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Inner-City Poverty in the United States (1990)

Chapter: 2 Ghetto Poverty: Basic Questions

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Suggested Citation:"2 Ghetto Poverty: Basic Questions." National Research Council. 1990. Inner-City Poverty in the United States. Washington, DC: The National Academies Press. doi: 10.17226/1539.
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Suggested Citation:"2 Ghetto Poverty: Basic Questions." National Research Council. 1990. Inner-City Poverty in the United States. Washington, DC: The National Academies Press. doi: 10.17226/1539.
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Suggested Citation:"2 Ghetto Poverty: Basic Questions." National Research Council. 1990. Inner-City Poverty in the United States. Washington, DC: The National Academies Press. doi: 10.17226/1539.
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Suggested Citation:"2 Ghetto Poverty: Basic Questions." National Research Council. 1990. Inner-City Poverty in the United States. Washington, DC: The National Academies Press. doi: 10.17226/1539.
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Suggested Citation:"2 Ghetto Poverty: Basic Questions." National Research Council. 1990. Inner-City Poverty in the United States. Washington, DC: The National Academies Press. doi: 10.17226/1539.
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Suggested Citation:"2 Ghetto Poverty: Basic Questions." National Research Council. 1990. Inner-City Poverty in the United States. Washington, DC: The National Academies Press. doi: 10.17226/1539.
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Suggested Citation:"2 Ghetto Poverty: Basic Questions." National Research Council. 1990. Inner-City Poverty in the United States. Washington, DC: The National Academies Press. doi: 10.17226/1539.
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Ghetto Poverty: Basic Questions PAUL -A. JARGOWSKY AND MARY JO BANE INTRODUCTION Dimensions of Urban Poverty After years of neglect, a series of events in the 1980s rekindled public interest in the problems of urban poverty. The first event was the growing visibility of homeless people in urban areas in the early 1980s. Second, the popular media began to pay attention to what it dubbed the "underclass," a group of persons, mostly black and urban, who were said to be outside the American class system. Prominent examples of this coverage are Ken Auletta's (1982) book on The Underclass, Bill Moyer's 1986 television documentary on "The Vanishing Black Family," and a series of articles in The Atlantic Month) by Nicholas Lehmann (1986~. Third, academic interest in social problems among urban blacks was rekindled by circulation of papers by University of Chicago sociologist William Julius Wilson. The papers, eventually published as The ltu) Disadvantaged (1987), represented a return to the study of the urban ghetto that had been choked off by the furor over the Moynihan (1965) report on the black family in the 1960s. Despite intense interest in the topic, no consensus has emerged on such questions as how to define and measure ghettos, whether ghetto poverty has gotten worse, whether ghettos harm their residents, and what if anything public policy can do about the problem. One of the key reasons for this ongoing confusion is that several different concepts are being discussed simultaneously: · Persistent poverty individuals and families that remain poor for long periods of time and, perhaps, pass poverty on to their descen- dants. 16

GHETTO POVERTY: BASIC QUESTIONS 17 Neighborhood poverty spatially defined areas of high poverty, usu- ally characterized by dilapidated housing stock or public housing and high levels of unemployment. Underclass poverty defined in terms of attitudes and behavior, especially behavior that indicates deviance from social norms, such as low attachment to the labor force, drug use and habitual criminal behavior, bearing children out of wedlock, and receiving public assistance. The first concept is defined in terms of time, the second in terms of space, and the third in terms of behavior.) Sometimes, the concepts are combined, for example, in journalistic depictions of third-generation welfare families living in bad neighborhoods and using drugs. Nevertheless, it is important to keep the separate dimensions of the problem clear. In this chapter, we focus on the spatial dimension- the poverty of neighborhoods. We set up a criterion for defining some neighborhoods as ghettos based on their level of poverty. We then identify ghetto neighbor- hoods in metropolitan areas and develop a summary measure for standard metropolitan statistical areas (SMSAs) describing the proportion in ghetto neighborhoods. Finally, we review the cross-sectional data and the trends between 1970 and 1980. We do not attempt to define or measure an underclass. The term is used by many different people in many different ways. In a formal interpretation of the term, it refers to a "heterogeneous grouping of families and individuals who are outside the American occupational system . . . a reality not captured in the more standard designation lower class" (Wilson, 1987:8~. Thus, the claim that the underclass is growing implies that the lowest income or social class is now more isolated from the mainstream in terms of the opportunity for upward mobility. The census data with which we work cannot answer questions about economic mobility, at least not directly, because they are not longitudinal. In a less formal use of the term underclass, saying that an underclass has developed amounts to little more than a shorthand way of saying that, on a variety of measures, the poor do worse today than in the past. There is plenty of evidence for this. For example, the rate of labor force participation among the poor has declined, the proportion of children in single-parent families is up, and so on. On some measures, however, the poor do better today than in the past; for example, high school graduation ~ The persistent poverty concept is used by Adams et al. (1988), among others. The underclass concept, defined on the basis of behavior measured at the neighborhood level, is developed by Ricketts and Sawhill (1988~. A neighborhood concept is also used by Hughes (1989) in identify- ing what he calls "impacted ghettos."

18 INNER-CITY POVERTY IN THE UNITED STATES is up (Jencks, 1989~. We are troubled by the vagueness of the term when it Is used this way. 1b reiterate, we are not defining or measuring the underclass. Instead, we are defining ghettos and counting the ghetto poor in all metropolitan areas in the United States.2 We ask several basic questions about ghetto poverty: How can the concept be operationalized so that it can be measured over time and across cities? How extensive is the problem nationally? What are the characteristics of ghetto areas? How serious is the problem of ghetto poverty within specific urban areas? · How does it vary by region and race? · Has the problem been growing? · What are the typical patterns associated with the growth of ghetto poverty? We do not attempt to explain why ghetto poverty has been increasing in some areas and decreasing in others. We do, however, discuss a framework for thinking about these issues. Defining and Measuring Ghetto Poverty The Random House Diction any defines a ghetto as "a section of a city, especially a thickly populated slum area, inhabited predominantly by members of a minority group, often as the result of social or economic restrictions" (FIexner, 1987~. Historically, the term referred to segregated Jewish areas of European cities, and in the United States the term was often used to refer to any racial or ethnic enclave, without the emphasis on its economic status. Current usage, however, almost always implies impoverishment of ghetto residents and a run-down housing stock Thus, a completely black but middle-class neighborhood, an increasingly common occurrence in the United States, is not typically referred to as a ghetto. People have an idea in their heads of what and where ghetto neigh- borhoods are. Most city officials in large urban areas could point out on a map which neighborhoods they consider ghettos. But not everyone would agree on what the boundaries were. One person's ghetto might be another's up-and-coming neighborhood ripe for gentrification. In order to 2Since most definitions of the underclass assume, implicity or explicity, that the''r live in ghetto neighborhoods, our work could be seen as a starting point from which a national study on the underclass could be done. Van Haitsma (1989), for example, argues that the underclass is defined by (a) poor attachment to the labor force and (b) a social context that supports and encourages poor attachment to the labor force.

GHE170 POVERTY: BASIC QUESTIONS 19 study ghetto neighborhoods on a national scale, thus, the concept must be operationalized in a manner that can be consistently applied to the available national data. There are two basic strategies for operationalizing a measure of ghetto poverty. One is an approach that calculates a summary measure for a metropolitan area.3 Massey and Eggers (1989), for example, define a mea- sure of poverty concentration as the exposure of the black poor to poverty. This is the probability that a black poor person has poor neighbors. This measure allows characterization of SMSAs according to their overall level of ghetto poverty. It does not, however, identify specific neighborhoods that are ghettos and others that are not. The second strategy attempts to classier specific neighborhoods as ghettos based on a set of criteria. Wilson (19g7) defines an underclass area as a neighborhood (using Chicago's well-known "community areas") with a poverty rate greater than 30 percent. Ricketts and Sawhill (1988) define underclass areas as neighborhoods that are one standard deviation worse than the national norm on four measures: high school graduation, labor force participation of men, welfare receipt, and single-parent families. For the reasons described above, we do not use the term underclass area and we do not attempt to define or measure underclass neighborhoods. However, we take an approach similar to Wilson's by using census tracts as our prosy for neighborhoods.4 We then create a summary measure for an SMSA based on the population in ghetto tracts.5 We define a ghetto as an area in which the overall census tract poverty rate is greater than 40 percent. We define the ghetto poor as those poor, 3 Massey and Denton (1988a) define five summary measures in the context of racial segrega- tion: evenness, exposure, concentration, centralization, and clustering. These measures and techniques can also be applied in the context of residential segregation of the poor from the nonpoor. The two dimensions, race and poverty, are both involved in creating ghetto neigh- borhoods. See Massey and Eggers (1989) and Massey et al. (1989) for examples of applying aggregate-level measures of ghetto poverty. 4Census tracts are areas defined by the Census Bureau, typically containing about 2,000 to 8,000 people. In a densely settled neighborhood, a census tract may be the size of four or five city blocks. 5 Massey and Eggers (1989) argue against "ad hoc and arbitrary definitions" of poverty neighbor- hoods. Further, they argue that standard measures of segregation "use complete information on the spatial distribution of income" (1989:4~. This is not entirely true, however. Standard mea- sures of segregation, such as the dissimilarity index and the exposure measure, treat each census tract as if it is an isolated entity. An area's segregation score would not change if all the tracts were scrambled like the pieces of a jigsaw puzzle. Our strategy enables us to identify and map census tracts, which becomes important to understanding the pattern of population movements that led to the absented changes between 1970 and 1980. It is reassuring, however, that Massey and Eggers's main measure of poverty concentration (the exposure of the black poor to poor persons) is highly correlated with the level of ghetto poverty for blacks as we define it. Both measures appear to reflect the same underlying reality.

20 INNER-CITY POVERTY IN THE UNITED STATES of any race or ethnic group, who live in such high-povertr census tracts. We define the level of ghetto poverty in an SMSA as the percentage of the SMSAs poor that lives in ghetto census tracts. However, for reasons described below, we usually report levels of ghetto poverty separately for blacks and Hispanics, that is, the percentage of the black poor living in ghetto census tracts and the percentage of the Hispanic poor living in ghetto census tracts. We describe our rationale for these definitions in the sections that follow. The 40 Percent Poverty Criterion In earlier work (Bane and Jargowsky, 1988), we were limited to the poverty rate cutoffs that were used in data published by the Census Bureau, that is, either 20, 30, or 40 percent (Bureau of the Census, 1973b, 1985~. Based on visits to several cities,6 we found that the 40 percent criterion came very close to identifying areas that looked like ghettos in terms of their housing conditions. Moreover, the areas selected on the basis of the 40 percent criterion corresponded rather closely with the judgments of cider officials and local Census Bureau officials about which neighborhoods were ghettos. Even though we are now working with data tapes and have the flexibility to choose any poverty rate as the ghetto criterion, we continue to use 40 percent as the dividing line between ghettos and mixed-income neighborhoods. With somewhat less justification, we use 20 percent poverty as the dividing line between m~xed-income and nonpoor neighborhoods. Any fixed cutoff is inherently arbitrary. A census tract with a 39.9 percent poverty rate is not that different from a census tract with a 40.1 percent poverty rate. Moreover, the poverty rate in a census tract is an estimate based on a sample, even in the census. This problem does not affect aggregate numbers because errors will occur in both directions. However, individual census tracts, especially near the boundaries of ghettos, may be misclassified (Coulton et al., 1990~. Nonetheless, we are convinced that the 40 percent poverty criterion appropriately identifies most ghetto neighborhoods. ~ illustrate this, we have mapped the ghetto census tracts in Philadelphia and Memphis. Shown are nonpoor tracts (0 to 20 percent poverty), mixed-income tracts (20 to 40 percent poverty, and ghetto tracts (greater than 40 percent poverty). In Figure 2-1, the large North Philadelphia ghetto is clearly visible. (The island in the middle is 6The cities we visited include Baltimore, Boston, Detroit, Little Rock, Memphis, Omaha, Phila- delphia, San Antonio, and a number of smaller cities. The correspondence of tract poverty rates with the conditions we observed was especially striking because we were using 1980 census tract data as our guide to cities in 1987 to 1989.

GHETTO POVERTY: BASIC QUESTIONS ~) ~ ~ ~} I~ ~ . ~ ~ _ no ~ _ ~ l ~ ~ - U[X"(20-~) At' = FIGURE 2-1 Philadelphia SMSA by Neighborhood Poverty Type, 1980. 21 Type {Poverty Rate) Not Poor to-20) Chatto (~D and Up) Temple University.~7 This area consists of densely packed 3- to 5-story row houses, many boarded up and vacant. In addition, there are several high- and low-rise housing projects scattered throughout the region. The signs of urban decay are overwhelming in this neighborhood: broken glass, litter, stripped and abandoned automobiles, and young men hanging out on street corners.8 The other major ghetto areas in Figure 2-1 are West Philadelphia and Camden, New Jersey, on the other side of the Delaware River. A smaller ghetto area is visible in South Philadelphia. The 20 to 40 percent poverty areas are basically working class and lower middle income. In our visit to Philadelphia, the 40 percent census tracts looked and felt quite different, especially in North Philadelphia. It is important to distinguish our definition of ghetto tracts, based on a poverty criterion, from a definition of ghettos based on racial composition. Not all majority black tracts are ghettos under our definition, nor are all ghettos black. In general, ghetto tracts are a subset of a city's majority black or Hispanic tracts. Figure 2-2 shows this relationship for Philadelphia. Census tracts are divided into three groups by race: less than one-third minority (white), one-third to two-thirds minority (mixed), and more than 7Because the majority of tracts were not poor in 1970 and did not become ghettos by 1980, the maps "zoom in" on the downtown areas, where most ghetto and mixed-income tracts are located. awe observed these conditions in a visit to Philadelphia in spring 1988. We were guided to the various areas of the city by an extremely helpful professional employed lay the regional office of the Census Bureau.

