempt to remedy this by providing additional empirical analysis; indeed, there appears to be no research that relates political fragmentation to income heterogeneity, as she terms it, in the metropolitan-area population.

Other research has examined the impact of fragmentation on the income differential between the central city and its suburbs. Logan and Schneider (1982), Bollens (1986), and Morgan and Mareschal (1996) all fail to find a significant relationship between fragmentation (governments per capita) and city-suburban income differences in metropolitan areas. This is not surprising; it simply suggests that the difference between city and suburban per capita income is not affected by the number of suburbs (relative to population) in the metropolitan areas. Ellen (this volume), however, found that fragmentation (number of general-purpose governments per 100,000 people) is negatively and significantly related to an index of disparities in a multivariate model that includes region, metropolitan demographic characteristics, and elasticity: the greater the degree of fragmentation, the lower the disparity between central city and suburbs.

Fragmentation has been implicated as a contributor to some of the other factors that we have shown to be related to unequal outcomes. Cutler and Glaeser (1997) found that the number of municipal and township governments in metropolitan areas is positively related to metropolitan-area racial segregation as measured by the dissimilarity index. However, since their purpose is to use number of governments as an instrument for segregation, they do not develop a fully specified model to estimate the relationship. Hamilton and colleagues (1975) measured the link between income segregation across census tracts in a metropolitan area and metropolitan government structure. They found that income segregation is greater when there is more choice, i.e., when the number of school districts is greater.

Galster and Keeney (1988) found that residential segregation was related to black-white income differentials in metropolitan areas, but only for metropolitan

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
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areas that were characterized by high governmental fragmentation (as measured by the number of jurisdictions in the area). They concluded (1988:104-105): "this finding, that SMSAs with more segregation have lower relative black incomes only to the extent they are jurisdictionally fragmented, suggests that the direct link . . . [between segregation and black/white income differentials] transpires through interracial differentials in public service packages consumed, presumably education primarily."

Lewis (1996) examined the relationship between fragmentation and spatial mismatch, arguing that there should be greater mismatches between job areas and housing areas in more fragmented metropolitan areas. He found that his fragmentation index was positively and significantly related to average commuting time.11

Other Causes With Spatial Components

We now turn to causes of disparities in outcomes between residents of central cities and their suburbs and between minorities and whites that are traditionally conceived of as less related, or unrelated, to metropolitan phenomena. However, as we note, all of them have important spatial components that are affected by the spatial structure of metropolitan areas.

Human Capital

Differences in black-white labor and city-suburban labor market outcomes may be related to differences in human capital—that is, to the skills that prospective employees bring with them to the workplace. These differences, although unrelated to metropolitan phenomena, may nonetheless result, in part, from adverse neighborhood effects or unequal provision of education services, as discussed above. Neal and Johnson (1996) found that differences between blacks and whites in educational attainment and test scores (which are a likely proxy for the quality of education) account for most of the differences in hourly wages, although they account for less of the differences in employment rates. Holzer (1994) emphasizes the point that quality of education must be taken into account as well as educational attainment. He cites literature indicating that reading and numerical skills of blacks are not comparable to those of whites in the same educational categories, and that these differences in scores on reading and math tests account for much of the racial differences between blacks and whites in earnings and in employment probabilities.

Hill and Wolman (1997b:574) found that differences in human capital between central-city and suburban residents (measured by the difference in the percentage of residents with more than a high school education in the two areas) were significantly and strongly related to their differences in per capita income. Each percentage point difference in the percentage of suburban and central-city

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
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residents with more than a high school education was associated with a 1.41 percentage point difference in per capita income.

Decline in Demand for Less-Skilled Labor

The national economy has undergone substantial structural change over the past 25 years that has greatly reduced the proportion of employees in manufacturing jobs and increased the proportion in service-sector jobs. In 1970, 26 percent of all U.S. workers were employed in the manufacturing sector, compared with only 16 percent in 1994. In addition, technological change has increased skill requirements in many sectors of the economy, including manufacturing. These changes have shifted labor demand from less-educated to more-educated portions of the workforce. Well-paid, less-skilled jobs in the manufacturing and other sectors have largely disappeared. When combined with differences in human capital on the supply side, the result is a skills mismatch that disadvantages less-skilled workers in general and blacks, a higher proportion of whom are less skilled, in particular (see Wilson, 1987, 1996).

