Joseph B. Townsend’s research while affiliated with Stanford University and other places

Several recent studies have concluded that residential segregation by income in the United States has increased in the decades since 1970, including a significant increase after 2000. Income segregation measures, however, are biased upward when based on sample data. This is a potential concern because the sampling rate of the American Community Survey (ACS)—from which post-2000 income segregation estimates are constructed—was lower than that of the earlier decennial censuses. Thus, the apparent increase in income segregation post-2000 may simply reflect larger upward bias in the estimates from the ACS, and the estimated trend may therefore be inaccurate. In this study, we first derive formulas describing the approximate sampling bias in two measures of segregation. Next, using Monte Carlo simulations, we show that the bias-corrected estimators eliminate virtually all of the bias in segregation estimates in most cases of practical interest, although the correction fails to eliminate bias in some cases when the population is unevenly distributed among geographic units and the average within-unit samples are very small. We then use the bias-corrected estimators to produce unbiased estimates of the trends in income segregation over the last four decades in large U.S. metropolitan areas. Using these corrected estimates, we replicate the central analyses in four prior studies on income segregation. We find that the primary conclusions from these studies remain unchanged, although the true increase in income segregation among families after 2000 was only half as large as that reported in earlier work. Despite this revision, our replications confirm that income segregation has increased sharply in recent decades among families with children and that income inequality is a strong and consistent predictor of income segregation.

This paper investigates to what extent socioeconomic status (SES)‐based affirmative action in college admissions can produce racial diversity. Using simulation models, we investigate the racial and socioeconomic distribution of students among colleges under the use of race‐ or SES‐based affirmative action policies, or targeted, race‐based recruitment policies. We find, first, that neither SES‐based affirmative action nor race‐targeted recruiting on their own produce levels of racial diversity achieved by race‐based affirmative action. However, the two policies in combination, although likely expensive, may yield racial diversity comparable to race‐based affirmative action. Second, the use of affirmative action policies by some colleges reduces the diversity of similar‐quality colleges without such policies. Third, the combination of SES‐based affirmative action and race recruiting results in fewer academically‐overmatched Black and Hispanic students than under race‐based affirmative action, but the schools that use both also see a reduction in the academic achievement of enrolled students.

We develop and illustrate a general and innovative method for describing in detail the joint distribution of race and income among neighborhoods when only coarse income data are available. The approach provides estimates of the average income distribution and racial composition of the neighborhoods of households of a given racial category and specific income level. We illustrate the method using 2007–2011 tract-level data from the American Community Survey. We show, for example, that blacks and Hispanics of any given income typically live in neighborhoods substantially poorer than those of whites and Asians of the same income. Our approach provides a general method for fully characterizing the joint patterns of racial and socioeconomic segregation, and so may prove useful in understanding the spatial foundations and correlates of racial and socioeconomic inequality.

Residential segregation, by definition, leads to racial and socioeconomic disparities in neighborhood conditions. These disparities may in turn produce inequality in social and economic opportunities and outcomes. Because racial and socioeconomic segregation are not independent of each other, however, any analysis of their causes, patterns, and effects must rest on an understanding of the joint distribution of race/ethnicity and income among neighborhoods. In this article, we use a new technique to describe the average racial composition and income distributions in the neighborhoods of households with different income levels and race/ethnicity. Using data from the decennial censuses and the American Community Survey, we investigate how patterns of neighborhood context in the United States over the past two decades vary by household race/ethnicity, income, and metropolitan area. We find large and persistent racial differences in neighborhood context, even among households with the same annual income.