22 INNER-CITY POVERTY IN THE UNITED STATES it in ~ 111 111 111 .. ~ ~,7 I]~eQiPove~y Status C1 Whi1!e/lMon-Poor L3 ~lte~;hetto lli~d/Non-Poor __ blixed/Ghatt~ llinonty/blan-Poor blinon'ty/Ghetto FIGURE 2-2 Philadelphia SMSA, 1980 Neighborhoods by Race and Poverty Status. two-thirds minority (minority).9 Each of these groups is divided into ghetto and nonghetto tracts on the basis of their poverty rates. Given that the overall proportion minority in the city is about 20 percent, the existence of many census tracts that are more than two-thirds minority indicates a high degree of racial segregation. Most of the ghetto tracts are more than two-thirds minority. Only a few are mixed race, and even fewer non-Hispanic white. There are, however, many segregated minority areas in Philadelphia that are not ghettos by our criterion, as there are in all the cities with substantial black populations we visited. Figure 2-3 shows the ghetto areas of Memphis. The ghetto area of North Memphis, which is clearly visible, consists of predominantly single- family houses, many in dilapidated condition, although there are a few low- rise housing projects, such as Hurt Village.l° North of Chelsea Avenue, one of the main corridors in this region, the housing stock is mostly run-down shacks. The high-poverty area continues south, to the east of downtown Memphis, on the Mississippi River. The South Memphis ghetto is mostly two- and three-story housing projects. The one large ghetto tract on the Arkansas side of the river is largely swampland. The other Arkansas ghetto 9 Minority here includes blacks, Hispanics, and "other races." 10We visited Memphis in June 1988 and again in May 1989. Many people helped us understand the city, including State Representative Karen Williams and various officials associated with the county's Free the Children project.

GHETTO POVERTY: BASIC QUESTIONS .'~J ~ by 1 4.' FIGURE 2-3 Memphis SMSA lay Neighborhood Poverty ~e, 1980. 23 Type {Poverty Rote) Not Poor to-20) Axe (20-~) tracts are in West Memphis City. Here the housing stock is a mixture of single-family homes and rusting trailers. In both cities, tracts in the 20 to 40 percent range had a very different look and feel. The housing stock is in better condition, and street-corner markets and other businesses are more numerous. Such areas appeared to us to be working-class or lower middle class neighborhoods, not ghettos. Although outside appearances can be deceiving, cite and Census Bureau officials and other knowledgeable individuals generally confirmed our as- sessments. The Level of Ghetto Poverty Having set up a criterion for identifying neighborhoods (census tracts) as either ghettos or not, we now need a way to assess how serious a problem ghetto poverty is within a given metropolitan area. One potential measure could be the percentage of census tracts that are ghettos. Since census tracts vary in population, however, this criterion would be misleading. Other possibilities include the proportion of the population in ghetto areas, the proportion of the poor in ghetto areas, and the proportion of the black and/or Hispanic poor in ghetto areas. All three of these measures are interesting in certain ways. The percentage of the population in ghetto areas is, however, affected by both the overall poverty rate in the SMSA and the proportion of the poor in ghetto areas. Using it as the summary

24 INNER-CITY POVERTY IN THE UNITED STATES measure for SMSA-level ghetto poverty makes it hard to distinguish the two phenomena. The percentage of the poor who live in ghetto areas is also a potentially misleading measure. As will be shown below, the white poor almost never live in ghettos, the Hispanic poor sometimes do, and the black poor frequently do. As a result, the percentage of all poor living in ghettos can vary dramatically with the racial composition of the SMSA and is partly a proxy for percent minority. We solve this problem by defining levels of ghetto poverty separately by race. In most of our analyses, we look at the percentage of the black poor and the percentage of the Hispanic poor living in ghettos. The level of ghetto poverty among whites is extremely low and varies very little among regions and cities; consequently, we generally omit whites from our discussion of levels of ghetto poverty. A potential pitfall of this measure is that it fails to take spatial proximity into account. It seems reasonable to assume that a city with 25 contiguous high-poverty tracts has a worse ghetto problem than one with 25 tracts scattered throughout the metropolitan area.~3 However, in our experience, most of the ghetto tracts in an area tend to be in one or two main clusters. Since this pattern is relatively constant across cities, the lack of a spatial dimension in our measure of ghetto poverty is not much of a problem. Moreover, because our measure identifies specific tracts, we are able to map ghetto tracts and visually inspect their spatial relationships. The value of this approach will be evident below, especially in the section on "The Geography of Ghetto Poverty." Data Sources We have compiled data for all metropolitan census tracts (approxi- mately 40,000) in 1970 and 1980. The data for 1980 are from the Census of Population and Housing, 1980, Summary lope File 4N Outside metropoli- tan areas, counter data are included from Summary lope File 4C, so that the 1980 data set is national in scope. The 1970 data are from the 1970 Census of Population, Fourth Count, File A, and include all metropolitan tracts. Appendix A discusses several issues related to processing the tapes 1 1 The data reported in our earlier work used this definition of the level of ghetto poverty (Bane and Jargowsly, 19883. i2The only places where the level of ghetto poverty among whites is greater than 20 percent are college towns, like Madison, Wisconsin, and Texas towns, where one assumes many of the whites are Hispanic. i3Those in the scattered tracts will have partial access to the amenities of their better-oaf nearby neighbors, more role models, and so on. Readers who find this unconvincing might consider whether they would rather live in one of the scattered tracts or in the center of the 25 census tract ghetto area.

GHETTO POVERTY: BASIC QUESTIONS 25 and compiling the data set, such as complementary suppression in 1980 and changes in SMSA boundaries between 1970 and 1980. The data reported here improve on the data presented in our earlier work (Bane and Jargowsky, 1988) in several ways. First, they cover entire metropolitan areas, not merely central cities. Ghettos such as East St. Louis, Illinois, and Camden, New Jersey, were excluded from our earlier data simply because they were outside the political boundaries of the central cities of their metropolitan areas. Second, all metropolitan areas are included, not just the 100 largest. It is dangerous to judge a trend from only two data points (1970 and 1980), the most recent of which is almost a decade ago. Nevertheless, there is simply no source of data other than the decennial census that has a large enough sample to allow analysis at the neighborhood level. The Census Bureau's Current Population Survey (CPS) does report "poverty area data" annually, but we do not think these data are useful. First, the criterion used is a poverty rate of 20 percent for the census tract. We argued above that this criterion does not identify ghetto poverty very well. Second, the CPS uses the tract poverty rate from a previous decennial census until the next one becomes available. As a result, the tract poverty rates are attached to data that are as many as 10 or more years out of sync. With the rapid changes and movements common in ghetto areas (see "The Geography of Ghetto Poverty"), this procedure is simply too flawed to make the data it generates useful. We rely, therefore, on 1970 and 1980 census data. In the next section, as above, we report tract-level data on the characteristics of ghetto neigh- borhoods in Memphis and Philadelphia. We then present our aggregate analyses of tract-level data for all metropolitan areas in the United States. Next, we return to Memphis and Philadelphia and add Cleveland and Mil- waukee in an analysis of the changing geography of ghetto poverty. In the final section, we present our conclusions as well as implications for public policy. CHARACTERISTICS OF GHETTO NEIGHBORHOODS What are the ghetto neighborhoods defined by the 40 percent povertr criterion like? What is known about the quality of life for people who live in ghettos, especially poor people? These questions are addressed in this section. A separate and quite different question is whether living in a ghetto makes poverty worse. Does living in a ghetto have an independent effect on poor persons? One could attempt to answer this question by comparing poor people who live in ghettos with poor people who do not on a variety of characteristics. Unfortunately, this strategy ignores the possibility of

26 INNER-CITY POVERTY IN THE UNWED STATES unobserved differences between the two groups that are directly related to their residential status. For example, it could be that employed adults move out of ghettos, leaving the unemployed behind. The resulting difference in employment rates would reflect selection effects, not neighborhood effects. Controlled experiments and/or longitudinal data are needed to sort this out. In Chapter 4, Jencks and Mayer review the data on what is known about neighborhood effects. In this section we do not deal with neighborhood effects; we simply describe differences in neighborhood characteristics. As above, we use data for Philadelphia and Memphis as examples. Race/Ethnicity Table 2-1 shows the distribution by race and Hispanic origin for resi- dents of Memphis and Philadelphia by the level of poverty in their neigh- borhoods. The poorer the neighborhood, the greater the proportion of residents who are minority group members. In Memphis, where there are very few Hispanics, ghettos are nearly 90 percent black; in Philadelphia, blacks and Hispanics account for nearly 85 percent of ghetto residents. Nonpoor neighborhoods, those with poverty rates of less than 20 percent, have just the opposite race/ethnicity composition. Non-Hispanic whites make up the vast majority of persons in nonpoor neighborhoods and only a small proportion of those in ghettos.~4 Family Structure and Demographics Family structure is also quite different in ghetto neighborhoods, as seen in Table 2-2. Three in four families in the Memphis and Philadelphia SMSAs are married-couple families. Only about 10 percent of all families are single-parent families with children. In ghetto neighborhoods, however, the pattern is quite different. Less than half of all families are headed by a married couple, and less than a quarter are married couples with children. The modal family type is a single parent with children. Sixty to seventy percent of all families with children are headed by single parents, compared with 20 to 30 percent in the SMSAs overall. Looking only at blacks reduces the differences in family type, but by no means eliminates them. i40ur estimate of the number of non-Hispanic whites is not completely accurate because the tract-level data are not categorized simultaneously by race, Hispanic origin, and poverty status. Although Hispanics can be either white or black, the majority of Hispanics identified themselves on the 1980 census as eitherwhite or "other race." Only 2.6 percent identified themselves as black (Bureau of the Census, 1983a). Therefore, a pretty good approximation can be achieved with aggregate data by subtracting black and Hispanic data from the total, which yields non-Hispanic whites and other races.

GHElTO POVERTY: BASIC QUESTIONS TABLE 2-1 Race/Ethnicity Composition of Memphis and Philadelphia, by Neighborhood Poverty Level, 1980 27 Neighborhood Poverty Level SMSA Not Poor Mixed Ghetto Total (0-20%) (20-40%) (>40%) Memphis SMSA Total persons 913,468 570,331 234,890 108,247 Black 39.8% 15.8% 75.6% 88.9% Hispanic 0.8 0.7 1.0 0.9 Non-Hispanic white S9.4 83.6 23.5 10.2 and other races* Philadelphia SMSA Total persons 4,713,242 3,825,962 620,769 266,511 Black 18.6% 7.9% 62.3% 69.1% Hispanic 2.3 1.0 4.8 14.5 Non-Hispanic white 79.2 91.0 32.9 16.4 and other races* *See footnote 14. TABLE 2-2 Families by Type and Presence of Children: Memphis and Philadelphia SMSA Averages and Ghetto Neighborhoods, 1980 Memphis SMSA Philadelphia SMSA SMSA Ghetto SMSA Ghetto Total families Married-couple families With children Without children Single-parent families With children Without children Black families Mamed-couple families With children Without children 232,787 23,387 39.1% 36.4 14.7 9.8 21.1% 24.7 35.0 19.1 1,209,923 57,508 38.7% 20.1% 39.9 20.4 11.0 10.5 81,834 20,849 204,878 41,245 31.8% 23.1 39.6 20.0 19.5% 22.1 27.2% 24.2 15.9% 17.7 Single-parent families With children 29.2 38.1 30.1 44.3 Without children 15.9 20.3 18.6 22.1 As a result of this difference in family structure, a much greater proportion of the children in ghetto areas have only one parent. On average, children of single parents are poorer in terms of income and other resources. In addition, one parent often cannot provide the same level of guidance and discipline as two. Children of single-parent families do significantly worse, on average, than other children in terms of educational

28 INNER-C~ POW IN THE UNFED STATES attainment, earnings, and family formation, and they are somewhat more likely to be arrested (Dembo, 1988; Dornbusch et al., 1985; Garfinkel and McLanahan, 1986~.~5 Economic Characteristics Able 2-3 compares the economic characteristics of ghettos in Philadel- phia and Memphis with those of their SMSAs. Given that the stratifying variable is the neighborhood poverty rate, one would expect differences on economic measures. Nevertheless, it is interesting to note how large the differences are. Although nearly 90 percent of the males aged 25 to 44 in the SMSA are employed, in ghettos only two-thirds in Memphis and just over half in Philadelphia are employed. A far greater proportion of ghetto males are not in the labor force at all. Those who are in the labor force are three times more likely to be unemployed. Once again, this is partly an effect of the racial composition of the neighborhoods, but after controlling for race, substantial differences remain. Table 2-3 also shows the median earnings of males who worked full- year, full-time in effect, the wage rate for full-time male workers multi- plied by 2,000 (40 hours times 50 weeks). Consider what these numbers mean. The average wage rate in Memphis for full-year, full-time male work- ers was about $8.00 per hour ($16,000/2,000) in 1979 dollars. For blacks, the rates were $5.60 for the SMSA and $4.62 for ghettos. In Philadelphia, wage rates were generally higher, although the pattern of differences is the same. Although considerably higher than the minimum wage in 1979 ($2.90), these wage rates suggest that the kinds of jobs ghetto residents are working at, even when they work full-time, year-round, are low paid and probably low skilled. Ware rates for nart-vear and/or Dart-time work are undoubtedly lower. cat r - ~rid These wage and employment numbers tell a story about three separate factors that contribute to the low average earnings of blacks in ghetto neighborhoods. First, just by virtue of the area's being mostly black, the employment and wage rates for ghetto residents are lower than the SMSA averages. Second, controlling for race, ghetto residents are more often out of the labor force or unemployed. Third, even when black ghetto residents work, they earn lower wages than nonghetto blacks. The numbers also tell a story about the sources of support for families. The average income of all prime-age men in the Memphis and Philadelphia i5We have focused on families in this section mainly because we did not find important differ- ences between ghetto areas and the rest of the SMSA in the proportion of nonfamily households. Only about 10 percent of residents live in nonfamily households or group quarters.

