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The Geography of Economic and Social Opportunity in Metropolitan Areas Keith R. Ihlanfeldt Georgia State University Much has been written lately concerning the "geography of opportunity," which most commonly means that "where individuals live affects their opportunities and life outcomes" (Rosenbaum, 1995:231). Although this is certainly not a new idea (see, for example, Kain and Persky, 1969), it has received a revival of interest as the result of the writings of William Julius Wilson (1987, 1996). Wilson maintains that an urban underclass population has grown rapidly in central-city ghettos as the result of an erosion in economic opportunities in these areas and the exodus of working-class and middle-class blacks to better neighborhoods. More generally, there is concern that a continuing high level of racial segregation and increasing income segregation in metropolitan area housing markets have increased the proportion of poor people residing in "bad" neighborhoods, in the sense that the latter offer poor proximity to available jobs, inferior schools, and negative neighborhood effects.1 If the geography of opportunity has indeed worsened over time for less educated and minority households, this may help to explain growing income inequality among racial and educational groups documented at the national level (Levy and Murnane, 1992). The purposes of this paper are fourfold. First, I review what is known about the relationships between residential location and the economic and social prospects of individuals. Location both in and among metropolitan areas is considered. Second, policy solutions to unequal spatial opportunities are reviewed in light of considerable new evidence that has surfaced in recent years. Third, scholars have generally overlooked the role that the system of local government may play in influencing the residential location/opportunity nexus; the effects of local government fragmentation on the latter as well as on possible policy solu-
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tions are discussed. Finally, since there are major gaps in knowledge in all three of the above areas, suggestions are made regarding future research needs. Spatial Inequality in Economic Welfare Before considering the hypothesized links between residential location and opportunities, some documentation of the spatial inequalities that these links purport to explain is in order. Table 1 reports unemployment rates and rates of nonparticipation in the labor force for central-city and suburban residents, respectively; Table 2 shows real median family income for these areas. Unemployment rates were only slightly higher among central-city residents for both blacks and whites in comparison to their suburban counterparts in 1970. However, unemployment rate differences between central-city and suburban residents grew during both the 1980s and the 1990s for both racial groups, but this growth was more than four times greater for blacks than whites. In 1990 unem- TABLE 1 Unemployment Rates and Nonparticipation Rates Inside and Outside Central Cities of Metropolitan Statistical Areasa Inside Central Cities Outside Central Cities 1970 1980 1990 1970 1980 1990 Unemployment Rate All races, both sexesb 4.7 7.3 7.8 3.9 5.7 5.0 White, both sexes 4.1 5.7 5.7 3.7 5.4 4.5 Male 3.8 5.9 6.0 3.2 5.3 4.6 Female 4.4 5.4 5.4 4.5 5.4 4.4 Black, both sexes 6.9 12.8 14.4 6.4 9.6 9.5 Male 6.7 13.9 15.9 5.8 9.7 9.8 Female 7.3 11.7 13.2 7.2 9.4 9.1 Rate of Nonparticipation in Labor Force, Workers Aged 25-64c All races, both sexesb 30.0 26.6 22.3 30.8 25.6 19.2 White, both sexes 29.6 25.6 20.3 30.8 25.7 19.7 Male 8.6 11.6 11.8 6.0 8.9 9.4 Female 49.0 39.0 28.7 54.5 41.9 29.8 Black, both sexes 30.0 28.9 27.0 29.4 23.6 21.0 Male 14.3 20.2 22.6 15.7 16.3 18.9 Female 42.9 35.7 30.6 41.8 30.2 23.0 a Update of Table 11.6, p. 293, Urban Economics and Public Policy by James Heilbrum, St. Martin's Press, 1987. b "All races" includes white, black, and others not shown separately. c Rate of nonparticipation equals the number of persons not in the labor force divided by the total population for the designated age group. Sources: U.S. Bureau of the Census, Census of Population: General Social and Economic Characteristics, 1970, Tables 107, 112, 124, and 126; 1980, Table 144; 1990, Tables 33, 69, and 70.
