This paper examines the effect of property rights on economic development within local labor markets, including how property rights change the equilibrium response to place-based policies. It does so in the context of federally recognized American Indian reservations, where a fraction of the land is held in trust by the US federal government and associated with restrictions on transactions. I find that incomplete property rights on reservations are responsible for lower wages and higher levels of unemployment. The direction of these findings is robust to an instrumental variables approach to dealing with the endogeneity of property rights. Next I shed light on the extent to which place-based policies can improve economic outcomes on reservations. I use a spatial equilibrium framework to study the incidence of casino adoption, a place-based policy unique to reservations. The key insight from the model is that incomplete property rights impose frictions in the housing market that lower the migration response to casino adoption, improving the likelihood that the local population benefits. Consistent with the model's predictions, I find that casino adoption raises average wages and that the wage effect is greater on reservations with more land in trust. My estimates suggest that wage increases correspond to welfare improvements. This paper provides insights into how place-based policies and property rights jointly shape economic outcomes through changes in the labor market, the housing market, and the mobility of workers.
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The Opportunity Atlas: Mapping the Childhood Roots of Social Mobility
September 2018
Working Paper Number:
CES-18-42R
We construct a publicly available atlas of children's outcomes in adulthood by Census tract using anonymized longitudinal data covering nearly the entire U.S. population. For each tract, we estimate children's earnings distributions, incarceration rates, and other outcomes in adulthood by parental income, race, and gender. These estimates allow us to trace the roots of outcomes such as poverty and incarceration back to the neighborhoods in which children grew up. We find that children's outcomes vary sharply across nearby tracts: for children of parents at the 25th percentile of the income distribution, the standard deviation of mean household income at age 35 is $4,200 across tracts within counties. We illustrate how these tract-level data can provide insight into how neighborhoods shape the development of human capital and support local economic policy using two applications. First, we show that the estimates permit precise targeting of policies to improve economic opportunity by uncovering specific neighborhoods where certain subgroups of children grow up to have poor outcomes. Neighborhoods matter at a very granular level: conditional on characteristics such as poverty rates in a child's own Census tract, characteristics of tracts that are one mile away have little predictive power for a child's outcomes. Our historical estimates are informative predictors of outcomes even for children growing up today because neighborhood conditions are relatively stable over time. Second, we show that the observational estimates are highly predictive of neighborhoods' causal effects, based on a comparison to data from the Moving to Opportunity experiment and a quasi-experimental research design analyzing movers' outcomes. We then identify high-opportunity neighborhoods that are affordable to low-income families, providing an input into the design of affordable housing policies. Our measures of children's long-term outcomes are only weakly correlated with traditional proxies for local economic success such as rates of job growth, showing that the conditions that create greater upward mobility are not necessarily the same as those that lead to productive labor markets.
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The Privacy-Protected Gridded Environmental Impacts Frame
December 2024
Working Paper Number:
CES-24-74
This paper introduces the Gridded Environmental Impacts Frame (Gridded EIF), a novel privacy-protected dataset derived from the U.S. Census Bureau's confidential Environmental Impacts Frame (EIF) microdata infrastructure. The EIF combines comprehensive administrative records and survey data on the U.S. population with high-resolution geospatial information on environmental hazards. While access to the EIF is restricted due to the confidential nature of the underlying data, the Gridded EIF offers a broader research community the opportunity to glean insights from the data while preserving confidentiality. We describe the data and privacy protection process, and offer guidance on appropriate usage, presenting practical applications.
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Race and Mobility in U.S. Marriage Markets: Quantifying the Role of Segregation
December 2022
Working Paper Number:
CES-22-59R
We examine racial disparities in upward intergenerational mobility of family income by linking American Community Survey respondents born in 1978-87 to their parents' tax records. This linkage facilitates better measurement of marriage-market processes than tax records alone. Relative to White individuals, we document lower upward mobility of partner income for Black, Hispanic, and Asian individuals. These disparities offset Asian women and men's advantages in personal income mobility, overturn Black women's small advantage, and compound Black men's disadvantage. We develop a novel nonparametric decomposition which reveals that these disparities are driven primarily by racial differences in marriage-market opportunities, but also by different partnering rates conditional on opportunities. We then apply a selection-correction methodology to estimate causal effects of childhood exposure to racial segregation. Our design approximates a shift in the current generation's segregation exposure, holding historical exposures constant. This channel generates substantial Black-White intergenerational mobility gaps across all income measures, and we show that these effects cumulate over a multigenerational horizon.