GHETTO POVERTY: BASIC QUESTIONS TABLE 2-3 Economic Characteristics of Memphis and Philadelphia SMSA Averages and Ghetto Neighborhoods, 1980 29 Memphis SMSA Philadelphia SMSA SMSA Ghetto SMSA Ghetto All Races Males. aced 25-44 . . ~ Employed 86.7% 63.6% 86.3%51.~% Unemployed 5.2 11.9 5.814.4 Not in labor force 8.1 24.5 7.933.8 Unemployment rate 5.7 15.8 6.321.8 Median earnings of full-year, full-hme adult male workers Proportion of households with income from Eamings Public assistance Blacks Males, aged 25-44 $16,067 $9,701 $18,933 $12,019 82.1% 60.3% 79.3% 52.6% 11.1 33.1 10.0 42.8 Employed 75.5 62.1 69.2 49.7 Unemployed 10.1 13.9 12.0 17.0 Not in labor force 14.3 24.1 18.8 33.3 Unemployment rate 11.8 18.3 14.8 25.5 Median earnings of full-year, full-time adult male workers Proportion of households with income from ua'Tlmgs Public assistance $11,195 $9,241 $13,916 $11,653 74.4% 59.0% 71.0% 50.5% 24.4 36.5 28.4 47.5 ghettos was about $5,700 per year.l6 This was well below the $7,421 that was needed in 1979 to support a family of four at the poverty line. It is perhaps not surprising, therefore, that so many ghetto families are headed by women and that so many rely on income from public assistance. Social Characteristics One common thread of the literature on ghettos, both academic and popular, is that the harshness of living in a ghetto is only partly economic. 1 6This is an estimate obtained by multiplying the earnings of full-year, full-time workers by the percent employed. It implicitly assumes that all the employed are working full-year, full-time, and it is thus an overestimate of average earnings.

30 INNER-C~ POW IN THE UNFED STATES TABLE 2-4 Social Indicators in Memphis and Philadelphia, by Poverty Level of Neighborhood, 1980 Memphis SMSA Philadelphia SMSA SMSA Ghetto SMSA Ghetto Blacks of specified ages Median years of school completed, age 25 and up Hangout rate, 16-21* MMPI, 25-44* 10.8 9.5 1 1.7 10.8 25.7 31.1 29.5 40.3 60.3 44.5 53.2 32.7 *See accompanying text for explanation. For example, it is highly likely that ghetto residents are more often the victims of crime than nonghetto residents, as well as perpetrators of crime. Ghetto residents probably are more likely to have problems with substance abuse. They are probably more likely to have been victims of racial dis- crimination, police brutality, and environmental health hazards. Recently, a number of sociologists and ethnographers have painted vivid pictures of ghetto life for specific neighborhoods (Anderson, 1989; Coulton et al., 1990; O'Regan and Wiseman, 1990; Wilson, 1987~. The census does not give us such details. There are, however, a few useful measures available at the census-tract level. Differences in attachment to the labor force and in welfare recipiency were noted earlier. Several other differences are shown in Bible 2~. All figures in the table are for blacks only, so none of the differences between neighborhoods is due to racial composition. The table shows a large difference in years of school completed. This difference may reflect the socioeconomic level of ghetto residents, lower educational aspirations in ghetto neighborhoods, or the quality of education in ghetto schools. Whatever the reason, however, it clearly indicates the low levels of education among ghetto residents. The median adult in a Memphis ghetto, for example, has not finished his or her sophomore year in high school.~7 The other two indicators in the table require some explanation. The "hangout rate" is an attempt to measure "idleness" or exclusion from the mainstream economy among young people. The measure is the proportion of civilian 16- to 21-year-olds who are not in i7In comparison, the median level for all adults in the SMSA is 1~1 years, indicating a small amount of postsecondary education.

GHETTO POLEMIC: BASIC QUESTIONS 31 school and not working (either unemployed or not in the labor force. This measure should almost certainly be interpreted differently for men and women, who unfortunately are grouped together in the census-tract datable Among young men, those "hanging out" may be thought of as the pool available for criminal enterprises, although by no means should one assume that all of these individuals turn to crime. Among young women, a significant proportion are likely to be poorly educated and unemployed young mothers, many (at least in the ghetto) unmarried. In the Philadelphia ghetto, 40 percent of the young adults are "hanging out." Some are almost certainly raising children. Some may be engaged in crime or other aspects of the underground economy. Some may simply be doing nothing at all, which in some ways is equally worrisome. However, the rate for blacks in the SMSA as a whole is just under 30 percent, so the difference is not as great as one might have thought. The "MMPI" is the Male Marriageable Pool Index, defined by Wilson and Neckerman (1986~. As used here, the MMPI is the ratio of employed men aged 25 to 44 to women of the same age. Wilson and Neckerman argue that women are not inclined to marry men who are not in a position to support them and that the low level of the MMPI in ghetto communities helps to explain the high level of female-headed families. The data for Memphis and Philadelphia certainly confirm that the MMPI is dramatically lower in ghettos. In Philadelphia ghettos, there is 1 employed male for every 3 females in the 25 to 44 age group; in Memphis, 9 for every 20. In part, this reflects the census undercount of urban black males. No one, however, alleges an undercount large enough to explain this difference. The second factor contributing to such low MMPI is males who have died, joined the army, or gone to prison. The third factor is the low employment level of the remaining males, as discussed above. Public Policy and Ghettos In short, ghettos contain a concentration of economic and social prob- lems. Census data reveal only the tip of the iceberg; those who live and work in ghetto communities could doubtless paint a much more vivid pic- ture. Although we have not attempted to argue that ghettos have effects on their residents, in some ways it does not matter. It is clear that a great many people with economic hardships, educational deficits, and social problems are clustered in the ghetto. Moreover, the quality of life in ghettos is 18See Mare and W'nship (1984) for a discussion of the importance of considering the employ- ment of black youths in the context of their school enrollment and military enlistment. 19The data are from Table PB49, "Age by School Enrollment, Years of School Completed and Labor Force Status," Summary Tape File 4^

32 INNER-CITY POVERTY IN THE UNITED STATES unfortunate enough that a compassionate society should worry about it. If, in addition, later research shows that ghetto poverty makes it even harder for the poor to escape poverty, that will only provide one more incentive to tackle the problem. GHETTO POVERTY, 197~1980: THE NATIONAL PICTURE Having defined ghettos and described their characteristics in two cities, we now step back to examine the national pattern. In this section we estimate the number of ghetto poor in 1980, look at changes between 1970 and 1980, and document regional and city-to-city variations. The Number of Ghetto Poor In 1980, there were 27 million poor persons in the United States 12.4 percent of the population.20 Of these, 18.8 million (68.7 percent) lived in the 318 SMSAs defined at the time of the census.2i It would be a mistake, however, to assume that all persons who were poor and lived in metropolitan areas lived in ghettos. The total number of poor persons who lived in a metropolitan census tract in which the poverty rate was greater than 40 percent was 2.4 million. The number of poor, metropolitan poor, and ghetto poor, by race, is shown in Table 2-5. Several interesting facts emerge from the table. First, less than 9 percent of all poor in the United States lived in ghettos in 1979.22 Even within metropolitan areas, only 13 percent of the poor lived in ghettos. The rest lived in mixed-income and nonpoor neighborhoods. Thus, ghetto 20Although the census uses income figures from the previous year, in this case 1979, it reports the residence in the current year, in this case 1980. Moreover, the census somewhat overstates poverty. The CPS poverty rate in 1979 was somewhat lower 11.7 percent. In general, the CPS seems to do a better job of measuring income than the census, which results in a lower measured poverty rate. Underreporting of income in the census may be particularly serious for public assistance and other unearned income. The general direction of bias should be toward some overstatement of poverty rates and perhaps poverty concentrations as well. 21 Several more SMSAs were defined after the census, and major changes were made in metro- politan area boundaries in 1983. In addition, the terminology was changed somewhat. The term SMSAwas eliminated, replaced by consolidated metropolitan statistical areas (CMSAs), primary metropolitan statistical areas (PMSAs), and metropolitan statistical areas (MSAs). CSMAs con- tain more than one PMSA. PMSAs and MSAs, taken together, are roughly comparable to the pre-1983 SMSAs (Bureau of the Census, 1989:Appendix II). We continue to use the term SMSA to indicate that our data are based on the pre-1983 concepts and boundaries. 22 Bane and Jargowsly (1988) reported that 6.7 percent of the poor lived in ghettos in the 100 largest central cities. The increase to 8.9 percent reflects the addition of smaller SMSAs and suburbs, i.e., non~entral-city portions of SMSAs.

GHETTO POVERTY: BASIC QUESTIONS TABLE 2-5 Distnbuiion of Poor Persons, 1980 (thousands) Metropolitan Ghetto Areas U.S. Areas (Poverty > 40%) All 27,388 (100.0%) 18,820 (68.7%) 2,449 (8.9%) Black Hispanic Non-Hispanic white* 7,548 (100.0) 3,348 (100.0) 16,492 (100.0) 5,734 (76.0) 2,869 (85.7) 10,217 (62.0) 1,590 (21.1) 534 (15~9) (2.0) *See footnote 14. 33 poverty is a relatively small part of the overall problem of poverty in the United States. This is not to say that the problem is not important far from it. It may be far more degrading and harmful to be poor in an urban ghetto than elsewhere. Nevertheless, it must be emphasized that the poverty problem in the United States is far broader than just urban ghettos. Policy makers should not assume that the ghetto problem and the poverty problem are synonymous. Able 2-5 also indicates that the proportion of the poor in ghettos varies dramatically by race. Only 2 percent of the non-Hispanic white poor lived in ghettos, compared with 21 percent of black poor and 16 percent of Hispanic poor. Within metropolitan areas, almost 3 in 10 poor blacks lived in a ghetto. As a result, the 2.4 million ghetto poor in the United States were distributed as follows: black~4.9 percent; Hispanic-21.8 percent; non-Hispanic white and other races-13.3 percent. Thus, ghettos were predominantly populated by blacks and Hispanics, and black and Hispanic poor were much more likely to live in a ghetto than white poor. An Aside: Rural High-Poverty Areas This is a study of urban ghettos. Nevertheless, it is clear that a substan- tial minority of the poor (31 percent from Table 2-5) live in nonmetropolitan areas and that there are many pockets of poverty in rural areas, particu- larly among blacks in the South and Hispanics in Texas and Florida. Such areas are not usually divided into census tracts, so poverty rates cannot be calculated for them. Using the county poverty rates as an approximation, however, indicates that of 1.S million poor blacks in rural areas, 107,716 (5.9 percent) lived in counties with poverty rates over 40 percent. Because a county is so much bigger than a tract, however, these figures are not really comparable with tract-based figures. Almost all rural blacks live in the South, and such counties tend to be highly segregated. Therefore, the black poverty rate for the county may be a better approximation of the neighborhood poverty rate for blacks than the overall poverty rate in the county. Using this criterion for high-poverty areas, a vastly different