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TABLE 2 Median Family Income by Race Inside and Outside Central Cities of Metropolitan Statistical Areasa Median Family Incomeb (1985 Dollars) 1959 1969 1979 1989 1995 Central Cities All racesc 21,752 27,515 26,801 26,655 24,292 White 23,112 29,472 29,560 30,538 27,303 Black 14,193 19,245 17,183 16,716 16,373 Outside Central Cities All racesc 24,490 32,417 33,992 35,431 33,648 White 24,886 32,895 34,556 37,871 34,315 Black 12,853 20,298 22,294 25,010 24,164 a Update of Table 11.7, p. 294, Urban Economics and Public Policy by James Heilbrum, St. Martin's Press, 1987. b Income in the year shown for families by place of residence in the following year. c Includes other races not shown separately. Sources: U.S. Bureau of the Census, Current Population Reports, series P-23, no. 37, June 24, 1971, Table 7; series P-23, no. 75, November 1978, Table 17; series P-60, no. 180, November 1992, Table 13; series P-60, no. 193, October 1996. ployment rates were 4.9 and 1.2 percentage points higher in central cities for blacks and whites, respectively. The central-city unemployment rate was especially high for black males (16 percent). Rising central-city unemployment rates may illustrate only a portion of the labor market disadvantage associated with a central-city location, since many blacks living in central cities are believed to be "discouraged workers" (i.e., workers who have become so discouraged by their inability to find work that they dropped out of the labor force entirely). Discouraged workers are not counted as being unemployed, because they have stopped searching for work. The rates of labor force nonparticipation, which capture discouraged workers but also those with other reasons for not looking for work, tell a similar story to that of unemployment rates, i.e., there has been little change in the nonparticipation rate difference between whites living in central cities and suburbs, whereas there have been substantial increases in the nonparticipation rates of both central-city black males and black females relative to their suburban counterparts. Finally, as was true for unemployment and nonparticipation rates, there has been a growing gap in real median family income between central-city and suburban residents over time (for income the data cover a longer period, 1959-1995). Although the growth in the gap in dollar magnitude was comparable between whites and blacks, due to the lower average income of blacks the central city-suburban income
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difference in percentage terms was roughly twice as large for blacks as whites in 1995. In summary, regardless of the indicator, spatial differences are becoming greater over time for both blacks and whites living in metropolitan areas. But for blacks these differences have grown much more rapidly. The observed growth in spatial differences may reflect two possible phenomena: (1) the labor market outcomes for central-city residents may be worsening relative to those of suburban residents and (2) people with better labor market outcomes may be choosing with greater frequency a suburban over a central-city residential location. Since the data presented in Tables 1 and 2 are consistent with both of these possible scenarios, they suggest but do not demonstrate the existence of a causal link between residential location and opportunity. Residential Location and Opportunity: the Links Numerous specific hypotheses relate residential location either in or among metropolitan areas to the opportunities and life outcomes of individuals; however, these purported linkages share two assumptions: (1) that there are spatial variations in the resources offered by markets and/or institutions in or across metropolitan areas and (2) that households have unequal ability to reside in locations where they deem these markets and institutions to be most desirable (Galster and Killen, 1995). The various hypotheses that link location and social and economic prospects differ in that they focus on different markets and/or institutions. They can also be distinguished by whether they focus on intraversus intermetropolitan location. In this section, these hypotheses are first stated and discussed. The empirical evidence related to each hypothesis is then reviewed with an eye toward identifying conclusions for which there seems to be some agreement. Hypotheses dealing with the relationship between intrametropolitan location and opportunity are considered first, followed by those that relate opportunity to intermetropolitan location. The Spatial Mismatch Hypothesis Certainly, the most researched hypothesis relating intrametropolitan location to economic opportunity is commonly labeled the "spatial mismatch hypothesis." This hypothesis states that the suburbanization of jobs and involuntary housing market segregation have acted together to create a surplus of workers relative to the number of available jobs in central-city neighborhoods where blacks are concentrated. The spatial mismatch hypothesis, which was first advanced by John Kain way back in 1968, has recently enjoyed a comeback after many years of dormancy. The revival of interest in it can be attributed to a number of factors (Ihlanfeldt, 1994), but probably the most important is Wilson's (1987) and Kasarda's (1989) emphasis on job decentralization as a causative factor in the
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growth of the underclass.2 As mentioned above, a common element of all hypotheses that relate residential location to opportunity are the assumptions that resources are spatially nonuniform and residential mobility is differentially constrained. In the case of the spatial mismatch hypothesis as originally formulated, the resource that varies is job accessibility, and the residential mobility constraint is the inability of blacks to follow jobs to the suburbs because of racial discrimination in the suburban housing market. However, Ihlanfeldt and Sjoquist (1989) have argued that spatial mismatch may also affect the labor market opportunities of low-skilled white workers, since they too are constrained in their ability to follow jobs to the suburbs by a relative scarcity of affordable housing units in those suburban areas where job growth is occurring.3 The surplus of workers in central-city neighborhoods that results from spatial mismatch may reduce the economic welfare of these workers by making it more difficult to find work, by reducing wage rates in the central city relative to suburban areas, or by increasing commuting costs. All of these possible effects, which may occur alone or in combination, translate into the same outcome—namely, lower net annual earnings for central-city blacks and less educated whites. From a policy perspective, an important issue is why spatial mismatch would persist in the long run. Spatial mismatch implies a labor market disequilibrium that should be eliminated by market forces. Although racial discrimination in the housing