Research results suggest that a skill mismatch exists and that declining manufacturing employment has contributed to black-white disparities by reducing the relative earnings and employment of blacks, with particular impact on the youngest and least educated black males (see Holzer, 1994, for a review of this literature). Holzer emphasizes, however, that substantial earnings and employment gaps between blacks and whites remain even after the decline of manufacturing employment and skill mismatch are taken into account.

Spatial factors also interact with the decline in demand for less-skilled jobs. Kasarda (1995) and Holzer (1996) both found that job growth in the central city has been in sectors that require higher skills, such as finance and business services, than do the sectors of suburban job growth, such as retail trade, personal services, and traditional blue-collar manufacturing. Kasarda (1995) notes that this exchange of goods-processing for information-processing jobs (requiring higher skills) in central cities has meant that central-city jobs are no longer functionally accessible to less-educated city residents, even if they are physically accessible. Meanwhile, opportunities for the relatively less-skilled jobs that might be appropriate for less-educated city residents are constrained by the spatial mismatch problems discussed earlier.

Racial Discrimination in Employment

Part of the black-white gap in labor market outcomes may simply be due to employer discrimination in labor markets. Indeed, there is very good reason to believe this is the case. Holzer (1994) summarizes recent evidence, which appears in Turner et al. (1991) and is based on an Urban Institute audit study, in which matched pairs of black and white job applicants, with employment histories and

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
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skills designed to be exactly comparable, applied to several hundred firms in two major metropolitan areas. Blacks received significantly fewer job offers than did whites (19 versus 29 percent).

Furthermore, there appears to be a spatial element in employer discrimination. Holzer (1996) found that the ratio of black new hires to black applicants is lower in the suburbs than in the central city. He concludes that there is a "relatively lower employer preference for black applicants in suburban areas than elsewhere" (1996:95). In a multivariate analysis, he found that the probability of a firm's hiring blacks is lower for those with mostly white customers, which are more likely to be located in the suburbs. Finally he indicates that the evidence suggests "that discriminatory employers may deliberately choose locations for their firms that make them inaccessible to blacks" (1996:95).

Costs of Unequal Opportunity

The costs of unequal opportunity are clearly borne by those who are most directly affected in terms of lower income, higher unemployment, and constrained choices. But in addition, there are very real costs imposed on the entire metropolitan area as well as on the nation as a whole.

In work undertaken at the request of the committee, Harry Holzer arrived at a rough estimate, for the purposes of this report, of the costs that segregation imposes on young blacks (ages 20-30) in metropolitan areas, as well as on the metropolitan areas overall. He first used regression results from Cutler and Glaeser (1997) to calculate the effects of differences in the levels of segregation across metropolitan areas (as measured by the dissimilarity index) on several major outcomes for young blacks in these areas: high school graduation, college graduation, the probability of not being employed, the log of annual earnings, and the probability of being a single mother. He then linked the costs borne by the young people themselves to their outcomes for the metropolitan areas overall.

Holzer's calculations estimate the impact of segregation by contrasting the most highly segregated metropolitan areas with the least segregated metropolitan areas. He derived two estimates of the effects of segregation on young blacks. The first is based on the difference between high and low segregation levels (i.e., dissimilarity indexes of between .70 and .75 at the high end and between .45 and .50 at the low end). Examples of metropolitan areas with high segregation levels include New York and Philadelphia; those with low levels include Phoenix and Raleigh; the difference constitutes a change of two standard deviations in the distribution of segregation levels in metropolitan areas.

The second estimate is based on differences in segregation between the most and the least segregated areas (dissimilarity indexes of between .80 and .90 for the most segregated and between .30 and .40 for the least segregated). Examples of metropolitan areas with the most segregation include Detroit, Chicago, and Gary; those with the least include Albuquerque and San Jose. This difference

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
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constitutes a change of four standard deviations in the distribution of segregation levels (almost the entire range).

Using this technique, Holzer found very large negative effects of segregation on blacks when comparing the least segregated to the most segregated metropolitan areas. An increase in segregation from low to high levels caused a drop in high school graduation rates of 6 percentage points. An increase in segregation from the level of the least segregated areas to that of the most segregated reduced high school graduation rates by 12 percentage points. Similar increases in segregation caused college graduation rates of young blacks to drop by 2.5 to 5 percentage points, the percentage of those not employed or in school to increase by 7.5 to 15 points, annual earnings to decline by 20 to 40 percent, and the probability of being a single mother to increase by 10 to 20 percentage points.