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What Drives Racial Segregation? New Evidence Using Census Microdata
October 2002
Working Paper Number:
CES-02-26
Residential segregation on the basis of race is widespread and has important welfare consequences. This paper sheds new light on the forces that drive observed segregation patterns. Making use of restricted micro-Census data from the San Francisco Bay Area and a new measurement framework, it assesses the extent to which the correlation of race with other household characteristics, such as income, education and immigration status, can explain a significant portion of observed racial segregation. In contrast to the findings of the previous literature, which has been hampered by serious data limitations, our analysis indicates that individual household characteristics can explain a considerable fraction of segregation by race. Taken together, we find that the correlation of race with other household attributes can explain almost 95 percent of segregation for Hispanic households, over 50 percent for Asian households, and approximately 30 percent for White and Black households. Our analysis also indicates that different factors drive the segregation of different races. Language explains a substantial proportion - more than 30 percent - of Asian and Hispanic segregation, education explains a further 20 percent of Hispanic segregation, while income is the most important non-race household characteristic for Black households, explaining around 10 percent of Black segregation.
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RESIDENTIAL MOBILITY ACROSS LOCAL AREAS IN THE UNITED STATES AND THE GEOGRAPHIC DISTRIBUTION OF THE HEALTHY POPULATION
February 2014
Working Paper Number:
CES-14-14
Determining whether population dynamics provide competing explanations to place effects for observed geographic patterns of population health is critical for understanding health inequality. We focus on the working-age population where health disparities are greatest and analyze detailed data on residential mobility collected for the first time in the 2000 US census. Residential mobility over a 5-year period is frequent and selective, with some variation by race and gender. Even so, we find little evidence that mobility biases cross-sectional snapshots of local population health. Areas undergoing large or rapid population growth or decline may be exceptions. Overall, place of residence is an important health indicator; yet, the frequency of residential mobility raises questions of interpretation from etiological or policy perspectives, complicating simple understandings that residential exposures alone explain the association between place and health. Psychosocial stressors related to contingencies of social identity associated with being black, urban, or poor in the U.S. may also have adverse health impacts that track with structural location even with movement across residential areas.
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What Caused Racial Disparities in Particulate Exposure to Fall? New Evidence from the Clean Air Act and Satellite-Based Measures of Air Quality
January 2020
Working Paper Number:
CES-20-02
Racial differences in exposure to ambient air pollution have declined significantly in the United States over the past 20 years. This project links restricted-access Census Bureau microdata to newly available, spatially continuous high resolution measures of ambient particulate pollution (PM2.5) to examine the underlying causes and consequences of differences in black-white pollution exposures. We begin by decomposing differences in pollution exposure into components explained by observable population characteristics (e.g., income) versus those that remain unexplained. We then use quantile regression methods to show that a significant portion of the 'unexplained' convergence in black-white pollution exposure can be attributed to differential impacts of the Clean Air Act (CAA) in non-Hispanic African American and non-Hispanic white communities. Areas with larger black populations saw greater CAA-related declines in PM2.5 exposure. We show that the CAA has been the single largest contributor to racial convergence in PM2.5 pollution exposure in the U.S. since 2000 accounting for over 60 percent of the reduction.