market and high suburban housing costs may permanently keep less educated workers from residentially relocating to the suburbs, disequilibrium can still be eliminated by either labor demand increases in the central city or by workers shifting their labor supply to the suburbs by making a reverse commute. However, both of these adjustment mechanisms may be short-circuited. Regarding the former mechanism, it is frequently argued that the relative magnitudes of taxes, insurance premiums, land costs, skilled workers' wages, and congestion diseconomies may work against businesses selecting a central-city location, even if low-skilled labor costs are lower there than elsewhere due to spatial mismatch. The reverse-commuting mechanism may fail to work for a wide variety of reasons. These include the time and out-of-pocket costs associated with the commute, the possibility that central-city workers do not have knowledge of suburban job openings, greater hiring discrimination in the suburbs, the physical inaccessibility of many suburban job sites by public transit, and blacks' anticipation of being mistreated by suburban whites. Neighborhood Effects Under the rubric of "neighborhood effects" falls a variety of mechanisms that link the neighborhood milieu to individual behaviors and opportunities. The nature of these mechanisms are the subject of considerable debate among social scientists. The purpose here is not to provide an exhaustive review of this debate
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but rather to highlight those channels of neighborhood influence that seem most plausible and susceptible to policy intervention. One list of possible neighborhood effects is provided by Jencks and Mayer (1990b) in their survey of the empirical literature. Their list includes peer influences, indigenous adult influences, and outside adult influences. Peer influences refer to the effects that peers have on one another's behavior. To be accepted by one's peer group, the individual adopts the same behaviors, whether good or bad, that characterize the group. Since behaviors considered "bad" according to establishment norms are more prevalent in poor neighborhoods, individuals living in such neighborhoods are more likely to be induced by peers to engage in self-destructive or antisocial activity. The individual's susceptibility to peer group effects is believed to vary with age, with young people, especially teenagers, being most at risk. Indigenous adults in the neighborhood may also affect individual behaviors by serving either as role models or "enforcers" of public order and decency. Once again, the nature of these effects is thought to vary between poor and affluent neighborhoods, with the former containing fewer positive role models and involved enforcers of community standards. Among the neighborhood effects identified by Jencks and Mayer, it has been this particular type of effect—the influence of indigenous adults—that has received the most attention in policy discussions. This does not stem from any evidence regarding the strength of this effect relative to others, but rather from the influential writings of Wilson (1987), who argues that the migration of working-class and middle-class blacks from ghettos has left these areas without mainstream role models. He believes that the resulting concentration of poverty has played an important role in the growth of social pathologies in the black community. In addition to serving as role models, Wilson emphasizes that middle-class blacks are the chief supporters of mainstream institutions, such as churches and schools. As successful people have left the ghetto, these neighborhood institutions have undergone a severe deterioration in quality. The final neighborhood effect identified by Jencks and Mayer is adults living outside the neighborhood who may indirectly influence behaviors and opportunities in the neighborhood. This presumably occurs as the result of more qualified providers of public services preferring to work in better neighborhoods. Hence, this factor may contribute to other possible causes, resulting in the inferior schools, police forces, and other neighborhood institutions found in poorer neighborhoods. Of course, privately provided goods and services in poorer neighborhoods may suffer in quality for this reason as well. In addition to the neighborhood effects listed by Jencks and Mayer, there are two other possibly important linkages that can be mentioned. First, results from the Gautreaux program (Rosenbaum, 1995) suggest that many ghetto and public housing residents may be unwilling to work out of fear that they will be victimized while traveling to and from work, robbed of their rewards from working, or
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their unsupervised children will get hurt or get in trouble with gangs. (The Gautreaux program is reviewed in the next major section.) Second, informal sources of job market information, which are heavily relied on by less educated workers in searching for jobs (Holzer, 1987), may vary in quality between good and bad neighborhoods. Wilson (1987) argues that people living in underclass neighborhoods have poor information about legitimate jobs because they lack contact or interaction with individuals and institutions that represent mainstream society. I have argued (Ihlanfeldt, 1997) that Wilson's hypothesis can be couched in terms of the decision to invest in the acquisition of labor market information. In underclass neighborhoods, fewer people make the investment in information about jobs because fewer people choose to participate in the labor force. There is therefore a lower probability that one's neighbors will have accurate information to share on the spatial distribution of available jobs. However, the influence of neighborhood is more complicated than Wilson's hypothesis suggests. Although labor force participation is lower in underclass neighborhoods, among those who do participate there is likely to be a greater investment in obtaining information about jobs that less educated people would be qualified to hold. In affluent neighborhoods, there may collectively be a dearth of information on these types of jobs, simply because the typical resident has some postsecondary education and is employed where few workers are hired into blue-collar or service occupations. It is therefore unclear whether less educated people obtain more useful information about the labor market from their neighbors if they live in better (i.e., more affluent) neighborhoods. The attention that social scientists have given to these neighborhood effects has increased in recent years, since decennial census data indicate that poor people are increasingly isolated from nonpoor people in metropolitan areas. For example, Abramson et al. (1995) found that poor households became 13 percent more segregated from 1970 to 1990 in the 40 largest metropolitan areas, and Kasarda (1993) shows that in the 100 largest cities the share of the poor living in tracts with a poverty rate over 40 percent increased from 16 to 28 percent over this same time period. The growth in the likelihood that an individual poor person has mostly poor neighbors suggests that negative neighborhood effects are having a greater influence on the opportunities and life outcomes of poor people today than was true in the past (Wilson, 1987). Educational Opportunity As alluded to above, all of the neighborhood effects identified by Jencks and Mayer—peer influences, indigenous adult influences, and outside adult influences—may cause differences in educational opportunities between poor and nonpoor neighborhoods. Peer influences may act to reduce learning opportunities in poor neighborhoods by depriving poor students of the possible benefits of being surrounded by smart and motivated students. The adults who reside in poor
