Papers Containing Tag(s): 'American Community Survey'
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Viewing papers 1 through 10 of 302
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Working PaperExperimental Capture/recapture Estimation Using Census and Administrative Data
June 2026
Working Paper Number:
CES-26-38
This report expands upon the innovation of utilizing administrative records and third-party data implemented in the 2020 Census. The 2020 Census used administrative records and third-party data in address canvassing and nonresponse followup operations. The Census Bureau also has a long history of using administrative records of births, deaths, and other information to produce Demographic Analysis coverage estimates. Since 1980, the Census Bureau has produced capture-recapture coverage estimates by conducting an independent post-enumeration survey and utilizing dual system estimation approaches. This report presents the research results of attempting to see if administrative records and third-party data could be utilized to produce capture-recapture coverage estimates. This work uses an Expectation Maximization Log Linear Modeling approach previously researched by Statistics Netherlands and Statistics New Zealand. This report documents some of the experimental results from an evaluation that was part of the 2020 Census Program for Evaluation, Experiments, and Assessments.View Full Paper PDF
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Working PaperFlood Risk, Insurance, and Housing in the United States
June 2026
Working Paper Number:
CES-26-37
Flooding is among the most salient natural hazards facing households in the United States. A large body of evidence has documented a pattern of disproportionate social vulnerability in floodplains. However, little evidence exists on how household-level exposure to flood risk is distributed. We fill this gap by combining parcel-level flood risk with confidential linked survey and administrative data held at the US Census Bureau. Although net migration to Census blocks in floodplains has increased in recent years, there has been essentially no net migration to parcels with flood risk or change in the overall share of households living in floodplains. Income gradients in flood risk are highly non-linear at the household level, with slightly negative income gradients for the bottom 90 percentiles of the income distribution that are dwarfed by disproportionate exposure in the top decile, especially when considering multiple property ownership. This nonlinearity is largely driven by differences in building type and homeownership within narrow income groups. In contrast to the conclusions in the literature using aggregate data, our household-level analysis suggests that households in floodplains are less disadvantaged and increasingly protected from the impacts of flooding, even as a vulnerable subpopulation of low-income, uninsured homeowners remains.View Full Paper PDF
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Working PaperRemote Work and Residential Sorting: IV Evidence From Expiring Office Leases
June 2026
Working Paper Number:
CES-26-34
How has remote work reshaped residential sorting and housing demand, and what are the implications for state and local governments? To estimate causal effects, I propose a novel instrument for remote work that exploits quasi-random variation in the timing and size of office lease expirations, captured through a Bartik-style exposure measure at the residential block level. Expirations allow tenant firms to reduce office space and switch employees to remote work, generating strong first-stage effects. Remote work causes modest increases in housing and property tax expenditures in exchange for space, homeownership, and public schools, but not other neighborhood characteristics. It significantly increases migration, particularly out of cities and states that levy income taxes. At the neighborhood level, higher 2020 remote work shares cause subsequent residential turnover, demographic clustering, and property tax revenue windfalls. Taken together, the results indicate that remote work induces migration consistent with Tiebout sorting, and accounts for 10% of migration since 2020. Residential choices and tax bases now depend less on employment proximity and more on affordability and tax-benefit linkage.View Full Paper PDF
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Working PaperEmployees in the US Nonprofit Sector
May 2026
Working Paper Number:
CES-26-33
The nonprofit sector employs roughly 10% of the American workforce, making it the third largest workforce behind the retail and manufacturing sectors. Despite this, relatively little is known about its employees. This paper is the first to use comprehensive administrative tax data, covering the near-universe of workers in the US, to quantify and explain the causes of the nonprofit pay differential. Unconditionally, we find the nonprofit earnings penalty to be 12% relative to for-profit workers. Estimating an 'AKM' worker-firm job ladder model, we show that most of the penalty is causal and not driven by selection. We also document considerable heterogeneity across industries, both in terms of earnings premia/penalties and worker selection, and show that nonprofit and for-profit earnings have been converging over time.View Full Paper PDF
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Working PaperThe Impact of Expanding Public Health Insurance on Safety Net Program Participation: Evidence From the ACA Medicaid Expansion
May 2026
Working Paper Number:
CES-26-32
We examine spillover effects from the ACA Medicaid expansion to public programs providing cash and food assistance. We consider program participation in contiguous county pairs crossing state borders, where one state took up the Medicaid expansion and the other did not, allowing us to better control for local economic trends that could affect program participation. We find that the Medicaid expansion increased participation in food assistance and one of the cash programs, with impacts mainly due to participation conditional on eligibility, rather than from labor supply responses. Our results demonstrate the potential for spillovers across safety net programs.View Full Paper PDF
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Working PaperEmployment and Earnings Trajectories of HUD Program Participants
May 2026
Working Paper Number:
CES-26-31
