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The Long-Run Effects of Parental Homeownership and Housing Quality on Later Life Outcomes
August 2026
Working Paper Number:
CES-26-54
We measure the effects of housing quality and living in renter- versus owner-occupied housing as a child on later life outcomes. Homeownership is the primary source of most US households' wealth, and homeownership and housing quality potentially have large impacts on children, yet we know relatively little about any long-term effects. Ownership and housing quality are correlated with income, neighborhood characteristics, and many other socioeconomic characteristics, making causal estimation difficult. Using the US Census Bureau's data linkage infrastructure, we create a new data linkage between the American Housing Survey (1995-2002) and administrative tax data (2016-2019), to investigate adult outcomes such as earnings and having a mortgage or owning a home, while comprehensively controlling for a wide variety of variables, including housing quality. We find strong positive correlations with growing up in a parent-owned home, approximately $2,000 higher incomes and a 6 percentage point increased likelihood of ownership. However, we find no evidence of causal effects: unobservables that are significantly less correlated with outcome and treatment than observables would drive the coefficients of interest to zero, and family fixed effects models that compare siblings to each other show no effect of years of childhood spent in an owned home or being born into an owned home.
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Regional Trends in Hospitals in the United States
August 2026
Working Paper Number:
CES-26-51
Regional disparities in healthcare access and health outcomes are well-documented in the United States. Rural localities face worse health outcomes and greater challenges to accessing care than urban localities, particularly in the South. This study examines national and regional trends in hospital establishments (openings and closings), employment, size (employees per establishment), and regional concentration over three decades. We document an era of declining hospital counts and increasing employment within the industry, highlighting how the trends have differed across regions and rurality. Finally, we consider how these trends relate to the current policy environment in the United States.
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Gifted Identification Across the Distribution of Family Income
December 2025
Authors:
Quentin Brummet,
Andrew Penner,
Emily Penner,
Leah R. Clark,
Michelle Spiegel,
Paul Hanselman,
Nicholas J. Ainsworth,
Aaron J. Ainsworth,
Christopher Cleveland,
Jacob Hibel,
Andrew Saultz
Working Paper Number:
CES-25-73
Currently, 6.1 percent of K-12 students in the United States receive gifted education. Using education and IRS data that provide information on students and their family income, we show pronounced differences in who schools identify as gifted across the distribution of family income. Under 4 percent of students in the lowest income percentile are identified as gifted, compared with 20 percent of those in the top income percentile. Income-based differences persist after accounting for student test scores and exist across students of different sexes and racial/ethnic groups, underscoring the importance of family resources for gifted identification in schools.
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Parental Death, Inheritance, and Labor Supply in the United States
December 2025
Working Paper Number:
CES-25-71
We are the first to study how inheritances affect labor supply in the U.S. using large-scale administrative data. Leveraging federal tax and Social Security records, we estimate event studies around parental death to investigate impacts on adult children. Our results indicate that the death of a last parent causes sizable gains in investment income'our main proxy for inheritances'and proportionate reductions in labor supply. On average, annual per-adult investment income at the tax unit level increases by about $300 (45 percent) and annual per-adult wage earnings decrease by $600 (2 percent). These earnings responses are large relative to the implied wealth transfer. Income effects are the dominant channel through which parental death reduces earnings, with children of wealthier parents exhibiting larger earnings reductions. Over six years, inheritances slightly equalize the distribution of investment income.
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Housing Capital and Intergenerational Mobility in the United States
August 2025
Working Paper Number:
CES-25-55
Housing represents the most important capital asset for most U.S. families. Despite substantial analysis of the intergenerational mobility of income, large gaps in our knowledge of the distribution of housing assets and their transmission over time remain, as housing is generally not reflected by income flows. Using novel linked data that combines survey responses with administrative tax data and information on ownership and valuation from property tax records for over 3.4 million families, we provide new evidence on the intergenerational transmission of housing capital. We find that housing capital is more persistent across generations than labor income. We document important disparities between average housing outcomes for White and Black children. These difference persist even conditional on parent rank in the distribution of housing assets, with the gap growing throughout the parental housing capital distribution. A decomposition shows that average differences in children's labor market outcomes associated with parental assets explain about half of the observed intergenerational persistence (a 'labor income channel'), and that there is also a substantial 'direct channel' ' conditional on children having the same earnings, children of parents with more housing assets have more assets themselves on average. The direct channel is also important for explaining the intergenerational gap in outcomes of Black and White children. Finally, we present quasi-experimental evidence that local housing supply constraints help explain spatial differences in intergenerational persistence across US counties. Our results establish the importance of housing markets, both independently from and jointly with labor markets, in shaping the intergenerational persistence of economic resources.