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Separate but Not Equal: The Uneven Cost of Residential Segregation for Network-Based Hiring
October 2024
Working Paper Number:
CES-24-56
This paper studies how residential segregation by race and by education affects job search via neighbor networks. Using confidential microdata from the US Census Bureau, I measure segregation for each characteristic at both the individual level and the neighborhood level. My findings are manifold. At the individual level, future coworkership with new neighbors on the same block is less likely among segregated individuals than among integrated workers, irrespective of races and levels of schooling. The impacts are most adverse for the most socioeconomically disadvantaged demographics: Blacks and those without a high school education. At the block level, however, higher segregation along either dimension raises the likelihood of any future coworkership on the block for all racial or educational groups. My identification strategy, capitalizing on data granularity, allows a causal interpretation of these results. Together, they point to the coexistence of homophily and in-group competition for job opportunities in linking residential segregation to neighbor-based informal hiring. My subtle findings have important implications for policy-making.
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County-Level Estimates of the Employment Prospects of Low-Skill Workers
July 2000
Working Paper Number:
CES-00-11
This study examines low-skill wage and employment opportunities for men and women at the county level over the period 1989-96. Currently, reliable direct measures of wages and employment rates for different demographic and skill groups are only available for large geographic areas such as regions and populous states or at infrequent intervals (e.g., from the Decennial Census) for some smaller areas. This study constructs indirect annual measures for all counties from 1989-96 by combining skill-specific information on earnings and employment from the Sample Edited Detail File (SEDF) of the 1990 Decennial Census and the 1990-97 Annual Demographic files of the Current Population Survey (CPS) with annual industry-specific information from the Regional Economic Information System (REIS). Special versions of the SEDF and CPS files that identify county of residence are used. The study regresses the low-skill wage and employment data from the SEDF and CPS files on a set of personal variables from the combined files and local employment measures derived from the REIS. The wage regressions are corrected for selectivity from the employment decision and account for county-specific effects as well as general time effects. Estimates from the regressions are then combined with the available employment data from the REIS to impute wage and employment rates for low-skill adults across counties.
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Race and Economic Opportunity in the United States: An Intergenerational Perspective
September 2018
Working Paper Number:
CES-18-40R
We study the sources of racial and ethnic disparities in income using de-identified longitudinal data covering nearly the entire U.S. population from 1989-2015. We document three sets of results. First, the intergenerational persistence of disparities varies substantially across racial groups. For example, Hispanic Americans are moving up significantly in the income distribution across generations because they have relatively high rates of intergenerational income mobility. In contrast, black Americans have substantially lower rates of upward mobility and higher rates of downward mobility than whites, leading to large income disparities that persist across generations. Conditional on parent income, the black-white income gap is driven entirely by large differences in wages and employment rates between black and white men; there are no such differences between black and white women. Second, differences in family characteristics such as parental marital status, education, and wealth explain very little of the black-white income gap conditional on parent income. Differences in ability also do not explain the patterns of intergenerational mobility we document. Third, the black-white gap persists even among boys who grow up in the same neighborhood. Controlling for parental income, black boys have lower incomes in adulthood than white boys in 99% of Census tracts. Both black and white boys have better outcomes in low-poverty areas, but black-white gaps are larger on average for boys who grow up in such neighborhoods. The few areas in which black-white gaps are relatively small tend to be low-poverty neighborhoods with low levels of racial bias among whites and high rates of father presence among blacks. Black males who move to such neighborhoods earlier in childhood earn more and are less likely to be incarcerated. However, fewer than 5% of black children grow up in such environments. These findings suggest that reducing the black-white income gap will require efforts whose impacts cross neighborhood and class lines and increase upward mobility specifically for black men.
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DOES PARENTS' ACCESS TO FAMILY PLANNING INCREASE CHILDREN'S OPPORTUNITIES? EVIDENCE FROM THE WAR ON POVERTY AND THE EARLY YEARS OF TITLE X
January 2017
Working Paper Number:
CES-17-67
This paper examines the relationship between parents' access to family planning and the economic resources of their children. Using the county-level introduction of U.S. family planning programs between 1964 and 1973, we find that children born after programs began had 2.8% higher household incomes. They were also 7% less likely to live in poverty and 12% less likely to live in households receiving public assistance. After accounting for selection, the direct effects of family planning programs on parents' incomes account for roughly two thirds of these gains.
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