Federal housing assistance programs, such as those run by the U.S. Department of Housing and Urban Development (HUD), have been shown to reduce rent burden and improve housing stability for program participants, which may in turn have downstream impacts on their labor market attachment and career trajectories. However, existing studies from individual cities or states provide mixed evidence on the association of housing assistance with labor market outcomes. By linking HUD administrative records to matched employee-employer earnings records from the Longitudinal Employer-Household Dynamics (LEHD) program, we document how the labor market trajectories of program participants change as they enter and exit federal housing assistance programs, examining outcomes over a 14-year window surrounding entry or exit. In our analysis of entry, we find that the employment rates and earnings of first-time HUD program participants begin to increase upon entering a HUD program, which represents a reversal of prior declining trends in these outcomes. Suggestive of a positive association, these increases in employment and earnings trends exceed those of low-income non-participants from the American Community Survey (ACS). In our analysis of exits, we find that program participants who eventually leave a HUD program have increasing pre-exit trends in employment and earnings that then flatten upon exiting. Comparing these negative changes in trend to the relatively stable trajectories of those who remain in HUD programs throughout the analysis suggests that exits are associated with diminished employment and earnings trajectories.View Full Paper PDF
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Working PaperLands of Opportunity: Differences in the Geography of Wealth and Income Mobility in the United States
May 2026
Working Paper Number:
CES-26-30
We provide new county-level estimates of intergenerational mobility, covering multiple economic concepts: total income, labor income, homeownership, housing wealth, and total wealth. This is possible via small-area estimation techniques and linked survey and administrative data covering millions of U.S. children born between 1978 and 1986. We find that relative mobility in wealth concepts shows less spatial clustering and more spatial variation than relative mobility in income concepts. Many cities and their suburbs exhibit lower relative mobility (i.e. higher intergenerational persistence) in wealth concepts than in income concepts. Next, we show that various local characteristics are associated with some concepts of economic mobility but not with others. For example, we estimate a strong negative association between the local severity of the Great Recession and child income, regardless of parent position in the income distribution. However, the negative association between recession severity and wealth only exists among children from poorer families. We provide a public-use data package on census.gov to facilitate further research.View Full Paper PDF
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Working PaperYou're (not) Hired: Artificial Intelligence and Early Career Hiring in the Quarterly Workforce Indicators
April 2026
Working Paper Number:
CES-26-27
Using detailed tabulations from matched employer-employee administrative data, I document evidence of an immediate, sizable, and persistent decrease in the level of early career (22-24 year old) hires following introduction of ChatGPT within the industry-state cells that are most exposed to AI. The decline in hires is the primary cause of large observed declines in employment over the subsequent period. Regressionadjusted employment of early career workers in the most AI-exposed quintile of industry-state cells declined by 12% over the 10 quarters following the introduction of ChatGPT, even as employment in lessexposed industries has remained stable. The rate of hiring largely recovered by early 2025, attributable to a smaller employment base. Earnings growth of early career workers in the most exposed industries slowed slightly relative to those in less exposed industries. Although the most AI-exposed quintile of detailed industries is dominated by a handful of industry sectors, I find that the association of higher AI exposure with reduced early career employment and fewer hires is observed across most sectors of the economy. Timing of effects in event studies is consistent with an immediate effect on hiring following introduction of ChatGPT. However, triple difference estimates provide some evidence of earlier trend shifts on employment, hiring, and separations around the onset of the COVID pandemic. I discuss potential explanations, including the increase in remote work and increased educational attainment among workers in AI-exposed occupations. Nonetheless, job gains to early career workers and backfill hires show evidence of discontinuous decline at the time of ChatGPT's release in comparison to older workers in the same industries. A local projections analysis at the NAICS industry group level shows that industries with high AI exposure are not particularly sensitive to unexpected fluctuations in monetary policy on average relative to other industries in employment, hiring, or separations. A historical decomposition suggests that up to one quarter of relative early career employment declines through 2025q2 may be attributable to monetary policy shocks through 2023, but the analysis does not find evidence that these shocks can explain the rapid decline in hires at the most AI-exposed firms in comparison to others.View Full Paper PDF
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Working PaperCommunity Engagement and Public Safety: Evidence From Crime Enforcement Targeting Immigrants
April 2026
Working Paper Number:
CES-26-23
We study the role of victim reporting in the production of public safety. We examine the Secure Communities program, a crime-reduction policy that involved police in detecting unauthorized immigrants and increased deportation fears in immigrant communities. We find that the policy reduced the likelihood that Hispanic victims report crimes to police and increased offending against Hispanics. The number of reported crimes is unchanged, masking these opposing effects. We show that reduced reporting drives the offending increase and provide the first elasticity of offending to victim reporting in the literature, calculating that a 10% decline in reporting increases offending by 7.9%.View Full Paper PDF
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Working PaperThe Role of Homophily in Response to Labor Market Opportunities: Differences Across Race and Ethnicity
March 2026
Working Paper Number:
CES-26-22
This paper investigates the role that homophily might play in explaining racial/ethnic disparities in the labor market. We find that Black and Hispanic workers are less responsive than White workers to changes in job opportunities, but responsiveness increases when those opportunities present themselves in locations with a higher share own-race population. The analysis makes use of restricted American Community Survey data, accessible through the Federal Statistical Research Data Centers, allowing us to include commuting zones that may otherwise not be identified because of suppressed location information in the public dataView Full Paper PDF