Holzer then linked these adverse consequences on individuals to costs for the metropolitan area and beyond. Assuming that worker productivity is proportional to earnings and that blacks are about 15 percent of the population in large metropolitan areas, then, in a steady state over time, a 20 to 40 percent reduction in earnings due to high segregation translates into a 3 to 6 percent decline in productivity for the area as a whole.

Segregation also affects labor turnover through increasing high school dropout rates. Turnover imposes major costs on employers, in the form of fixed costs for recruiting, hiring, and training, as well as in lower productivity from lost accumulation of work experience. Turnover rates are at least 40 percent higher per year among high school dropouts than among high school graduates (Bernhardt et al., 1997). An increase in dropout rates of 6 to 12 percentage points implies increases in dropout rates of 30 to 60 percent (since the dropout rate of blacks in low-segregation cities is about 20 percent). This in turn implies an increase in dropout rates of 4.5 to 9 percent for the metropolitan area as a whole (if blacks constitute 15 percent of the population) and an increase in turnover rates of 2 to 4 percent for area employers.

Finally, Holzer notes that the result in effects on area crime also are substantial. Freeman (1992) has shown that well over 50 percent of black male dropouts between the ages of 16 and 34 are in the criminal justice system, compared with only 10 percent for black male high school graduates. Thus, an increase in black high school dropout rates due to an increase in segregation will lead to huge increases in crime. Assuming young black males account for approximately 30 to 40 percent of serious crime in less-segregated metropolitan areas, Holzer calculated that the impact of moving from low to high segregation levels will increase serious crime in the metropolitan area by 45 to 60 percent. The impact of moving from segregation levels of the least segregated areas to those of the most segregated areas will increase serious crime by 90 to 120 percent.

Holzer's estimates should be taken as rough approximations of the impact of high compared with low degrees of segregation. As such, they are an overstate-

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
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ment of the impact for most metropolitan areas. And, as he cautions, they may also overestimate somewhat the effect on employers of labor turnover (because employers are likely to pay lower wages to employees who have a higher probability of turnover) and the effect on crime (since the causality may run both ways: high school dropouts may be more likely to engage in crime, but those who have a propensity to engage in crime may be more likely to drop out of school). Nonetheless, they provide an illustrative estimate of the potential costs, both to blacks and to the metropolitan area as an entity, that are imposed by highly segregated areas compared with what would be the case if these areas had very low levels of segregation.

To what extent are these overall costs in metropolitan areas borne by white suburban residents as well as by black inner-city residents? Although it is difficult to make Precise estimates, it is very likely that some significant costs are borne by whites as well as blacks.

For instance, the lower earnings of less-educated black workers brought about by unequal opportunity will reduce white income through the multiplier effect, as blacks purchase fewer goods and services throughout the area. In addition, the lower earnings and productivity of these black workers will generate lower tax revenues from them and higher transfer payments to them, both of which are ultimately borne by middle-class taxpayers of both races. Higher poverty rates among blacks will also generate other costs to the white middle class, such as greater expenditures on law enforcement (discussed below) and health care for these groups.

Lower productivity of black employees in a given set of jobs will almost certainly result in lower profits to their employers. Even if their lower productivity could be fully offset through lower wages, the "surplus" that accrues to employers as a result of their efforts will still be reduced. And, to the extent that the lower productivity of these employees generates higher turnover, this results in higher direct costs to their employers (in the form of recruitment, screening, and training costs) as well as foregone output while their jobs are vacant. When labor markets are tight, the costs to employers of attracting and keeping good employees can be especially high.

Finally, the costs of central-city crime to suburban residents are likely to be substantial. The direct costs of administering the criminal justice system (including the building and staffing of prisons) are currently about 2 percent of gross domestic product nationally, or $150 billion, borne entirely by taxpayers. Although the majority of crime victims are themselves minorities who live in high-crime neighborhoods, some urban crime clearly spills over into neighboring suburban areas; a fear of crime often pervades those areas, above and beyond what actually occurs. Even for those who have effectively escaped the risk of crime by residing in outlying suburbs, the loss of enjoyment of urban amenities may entail some real costs.

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
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Disparities in Fiscal Capacity

In turning from disparities in outcomes among individuals or groups of individuals to disparities among jurisdictions, we focus on disparities in fiscal capacity among local governments. Tax/service disparities—using the term synonymously with fiscal capacity disparities—are an important part of the metropolitan spatial opportunity structure; they themselves contribute to the disparities in outcomes between central-city and suburban residents and between minority and white households.