34 INNER-C~ POPLIN THE UNFED STATES picture emerges: more than 1 million poor blacks (56.2 percent of non- metropolitan blacks) lived in rural counties in which the black poverty rate was above 40 percent. Similarly, only 4.2 percent of the country's 479,000 Hispanic rural poor lived in counties in which the overall poverty rate was greater than 40 percent. ~enty-eight percent, however, lived in rural counties in which the Hispanic poverty rate is that high. In Texas, which contains by far the largest number of Hispanic rural poor, 46 percent lived in counties in which the Hispanic poverty rate was greater than 40 percent. Rural poverty areas often have dreadful conditions. Monica, Mississippi, is an example.23 The houses are little more than run-down shacks, without plumbing or sewage fixtures in many cases. The streets are unpaved and social problems are rampant Clearly, these conditions are in some ways the equal of, if not worse than, conditions in urban ghettos. We know very little about rural pockets of poverty, and the subject deserves much greater attention. Nevertheless, Monica, Mississippi, and Harlem, New York, are very different places. In the remainder of this chapter, we talk about ghetto poverty in metropolitan areas only. The Growth of Ghetto Povertr, 197~1980 Much of the concern about ghetto poverty stems from a sense that ghettos, and the social problems they contain, have been getting worse. 1b evaluate these claims, we present data on the changes in ghetto poverty between 1970 and 1980.24 Between 1970 and 1980, the number of poor living in ghettos in metropolitan areas increased by 29.5 percent, from 1,890,925 in 1970 to 2,449,324 in 1980. This is a much smaller growth rate than the 66 percent reported previously (Bane and Jargowsky, 1988; Nathan and Lego, 1986~. That estimate was based on published data for the 50 largest central cities. The difference comes mainly from our inclusion in these analyses of smaller SMSAs, many of them southern, many of which as we discuss below had substantial decreases in ghetto poverty. Thus, the focus on large central cities left out an important part of the story. 23We visited Monica in May 1989 as part of a trip that took us from Memphis down through the Mississippi delta area to Jackson and then up through the Arkansas side of the delta to Little Rock. 24Not all metropolitan areas that existed in 1980 were defined in 1970, and there were numerous boundary changes. We tried to adjust for significant boundary changes by recoding the 1970 data to be consistent with 1980 boundaries. For more information, see Appendix ~

GHETTO POVERTY: BASIC QUESTIONS TABLE 2-6 Change in Number of Ghetto Poor, 1970-1980 Number Ghetto Poor (thousands) . of SMSAs 1970 1980 Change Percent Change All races 3181,8912,449558 +29.5 Creases 1~77851,712927 +118.0 No change 44000 - Decreases 881,106668-437 -39.6 New in 1980 79--6767 - Black 3181,2471,590343 Deceases 965581,121563 +100.9 No change 62000 - Decreases 81689426-263 -38.1 New in 1980 79--4242 - Hispanic 318385534149 +38.7 Creases 11696361265 +277.6 No change 86000 - Decreases 37289170-119 -41.6 New in 1980 79--33 - 35 The number of black ghetto poor grew by 27 percent over the 10-year period and the number of Hispanic poor by 39 percent.25 The aggregate figures, however, are extremely misleading because they conceal a substan- tial amount of variation among metropolitan areas. The aggregate increase of more than 500,000 ghetto poor obscures the fact that some metropolitan areas had large increases and some large decreases. Table 2~ shows the number of SMSAs with increases and decreases in all ghetto poor, black ghetto poor, and Hispanic ghetto poor. There were more SMSAs with decreases or no change than SMSAs with increases. The number of ghetto poor in those SMSAs in which there were increases more than doubled. For Hispanics, it more than tripled. The metropolitan areas with decreases in ghetto poverty had more than one-third fewer ghetto poor in 1980 as 1970. Also important to note is that the addition of new SMSAs between 1970 and 1980 does not account for much of the growth in ghetto poverty~nly about 12 percent of the growth came from new SMSAs, overall.26 2sHowever, the aggregate level of concentration-the percentage of the metropolitan poor liv- ing in ghettos increased only modestly among blacks (from 26.4 to 27.7 percent) and actually decreased among Hispanics (from 23.7 to 18.6 percent). See the following section. 26Looking only at the 239 SMSAs that were defined in both years, there was a net increase of just under 500,000, and a growth rate of 25.9 percent.

36 INNER-CITY POVERTY IN THE UNWED STATES TABLE 2-7 Metropolitan Areas With the Most Ghetto Poor, 1980 Number of Cumulative SMSA Ghetto Poor Percent New York, N.Y.-N.J. 477,621 19.5 Chicago, Ill. 194,33B 27.4 Philadelphia, Pa.-N.J. 127,134 32.6 Baltimore, Md. 60,983 35.1 McAllen-Pharr-Ed~nburg, Tex. 58,222 37.5 Memphis, Tenn.-Ark.-Miss. 56,915 39.8 New Orleans, La. 56,504 42.1 Newark, N.J. 54,720 44.4 Detroit, Mich. 54,572 46.6 Los Angeles-Long Beach, Calif. 51,306 48.7 Remaining 308 metropolitan areas 1,257,009 100.0 Thus, there is a great deal of variation among metropolitan areas. It is important to look more closely at specific SMSAs in order to understand the variations in the level of ghetto poverty and changes over time. As we discuss, the often-cited aggregate figures mask considerable regional variation and, to a lesser degree, city-to~ity variation within regions. Where Are the Ghetto Poor? The most visible ghetto poor are those who live in the largest urban areas. These very large cities, in fact, contain a large proportion of the ghetto poor. Slightly more than one-fourth of the ghetto poor in 1980 lived in just two metropolitan areas: New York and Chicago. The 10 metropolitan areas with the largest numbers of ghetto poor in 1980 are shown in Table 2-7. Idgether, they account for almost half of the ghetto poor. Every region of the United States is represented on the top 10 list. The South contributes four of the metropolitan areas with the largest numbers of ghetto poor, the Northeast, three, the North Central, two, and the West one. Most of the 10 cities have large black populations, which account for most of the ghetto poor. The exception is McAllen-Pharr-Edinburg, Texas, on the southern tip of the state on the border with Mexico, which has a large Hispanic population that accounts for almost all of its ghetto poor. The top 10 list in 1970 is similar Cable 2-8), but there are some important differences. For example, the top 10 accounted for only about one-third of the ghetto poor in 1970, rather than one-half. In addition, there was also a greater representation of southern cities (6 of 10), both deep South cities (where the ghetto poor are predominantly black) and Texas cities (where they are predominantly Hispanic).

GHEl7O POVERTY: BASIC QUESTIONS TABLE 2-8 Metropolitan Areas With the Most Ghetto Poor, 1970 Number of Cumulative SMSA Ghetto Poor Percent New York,N.Y.-N.J. 134,139 7.1 McAllen-Pharr-Ed~nburg, Tex. 80,477 11.3 Memphis, Tenn.-Ark.-Miss. 77,589 15.5 Chicago, Ill. 74,370 19.4 New Orleans, La. 71,932 23.2 San Antonio, Tex. 54,749 26.1 Brownsville-Harlingen-San Benito, Tex. 53,632 28.9 Philadelphia, Pa.-N.J. 49,657 31.5 Baltimore, Md. 45,732 34.0 Los Angeles-Long Beach, Calif. 41,885 36.2 Remaining 229 metropolitan areas 100.0 37 Shifts in the location of ghetto poverty between 1970 and 1980 are well illustrated by charting the cities with the largest increases and decreases in ghetto poverty. Figures 2-4 and 2-5 show the increases and decreases, respectively, for the 10 cities with the largest increases and decreases. The 10 cities with the largest increases in ghetto poverty accounted for three-fourths (74 percent) of the total increase (Figure 24~. New York alone accounted for more than one-third, and New York and Chicago together accounted for half. Adding Philadelphia, Newark, and Detroit brings the total to two-thirds. Atlanta and Baltimore, unlike many other cities in the South, also had large increases. The eight northern cities on the list exhibit doubling and tripling of their ghetto poor populations. The increases were largely among blacks, although there was a significant Hispanic increase in New York The cities with large decreases (Figure 2-5) are of two types. The first are Texas cities with large decreases in ghetto poverty among Hispanics. The second are southern cities, with large decreases among blacks. The decreases were not nearly as localized in a few cities as were the increases. The 10 cities in the figure account for less than half (46 percent) of the total decrease. ,m, These facts begin to explain the widespread impression of rapidly increasing ghetto poverty. In certain cities, the area of the ghetto and the number of people affected are both increasing rapidly. These cities include some of the nation's largest population centers and the location of many large foundations, universities, and news organizations. What receives less notice are the decreases in ghetto poverty in the deep South and Texas. Many of the largest decreases in ghetto poverty occurred in small- to medium-sized metropolitan areas.

38 INNER-CllY POVERTY IN THE UNITED STATES 350 300 a: o s co _ 0 ~ cot ~ ~ c 3 LLI Or 250 200 150 1 00 50 o New York I Philadelphla I Detrolt I Atlanta I Putfalo I Chicago Newark Columbus (OH) Bal11more Paterson (NJ) STANDARD METROPOLITAN STATISTICAL AREA BLACK 1~\\~ HISPANIC 1~ NH WHITE/OTHER FIGURE 24 Increases in Number of Ghetto Poor, 1970-1980, by Race. o -2 4 -6 -8 to E CD it_ -~ o ." o ~ ~ o z z -1 2 -14 -1 6 -1 8 -20 -22 -24 -26 -28 _ Columbus (GA) I San Antonlo I Memphis I Charleston I Shreveport I New Orleans Corpus Crlstl Jackson (MS) McAllen, TX Brownsville STAN DARD M ETRO PO LITA N STATIST I CAL AR EA [~ E LACK ~ HISPANIC ~ N.H. WHITE/OTHER FIGURE 2-5 Decreases in Number of Ghetto Poor, 1970-1980, by Race.

GHETTO POVERTY: BASIC QUESTIONS TABLE 2-9 Distribution of Metropolitan Poor, 1970 and 1980, by Neighborhood Type, Region, and City Size Metropolitan Areas Ghetto Areas 1970 1980 19701980 Poor (thousands) 15,240 18,820 1,8912,449 100.0% 100.0% 100.0%100.0`Yo Region Northeast 25.0 24.2 13.032.7 North Central 22.1 21.3 14.221.8 South 34.4 34.5 65.039.4 West 18.5 19.9 7.76.1 Urban area type Central city -- 51.2 --86.6 "Suburbs" -- 48.4 --13.4 SMSA size Less than 500,000 26.7 30.2 38.524.0 500,000-1 ,000,000 16.6 16.0 16.213. 1 More than 1,000,000 56.6 53.8 45.462.9 39 The regional pattern is shown in Able 2-9, which also gives distribu- tions by city size. Relative to all metropolitan poor, the ghetto poor in 1980 were more likely to live in the Northeast or North Central region and to live in large cities.27 A substantial majority were in central cities. Moreover, most of those in "suburbs" were probably in places like East St. Louis, Illinois, and Camden, New Jersey, which are suburbs only in a technical sense. In 1970, in contrast, almost two-thirds of the ghetto poor were in the South, and more than half were in cities of less than a million population. The Level of Ghetto Poverb Table 2-9 shows that the distribution of the total metropolitan poor by region and city size did not change substantially between 1970 and 1980. Thus, changes in the regional and city-size distribution of the ghetto poor must have been brought about because of changes in the percentage of the poor living in ghettos, which we call the level of ghetto poverty.28 Looking first at the national data, Able 2-10 shows that the level of ghetto poverty increased only modestly among blacks (+1.2 percentage 27A few tracts are split across central-city boundaries; we have included these in suburbs. A comparable variable is not available on the 1970 census data tapes. 28Both the number of poor living in ghettos and the total number of poor in an area can change. Thus, the change in the number of ghetto poor (described above) and the change in the level of ghetto poverty (described in this section) can be quite different.

40 INNER-CITY POVERTY IN THE UNITED STATES TABLE 2-10 Change in Me Level of Ghetto Poverty, 1970-1980 No. of SMSAs Level of Ghetto Poverty 1970 1980 Change Black 176 26.5% 27.7% + 1.2 Creases 89 19.1 31.8 +12.8 Decreases 87 37.7 23.9 -13.8 Hispanic 151 23.7 18.6 Increases 99 14.2 28.1 +14.0 Decreases 52 32.4 14.4 -18.0 points) and decreased among Hispanics ~-5.1 percentage points). As with the changes in the number of ghetto poor, however, the aggregate levels conceal substantial variation. Some cities experienced large increases in the level of ghetto poverty and other cities experienced large decreases, changes that average out to a very modest national increase in ghetto poverty among blacks. Among Hispanics, the level of ghetto poverty doubled in the 99 cities where it increased, and it fell by more than half in the 52 cities where it decreased.29 The suggestion of strong regional shifts mentioned in the preceding section is borne out by the changes in the level of ghetto poverty in the metropolitan areas aggregated by region. The Northeast, dominated by New York, had an increase of nearly 20 percentage points in the level of ghetto poverty among blacks, as shown in Table 2-11. The North Central region also had a substantial increase. The South and West moved in the opposite direction. Again, it is clear that the appearance of a modest aggregate increase in ghetto poverty of 1.2 percentage points is quite misleading. Able 2-11 also shows the level of ghetto poverty by size of the metropolitan area. The SMSAs are divided into three groups by total population: less than 500,000; 500,000 to 1 million; and more than 1 mil- lion. The data for blacks show a remarkable reversal. In 1970, the highest level of concentration was in the smallest metropolitan areas; by 1980, the opposite was true. Disaggregating by region shows that the reversal is due to the fact that most of the smaller SMSAs are in the South. The general decline in the level of ghetto poverty in the South is most evi- dent in smaller SMSAs. The West also had larger decreases in the smaller SMSAs. In the Northeast and North Central regions, however, even smaller 2 9 The aggregate level of ghetto poverty as reported in the table is the weighted average of SMSAs in the group; some SMSAs were not included because (a) they did not exist in 1970 or (b) they existed but had zero blacks (or Hispanics) in 1970 or 1980 and, therefore, did not have a level of ghetto poverty (division by zero).

