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Geographic Immobility in the United States: Assessing the Prevalence and Characteristics of Those Who Never Migrate Across State Lines Using Linked Federal Tax Microdata
March 2025
Working Paper Number:
CES-25-19
This paper explores the prevalence and characteristics of those who never migrate at the state scale in the U.S. Studying people who never migrate requires regular and frequent observation of their residential location for a lifetime, or at least for many years. A novel U.S. population-sized longitudinal dataset that links individual level Internal Revenue Service (IRS) and Social Security Administration (SSA) administrative records supplies this information annually, along with information on income and socio-demographic characteristics. We use these administrative microdata to follow a cohort aged between 15 and 50 in 2001 from 2001 to 2016, differentiating those who lived in the same state every year during this period (i.e., never made an interstate move) from those who lived in more than one state (i.e., made at least one interstate move). We find those who never made an interstate move comprised 75 percent of the total population of this age cohort. This percentage varies by year of age but never falls below 62 percent even for those who were teenagers or young adults in 2001. There are also variations in these percentages by sex, race, nativity, and income, with the latter having the largest effects. We also find substantial variation in these percentages across states. Our findings suggest a need for more research on geographically immobile populations in U.S.
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From Marcy to Madison Square? The Effects of Growing Up in Public Housing on Early Adulthood Outcomes
November 2024
Working Paper Number:
CES-24-67
This paper studies the effects of growing up in public housing in New York City on children's long-run outcomes. Using linked administrative data, we exploit variation in the age children move into public housing to estimate the effects of spending an additional year of childhood in public housing on a range of economic and social outcomes in early adulthood. We find that childhood exposure to public housing improves labor market outcomes and reduces participation in federal safety net programs, particularly for children from the most disadvantaged families. Additionally, we find there is some heterogeneity in impacts across public housing developments. Developments located in neighborhoods with relatively fewer renters and higher household incomes are better for children overall. Our estimate of the marginal value of public funds suggests that for every $1 the government spends per child on public housing, children receive $1.40 in benefits, including $2.30 for children from the most disadvantaged families.
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The Census Historical Environmental Impacts Frame
October 2024
Working Paper Number:
CES-24-66
The Census Bureau's Environmental Impacts Frame (EIF) is a microdata infrastructure that combines individual-level information on residence, demographics, and economic characteristics with environmental amenities and hazards from 1999 through the present day. To better understand the long-run consequences and intergenerational effects of exposure to a changing environment, we expand the EIF by extending it backward to 1940. The Historical Environmental Impacts Frame (HEIF) combines the Census Bureau's historical administrative data, publicly available 1940 address information from the 1940 Decennial Census, and historical environmental data. This paper discusses the creation of the HEIF as well as the unique challenges that arise with using the Census Bureau's historical administrative data.
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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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Household Wealth and Entrepreneurial Career Choices: Evidence from Climate Disasters
July 2024
Working Paper Number:
CES-24-39
This study investigates how household wealth affects the human capital of startups, based on U.S. Census individual-level employment data, deed records, and geographic information system (GIS) data. Using floods as a wealth shock, a regression discontinuity analysis shows inundated residents are 7% less likely to work in startups relative to their neighbors outside the flood boundary, within a 0.1-mile-wide band. The effect is more pronounced for homeowners, consistent with the wealth effect. The career distortion leads to a significant long-run income loss, highlighting the importance of self-insurance for human capital allocation.
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The Impact of Parental Resources on Human Capital Investment and Labor Market Outcomes: Evidence from the Great Recession
June 2024
Working Paper Number:
CES-24-34
I study the impact of parents' financial resources during adolescence on postsecondary human capital investment and labor market outcomes, using house value changes during the Great Recession of 2007-2009 as a natural experiment. I use several restricted-access datasets from the U.S. Census Bureau to create a novel dataset that includes intergenerational linkages between children and their parents. This data allows me to exploit house value variation within labor markets, addressing the identification concern that local house values are related to local economic conditions. I find that the average decrease to parents' home values lead to persistent decreases in bachelor's degree attainment of 1.26%, earnings of 1.96%, and full-time employment of 1.32%. Children of parents suffering larger house value shocks are more likely to substitute into two-year degree programs, drop out of college, or be enrolled in a college program in their late 20s.
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Neighborhood Revitalization and Residential Sorting
March 2024
Working Paper Number:
CES-24-12
The HOPE VI Revitalization program sought to transform high-poverty neighborhoods into mixed-income communities through the demolition of public housing projects and the construction of new housing. We use longitudinal administrative data to investigate how the program affected both neighborhoods and individual residential outcomes. In line with the stated objectives, we find that the program reduced poverty rates in targeted neighborhoods and enabled subsidized renters to live in lower-poverty neighborhoods, on average. The primary beneficiaries were not the original neighborhood residents, most of whom moved away. Instead, subsidized renters who moved into the neighborhoods after an award experienced the largest reductions in neighborhood poverty. The program reduced the stock of public housing in targeted neighborhoods but expanded access to housing vouchers in other, lower-poverty neighborhoods. Spillover effects on the poverty rates of other neighborhoods were small and dispersed throughout the city. Our estimates imply that cities that revitalized half of their public housing stock reduced the average neighborhood poverty rate among all subsidized renters by 4.1 percentage points.
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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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When and Why Does Nonresponse Occur? Comparing the Determinants of Initial Unit Nonresponse and Panel Attrition
September 2023
Working Paper Number:
CES-23-44
Though unit nonresponse threatens data quality in both cross-sectional and panel surveys, little is understood about how initial nonresponse and later panel attrition may be theoretically or empirically distinct phenomena. This study advances current knowledge of the determinants of both unit nonresponse and panel attrition within the context of the U.S. Census Bureau's Survey of Income and Program Participation (SIPP) panel survey, which I link with high-quality federal administrative records, paradata, and geographic data. By exploiting the SIPP's interpenetrated sampling design and relying on cross-classified random effects modeling, this study quantifies the relative effects of sample household, interviewer, and place characteristics on baseline nonresponse and later attrition, addressing a critical gap in the literature. Given the reliance on successful record linkages between survey sample households and federal administrative data in the nonresponse research, this study also undertakes an explicitly spatial analysis of the place-based characteristics associated with successful record linkages in the U.S.
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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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