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neighborhoods may devote less time and money toward the support of neighborhood schools and the enforcement of antitruancy laws. Finally, poor neighborhoods may repel more qualified teachers and school administrators. In addition to educational differences arising from neighborhood effects, educational opportunities may also vary across school districts due to interdistrict fiscal disparities. These disparities are particularly severe between central cities, where the poor are concentrated, and white suburban areas (Bahl, 1994). Moreover, there is evidence that these disparities have grown worse over the past decade (Bahl et al., 1992). The conventional wisdom is that resources spent on education have little effect on observed educational outcomes (Hanushek, 1986), but Card and Krueger (1996) have questioned this conclusion in their recent review of the empirical literature. They note that several meta-analyses—quantitative summaries of the estimates in the literature—suggest that greater resources do in fact lead to higher test scores. More important, they conclude that school resources positively affect long-term outcomes like educational attainment and earnings. Intermetropolitan Location and Opportunity In comparison to the linkages that may exist between intrametropolitan location and opportunities, possible effects of intermetropolitan location on opportunity have received far less attention. Nevertheless, a number of new theories suggest that the economic and social prospects of specific groups may vary among metropolitan areas due to differences in growth rates or levels of housing segregation. Local shifts in labor demand that disturb the steady-state relationship among the unemployment rates of metropolitan areas may cause intermetropolitan differences in the employment and earnings opportunities of indigenous residents. However, the conventional wisdom has been that these differences would be eliminated in the long run because immigration returns all areas to equilibrium. However, Bartik (1991) argues that increases in local labor demand may have beneficial long-run effects on the human capital of indigenous workers, since growth may cause firms to promote their workers to higher-paying jobs more rapidly. Growth may also shorten unemployment durations among local residents, decreasing the likelihood that their human capital will be eroded by inactivity. If blacks or poor people are concentrated in slower growth areas, these so-called hysteresis effects may play a role in explaining the growth in income and racial inequality at the national level.4 Neighborhood effects and spatial mismatch imply that blacks living in segregated areas are worse off than blacks living in integrated or predominately white areas. Cutler and Glaeser (1995) have espoused the idea that housing segregation hurts all blacks equally in the same metropolitan area whether they live inside or outside the ghetto. They label their idea "the weak form of the spatial mismatch
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hypothesis'' (1995:3): ''This form of the hypothesis does not specify the mechanism relating segregation to poor outcomes, and does not assume that black mobility is constrained. With unconstrained mobility, we would expect outcomes for equivalent people to be equalized across locations in a single city, so that all minorities regardless of location will be hurt by segregation." Cutler and Glaeser's version of the spatial mismatch hypothesis implies that the welfare of blacks residing in more segregated metropolitan areas is worse in comparison to those living in less segregated areas, other things being equal. Evidence on the Spatial Mismatch Hypothesis More than 60 studies have provided evidence on the spatial mismatch hypothesis. In the early 1990s, six different reviews of the literature were published (Wheeler, 1990; Jencks and Mayer, 1990a; Moss and Tilly, 1991; Holzer, 1991; Kain, 1992; Ihlanfeldt, 1992). With the exception of Jencks and Mayer, these reviews concluded that the weight of the empirical findings provided either strong (Kain, Ihlanfeldt) or moderate (Wheeler, Moss and Tilly, Holzer) support for the hypothesis. Jencks and Mayer, in contrast, concluded that "support [for the idea that job proximity increases the supply of black workers] is so mixed that no prudent policy analyst should rely on it" (1990a:19). Since the above reviews were written, roughly a dozen new studies have been completed in this area. In general, these studies use more suitable data and superior methodologies than earlier studies and therefore provide the most reliable evidence to date on the spatial mismatch hypothesis. Since Ihlanfeldt and Sjoquist (1998) have already provided a detailed review of each of these new studies, the approach here will be twofold: (1) to summarize the results of these studies and (2) to highlight a couple of studies that provide particularly noteworthy evidence on the spatial mismatch hypothesis. Of the new studies providing evidence, only two reject the hypothesis (Taylor and Ong, 1995; Cooke, 1997). However, neither of these studies deals with the endogeneity of residential location, which is the most common methodological error that has plagued empirical investigations of the spatial mismatch hypothesis (Ihlanfeldt, 1992). The hypothesis implies that job accessibility affects labor market outcomes, but both the standard theory of residential location (Muth, 1969) and existing evidence (Ellwood, 1986) indicate that commuting distances rise with earnings.5 Hence, earnings and proximity to jobs are jointly determined. The failure to account for this simultaneity results in the underestimation of the true effect of job accessibility on labor market outcomes (Ihlanfeldt, 1992). One approach to handling the simultaneity between employment/earnings and residential location is to focus the analysis on youth. still living at home, based on the assumption that for them residential location is exogenously determined by their parents or guardians. The convenience of this approach explains why so many studies of spatial mismatch have focused exclusively on youth.