GHEITO POVERTY: BASIC QUESTIONS TABLE 2-11 Level of Ghetto Poverty by Region and Metropolitan Area Size, Black and Hispanic, 1970 and 1980 (percentage) 41 1970 SMSA Population All 1980 SMSA Population All S M L SMSAs S M L SMSAs Black poor in ghettos U.S. metro 37 29 22 27 22 25 31 28 Northeast 4 7 17 15 17 17 38 34 North Central 7 8 23 20 20 21 33 30 South 45 35 29 36 24 28 28 26 West 21 47 14 16 6 23 11 11 Hispanic poor in ghettos U.S. metro 48 12 14 24 22 10 19 19 Northeast 4 7 21 19 22 18 42 37 Nonh Central 4 0 4 3 5 4 10 9 South 64 17 23 45 32 1 1 1 1 21 West 11 13 6 8 2 3 5 4 Note: S = < 500,000; M = 500,000-999,999; L = > 1 million. Table contains data for 239 SMSAs in 1970 and 318 SMSAs in 1980. See Appendix A. SMSAs showed increases, although not as rapidly as larger SMSAs. His- panics followed similar patterns. The regional pattern is quite consistent in the North, less so in the South. In the North, all large cities except Boston had increases in their levels of ghetto poverty among blacks.30 The size of the increase varied considerably, however. In the South, the picture was more mixed. Most cities had decreases in ghetto poverty levels among blacks, some of them quite large. But Baltimore, Atlanta, and Miami had modest increases in ghetto poverty among blacks, and Fort Lauderdale had a large increase. There were also increases in a few smaller cities. Ghetto Poverty and the SMSA Poverty Rate What accounts for this strong regional pattern? Many factors are potentially involved, including regional differences in racial and economic segregation, changes in the economic structure of metropolitan areas, and 30Appendix A provides data for individual cities, organized by region and size of the metropoli- tan area.

42 o.so to 0.30 ~0.20 lo I_ , ~0.10 Cal Cal - -0.20 -0. 60 -0.70 INNER-CITY POVEKIY IN THE UNITED STATES n n S 0.00 -0.1 0 - _0,30 a S en _0.40 _ , ~ -O.SO _ ~' _ N n us. N t ~ s s - : N N n n N 4 N N :' An N N ~_ ~n n ~ n S. W ~S W S S w W w s n l l l l l -0.2S -0.1 S -0.OS 0.05 0.15 Chg. In Blac k Poverty Rate, 70 - 80 SMSAs Greater than 1 Million: N = North; S = South; W = West SMSAs Smaller than 1 Million: n = North; s = South; w = West FIGURE 2~ Ghetto poverty among blacks and the black poverty rate (changes 1970-1980, by region and size). interregional migration.3i One set of factors, however, that is clearly im- portant is the SMSA poverty rate among blacks and Hispanics. Figure 2~ shows the change in the level of ghetto poverty among blacks plotted against the change in the black poverty rate between 1970 and 1980. Each point represents an SMSA, and the symbols indicate the region and size of the metropolitan area.32 Clearly, there is a strong relationship between the change in the black poverty rate and the change in the level of ghetto poverty.33 Moreover, most of the cities with decreases in poverty are southern cities, especially smaller southern cities. Large northern cities are more often in the quadrant 3iTo cite just a few examples of research concerning the importance of these different factors, Wilson (1987) argues that changes in economic segregation among blacks play a key role; Massey and Eggers (1989) argue that interactions between black poverty and racial segregation are more important than economic segregation among blacks; others (Hughes, 1989; Kasarda, 1988) ex- amine the role of changes in the location of jobs within the metropolitan area. 32Figure 2~ includes only SMSAs that were defined in both decades and that had at least 10,000 blacks in 1970. Of 318 SMSAs, 148 satisfy both conditions. We excluded the smaller SMSAs because the level of ghetto poverty in such cities depends on the poverty rate of just one or two tracts and is therefore highly subject to random noise. 33The relationship is similar among Hispanics. Plotting the levels of poverty against the level of ghetto poverty, rather than against changes in levels, also shows a relationship, but a less strong one.

GHETTO POVERTY: BASIC QUESTIONS 43 with increases in black poverty and increases in ghetto poverty among blacks. The strength and consistency of the relationship might lead one to conclude, erroneously as it turns out, that the increases and decreases in ghetto poverty described above arose mechanically from changes in the poverty rate. In other words, as the poverty rate rises, more tracts are above 40 percent poverty and, thus, more of the poor live In ghettos. This is part of what happened, but the full picture is quite a bit more complex. In the section that follows, we look very carefully at the geography of the ghetto. We examine in detail the population movements and changes in poverty that actually occurred in several metropolitan areas. Any theory that attempts to explain what causes ghettos must not only explain the aggregate numbers presented in this section, but also the movements and changes observed at the tract level. As will be abundantly clear, the hypothesis that changes in poverty rate alone explain changes in ghetto poverty falls far short of this standard. THE GEOGRAPHY OF GHETTO POVERTY In the preceding section, we described changes in the number of persons living in ghettos and also in the level of ghetto poverty. We did not say much about the size of the ghetto, the location of the ghetto, nor the typical patterns of economic changes and population movements. This set of topics, which we refer to as the geography of ghetto poverty, is the subject of this section. We look at four specific cities two with large increases in the level of ghetto poverty, one with a modest increase, and one with a large decrease and describe what actually happened to the geography of the ghetto. We also describe the population changes that took place in different areas of the city, as a way of beginning to understand the complicated process by which groups of census tracts remain, become, or stop being ghettos. Finally, we look across SMSAs at the relationship between the black poverty rate and ghetto poverty.34 Understanding Increases in Ghetto Poverty The level of ghetto poverty that we discuss here is the percentage of the black poor living in ghetto areas.35 This level could have risen between 1970 and 1980 in several different ways: 34we do not look at interregional migration, despite suggestive evidence of its importance in the previous section. we are exploring this topic in our continuing work, along with other aspects of change in ghetto poverty. 35None of the four cities had substantial Hispanic populations.

44 INNER-CITY POVERTY IN THE UNWED STATES More of the black poor could have moved from other areas of the city into the ghetto. Without anyone's moving, the poverty rate could have gone up, causing some additional census tracts to go over the 40 percent cutoff. The poor in those tracts were then added to the count of the ghetto poor. With no change in the poverty rate, and no movements by poor people, nonpoor people could have move out of mixed-income census tracts. This would cause the group left behind to be poorer, and some additional census tracts would go over the 40 percent cutoff. Several of the above could happen simultaneously, with differential fertility and mortality and changes in family structure also playing a role. Each of these explanations can be identified in the data for specific census tracts. If poor people moving into the ghetto were the cause of the increase in ghetto poverty, there would be no new ghetto poverty tracts, and the number of people in the ghetto tracts would be increasing. If new ghetto tracts were being added mechanically by changes in the poverty rate, then the number of ghetto tracts should increase. The total number of people in both the 1970 ghetto tracts and the new ghetto tracts also should not change very much. The number of poor would go up, but by about the same amount as the decrease in the number of nonpoor people would simply be reclassified from nonpoor to poor. The data would look quite different, however, if the increase was caused by movement of the nonpoor out of mixed-income tracts. Again, there should be more ghetto tracts. But now, the new ghetto tracts should have fewer people in 1980 than in 1970. ~ examine these mechanics, we present data and ghetto maps for four cities: Cleveland, Memphis, Milwaukee, and Philadelphia. We examine the location of the 1970 and 1980 ghetto census tracts and the movement of people into and out of different areas. Identifying who was moving where does not tell us anything about why they moved. The root causes of the increases in ghetto poverty lie beyond these mere descriptions. Understanding these dynamics, however, is an Important first step and can help to frame the right questions to ask about the deeper causes. The four cities show different patterns of change. Cleveland is a large north-central city with a high level of poverty concentration in 1970 (32.8 percent) and a modest growth in con- centration (3.8 percentage points) from 1970 to 1980 (Figure 2-7~. Memphis is a large southern city with a large black population. It had an extremely high level of poverty concentration in 1970 (56.2 at.

GHEl7O POVERTY: BASIC QUESTIONS Jim - .li~' in. 1~ ..,.'. 't 1$':4 FIGURE 2-7 Cleveland SMSA change in tract poverty, 1970-1980. 45 S\CI1U!S 70/St~tUS 80 Naw/Spilt,/No Deta Not Pcor/Nc~t Ghetto Not Poor/Ghetm A.. ~Ji~d/Nat Ghatto 10_I Mixod/0hctl~ Chad~NDt chard ~ ch~n~ch~na percent) and a large decrease in concentration (-16.9 percentage points) between 1970 and 1980 (Figure 2-8~. · Milwaukee is a large north-central city with a small but growing black population. It had a low level of poverty concentration in 1970 (8.6 percent) but experienced very rapid growth (15.5 percentage points) (Figure 2-94. · Philadelphia is a large northeastern city with a moderate level of poverty concentration in 1970 (21.3 percent) and rapid growth in concentration (15.6 percentage points) between 1970 and 1980 (Figure 2-10~. The maps of the four cities show categories of census tracts, as follows: · Facts that were ghettos in 1970, divided into those that remained ghettos in 1980 and those that improved; Tracts that were mixed income (20 to 40 percent poor) in 1970 divided into those that had become ghettos by 1980 and those that had not; Tracts that were not poor (less than 20 percent) in 1970, again divided into those that had become ghettos by 1970 and those that had not; and

46 INNER-CITY POVERTY IN TlIE UNITED STATES FIGURE 2-8 Memphis SMSA change in tract poverty, 1970-1980. FIGURE 2-9 Milwaukee SMSA change in tract poverty, 1970-1980. .S101US 70/St~tUS 80 New/Spilt/Nc Deto Nat Poar/Not Ghetto Not Poor/Ghet~7 Mixod/Not Ghetto lli~/Ghott~ Chott~NDt Ch~tD (;hotto/~;hotto SIC]1US 70/St<:ltUS 80 New/Spil~Nn Dato Not Poor/Not Ghetto or . T ~1 3~ Not Pc~r/Ohatb, ~ ~Ji~d/Not Ghatto __ Mixed/Gh~tto Chett~NDt chid Chett~/~;hatta

GHElTO POVERTY: BASIC QUESTIONS Not Poor/Not Ghetto ~:~ 47 Status 70/Statue 80 New/Spilt/No Dato ~ ~ L is-_ r~; FIGURE 2-10 Philadelphia SMSA change in tract poverty, 1970-1980. Not Pwr/Bhet~ Cot Ghetto 11ixed/Chetto Ched~NDt ch~tD Ched - Chedo · Itacts that were added to the SMSA between 1970 and 1980, some of which resulted from splitting existing tracts, virtually none of which was poor in 1980. Ibble 2-12 shows the number of tracts that fell into the various categories. The table and the maps illustrate some important aspects of how changes in poverty concentration actually took place. The Geographic Spread of the Ghetto The maps of the four cities and Table 2-12 show that the ghetto areas in three of the four cities expanded geographically. Even in Memphis, where the proportion of the poor living in high-poverty areas declined substan- tially, the number of ghetto tracts decreased by only two. In Philadelphia, Milwaukee, and Cleveland, the geographical areas included in the ghetto expanded dramatically. In general, the areas that became ghettos between 1970 and 1980 were mixed-income tracts in 1970 that were contiguous to the 1970 ghetto areas. The maps illustrate that the process was not com- pletely orderly. Some 1970 ghetto tracts were no longer ghettos in 1980, even in the cities where ghetto poverty increased. Some 1980 ghetto tracts were not contiguous to the 1970 ghetto; a few were not poor-less than 20 percent in 1970. Nonetheless, the basic pattern was one of expansion of the ghetto into adjacent, mixed-income tracts.

