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Creating High-Opportunity Neighborhoods: Evidence from the HOPE VI Program
January 2026
Working Paper Number:
CES-26-02
We study whether low-economic-mobility neighborhoods can be transformed into high-mobility areas by analyzing the HOPE VI program, which invested $17 billion to revitalize 262 distressed public housing developments. We estimate the program's impacts using a matched difference-in-differences design, comparing outcomes in revitalized developments to observably similar control developments using anonymized tax records. HOPE VI reduced neighborhood poverty rates by attracting higher-income families to revitalized neighborhoods, but had no causal impact on the earnings of adults living in public housing units. Children raised in revitalized public housing units earn more, are more likely to attend college, and are less likely to be incarcerated. Using a movers exposure design and sibling comparisons, we show that these improvements were driven by changes in neighborhoods' causal effects on children's outcomes. The improvements in neighborhood causal effects were driven in large part by changes in social interaction: HOPE VI increased interaction between public housing residents and peers in surrounding neighborhoods and increased earnings more for subgroups with higher-income peers. Many low-income families in the U.S. currently live in neighborhoods that are as socially isolated as the HOPE VI developments were prior to revitalization. We conclude that it is feasible to create high-opportunity neighborhoods and that connecting socially isolated areas to surrounding communities is a cost-effective approach to doing so.
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Credit Access in the United States
July 2025
Working Paper Number:
CES-25-45
We construct new population-level linked administrative data to study households' access to credit in the United States. These data reveal large differences in credit access by race, class, and hometown. By age 25, Black individuals, those who grew up in low-income families, and those who grew up in certain areas (including the Southeast and Appalachia) have significantly lower credit scores than other groups. Consistent with lower scores generating credit constraints, these individuals have smaller balances, more credit inquiries, higher credit card utilization rates, and greater use of alternative higher-cost forms of credit. Tests for alternative definitions of algorithmic bias in credit scores yield results in opposite directions. From a calibration perspective, group-level differences in credit scores understate differences in delinquency: conditional on a given credit score, Black individuals and those from low-income families fall delinquent at relatively higher rates. From a balance perspective, these groups receive lower credit scores even when comparing those with the same future repayment behavior. Addressing both of these biases and expanding credit access to groups with lower credit scores requires addressing group-level differences in delinquency rates. These delinquencies emerge soon after individuals access credit in their early twenties, often due to missed payments on credit cards, student loans, and other bills. Comprehensive measures of individuals' income profiles, income volatility, and observed wealth explain only a small portion of these repayment gaps. In contrast, we find that the large variation in repayment across hometowns mostly reflects the causal effect of childhood exposure to these places. Places that promote upward income mobility also promote repayment and expand credit access even conditional on income, suggesting that common place-level factors may drive behaviors in both credit and labor markets. We discuss suggestive evidence for several mechanisms that drive our results, including the role of social and cultural capital. We conclude that gaps in credit access by race, class, and hometown have roots in childhood environments.
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Impact Investing and Worker Outcomes
May 2025
Working Paper Number:
CES-25-30
Impact investors claim to distinguish themselves from traditional venture capital and growth equity investors by also pursuing environmental, social, and governance (ESG) objectives. Whether they successfully do so in practice is unclear. We use confidential Census Bureau microdata to assess worker outcomes across portfolio companies. Impact investors are more likely than other private equity firms to fund businesses in economically disadvantaged areas, and the performance of these companies lags behind those held by traditional private investors. We show that post-funding impact-backed firms are more likely to hire minorities, unskilled workers, and individuals with lower historical earnings, perhaps reflecting the higher representation of minorities in top positions. They also allocate wage increases more favorably to minorities and rank-and-file workers than VC-backed firms. Our results are consistent with impact investors and their portfolio companies acting according to non-pecuniary social goals and thus are not consistent with mere window dressing or cosmetic changes.
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Divorce, Family Arrangements, and Children's Adult Outcomes
May 2025
Working Paper Number:
CES-25-28
Nearly a third of American children experience parental divorce before adulthood. To understand its consequences, we use linked tax and Census records for over 5 million children to examine how divorce affects family arrangements and children's long-term outcomes. Following divorce, parents move apart, household income falls, parents work longer hours, families move more frequently, and households relocate to poorer neighborhoods with less economic opportunity. This bundle of changes in family circumstances suggests multiple channels through which divorce may affect children's development and outcomes. In the years following divorce, we observe sharp increases in teen births and child mortality. To examine long-run effects on children, we compare siblings with different lengths of exposure to the same divorce. We find that parental divorce reduces children's adult earnings and college residence while increasing incarceration, mortality, and teen births. Changes in household income, neighborhood quality, and parent proximity account for 25 to 60 percent of these divorce effects.
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Where to Build Affordable Housing?
Evaluating the Tradeoffs of Location
December 2023
Working Paper Number:
CES-23-62R
How does the location of affordable housing affect tenant welfare, the distribution of assistance, and broader societal objectives such as racial integration? Using administrative data on tenants of units funded by the Low-Income Housing Tax Credit (LIHTC), we first show that characteristics such as race and proxies for need vary widely across neighborhoods. Despite fixed eligibility requirements, LIHTC developments in more opportunity-rich neighborhoods house tenants who are higher income, more educated, and far less likely to be Black. To quantify the welfare implications, we build a residential choice model in which households choose from both market-rate and affordable housing options, where the latter must be rationed. While building affordable housing in higher-opportunity neighborhoods costs more, it also increases household welfare and reduces city-wide segregation. The gains in household welfare, however, accrue to more moderate-need, non-Black/Hispanic households at the expense of other households. This change in the distribution of assistance is primarily due to a 'crowding out' effect: households that only apply for assistance in higher-opportunity neighborhoods crowd out those willing to apply regardless of location. Finally, other policy levers'such as lowering the income limits used for means-testing'have only limited effects relative to the choice of location.