Tax/Service Disparities

Local governments in metropolitan areas differ, sometimes widely, in the tax burden they impose on their citizens and in the level of services they provide. These observable variations in tax burden and services may be termed tax/service differences.12 They reflect a variety of causes, including variations in public preferences, in local government efficiency, and in tax capacity and expenditure need. The committee's concern, however, is not with these differences per se, but with tax/service disparities (sometimes called fiscal disparities), which we define as differences based on factors outside the control of local officials in the ability of their governments to provide a reasonable level of services with a reasonable tax burden on their residents (Yinger, 1996:1). In the absence of equalizing aid from higher levels of government, residents in local governments with low tax capacity or higher expenditure needs are faced with a difficult choice: they must either pay a higher percentage of their income in taxes than do wealthier communities in order to obtain equal levels of public services, or, if they tax themselves at a comparable rate, they must accept lower levels of public services.

To the extent that tax/service disparities reflect differences in tax capacity and service need rather than preference, the committee considers them undesirable both in terms of their impact on the spatial opportunity structure of metropolitan areas and in terms of equity.13 The problems stem from the fact that local services are financed largely out of locally raised revenues. In 1991-1992, 62 percent of all local government general revenue (and 72 percent of all municipal government general revenue) was raised from local government's own sources, with the remainder coming from intergovernmental aid (U.S. Bureau of the Census, 1996c). This means that, to the extent that quality of service is related to amount spent, residents of low-income communities face a difficult dilemma. Unless they live in a community with a substantial business tax base, or unless their community is compensated for its low tax base with disproportionate amounts of intergovernmental aid, they will be faced with paying more out of their income in order to receive similar levels of service or, if they do not wish to take on this extra burden, with receiving inferior levels of service. This has

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
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particularly severe effects with respect to services, such as education, that are related to life chances. As a consequence, the opportunity structure for residents of low-income communities is spatially constrained.

The equity problem is also serious. Let us consider two similar households, each with an income of $30,000, one residing in community A with a local tax base of $10,000 per capita and the other in community B with a local tax base of $40,000 per capita. For the sake of illustration, assume both communities impose only a tax on income to raise local revenues. In order to spend $2,000 per capita in public services, community A would have to impose a tax rate of 20 percent on income, and community B would have to impose a tax of only 5 percent. The $30,000 household in the lower-income community would thus face a tax of $6,000, and the $30,000 household in the wealthier community would face a tax of only $1,500. This clearly fails the test of horizontal equity.

Now consider a poor household with an income of $15,000 in community A and a middle-class household with an income of $40,000 in community B. In order to receive the same $2,000 of services per capita, the poor household in community A would have to pay $3,000 in taxes, and the wealthier household in community B would have to pay only $2,000. In short, poor people living in lower-income communities must pay a higher proportion of their income, in this example, a larger absolute amount of income, than wealthier people in more prosperous communities in order to receive the same level of spending on services. Thus, the test of vertical equity is also failed.

The fiscal system in metropolitan areas operates either to reduce the income of residents of low-income communities relative to those of wealthier communities, thus contributing to disparities, or to reduce the level of spending on public services financed out of local revenues, with negative effects on life chances.

It is true that the tax/service disparities described above are moderated to some extent by the capitalization of the relative taxes into house values (Oates, 1969; Hamilton, 1975). Thus, the purchase price of a house in a high-tax/low-service area would be lower than that of a similar house in a low-tax/high-service area. However, capitalization of these fiscal factors into house values are unlikely to fully offset tax/service disparities. In addition, they serve to reduce the wealth of existing owners of homes in central cities, most of whom, as the result of selective out-migration, have low and moderate incomes. As the tax burden of central-city residents increases and public services deteriorate, the value of the homes of existing homeowners declines to reflect these changes, thus bringing about a real decline in the value of their capital assets.

There has been relatively little research on intrametropolitan fiscal disparities, although Ladd and Yinger (1991) have shown that fiscal disparities among large cities are substantial. Empirical studies are fraught with difficulty. Obviously gross differences in own-source revenues and spending reflect differences among communities in preferences and in the efficiency with which services are provided, as well as differences in tax capacity and expenditure need. Further-

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
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more, communities may export taxes to those outside the area, so that own-source revenues may not always come from local residents. In addition, disparities due to tax base and expenditure need may be reduced to some extent through aid from higher levels of government. (For a more extensive discussion of this, see Ladd, 1994a, 1994b). Finally, as Pagano points out (this volume), most disparity studies have not taken into account the increasing reliance of local governments on fees and services and the effect of proliferating residential community associations and their ''voluntary'' contributions on service receipt and taxpayer burden.

