Papers Containing Tag(s): 'American Community Survey'
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Viewing papers 1 through 10 of 309
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Working PaperGender Differences in the Returns to Double Majoring: A Case of Signaling?
September 2026
Working Paper Number:
CES-26-60
Over 15 percent of college graduates in the United States graduate with more than one major. While much research exists on the returns to different individual majors, less is known about the causal effects of double majoring. This study provides novel estimates on the returns to those who choose to double major as an undergraduate. We improve on previous studies that rely on controls for observable characteristics by addressing selection concerns in two notable ways. First, we control for institution-specific differences that may influence both the decision to double major and subsequent earnings using proprietary data by including institution fixed effects. Second, we adopt a partial identification approach to address non-random selection into double majoring within institutions. Results broadly align with estimates from prior studies at the aggregate level, but reveal notable gender differences not previously detected. Women experience an earnings return to double majoring of approximately 5 percent, while the return for men is statistically negligible. Our analysis suggests that this discrepancy is consistent with double majors serving as a signaling effect in the labor market, which may help offset the gender pay gap.View Full Paper PDF
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Working PaperGraduating Into Disruption: Labor Market Outcomes for AI-Exposed College Majors
September 2026
Working Paper Number:
CES-26-56
How are new college graduates affected by the rise of artificial intelligence, and what can this tell us about the mechanisms behind AI's overall labor market effects? We use administrative records on college graduates to observe how economic outcomes among college majors with differing levels of labor market AI exposure have evolved since large language models became available. We find that post-graduation employment, earnings, and job switching patterns among the most AI-exposed college majors began to diverge immediately following the introduction of ChatGPT in late 2022. In regression-adjusted estimates, the most AI-exposed decile of college majors saw their likelihood of initial employment decline by five percentage points, while full-quarter initial earnings declined by thirteen percent. This earnings decline is comparable in magnitude to the earnings losses associated with graduating into a large recession. Roughly half of the decline in earnings is attributable to lower earnings within the industry sectors that employ these graduates, with the remainder resulting from a shift in the industry mix into lower-wage sectors such as restaurants and retail. The effects attenuate as graduates move further from labor market entry but remain substantial for the most exposed majors.View Full Paper PDF
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Working PaperThe 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.View Full Paper PDF
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Working PaperThe Distribution and Consequences of Natural Disasters: Evidence From U.S. Wildfire Victims
August 2026
Working Paper Number:
CES-26-53
The economic burden of natural disasters is shaped by who is exposed, who experiences losses, how those losses alter individual economic trajectories, and how affected communities evolve in the aftermath. We link property-level damage data from over 100 U.S. wildfires to administrative tax and Census data to understand individual level relationships between disaster damage and economic outcomes. Residents of burned areas are wealthier than the U.S. population on average, but within these wildfire perimeters the likelihood that a home burns is negatively correlated with pre-fire income. Home destruction imposes costs beyond rebuilding the property: occupants of destroyed homes experience lower income for three years post-fire, producing cumulative income losses equal to 26 percent of pre-fire annual income. We do not detect income or employment effects for residents without direct property damage. Community recovery is slow and accompanied by changes in composition. Four years after a fire, half of destroyed addresses remain unoccupied and reoccupied addresses house residents with substantially higher incomes than before.View Full Paper PDF
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Working PaperExtending Place-Based Innovation Policy to Rural Areas: Using Oaxaca-Blinder Decomposition to Identify Endowment Deficiencies
July 2026
Working Paper Number:
CES-26-48
Place-based policy is premised on the idea that productive investments that address endowment deficiencies may release latent comparative advantages, stimulating growth while reducing regional disparities. Extending place-based policy to the domain of innovation is conceptually challenging given conventional wisdom that settlement size is the principal determinant of agglomeration economies that fuels innovation. However, growing concern that more places are being left behind by the innovation economy has prompted greater interest in ways to expand the geography of innovation. Using confidential firm-level data from the 2018 Annual Business Survey, this study examines differences in self-reported innovation activity between firms in rural and urban counties to identify possible endowment deficiencies. We do this by employing the Oaxaca-Blinder decomposition method to quantify the urban-rural innovation gap to better understand the relative contributions of firm characteristics, owner characteristics, and county-level factors.View Full Paper PDF
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Working PaperAccess to the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) at the State and Substate Levels: Meaning and Measurement
July 2026
Working Paper Number:
CES-26-44
This study estimates eligibility and access rates for the U.S. Department of Agriculture's (USDA) Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) administrative data linked with American Community Survey (ACS) data. This study is one result of a long-term research collaboration among USDA's Economic Research Service; the U.S. Department of Commerce, Bureau of the Census; USDA's Food and Nutrition Service (FNS); and participating state WIC agencies.'By analyzing WIC participation at the state and substate levels, the report provides insights into program reach and demographic differences. The findings confirm that the Census Bureau estimates meet high statistical reliability standards, providing valuable data for program officials and managers, and other stakeholders, to enhance program outreach and effectiveness. A key focus of the report is the comparison between Census Bureau and USDA, FNS estimates, which differ in methodology and measurement scope.View Full Paper PDF
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Working PaperIntegrating Administrative and Survey Data to Estimate WIC Eligibility and Access
July 2026
Working Paper Number:
CES-26-43
The Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) provides benefits to low-income, nutritionally at-risk women, infants, and children. To administer WIC, officials and program managers at the federal and state level want to understand who is eligible for the program, who among the eligible population chooses to participate, and who is not accessing the program despite their eligibility. Novel individual-level data linkages between restricted-use WIC Administrative Records and the American Community Survey provide WIC access rates estimated at the state and county levels, as well as estimates disaggregated by the demographic and socioeconomic characteristics of individuals and their households. These estimates are developed by the Census-FNS-ERS Joint Project, a research partnership among the U.S. Census Bureau, the US Department of Agriculture's Food and Nutrition Service and Economic Research Service, and state WIC agencies that provide the requisite WIC administrative data to the Census Bureau. This paper details and evaluates our current data linkage and estimation methods, reports results, and identifies areas for improvement and further research.View Full Paper PDF
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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