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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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Expanding the Frontier of Economic Statistics Using Big Data: A Case Study of Regional Employment
July 2024
Working Paper Number:
CES-24-37
Big data offers potentially enormous benefits for improving economic measurement, but it also presents challenges (e.g., lack of representativeness and instability), implying that their value is not always clear. We propose a framework for quantifying the usefulness of these data sources for specific applications, relative to existing official sources. We specifically weigh the potential benefits of additional granularity and timeliness, while examining the accuracy associated with any new or improved estimates, relative to comparable accuracy produced in existing official statistics. We apply the methodology to employment estimates using data from a payroll processor, considering both the improvement of existing state-level estimates, but also the production of new, more timely, county-level estimates. We find that incorporating payroll data can improve existing state-level estimates by 11% based on out-of-sample mean absolute error, although the improvement is considerably higher for smaller state-industry cells. We also produce new county-level estimates that could provide more timely granular estimates than previously available. We develop a novel test to determine if these new county-level estimates have errors consistent with official series. Given the level of granularity, we cannot reject the hypothesis that the new county estimates have an accuracy in line with official measures, implying an expansion of the existing frontier. We demonstrate the practical importance of these experimental estimates by investigating a hypothetical application during the COVID-19 pandemic, a period in which more timely and granular information could have assisted in implementing effective policies. Relative to existing estimates, we find that the alternative payroll data series could help identify areas of the country where employment was lagging. Moreover, we also demonstrate the value of a more timely series.
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Contrasting the Local and National Demographic Incidence of Local Labor Demand Shocks
July 2024
Working Paper Number:
CES-24-36
This paper examines how spatial frictions that differ among heterogeneous workers and establishments shape the geographic and demographic incidence of alternative local labor demand shocks, with implications for the appropriate level of government at which to fund local economic initiatives. LEHD data featuring millions of job transitions facilitate estimation of a rich two-sided labor market assignment model. The model generates simulated forecasts of many alternative local demand shocks featuring different establishment compositions and local areas. Workers within 10 miles receive only 11.2% (6.6%) of nationwide welfare (employment) short-run gains, with at least 35.9% (62.0%) accruing to out-of-state workers, despite much larger per-worker impacts for the closest workers. Local incidence by demographic category is very sensitive to shock composition, but different shocks produce similar demographic incidence farther from the shock. Furthermore, the remaining heterogeneity in incidence at the state or national level can reverse patterns of heterogeneous demographic impacts at the local level. Overall, the results suggest that reduced-form approaches using distant locations as controls can produce accurate estimates of local shock impacts on local workers, but that the distribution of local impacts badly approximates shocks' statewide or national incidence.
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Producing U.S. Population Statistics Using Multiple Administrative Sources
November 2023
Working Paper Number:
CES-23-58
We identify several challenges encountered when constructing U.S. administrative record-based (AR-based) population estimates for 2020. Though the AR estimates are higher than the 2020 Census at the national level, they are over 15 percent lower in 5 percent of counties, suggesting that locational accuracy can be improved. Other challenges include how to achieve comprehensive coverage, maintain consistent coverage across time, filter out nonresidents and people not alive on the reference date, uncover missing links across person and address records, and predict demographic characteristics when multiple ones are reported or when they are missing. We discuss several ways of addressing these issues, e.g., building in redundancy with more sources, linking children to their parents' addresses, and conducting additional record linkage for people without Social Security Numbers and for addresses not initially linked to the Census Bureau's Master Address File. We discuss modeling to predict lower levels of geography for people lacking those geocodes, the probability that a person is a U.S. resident on the reference date, the probability that an address is the person's residence on the reference date, and the probability a person is in each demographic characteristic category. Regression results illustrate how many of these challenges and solutions affect the AR county population estimates.
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Output Market Power and Spatial Misallocation
November 2023
Working Paper Number:
CES-23-57
Most product industries are local. In the U.S., firms selling goods and services to local consumers account for half of total sales and generate more than sixty percent of the nation's jobs. Competition in these industries occurs in local product markets: cities. I propose a theory of such competition in which firms have output market power. Spatial differences in local competition arise endogenously due to the spatial sorting of heterogeneous firms. The ability to charge higher markups induces more productive firms to overvalue locating in larger cities, leading to a misallocation of firms across space. The optimal policy incen tivizes productive firms to relocate to smaller cities, providing a rationale for commonly used place-based policies. I use U.S. Census establishment-level data to estimate markups and to structurally estimate the model. I document a significant heterogeneity in markups for local industries across U.S. cities. Cities in the top decile of the city-size distribution have a fifty percent lower markup than cities in the bottom decile. I use the estimated model to quantify the general equilibrium effects of place-based policies. Policies that remove markups and relocate firms to smaller cities yield sizable aggregate welfare gains.
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