One study calculated estimates of fiscal capacity for a sample of general-purpose local governments in the Chicago metropolitan area for 1987 (Rafuse, 1991). Own-source revenue-raising ability was estimated by calculating how much revenue each local government would raise from each of 10 separate categories of revenues (e.g., property tax, sales tax, fees, and charges) if they were to levy rates at the average level for all governments in the area. Representative expenditure need was estimated by calculating what it would cost each local government to provide a standard (average) set of local public services, given the underlying socioeconomic and demographic composition of the community (and assuming the average level of efficiency for local governments in the area. Both the revenue and the expenditure capacity estimates were indexed to the average for the entire metropolitan area, so that the average overall fiscal capacity value was 100. An overall fiscal capacity index was created by dividing the own-source general revenue index for a local government by its index of representative expenditures.

Using this mechanism, the city of Chicago had an own-source general revenue index of 80 and an index of expenditure need of 111; this yielded an overall index of fiscal capacity of 72 (28 percent below the average for the metropolitan area). However, when Rafuse factored in federal and state grants and added them to own-source revenue, Chicago's index of fiscal capacity rose to 87, still 13 percent below the average for local governments in the metropolitan area. By contrast, Evanston's overall index of fiscal capacity (including federal and state grants) was 117, Lake Forest's was 266, and Winnetka's was 207. Several lower-income suburbs had fiscal capacity indexes considerably lower than Chicago's: Maywood's was 54, North Chicago's was 60, and Burbank's was 68.

Unfortunately, similar data are not available for a broad range of metropolitan areas. However, a similar analysis was performed for all municipal governments with populations over 2,500 in the state of Wisconsin for 1987-1991 (Green and Reschovsky, 1994). Using a slightly different methodology, Green and Reschovsky construct a need-expenditure gap similar to Rafuse's fiscal capacity index. The need-capacity gap for the "average" city was set at 0. Milwaukee had a gap between needed expenditures and revenue-raising capacity of $111 per capita after taking into account intergovernmental aid. Some other older suburbs also had very high gaps. These included Cudahy ($148), South Milwaukee ($143), and West Allis ($67). By contrast, many of Milwaukee's suburbs had

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
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negative need-capacity gaps: Brookfield (-$249), Glendale (-$198), Menomonee Falls (-$114), Whitefish Bay (-$102), and Wauwatosa (-$47).

Causes of Tax/Service Disparities

Why is there variation among citizens in a metropolitan area with respect to the local tax burden they face and the level and quality of local public services they receive? The first and most obvious reason is because, in virtually all metropolitan areas in the United States, there are many separate local governments, each with its own authority (albeit constrained authority) to make taxing and spending decisions and each highly dependent on its own local tax base for its revenues. As a consequence, residents in different local jurisdictions will naturally face variations in the tax rates they pay and in the level and type of services they receive.

As has been noted, these variations occur for a variety of reasons, including differences in preferences and in local government efficiency as well as differences in fiscal capacity. However, it is the differences in fiscal capacity with which we are here concerned. Fiscal capacity differences can reflect differences in both revenue-raising capacity and in expenditure needs.

Differences in the revenue-raising capacity of local governments (defined as the amount of revenue each local government could raise from various tax bases—the major ones are property, sales, and earnings—if it imposed a standard tax burden on its residents) arise for two reasons, according to Ladd (1994a:238); there are "differences in the average per capita income of residents and differences in the ability of cities to export tax burdens to nonresidents. For example, at the standard tax burden a city with richer residents can raise more revenue per resident from its residents than can a city with poorer residents. And a city with a large proportion of its property tax base in the form of business property, with a large proportion of its retail sales to nonresident commuters or tourists, or with a large proportion of earnings generated in the city accruing to nonresident commuters, can substantially increase its revenues by exporting tax burdens to nonresidents."

Differences in the expenditure needs of local governments (defined as the amount of money local governments must spend in order to achieve a standardized package of public services) reflect differences in the costs they face of providing public services. Costs may vary because of differences in input costs, such as the market-determined costs of attracting workers, and because of environmental factors (Ladd and Yinger, 1991). Environmental factors include both the composition of the population (a local government with a higher proportion of school-age children in the population will have greater expenditure need for education than will one with a lower proportion) and because of the difficulty in providing services (e.g., a local government with social and economic conditions

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
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that breed crime will have to spend more on police protection than will a typical upper-middle-class suburban community).