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Granular Income Inequality and Mobility using IDDA: Exploring Patterns across Race and Ethnicity
November 2023
Working Paper Number:
CES-23-55
Shifting earnings inequality among U.S. workers over the last five decades has been widely stud ied, but understanding how these shifts evolve across smaller groups has been difficult. Publicly available data sources typically only ensure representative data at high levels of aggregation, so they obscure many details of earnings distributions for smaller populations. We define and construct a set of granular statistics describing income distributions, income mobility and con ditional income growth for a large number of subnational groups in the U.S. for a two-decade period (1998-2019). In this paper, we use the resulting data to explore the evolution of income inequality and mobility for detailed groups defined by race and ethnicity. We find that patterns identified from the universe of tax filers and W-2 recipients that we observe differ in important ways from those that one might identify in public sources. The full set of statistics that we construct is available publicly as the Income Distributions and Dynamics in America, or IDDA, data set.
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An In-Depth Examination of Requirements for Disclosure Risk Assessment
October 2023
Authors:
Ron Jarmin,
John M. Abowd,
Ian M. Schmutte,
Jerome P. Reiter,
Nathan Goldschlag,
Victoria A. Velkoff,
Michael B. Hawes,
Robert Ashmead,
Ryan Cumings-Menon,
Sallie Ann Keller,
Daniel Kifer,
Philip Leclerc,
Rolando A. Rodríguez,
Pavel Zhuravlev
Working Paper Number:
CES-23-49
The use of formal privacy to protect the confidentiality of responses in the 2020 Decennial Census of Population and Housing has triggered renewed interest and debate over how to measure the disclosure risks and societal benefits of the published data products. Following long-established precedent in economics and statistics, we argue that any proposal for quantifying disclosure risk should be based on pre-specified, objective criteria. Such criteria should be used to compare methodologies to identify those with the most desirable properties. We illustrate this approach, using simple desiderata, to evaluate the absolute disclosure risk framework, the counterfactual framework underlying differential privacy, and prior-to-posterior comparisons. We conclude that satisfying all the desiderata is impossible, but counterfactual comparisons satisfy the most while absolute disclosure risk satisfies the fewest. Furthermore, we explain that many of the criticisms levied against differential privacy would be levied against any technology that is not equivalent to direct, unrestricted access to confidential data. Thus, more research is needed, but in the near-term, the counterfactual approach appears best-suited for privacy-utility analysis.
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The Long-run Effects of the 1930s Redlining Maps on Children
December 2022
Working Paper Number:
CES-22-56
We estimate the long-run effects of the 1930s Home Owners Loan Corporation (HOLC) redlining maps by linking children in the full count 1940 Census to 1) the universe of IRS tax data in 1974 and 1979 and 2) the long form 2000 Census. We use two identification strategies to estimate the potential long-run effects of differential access to credit along HOLC boundaries. The first strategy compares cross-boundary differences along HOLC boundaries to a comparison group of boundaries that had statistically similar pre-existing differences as the actual boundaries. A second approach only uses boundaries that were least likely to have been chosen by the HOLC based on our statistical model. We find that children living on the lower-graded side of HOLC boundaries had significantly lower levels of educational attainment, reduced income in adulthood, and lived in neighborhoods during adulthood characterized by lower educational attainment, higher poverty rates, and higher rates of single-headed households.
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Run Effects of Military Service: Evidence from the 911 Attacks
November 2021
Working Paper Number:
CES-21-36
We investigate the effect of military service on labor market, health and family formation outcomes, leveraging differential changes in enlistment rates brought about by the September 11th attacks (911). Using restricted microdata, we identify hundreds of 'high service" counties in which certain birth-county cohorts exhibit large enlistment responses to 911. We find that individuals born into high service counties between 1977 and 1983 (aged 18-24 at the time of the attack), enlisted at nearly twice the rate of earlier birth cohorts (older than 24 at the time of the attack). These high service birth-county cohorts experienced a 10% increase in wages, decreased unemployment and impacts on other labor market measures as well as key household formation measures including marriage and fertility. We also find increases in the hospitalization and mortality rates. Labor market benefits outweigh mortality costs at standard discount rates.
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Why the Economics Profession Must Actively Participate in the Privacy Protection Debate
March 2019
Working Paper Number:
CES-19-09
When Google or the U.S. Census Bureau publish detailed statistics on browsing habits or neighborhood characteristics, some privacy is lost for everybody while supplying public information. To date, economists have not focused on the privacy loss inherent in data publication. In their stead, these issues have been advanced almost exclusively by computer scientists who are primarily interested in technical problems associated with protecting privacy. Economists should join the discussion, first, to determine where to balance privacy protection against data quality; a social choice problem. Furthermore, economists must ensure new privacy models preserve the validity of public data for economic research.
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