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Among recent studies, Cutler and Glaeser (1995), Holzer et al. (1994), Holloway (1996), O'Regan and Quigley (1996), and Raphael (1998a, 1998b) reinforce the earlier finding of Ihlanfeldt and Sjoquist (1990) that job accessibility has an important effect on the probability that youth have jobs. In his assessment of the spatial mismatch literature in 1992, Kain concluded that most studies of spatial mismatch have focused on males and that more research was needed on females. Two of the recent studies have responded to this need by providing estimates for females (Thompson, 1997; Kasarda and Ting, 1996). Kasarda and Ting find that spatial mismatch has a stronger effect on the joblessness of women than men, regardless of race. They suggest that this may reflect women's more complex travel patterns and greater domestic responsibilities, both of which make them less able to commute to distant jobs. Although Thompson focuses exclusively on females and therefore provides no gender comparisons, his results are consistent with those of Kasarda and Ting's, in that he finds that job access strongly affects the labor force participation rates of white, black, and Hispanic women.6 As noted above, spatial mismatch may affect the employment and earnings of less educated whites as well as blacks. The findings of Holloway (1997), Kasarda and Ting (1996), and Ihlanfeldt and Young (1994) all lend support to this expectation. The last study is of particular interest, since it provides some rare evidence on differences in wage rates between workers employed by central-city and suburban firms. As predicted by the hypothesis, the wage rates of both black and white fast-food restaurant workers are found to be significantly greater in the suburbs than in the central city, after controlling for a lengthy list of individual and establishment characteristics. Among the recent studies, those by Raphael (1998b) and Rogers (1997) merit special consideration. Using 1990 census tract level data for San Francisco, Raphael regresses male youth employment to population ratios on a set of geographically defined job accessibility measures, a geographically defined competing labor supply variable, and variables describing the demographic composition of the neighborhood. This approach follows the basic methodology employed earlier by Ellwood (1986) and Leonard (1986). The latter two studies have played a major role in the spatial mismatch debate because each finds that racial differences in youth employment rates have little to do with job accessibility.7 The distinguishing characteristic of Raphael's model is that his access measure, which is obtained by estimating a gravity equation, is based on the change in jobs rather than the number of jobs in a specified commute of each census tract. He persuasively argues that proximity to employment growth comes closer than proximity to employment levels to the ideal measure of job accessibility, namely, the number of job openings per worker. The estimated effects of his job access variables have the expected signs and are highly significant. Moreover, contrary to the results of Ellwood and Leonard, when Raphael adds his job access variables to an equation that includes the
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proportion of the census tract's residents who are black, the coefficient on the latter variable falls precipitously. Differential accessibility is found to explain between 30 and 50 percent of the neighborhood employment rate differentials between average white and black male youth. It is remarkable that this range is nearly identical to the one found earlier by Ihlanfeldt and Sjoquist (1990) using 1980 data for Philadelphia. Raphael presents other results that may go a long way toward resolving the spatial mismatch debate, at least as it applies to youth. When he reestimates his models using Ellwood's and Leonard's employment level-based measures of job accessibility, he reproduces their insignificant results. Rogers analyzes the relationship between unemployment duration and job accessibility. This study is unique in that her data allow her to address the simultaneity problem between employment and residential location using a sample of males ages 18 to 55 residing in the Pittsburgh area who have submitted unemployment insurance claims. Hence, the results of this study provide some rare and seemingly reliable evidence on the spatial mismatch hypothesis as it applies to the employment of adults. She argues that simultaneity is not a problem for her sample because the residential location of laid-off workers is based on previous job location. Her measures of job access are essentially the same as those employed by Raphael; that is, gravity variables that measure either the worker's proximity to employment change or employment levels. Also consistent with Raphael are her findings that indicate employment change-based measures of access have a statistical effect on unemployment duration, whereas employment level-based measures do not. An increase of one standard deviation in the mean value of her access to job growth variable is found to decrease expected unemployment duration by about five weeks. In summary, there is now rather convincing evidence that job accessibility plays an important role in explaining the large differences that exist in the employment rates of black and white youth living in large metropolitan areas. Even Jencks and Mayer (1990a) and later Jencks (1992) alone concede this point in their otherwise critical review of the spatial mismatch literature, and this review was written prior to the excellent studies by Raphael (1998a, 1998b). But what can be concluded concerning the role that spatial mismatch plays in explaining racial differences in youth employment rates in smaller metropolitan areas? These differences are only modestly smaller than those for larger metropolitan areas (Ihlanfeldt, 1992). Unfortunately, none of the recent studies reviewed above addresses this issue. In fact, among all studies, only Ihlanfeldt (1992) provides separate estimates for metropolitan areas of different population sizes. These results suggest that the importance of job access as both a determinant of youth job probability and as an explainer of racial employment gaps is directly proportional to metropolitan area size. In fact, essentially no importance is found for metropolitan areas of less than 1 to 1.5 million people. As noted above, due to the simultaneity problem between employment/earn-