Using regression analysis to determine the impact of various environmental conditions on the cost of providing average levels of public service, Ladd reports that (1994a:239) "poverty, for example, has a big impact on the costs of providing public safety. A city with a poverty rate 1 percentage point higher than that of another city will have police costs that are 5.5 percent higher on average. Furthermore, a city with a poverty rate one standard deviation above the 1982 mean must pay 36.4 percent more for police services than a city with average poverty. The size of a city, as measured by its population, and the amount of its economic activity, as measured by private employment per capita, also increase the costs of public services."

It is clear that, given their population characteristics, central cities are likely to have both low standardized revenue-raising capacity and high expenditure needs. Suburbs may vary, with poorer, inner-core suburbs increasingly resembling central cities with respect to relative fiscal disparities or even being worse off, and with higher-income suburbs at the top end.

The actual fiscal condition of a city reflects not only its standardized revenue-raising capacity and expenditure needs, but the actual set of fiscal institutions it operates under (Ladd and Yinger, 1991). Local governments are constrained by their state with respect to the kinds of taxes they are actually permitted to levy and the rate at which they can levy them (see Pagano, this volume:Table 5, for variations among states in the extent to which they permit local governments to levy income and sales taxes); they may also be constrained by state limitations on the total amount of taxes they can raise or expenditures they can make. As Pagano notes, a city that is prohibited access to an earnings or income tax that can be imposed on nonresident employees who work in the city will find itself in a poorer revenue-generating position than one that is permitted to do so.

State governments also set forth the service responsibilities for local governments. Local governments with a broader range of service responsibilities will have greater expenditure needs than those with a narrower range of responsibility. Although most large city governments do not have responsibility for financing welfare, there are some, such as New York City, that do. The activity of overlying units of local government also affects the actual fiscal condition of a specific local government: the greater the taxes levied by overlying units of government, the less revenue-raising capability exists for the local government. Finally, actual fiscal condition is also affected by the amount of state and federal aid that a local government receives, since such aid makes up, to some extent, for the gap between local revenue-raising capacity and expenditure need.

Ladd and Yinger found substantial variations in actual fiscal health among large cities across metropolitan areas. Some of these variations reflect differences that are likely to be greater among metropolitan areas than within metropolitan areas, which is our concern. Thus, for example, differences facing local

Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
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governments in the cost of labor are likely to be smaller within a metropolitan area, and state fiscal rules conditioning local government behavior (taxes allowed, tax and expenditure limits) and defining service responsibilities are likely to vary much less among jurisdictions within a metropolitan area.

Thus, differences in state-imposed fiscal rules may explain the extent of fiscal disparities among local governments across metropolitan areas, particularly the relative fiscal health of cities. Pagano notes (this volume) that only 11 states permit some of their local governments to levy an income tax on nonresidents or a payroll tax on employees, regardless of residence. In most cases, the ability to levy such taxes is severely limited to the very largest municipal governments, although Ohio and Pennsylvania permit large numbers of municipalities access to these taxes.14

Notes

    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

    Suggested Citation:"3 Disparities in Outcomes." National Research Council. 1999. Governance and Opportunity in Metropolitan America. Washington, DC: The National Academies Press. doi: 10.17226/6038.
    ×

         

      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.

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      Governance and Opportunity in Metropolitan America Get This Book
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      America's cities have symbolized the nation's prosperity, dynamism, and innovation. Even with the trend toward suburbanization, many central cities attract substantial new investment and employment. Within this profile of health, however, many urban areas are beset by problems of economic disparity, physical deterioration, and social distress.

      This volume addresses the condition of the city from the perspective of the larger metropolitan region. It offers important, thought-provoking perspectives on the structure of metropolitan-level decisionmaking, the disadvantages faced by cities and city residents, and expanding economic opportunity to all residents in a metropolitan area. The book provides data, real-world examples, and analyses in key areas:

      • Distribution of metropolitan populations and what this means for city dwellers, suburbanites, whites, and minorities.
      • How quality of life depends on the spatial structure of a community and how problems are based on inequalities in spatial

        opportunity--with a focus on the relationship between taxes and services.

      • The role of the central city today, the rationale for revitalizing central cities, and city-suburban interdependence.

      The book includes papers that provide in-depth examinations of zoning policy in relation to patterns of suburban development; regionalism in transportation and air quality; the geography of economic and social opportunity; social stratification in metropolitan areas; and fiscal and service disparities within metropolitan areas.

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