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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

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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."

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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.

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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.

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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.

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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.

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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.

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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

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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.

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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

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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.

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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 .

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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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