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they should probably be answered before proceeding with any new costly social experiments. Research on Linkages The policy prescriptions for arresting negative neighborhood effects and spatial mismatch in the labor market overlap but do not coincide. It is therefore important to sort out the relative importance of these alternative linkages between residential location and opportunities. Moreover, as noted above, few studies have modeled neighborhood effects and job accessibility together, which suggests that a large portion of the results reported in the literature may be biased by omitted variables. Now that individual-level data are becoming available that identify the person's neighborhood location, much can be learned by estimating fully specified models of social and economic outcomes.26 Research on Policies There has been great interest, even excitement, among both scholars and policy makers in the success of the Gautreaux program.27 However, the effectiveness of all residential mobility programs—Gautreaux-type, antidiscrimination, and antiexclusionary—is jeopardized by the possible flight of incumbent suburban residents as their neighborhoods are infiltrated by the poor or minorities. Opening up the suburbs to central-city residents will have little long-run effect on their opportunities if stable, integrated neighborhoods cannot be achieved.28 The causal factors that underlie the white flight response (as well as the unwillingness of whites to move into changing neighborhoods) have not been clearly identified. Racial and income prejudice, concerns over property values and student peer group effects, as well as other factors may all play a role and need to be studied. More work, along the lines begun by Ellen (1996) comparing the traits of racially stable and unstable neighborhoods, can be recommended, since such research may point toward policy solutions. Research on the System of Local Government Income and racial segregation at the neighborhood level are strong forces limiting the social and economic opportunities of the poor and minorities. The reasons outlined and evidence reviewed above suggest that there may be important relationships between the system of local government and neighborhood segregation. Research is needed that focuses on explaining the substantial differences that exist in the degree of housing segregation across metropolitan areas.29 Farley and Frey (1994) addressed this issue by regressing the metropolitan area's black-white dissimilarity index for 1990 on the region, the functional specialization of the area, the age of the area, the pace of new construction, and a set of
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demographic characteristics. Descriptors of the system of local government in the metropolitan area were not included. However, they suggest that their regional results, which indicate that metropolitan areas in the West and the South are far less segregated than those in the Midwest and Northeast, largely reflect the types of local government systems that characterize each region. They point to two differences that may be important. First, zoning and policing decisions tend to be made at the county level in the South but at the municipality level in the Northeast and Midwest. County-level governance may open up more suburban housing opportunities for the poor and minorities. Second, metropolitan areas in the South and the West have more permissive annexation laws than areas located in the Northeast and the Midwest. Annexation by central cities limits the amount of land in metropolitan areas that is governed by suburban governments practicing exclusionary zoning. Moreover, as noted earlier, annexation permissiveness may alter the incentives that higher-income households have to move from central cities to suburban areas. These hypotheses and possibly others should be honed theoretically and examined empirically by estimating models that include variables fully describing the system of local government in metropolitan areas. References Abramson, Alan J., Mitchell S. Tobin, and Matthew R. VanderGoot 1995 The changing geography of metropolitan opportunity: The segregation of the poor in U.S. metropolitan areas, 1970 to 1990. Housing Policy Debate 6(1):45. American Public Transit Association 1993 Access to Opportunity: A Study of Reverse Commuting Programs. Washington, DC: American Public Transit Association. Bahl, Roy 1994 Metropolitan fiscal disparities. Cityscape: A Journal of Policy Development and Research 1(1):293-306. Bahl, Roy, Jorge Martinez-Vazquez, and David L. Sjoquist 1992 Central-city suburban fiscal disparities. Public Finance Quarterly 20(4):420-432. Bartik, Timothy J. 1991 Who Benefits From State and Local Development Policies? Kalamazoo, MI: W.E. Upjohn Institute for Employment Research. 1993 Economic Development and Black Economic Success. Upjohn Institute Technical Report No. 93-001. Kalamazoo, MI: W.E. Upjohn Institute for Employment Research. 1994 The effects of metropolitan job growth on the size distribution of family income. Journal of Regional Science 34:483-501. Bishop, John H., and Suk Kang 1991 Applying for entitlements: Employers and the targeted jobs tax credit. Journal of Policy Analysis and Management 10(1):24-45. Boarnet, Marlon G., and William T. Bogart 1996 Enterprise zones and employment: Evidence from New Jersey. Journal of Urban Economics 40:198-215.