48 INNER-CITY POVERTY IN THE UNITED STATES TABLE 2-12 Geographic Expansion of the Ghetto, 1970-1980 SMSA 1970 Neighborhood Type Cleveland Memphis Milwaukee Philadelphia Ghetto tracts 1970 19 37 11 26 Stayed ghetto in 1980 18 30 7 19 Improved by 1980 1 7 4 7 Mixed income 1970 51 31 43 99 Became ghetto by 1980 21 4 11 43 Did not become ghetto 30 27 32 56 Not poor 1970 Became ghetto by 1980 Did not become ghetto 340 57 3 337 303 1,047 1 1 4 302 1,043 Total ghetto tracts, 1980 42 35 l9 59 The expansion of the ghetto rules out the hypothesis that the increases in ghetto poverty (in the three cities with increases) were caused by poor people moving into the ghetto. To distinguish between the other two hypotheses that tracts became ghettos simply because of poverty rate changes or because the nonpoor moved out we look next at population movements. Movements from Ghetto and Mixed-Income Tracts Table 2-13 summarizes population changes between 1970 and 1980 in the 1970 ghetto and mixed-income areas. It shows population losses in both areas. This lends support to the idea that the nonpoor were moving out of mixed-income areas, causing them to "tip" and become ghettos. The patterns are complicated, however, and it is useful to lay them out in some detail. Table 2-13 shows what may appear to be a paradox: The 1970 ghetto area contained a smaller proportion of the black poor in 1980 than in 1970, even in cities in which the level of ghetto poverty increased substantially. The level of ghetto poverty, therefore, would have declined in these cities had not additional tracts been classified as ghettos. Mixed-income areas in all four cities what can be thought of as potential ghettos also saw sub- stantial population losses, even in Memphis, where the SMSA population was growing rapidly. In all four cities, the proportion of the black poor living in these areas declined substantially between 1970 and 1980. This is most consistent with the hypothesis that the increase in ghetto poverty was caused by the movement of nonpoor people out of the 1970 mixed-income areas. The poor were leaving as well, but the nonpoor left faster, leaving

GHETTO POVERTY: BASIC QUESTIONS TABLE 2-13 Population Loss in Ghetto and ~xed-~come Tracts, 1970-1980 SMSA Cleveland Memphis Milwaukee Philadelphia 1970 ghetto areas 1970 population 62,233 143,951 17,319 111,622 Change, population (%) -36.2 -21.6 -31.5 - 24.2 Change, black poor (%) -26.3 -23.5 -30.4 -14.2 % of black poor 1970 32.8 54.2 15.5 21.3 % of black poor 1980 21.9 38.2 7.1 14.8 1970 mixed-income areas 1970 population 151,638 134,609 119,090 491,169 Change, population (%) -36.8 -7.0 -20.9 -23.8 Change, black poor (%) -12.8 -6.1 +18.5 -1.6 % of black poor 1970 38.0 27.4 66.4 46.4 % of black poor 1980 30.0 23.7 52.0 37.0 49 behind a group of people in 1980 that were poorer than in 1970. As a result, some of the 1970 mixed-income tracts became ghettos by 1980. In three of the cities, the addition of the black poor in these new ghetto tracts to the shrinking proportion of the poor in the old ghetto was enough to result in an increase in the proportion of the poor living in ghettos. In other words, the level of ghetto poverty went up only because new areas were classified as ghettos.36 Perhaps it is not surprising that ghettos lost population over the decade. The data are consistent with the emptying out of downtown areas that has been observed in many cities. Given the harsh conditions of life in ghetto neighborhoods, anyone who could leave probably did. However, the fact that mixed-income areas also lost a large segment of their residents is somewhat surprising. One might have predicted increases in the number of black poor in these areas, at least in the cities in which ghetto poverty increased, since these are the areas from which new ghetto tracts formed. And one might have expected the people leaving the ghetto to settle there. Some may have, but on balance the population-poor and nonpoor declined substantially. The population, poor and nonpoor, black and white, was spreading out from poor and m~xed-income tracts into other areas. The next "ring," areas that were not poor and mostly white, became m~xed-~ncome and often mixed race, that is, they became home to a larger proportion of the black and poor population. The white nonpoor left these areas, which also lost population overall. Population growth took place 36This is a general pattern. Appendix A shows the number of ghetto census tracts in 1970 and 1980. In almost all of the areas in which the level of ghetto poverty increased, and even in many areas in which it decreased, the ghetto area was spreading out geographically.

50 INNER-CITY POVERTY IN THE UNITED STATES TABLE 2-14 Differential Movements in 1970 Mixed-~come Tracts, by Pattem of Change, 1970-1980 SMSA Cleveland Milwaukee Philadelphia Mixed-Inco~ne Tracts That Became Ghettos 1970 population 53,382 27,113 246,623 Change, black poor +1,085 +1,231 +4,164 Change, blaclc not poor -10,556 -3,149 -39,604 Change, white -11,124 -3,886 -26,034 Mixed-Income Tracts That Did Not Become Ghettos 1970 population 98,2S6 91,977 244,546 Mange, black poor -5,075 +2,269 -5,686 Change, blaclc not poor -16,323 -4,220 -26,619 Change, white -12,751 -18,228 -20,883 - by and large in tracts at the outskirts of the SMSAs, some of which were added to the metropolitan areas after 1:970. Tracts Becoming Ghettos In the three cities in which ghetto poverty increased (Cleveland, Mil- waukee, and Philadelphia), a part of what had been the mixed-income area became a ghetto. The number of mixed-income tracts that "tipped" into ghetto status varied by city, but was substantial in all three cities. A comparison of mixed-income tracts that became ghettos with those that did not reveals some interesting commonalities as well as contrasts. Ta- ble 2-14 shows population changes by race and poverty status in the 1970 mixed-income tracts that did and did not become ghettos in 1980. The 1970 mixed-income tracts that became ghettos lost population in all three cities. The number of black poor in these tracts generally went up, but the number of black nonpoor decreased by a much greater number. Since each of these three cities had an increase in the black poverty rate, the increase in the number of black poor came from a change of poverty status among some blacks. Declines in the white population occurred among both poor and nonpoor. Interestingly, the mixed-income areas that did not become ghettos showed, in all three cities, a pattern of population change that was basically similar to what occurred in the mixed-income tracts that became ghettos- although with somewhat different proportions of black and white, poor and nonpoor, among the movers and stayers. The mixed-income areas that did not become ghettos also lost population, both black and white. The

GHETTO POVERTY: BASIC QUESTIONS 51 difference between tracts that became ghettos and tracts that did not seems to be more one of degree than of kind. These data suggest that, at least in these four cities, the process by which geographical areas stayed, became, or stopped being ghettos was quite complicated. In none of the four cities was the process a simple matter of the poor moving into ghetto areas or the nonpoor moving out. Nor can the situation in any city be described as one in which people basically stayed put but changes in the poverty rate caused more areas to be pushed over the 40 percent line. Instead, we see a general pattern of dispersion probably part of a longer historical trend interacting with changes in the poverty rate and continuing high levels of racial segregation. CONCLUSIONS The purpose of this analysis was to investigate the problem of ghetto poverty. We have attempted to determine the size and extent of the ghetto problem in the United States and to learn if the problem was getting worse. We began with a belief in the conventional wisdom that urban ghettos were large and growing and deserved focused policy attention. Our tentative answers to our empirical questions about urban poverty reveal a much more diverse picture than we had anticipated. Our reading of the data for 1980 leads us to the following conclusions: · There were 2.4 million ghetto poor in the United States, about 9 percent of all poor persons, living predominantly in the central cities of large metropolitan areas. About half the ghetto poor lived in the Northeast or North Central regions, and another 40 percent lived in the South. The level of ghetto poverty varied greatly from city to city. . . The impression that ghetto poverty is growing rapidly turns out to be only partly true. Our reading of the data on the growth of ghetto poverty over the period 1970 to 1980 indicates the following: . . . Between 1970 and 1980 the number of ghetto poor increased by 29.5 percent, but the level of ghetto poverty (i.e., the percentage of the poor living in ghettos) increased only modestly among blacks and decreased among Hispanics. The aggregate numbers conceal substantial regional variation. Ghet- to poverty increased dramatically in large northern cities and de- creased equally dramatically in many southern cities, especially small- and medium-sized southern cities. Changes in the regional distribution of the ghetto poor were driven by changes in levels of ghetto poverty, which were very different

52 INNER-CITY POVERTY IN THE UNITED STATES among regions and to some extent varied from city to city within regions. Within four cities that we studied in detail, there was a pattern of emptying out of downtown neighborhoods. Ghettos and m~xed- income neighborhoods generally had substantial decreases in pop- ulation. In cities in which ghetto poverty increased, many new census tracts became ghettos. The process was driven by a combination of increases in the poverty rate and differential out-migration of the poor and nonpoor. There are large and growing ghetto poverty populations in perhaps a dozen large northern SMSAs. But the phenomenon of large and growing ghetto poverty populations characterizes only a canons of SMSAs. Prev~- ous work on this subject, including but not limited to our own (Bane and Jargowsky, 1988), usually was limited to the 50 or 100 largest metropolitan areas or central cities. The focus on large cities missed an important part of the picture. When we looked at the data for all SMSAs, we found that many had small increases in ghetto poverty and that in the South most SMSAs had substantial decreases. The implications of these findings for public policy are not entirely clear. For one thing, SMSAs differ dramatically in the scope and nature of their urban poverty problems. Much more needs to be learned, both in the aggregate and at the level of individual SMSAs, before we can draw firm conclusions about the growth of poverty areas and their effects on their residents. However, our reading of the data would lead us to support the following guidelines for public policies concerning ghetto poverty: It probably makes sense to have policies that focus specifically on those SMSAs with large and growing problems, rather than a national policy based on an assumption that all cities are alike. The policies and programs for those SMSAs with large and growing problems should recognize the strong relationship between the general economic vitality of SMSAs and regions and the problems of particular neighborhoods and population groups. Policies that affect the geographic mobility of the poor and nonpoor may play an important role in ghetto formation. Thus, housing and development policies may have an important role to play in many cities. We offer these as preliminary suggestions, drawn from the data we have examined. More detailed recommendations would need to be based on a better understanding of the causes of the changes and variations documented here. We are investigating the causes of these changes in

GHETTO POVERTY: BASIC QUESTIONS 53 our ongoing research, and we hope that the basic data presented here encourage others to do the same. ACKNOWLEDGMENTS We would like to acknowledge the support of the Ford and Russell Sage Foundations. We received helpful comments on this paper from David Ellwood, Naomi Goldstein, and Julie Wilson. REFERENCES Adams, Terry, Greg Duncan, and Willard Rodgers 1988 The persistence of poverty. Pp. 78-79 in Quiet Hots: Race and Poverty in the United States, Fred R. Harris and Roger Wilkins, eds. New York: Pantheon Books. Anderson, Elijah 1989 Sex codes and family life among inner-city youth. Annals of the American Academy of Political and Social Science 501 (Janua~y):59-78. Auletta, Ken 1982 The Underclass. New York: Random House. Bane, Mary Jo, and Paul ~ Jargowsky 1988 Urban Poverty Areas: Basic Questions Concerning Prevalence, Growth and Dynamics. Center for Health and Human Resources Policy Discussion Paper Series, John F. Kennedy School of Government, Harvard University. Bean, Frank D., and Marta Tienda 1987 The Hispanic Population of the United States. New York: Russell Sage Foundation. Bureau of the Census 1970 1973b 1982a 1982b 1983a l983b 1983c 1985 1970 Census User's Guide. Washington, D.C.: U.S. Government Printing Office. 1973a 1970 Census of Population. Detailed Characteristics. United States Summary. PC(1~-D1. Washington, D.C: U.S. Government Printing Office. 1970 Census of Population, Subject Reports, Low-Income Areas in Large Cities. PC(2~-9B. Washington, D.C.: U.S. Government Printing Office. Census of Population and Housing, 1980: Summary Tape File 3 Technical Documentation. Washington, D.C.: Bureau of the Census. User's Guide. PHCS0-R1. Washington, D.C.: U.S. Government Printing Office. Census of Population, 1980. Vol. 1, Ch. C General Social and Economic Characteristics. Part 1: U.S. Summary. PCS0-1-C1. Washington, D.C.: U.S. Government Printing Office. Census of Population and Housing, 1980: Geographic Identification Code Scheme. PHC80-R5. Washington, D.C.: U.S. Government Printing Office. Census of Population and Housing, 1980: Census Tracts. PHC80-Z Washing ton, D.C.: U.S. Government Printing Office. 1983d Census of Population and Housing 1980: Swear Tape File 4 Technical Documentanon. Washington, D.C.: Bureau of the Census. Census of Population and Housing, 1980. Vol. 2: Subject Reports. Poverty Areas in Large Cities. PC80-2-8D. Washington, D.C.: U.S. Government Printing Office.

54 INNER-CITY POVERTY IN THE UNITED STATES 1989 Statistical Abstract of the United States, 109th ed. Washington, D.C.: U.S. Government Printing Office. Coulton, Claudia J., Julian Chow, and Shanta Pandoy 1990 An Analysis of Poverty and Related Conditions in Cleveland Area Neighbor- hoods. Center for Urban Poverty and Social Change. Cleveland, Ohio: Case Western Reserve University. Danziger, Sheldon H., and Daniel H. Weinberg, eds. 1986 Fitting Poverty: What Works and What Doesn't. Cambridge, Mass.: Harvard University Press. Dembo, Richard 1988 Delinquency among black male youth. In Youn.; Black, and Male in America: An Endangered Species, Jewelle Taylor Gibbs, ed. Dover, Mass.: Auburn House. Dornbusch, Stanford M., J. Merrill Carlsmith, Steven J. Bushwall, Philip L. Ritter, Herbert Leiderman, Albert H. Hastorf, and Ruth T. Gross 1985 Single parents, extended households, and the control of adolescents. Child Development 56:324341. Ellwood, David ~ 1986 The spatial mismatch hypothesis: Are there jobs missing in the ghetto? Pp. 147-190 in Richard B. Freeman and Harry J. Holzer, eds., 17ze Black Youth Employment Crisis. Chicago: University of Chicago Press. Barley, Reynolds 1984 Blacks and Whites: Narrowing the Gap? Cambridge, Mass.: Haward University Press. 1989 1tends in the Residential Segregation of Social and Economic Groups Among Blacks: 1970 to 1980. Unpublished paper prepared for Conference on the Duly Disadvantaged, October 19-21, 1989, Evanston, Ill. Flexner, Stuart, ed. 1987 The Random House Dictionary of the English Language. 2nd ed. New York: Random House. Garfinkel, Irwin, and Sara S. McLanahan 1986 Single Mopers and Their Children. Washington, D.C: The Urban Institute Press. Gibbs, Jewelle Taylor, ed. 1988 Young;, Black, and Male a' Amenca: An Endangered Species. Dover, Mass.: Auburn House. Hughes, Mark Alan 1989 Misspeaking truth to power. A geographical perspective on the "underclass" fallacy. Economic Geography 65~3~:187-207. Jencks, Christopher 1989 What is the underclass and is it growing? Focus 12~1~:14-26. Kasarda, John D. 1988 Jobs, migration, and emerging urban mismatches. Pp. 148-198 in Michael G. H. McGraw and Laurence E. Lynn, Jr., eds., Urban Change and Poverty. Washington, D.C.: National Academy Press. Lehmann, Nicholas 1986 The origins of the underclass. Atlantic Months June:31-55 (part 1) and July:54 68 (part 23.

GHETTO POVERTY: BASIC QUESTIONS 55 Mare, Robert D., and Christopher Winship 1984 The paradox of lessening racial inequality and joblessness among black youth: Enrollment, enlistment, and employment, 19641981. Arnc~ican Sociological Review 49 39-55. Massey, Douglas S., and Nancy A. Denton 1987 [lends in the residential segregation of blacks, Hispanics, and Asians: 1970-1980. American Sociological Review 52 802~25. 1988a The dimensions of racial segregation. Social Forces 67~2~:281-315. 1988b Suburbanization and segregation in U.S. metropolitan areas. American Ja~r nal of Sociology 94~33:592-626. 1989 Hypersegregation in U.S. metropolitan areas Black and Hispanic segregation along five dimensions. Demography 26~3~:373-391. Massey, Douglas S., and Mitchell L Eggers 1990 The ecology of inequality Minorities and the concentration of poverty, 197~1980. American Journal of Sociology 95~5~:1153-1188. Massey, Douglas S., Mitchell Lo Eggers, and Nancy A. Denton 1989 Disentangling the Causes of Concentrated Poverty. Unpublished paper, Population Research Center, University of Chicago. McGeary, Michael G. H., and Laurence E. Lynn, Jr., eds. 1988 Urban Change and Poverty. Washington, D.C.: National Academy Press. Moynihan, Daniel P. 1965 The Nemo blandly: The Case for National Action. Washington, D.C: Office for Family Planning and Research, U.S. Department of Labor. Nathan, Richard 1986 The Underclas~W~ll It Always Be with Us? Paper presented at the New School for Social Research, New York City. Nathan, Richard, and John Lago 1986 The Changing Size and Concentration of the Poverty Population of Large Cities, 1970-1980. Unpublished memorandum, Princeton University, Prince- ton, NJ. O'Regan, Katherine, and Michael Wiseman 1990 Binh weights and the geography of poverty. Focus 12~23:1~22. Ricketts, Erol R., and Ronald Mincy In press The Growth of the Underclass, 197~1980. Journal of Human Resources. Ricketts, Erol R., and Isabel V. Sawhill 1988 Defining and measuring the underclass. Journal of Policy Analysis and Management 7~23:316-325. Van Haitsma, Martha 1989 A contextual definition of the underclass. Focus 12~1~:27-31. Wilson, William Julius 1987 The Truly Disadvantaged. The Inner City, The Underclass, and Pub& Policy. Chicago: University of Chicago Press. The American Underclass: Inner City Ghettos and the Norms of Citizen ship. The Godkin Lecture, delivered at the John F. Kennedy School of Government, April 26, Harvard University, Cambridge, Mass. Wilson, William Julius, and Kathryn M. Neckerman 1986 Poverty and family structure: The widening gap between evidence and public policy issues. Pp. 232-259 in Fit Poverty: What Woks Ed What Doesn't, Sheldon H. Danziger and Daniel H. Weinberg, eds. Cambridge, Mass.: Harvard University Press. 1988

56 INNER-CII~Y POVERTY IN THE UNITED STATES APPENDIX A Issues Related to the Processing of Census Tract lopes PRIMARY AND COMPLEMENTARY SUPPRESSION In order to protect confidentiality, the Census Bureau suppresses some data at the census-tract level (Bureau of the Census, 1983d). If a census tract has fewer than 30 persons, data on persons other than the raw count are suppressed. Similarly, if a tract has fewer than 10 households, data on households other than the count and all data on families are suppressed. The criteria on persons and households are applied independently. Suppression of this type is known as primary suppression. On Summary Tape File 4A, our primary data source for 1980, each census tract may have up to seven separate records, including a total record, a black record, a white record, a Hispanic record, and so on. Primary suppression criteria are applied independently to each record. A second and more worrisome type of suppression is known as com- plementary suppression. This refers to the practice of suppressing records for a racial group with more than 30 persons or 10 households. This is done whenever a race-specific record or records could be subtracted from the total record to obtain data on a remaining group of fewer than 30 persons or 10 households. For example, imagine a census tract with 1,000 total persons, 980 whites and 20 blacks. The black data are suppressed (primary suppression) and the white data are also suppressed (comple- mentary suppression). It can also be more complicated. Imagine a census tract with 1,000 total persons, 500 whites, 480 blacks, and 20 Asians. The Asian data are suppressed (primary) and the black data are suppressed (complementary). The white data are not suppressed because complemen- taIy suppression is always applied to the smallest possible racial group. As with primary suppression, person-level suppression and household-level complementary suppression are done independently. The effect of primary suppression is minimal and can easily be ignored. However, complementary suppression is a problem because very large numbers of people (or households) can be affected. Moreover, tracts affected are not selected randomly but occur more frequently in integrated neighborhoods. This could create systematic biases in the data. We have corrected for complementary suppression in the following way. When the largest racial group was suppressed, the data for all races were substituted if the suppressed group was at least 90 percent of the total. This is the easier case. When the second largest group is suppressed, data for the largest group are subtracted from data for all races, again only

GHE17~0 POVERTY: BASIC QUESTIONS 57 if the suppressed group was at least 90 percent of the group derived by subtraction. (The second method works only for counts, not medians.) After either correction has been applied, the data for a given racial group may contain some data for persons of other races, but no more than 10 percent. In our judgment, this is preferable to systematically missing the other 90 percent. How much difference does this make? Suppose that we wanted to calculate the percentage of children in female-headed families. Suppose that the true rate for blacks is 50 percent, but after fixing complementary suppression the data include 10 percent whites with a 20 percent rate. We would then calculate a 47 percent rate for blacks in the census tract; not correcting for suppression would result in no data for blacks for the tract. Primary suppression was also used in 1970, but not complementary suppression (Bureau of the Census, 1970~. For further information, contact the authors. CHANGES IN SMSA BOUNDARIES, 197~1980 SMSAs are areas defined by the Census Bureau to reflect "a large population nucleus and nearby communities which have a high degree of economic and social integration with that nucleus" (Bureau of the Census, 1982b:Glossary, p. 45~. After each decennial census (and at other times based on projections), adjustments are made to the boundaries of SMSAs. The most common adjustment is to add a peripheral county as the SMSA expands. However, more major adjustments are also made. For example, between 1970 and 1980, the Dallas and Ft. Worth, Texas, SMSAs were merged; Nassau and Suffolk counties in New York State were removed from the New York City SMSA and became an entirely new SMS~ The changes in boundaries must be taken into account when comparing 1970 and 1980 SMSA data. For this chapter we have handled SMSA changes in the following way: · Additions of peripheral counties. Almost half of the SMSAs defined in 1970 had counties added to them between 1970 and 1980 (Bureau of the Census, 1983b:11-17~. Many of these counties were sparsely populated in 1970 and suburbanized over the decade. Therefore, we did not make any adjustments. In such cases, the geographic areas being compared are not the same, but the comparison is conceptually consistent. In some cases, however, ignoring these additions may mean that the 1970 and 1980 data are not strictly comparable. Merger of two 1970 SMSAs into one 1980 SMS~ There are four such cases: Durham and Raleigh, North Carolina; Ft. Worth and Dallas, Texas; Ogden and Salt Lake City, Utah; and Scranton and .

58 INNER-ctrY povERry IN TnE UNITED STATES WiLkes-Barre, Pennsylvania (Bureau of the Census, 1983b:11-17). In these cases, we merged the 1970 data to conform to the 1980 boundaries. · Transfers of territory between SMSAs. There are five such cases that we have been able to identity.* In each case we adjusted the 1970 data to conform to the 1980 boundaries, as follows: 1. Nassau and Suffolk counties, New York, were removed from the New York SMSA and became a new SMSA. 2. Bergen County, New Jersey, was shifted from the Paterson- Clifton-Passaic SMSA to the New York SMS~ 3. Bellingham, Franklin, and Wrentham, Massachusetts, were shifted from the Providence-Pawtucket-Warwick Rhode Island- Massachusetts SMSA to the Boston SMS~ 4. Abington, Hanson, and Stoughton, Massachusetts, were shifted from the Brockton SMSA to the Boston SMSA 5. LaPeer County, Michigan, was shifted from the Flint SMSA to the Detroit SMS~ Creation of new SMSAs. Sixty-nine completely new SMSAs were defined between 1970 and 1980. We included these SMSAs in the 1980 data. These SMSAs were typically small and had few ghetto poor. Thus, the effect on the comparison of the 1970 and 1980 data is small and is noted in footnotes in the appropriate places. BASIC DATA ON GHETTO POVERTY, 197~1980 As a result of these changes and corrections, we have data on 239 SMSAs in 1970 and 318 SMSAs in 1980. The table that follows includes data on the 239 SMSAs that were defined in both 1970 and 1980, ordered by region and size of metropolitan area in 1980. Within groups, the SMSAs are listed alphabetically. *We would like to thank James Fitzsimmons of the Population Division, Bureau of the Census, for helping us to identify these changes.

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63 ~) O 0) 0 ~ d. d. 0 CO LO . . . . . . . . . . ~ (!) ~1 ~) d- CO O) CO O O O - ~ N U) - O a' 0 10 d. CM * ** ** ~ O O d. . . . O 0 0 E LL o G z '11 ,, ~ ~n O ~ ~ E I Z ~, a~ C~ O ~ a) 0 - d- CO d 0 0 ~ ~ 0 0 CO CO 40 C ~_ ~ ~) (C~ - 0 d q 0 C\l CO C`) o: u' C') a) ~ ~ c C~ ~ 0 d U~ N C~J 0 0 . . . . _ Co ~ _ - d. - ~ 0 U) r~ r~ ~ 0 0 d. 0 O d. 0 0 CM - N d. CM _ r~ r~ c: 0 0) ~ ~. - CM d- C\l ~t 0 _. 0 0 d~ J ~) d- C~J 40 C~J Ct) a) o~ 0 - - CO 0 0 - CO CO O - CO 0 0 ~ d C~ - Q - - - N - U) ~ a) O) ~ c~ _ r_ _ d. 0 CO L~ _ CO 0 ~ ~ 0 ~ ~ 0 0 d. ~ ~ ~ ~ , ~) _ _ 0 0 0 0 0 0 _ co ~ c~ 0 0 0 0 - a) 0 c~ 0 0 c~ r~ r~ r~ ~C ~O l£) _ ~ - 0 0 N CO - C~J C\1 0 ~ U) 0 0 0 0 ~ t_ ~O Lt) 0 h ~) 0 r_ - - N d. CO - - 0 - - 0 C~J ~O O O a' _ o) 0 0 Lo 0 ~0 cO 0 ~0 cu ~0 0 d. 0 0 0 0 ~- CO 0 C\1 ~0 0 d. ~) <D O ~C\l 0 N CC, de ~0 ~CO 0) - O) - 0 - C\1 LD O ~Ct) _ _ a ~_ 0 _ 0 0 0 1~ o) _ a~ 0 r- cYJ c~ N - ~ 0 N C\l C\l ~ CO O1 - ~0 N O - O O 0) 0 N O) CO O O ~It) C~ O O It) Lt) N O) I~) - O CD O CO C ~- O - CO 0 0 0 0 CO d- r_ 0 0 r ~0 o~ co c ~o~ ~ 0 0 ~ co o~ ~ ~ uo _ _ 0 0 ~- 10 Q ~ CO - (7) 0 - t~5 C\l - 0 r~ ~ ~ ~ ~ CO CO C~ _ _ 0 d. O _ CXJ - C~ (U _ 0 0 U, O Ct) - _ _ 0 a, 0 0 ~ - _ _ o I O I a g12~ ' 3 ~ ~ ~ o 3 =§ ~ ~ ,Y a ~ 9 ~ ~ 3 = 3 Z

64 o u LL o m z '11 11 ~ ~n 0~ ~ I Z ~ I. r~ a) . _ o C~ ~Z N ~ ~1~o ~o ~ O o=° o~ o~ ~ S~ ~ 3' ~o u~ ~r ~ co u) ~ o) 0 ~ (D ~ 0 0 ~ N r_ 0 0 <0 ~ a~ ~ r_ q3 Co l.0 - ~ Co ~) C~l N - N ~) ~ N - N N N ~ ~ ~ ~ 2~ ~ a~ ~ ~ a~ ~ ~ ~ ~ O) 0 It) ~ ~ ~ N ~ - h~ ~ ~ U) CO O 0 ~o 0 _ a) 0 ~ h_ o) (D 0 N ~t O ~ N ~) N ~ U N ~ C') N N N ~ N - ~ - - N O) C~ O ~D a) 0 N ~ C~ O N ~ O ~) N 0: O O) ~ ~ ~ C: C`l - U _ q" CO CO CO r_ N 0) C~ tD O ~ <0 ~ (D ~ <0 ~ - C c~ o~ r~ _ ~ _ N _ O - O - ~ CO O) - - O CiJ ~) ~t 0 0 O O) - - h~ ~ u, ~r u, ~ 0 0 _ (D ~ O C~ _ _ ~ _ ~, o~ < U) O) ~ _o <D 0 0 {D 0) ~ N _ ~ _ a~ 0= 0 r~ a' u, u, ~ a, a) ~ cO ~ co N CO O 0 0 0 r N O 1` 0 CO O - ~ - O O - Lt) 0 C`' (0 0 ~) 0 ~ ~ ~ N N _ N O O O N O O O O O U ~ o ~ ~ O O O O co 0 0 ~ r~ 0 0 ~ ~ ~ N U ~ 0 CO ~ N O) N _ O) a) (D CO O ~) N 0 C\1 (0 - 0 - 11' , _ _ ~ N 0 ~ 0) ~t CO N t_ U~ O lt) cO ~I tO C') U t£) 0 N r_ ~ N 0 0 <0 h~ 0 0 (D (D N ~) N 0 ~ (O N 0) - - N - C _ C: t£) N Co u, o h_ o _ _ N ~ ~ ~ ~ ~ ~ 0 0 ~ ~ ~ U~ 0) u~ r~ _ 0 - <D 0 <0 O) C: O0 N ~ 0 ~ ~ ~ N - 0 0 0 ~ ~ ~ - - N _ _ O O ~ N - co co a~ N _ O N - 0 ~) - N (D a) CO - N 0 ~ r~ O _ O <0 0 ~ C') ~ U N ~ - C,) CO O) C') tO - ~ C,) N a N _ N N 0) ~ O ~ O C') 0 ~ {D N 0) N (0 40 ~) 1~ CO (D CO C~) ~) ~ CO - Ct) ~C ~- _ O I · ~ t ~L1J O : ~ ~ s ~< C~ O ~ ~ ~ Z Z O O ~ ~ 6 6 6 6 6 m m m m m C) ~ ~ C~

uI' 65 < ~ ~ . CO CO * , o 0 CM _ ~ ~ . . ~o _ < < ~o ~ *~. ~. #~. ~. . *~. *~* N O O ~ a:' ~ 0 1n o 0 0 0 co U. 0 0 ~t <0 ~ - 1` 0 ~ O (D ~ O ~ 0) {0 u~ C~ 0 0 - d 0 - O a~ _ 0 ~ {D CO - O ~ ~) ~ CtJ N ~ . C\l CM ~ ~- CO - C~J CO *~. *. *~e *~. ~ #~. *~* u~ ~ a ~0 0 co u~ ~ {D ~ ~> U~ CD - 0 0 - O (D u~ _ 0 o _ - C~ - O ~ ~ ~ q. 0 C~ O ~ CO O ~ O O - ~ ~ ~C~ O - ~ ~ ~- ~ ~) (0 I~) ~ ~) ~t N ~ ~ u) ~ u, _ 0 0 r~ 0 c r~ (o o - o c~ ~ ~ - o 1~) N C~ O O tD CO 1` ~ ~D N C~J _ Co ~ - C CU N C\l ~ ~ CO - O O - U. ~ 0 10 ~ O O ~ 1` 0 co 0 0 u' r~ co a, r~ ~o 0 a: _ a) ~ ~ _ C~ O ~ C7 CO O 0 ~ O ~ _ co (D O CC (D <0 r~ a) ao u, C co co CO 0 C\l C~ CM CM ~n O co ~ ~ O O ~r O ~ ~ m E `= mNc ~ ~ O X O N _ lD lD C') O O ~ O ~ <0 0 0 ~t ~ O O - ~ O) O ~ O O Ct) N CO 0) 0 ~ O N ~ N ~ ~ ~ ~ ~ N O ~0 _ O o) 0 0 0 0 0 0 _ Co 1~ N O CO C~: d. Ct ~C O O O u) 0 0 a, 0 - - ~ 0 c r~ ~ oo 40 a N N N lt) a, ~ co O 0 ~ ~ ~ ~ ~ CO 0 CO O ~ C') q Lt, N 0) C a, .D cO _ CO - O <0 CO N CO O O q" ~ O q. CO 0 a:' 0 (D N O U, 03 N CD ~ 0 <0 ~ 0 03 O O ~ O_ _ ~ ~) 0 o co ~ tD Ct) O) N ~ q CO CO Cl~ ~£) oD ~ O) 0 0) ~ N N O) ~ - 0) {D N CO {D 0 CO - N N lD C`) - N - N C') ~ a) O CO ~ N - (0 N (D ~ O - ~ O O) d~ CO CO ~ <0 tD - t_ u~ 0 co u~ a) co O) 0 ~ 0 N - 0 0) N CO CO N ~ k0 C`) O Ct) O O ~ N N ~:t C (D - O O N ~ O d' CO O r~ co h~ ~r~ ~ ~ r~ ~ _ _ 0 CO 0 r_ CO 0 N - - N N N (D N O O ~) (D {D C ,_ 0 0 N d O O - (0 ~) N O Cr) Ct) O) O) ~ N C) ~ CO U) N - - 1 0 a, h_ 0 0 P_ ~ co c o~ r~ 0 CD CO ~ N - O N O O ~ CO CO - 0 CO . N 6 O ( ~X i ~ ~ ~ ~ ~ ~ ~ ~ O ~ ~ ~ ~ O ~ ~ ~ O .co m 5 ~ ~ c~ UJ ~ ~ ~ ~ ~ I ~ ~.. 5 5 . _ o ~ a~ ~r o ~ 0 <0 0 CD CO _ ~ 1 a~ 0 - N oo CO , 0 a) 0 ~ N _ O - O) N O ~ N 0) - t.t) r~ o I I I J 6 z J Q ' ° ~n Z ~ ~ LL llJ Z _ ~ {L ~ ~ o

66 · ~< * ~ ~* ~< ~* ~ * < N · ~ ~ * ~ · ~ * _ ~ o co O N . . . . . . N ~ ~ O O - N ~ N N CO ~ U. _ ~ O O) (0 O) O CO O O N ~ CO ~) N O O O (C lD ~ CO C\l N N _ LL z r~ 1- _ ~ ~ _ O N CO O ~ U' N N '1 CO ~ . o U. o ~ o ~ o O o U. ~ Q ~ N lD t_ N ~ 0 l~n N LO ~ O) ~ ~ ~) 0) N N N - N C') U~ o ~ _ 0) _ O lD lD ~ O ~ ~ CO q" O) ~ (D a~ c~ ~) N ~) ~ ~) N _ ~ O O CD O a, - N (J) O N CO U) - ~ ~ . ~ · ~ O O O N ~) a) a) N ~ ~ N CO O lD ~ O O co ~) N O - N N _ ~ q ~ ~ a~ co ~ - a:, ~ '`) ~ N C~ ~ 0) (O N ~ ~ ~ r_ ~ N U) _ C~ m Z o V, 6 i O G o E ~ ~ ~ ~ . 8' O N N O ~ ~ - C~ O ~ CO CE 6 6 CO ~ aD CO CO CO ~ N - - N _ - - N . . . . cc' ~ 40 N ~) N - O a:' N ~ C') _ q. Lt) O (D ~ _ O O N - 0 ~ O CD - O 0 0 . . . . . . . . . . . o u' ~ ~ _ O N N N O - _ N 0 ~o a~ ~ 0 ~ ~ - ~ - . . . . . . . . . . - ~ C') ~ O - - N O a' NN - 0 0 ~ ~r 0 ~ ~o - O - - 0) 0 CO , _ 0) N Co o, o r_ _ ~r 0 0 r~ o> co a 0 0 u, ~ {D O u, _ _ 4O _ a) - 0 r~ o) ~o - 0 0 o) 0 0 tD O N a) N Lt) N O <0 - N C~ 0 - CO ~) 0 0 O - tO 0 ~ ~t N a, ur - co ~ a N a, N _ iD a) (D ~ - ~) O) N O N N Lt) r~ O ~ CO U, - ~ O CO _ O N 10 0 O) N CO o) CD O, CO ~ 0 C~ ~ r~ CO 0 N 0 0 <0 0 ~ ~ ~ 0 1~) N N N (D O O lD _ P_ ~ O) ~ 1` 0) C~ ~ ~ ~ N h~ - 0) N - ~ - N U' _ _ 6 - o C56 Z~ UJ_ I 6 O 6 LU I O XZ ~ ~ QO ~ LLI O t13 X ~S O~ co o,,, LLI O <' IEI 6 z 6 ~6 ~ ~'_ ~ 6 C) J O - o ~: Z~ OJ 1 O < ~O ~ I 0 2 6 6 6 6 111 ~ ~ c: CO ~ c'~ ~ co

67 o o o r ~CO (0 CO - t 2 z ~ ~- N o ~ ~ _ ~ * * =, ~ _ ~ ~ O ~ ~ ~ ~ _ 2 ~ ~ ~ ~ ~ ~ ~ J * O ~ ~ ~ ~ _ O ~ ~ ~ ~ O C' ~* .*,,~, O _ ~ {D O ~ ~ O #,**** *~**0 O O) CO O ~ O Ct) ,N O o LO ~ ~ {D ~ CO u, ~N ~ W O CO CO _ O) 40 Z O Ct) ~ O ~ ~ ~ O C ~ W ~ "N ~ ~ ~O00~- OOOC a:_ N _ O ~ ~ ~ ~ O O O ~ O ~ O O O O C :; ~ O ~C~ ~ ~ ~ _ ~ _ ~ ~ ~ O ~ ~ O_ CO CO N t~ Z~ O - ~ O ~ ~ CO CO CO O ~ CO ~ W O ~ _ a¢~ ~=~0 ~ ~ W o cn (D ~ O O (D a:~ 0 0 0 ,N N O U8) O {D O Ct7 N o O ~ oo ~ r ~ co ~> 0 w c~ CO {0 C,) N O ~ {D aN C') ,N N O ~t - N CO - o · ~. ~ $ 1 ~ ° ~ o ~ s o ~ ~ § , ~ ~ . ' , ~ ~ 2 o ~ ~ cO ~;; O ~ ~ O cn ~ ~ 6 m m m ~ ~ C~ ~ ~ ~. o ~ c~ c~ c~: u~ u~ c~ ~- > ~ ~o LL u, 4, ._ w o w ~ . c ~ ~ _ o E ~ O W _ _ ~ 5 J o 1 W O _ _ - o C n · c ~ ._ ~ ~ ._ ~ 5 c w ._ 4) .to ~ I ~ - 0 ~ _ W W ~ _ o o o U) s _ ~o - 4, , - 1 .. _ ~ * o _ Z .

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Inner-City Poverty in the United States Get This Book
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This volume documents the continuing growth of concentrated poverty in central cities of the United States and examines what is known about its causes and effects. With careful analyses of policy implications and alternative solutions to the problem, it presents:

  • A statistical picture of people who live in areas of concentrated poverty.
  • An analysis of 80 persistently poor inner-city neighborhoods over a 10-year period.
  • Study results on the effects of growing up in a "bad" neighborhood.
  • An evaluation of how the suburbanization of jobs has affected opportunities for inner-city blacks.
  • A detailed examination of federal policies and programs on poverty.

Inner-City Poverty in the United States will be a valuable tool for policymakers, program administrators, researchers studying urban poverty issues, faculty, and students.

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