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Brewster, Karin L. 1994 Race differences in sexual activity among adolescent women: The role of neighborhood characteristics. American Sociological Review 59:408-424. Brooks-Gunn, Jeanne, Greg Duncan, and J. Lawrence Aber 1997 Neighborhood Poverty. Volume I: Context and Consequences for Children. New York: Russell Sage Foundation. Brooks-Gunn, Jeanne, Greg Duncan, Pamela Klebanov, and Naomi Sealand 1993 Do neighborhoods affect child and adolescent development? American Journal of Sociology 99:353-95. Burtless, Gary 1985 Are targeted wage subsidies harmful? Evidence from a large voucher experiment. Industrial and Labor Relations Review 39:105-114. Card, David, and Alan B. Krueger 1996 School resources and student outcomes: An overview of the literature and new evidence from North and South Carolina. The Journal of Economic Perspectives 10(4):31-50. Case, Anne C., and Lawrence F. Katz 1991 The Company You Keep: The Effects of Family and Neighborhood on Disadvantaged Youths. National Bureau of Economic Research Working Paper No. 3705, May. Cooke, Thomas J. 1997 Geographic access to job opportunities and labor force participation among women and African Americans in the Greater Boston Metropolitan Area. Urban Geography 18(3):213-227. Corcoran, Mary, Roger Gordon, Deborah Laren, and Gary Solon 1992 The association between men's economic status and their family and community origins. Journal of Human Resources 27(4):575-601. Crane, Jonathan 1991 The epidemic theory of ghettos and neighborhood effects on dropping out and teenage childbearing. American Journal of Sociology 96(5):1126-1159. Cutler, David M., and Edward M. Glaeser 1995 Are Ghettos Good or Bad? National Bureau of Economic Research Working Paper No. 5163, June. Downs, Anthony 1968 Alternative futures for the American ghetto. Daedalas Fall:1331-1378. 1992 Policy directions concerning racial discrimination in U.S. housing markets. Housing Policy Debate 3(2):685-742. 1993 Reducing regulatory barriers to affordable housing erected by local governments. In Housing Markets and Residential Mobility, G. Thomas Kingsley and Margery Austin Turner, eds. Washington, DC: The Urban Institute Press. 1994 New Visions for Metropolitan America. Washington, DC: The Brookings Institution. Drachman Institute 1992 Reverse Commute Transportation: Emerging Provider Roles. Prepared for the U.S. Federal Transit Administration by the University of Arizona. Duncan, Greg 1994 Families and Neighbors as Sources of Disadvantage in the Schooling Decisions of White and Black Adolescents. Working paper. Survey Research Center, University of Michigan. Eckert, Ross, and George Hilton 1972 The jitneys. Journal of Law and Economics 15:293-325. Edel, Matthew 1972 Development vs. dispersal: Approaches to ghetto poverty. Pp. 307-325 in Readings in Urban Economics, Matthew Edel and Jerome Rothenberg, eds. New York: Macmillan.
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taken from physics that refers to the time lag exhibited by a body in reacting to changes in the forces affecting it. 5 This fact is explained by the standard urban model if the income elasticity of housing demand exceeds the income elasticity of commuting cost. Alternatively stated, higher-income people may have longer commutes because they wish to consume more units of housing at a lower price. This explanation assumes that housing prices on average decline as distances to employment centers increase, which considerable empirical evidence suggests is the case (see, for example, Jackson, 1979). Other models suggest that higher-income workers travel farther to get to work because they are willing to trade commuting costs for either environmental amenities or better government services. 6 Kasarda and Ting find that their measure of job access—commute time of city residents for each racial group—has no effect on their outcome variables for black males, which unlike the rest of their results is inconsistent with the spatial mismatch hypothesis. However, all of their results may be underestimates of true effects, due to the crudeness of their access measure (which they acknowledge) and their failure to address the simultaneity between their endogenous variables and residential location. Thompson recognizes that simultaneity between labor force participation and job access may affect his results, but be believes the bias will be small, since the women in his sample have uniformly low earnings and household incomes, making it difficult for them to trade higher commuting costs for a more spacious home. 7 To quote Ellwood's often repeated aphorism, "The problem isn't space. It's race." 8 In comparison to adults, youth are less likely to have access to an automobile for commuting to work, they may place a higher value on their commuting time due to their school responsibilities, and have less information on distant jobs because of a greater reliance on informal sources of job information. 9 The results of Holzer et al. (1994) are also suggestive of information limitations. They find that black and white central-city youth do not offset greater job decentralization with greater distances traveled, for either search or work. 10 It should be noted that both of the regression studies use questionable measures of job accessibility. Both use variants of neighborhood mean commute times based on the reasonable assumption that a youth has better job access if he or she lives in a neighborhood where residents have to make only a short commute to get to work. However, neither study standardizes travel times for transportation mode and both use travel times to all jobs in computing means. Since there is considerable variation in travel times between public and private carriers and the spatial distribution of youth jobs differs from that of all jobs, the findings of Cutler and Glaeser and O'Regan and Quigley may understate the true effects of job access by a considerable amount. 11 The Gautreaux program does not admit families with more than four children, large debts, or unacceptable housekeeping. 12 More recent research by Bartik (1994) provides further support for this conclusion. He finds that metropolitan-area employment growth increases the income of households in the poorest income quintile by five times as much as the increase experienced by households in the richest quintile. 13 A fourth category of policies includes educational reforms, such as site-based management, charter schools, vouchers, and school choice. These reforms are not discussed here, since adequately covering them would extend this paper to unmanageable length. For a recent review of current issues in public urban education, see Picus, Lawrence O. 1996. Current Issues in Public Urban Education. Housing Policy Debate 7(4):715-730. 14 In fact, the dispersal (category three) versus development (category one) debate has been simmering and at times raging for over 25 years. Early participants in this debate include Kain and Persky (1969), Downs (1968), Edel (1972), and Harrison (1974). 15 Apparently, the problem with tax credits for targeted jobs is that they have a stigmatizing effect on members of the targeted group in the eyes of employers (Burtless, 1985; Bishop and Kang, 1991).
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16 Other place-based initiatives that could be listed are business retention and expansion programs focused on areas in central cities where jobs are most needed. Although a number of cities have such programs, no evidence could be located on their effectiveness. Nevertheless, their low cost in comparison to tax incentives and other types of programs designed to attract new firms makes these programs an attractive option. Downs (1994) recommends that city governments survey employers to see what problems they have and what can be done to solve them. 17 This approach is complicated by the heterogeneity of community development corporation employment programs. They may fare more or less well relative to urban enterprise zones depending on the specifics of their programs. 18 There was a series of reverse-commuting demonstration projects funded by the federal government in the 1960s. These projects produced at best only meager benefits. But these results may not be applicable today, since there have been major changes in the spatial distributions of jobs and people in metropolitan areas over the past 30 years. 19 Between 1915 and 1920 jitneys, which were private vehicles (mostly Ford Model Ts), profitably operated in many metropolitan areas throughout the United States (Eckert and Hilton, 1972). They had flexible destinations and carried multiple passengers, generally going to different but nearby locations. Their life in America was cut short by regulations passed by municipalities that made their costs of doing business prohibitive. Jitneys were put down in order to preserve streetcars, which were favored because, unlike jitneys, they were an important source of tax revenue for local governments. It was also believed that competition between streetcars and jitneys would make it impossible for streetcars to subsidize their longer routes from revenues generated by their shorter routes, which were rapidly losing patronage in favor of the faster, more convenient service provided by the jitneys. 20 Even with white flight, residential mobility policies will improve the job accessibility of minorities. Although retailing and personal services will follow whites to more distant suburbs, the immobility of capital will keep manufacturing jobs in those areas that undergo racial transition. 21 Other provisions include race-conscious counseling; housing centers that disseminate information on neighborhood change, provide counseling, and prevent the spread of rumors; and bonuses for metro-based organizations that work with several integrated communities. 22 Some additional evidence that whites' aversion to black neighbors in not based on pure racial prejudice is provided by Harris (1997). He estimates hedonic housing price equations and finds that the racial composition of the neighborhood is not a statistical significant explanatory variable, after controlling for nonracial characteristics of the neighborhood (e.g., percentage poor and percent affluent). 23 There is the possibility that Ellen's results reflect, at least in part, differences in prejudice between owners and renters and families with and without children. To the extent that this is true, policies to arrest structural decline will be less effective in achieving racially stable neighborhoods. 24 Cutler and Glaeser (1995) have also suggested that political fragmentation may impose an added cost on blacks trying to change neighborhoods because a different neighborhood may have different public goods and perhaps even public goods designed to discourage racial integration. Their examples of the latter are racist police officers and schooling designed particularly for white suburban residents. 25 Jargowsky studies the factors that determine what percentage of a metropolitan area's blacks will live in high-poverty census tracts. The latter are defined as tracts that have a poverty rate of 40 percent or higher and are commonly believed to contain the worst neighborhood effects. His regression model includes metropolitan-area mean household income, mean black income relative to overall mean income, measures of income inequality, and dissimilarity indexes to measure economic and racial segregation. The latter variable is found to have a strong and highly statistically significant effect on the percentage of blacks living in concentrated poverty. 26 For example, the Multi-City Study of Urban Inequality data identify respondents' home census tracts. Under special arrangements, tract identifiers can also be appended to the individual
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records of the Panel Study of Income Dynamics, the Public Use Microdata Samples, and the American Housing Survey.<End Popup Text> 27 The success of this program caused Congress in 1992 to fund a Gautreaux-type program, called Moving to Opportunity, which was initiated in five cities in 1994. The program encountered severe opposition in the suburbs of Baltimore, one of the five cities selected. This was all the fodder needed by opponents in Congress to kill the program after its first year. 28 Evidence suggests that white flight from inner to outer suburban areas during the 1980s was as virulent as the white flight from central cities to inner suburban areas during the 1960s and 1970s (Ihlanfeldt, 1994). 29 See Farley and Frey (1992), who report the 1980 and 1990 index of dissimilarity for each of 318 U.S. metropolitan areas.
Representative terms from entire chapter: