Papers Containing Tag(s): 'American Community Survey'
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Viewing papers 1 through 10 of 297
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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
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Working PaperStatus Inconsistency and Geographic Mobility in the United States
March 2026
Working Paper Number:
CES-26-20
This study examines how neighborhood status and individual status jointly shape geographic mobility in the United States. Drawing on restricted-use American Community Survey data, we conceptualize neighborhood status as the relative standing of a census tract's median family income compared to demographically similar reference neighborhoods, and individual status as a household's relative income rank within its tract. Building on comparison theory and status inconsistency perspectives, we test whether mismatches between neighborhood and individual status influence short-distance (within-county) and long-distance (between-county) mobility. Multinomial logistic models reveal that disadvantaged neighborhood status increases within-county mobility, particularly when paired with high individual status, supporting spatial assimilation arguments. Conversely, low individual status in high-status neighborhoods heightens mobility, consistent with relative deprivation theory rather than status signaling. Results suggest that status inconsistency plays a central role in residential decision-making and that neighborhood status primarily affects short-distance mobility. The findings advance research on stratification and internal migration by integrating relative contextual and positional mechanisms.View Full Paper PDF
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Working PaperNeighborhood Racial Status and White Out-Mobility
March 2026
Working Paper Number:
CES-26-19
Drawing on American Community Survey data, this study examines how whites' relative socioeconomic standing vis-'-vis nonwhite neighbors affects the association between minority presence and white out-mobility. Moving beyond the racial preferences versus racial proxy debate, we integrate group competition and contact theories with status theory to conceptualize 'racial status' as whites' first-order income rank relative to the subgroup status of Black, Hispanic, and Asian residents at the census tract level. Multilevel linear probability models show that whites lacking advantaged status are generally more likely to move. However, the positive association between Black or Asian concentration and white departure is weaker among status-disadvantaged whites, while the negative association with Hispanic concentration is stronger. These patterns lend greater support to contact theory than to group competition theory. By foregrounding relative status, the study demonstrates that racial and socioeconomic mechanisms are intertwined in shaping white residential mobility.View Full Paper PDF
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Working PaperHow Do Neighborhoods and Firms Affect Intergenerational Mobility?
March 2026
Working Paper Number:
CES-26-18
We use data from the Longitudinal Employer Household Dynamics linked to the 2000 Census to study intergenerational earnings mobility in the United States. We augment the standard intergenerational transmission model relating children's log earnings to those of their parent with an additional term representing mean log parent earnings in the childhood neighborhood. The between-neighborhood intergenerational relationship is twice as strong as the within-neighborhood relationship, even after adjusting for measurement error in parents' earnings. Moreover, mean earnings of the parents in a neighborhood capture over 80% of the variation in unrestricted neighborhood effects that reflect differences in 'absolute mobility'. Next, we use an AKM framework to decompose parents', children's, and neighboring parents' earnings into person effects and establishment premiums. Children's person effects are mainly influenced by parents' and neighbors' person effects, whereas children's establishment premiums are mainly influenced by parents' and neighbors' establishment premiums. These patterns point to separate channels for human capital and access to jobs in the intergenerational transmission process. Finally, we explore the implications for the Black-white earnings gap. Neighborhoods explain 30% of the Black-white gap in children's earnings conditional on parents' earnings, operating largely through gaps in average person effects. Conditional on neighborhood average earnings, children from neighborhoods with higher Black shares achieve higher adult earnings.View Full Paper PDF
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Working PaperTrade and Welfare (across Local Labor Markets)
February 2026
Working Paper Number:
CES-26-16
What are the welfare implications of trade shocks? Theoretically, we provide a sufficient statistic that measures changes in welfare (to a first-order approximation) for the set of workers who start within a region, taking into account adjustment in frictional unemployment, labor force participation, the sectors to which workers apply for jobs, and the regions in which workers choose to live. Our theory is flexible; for instance, it allows for arbitrary heterogeneity in worker productivity and non-pecuniary returns (amenities) across unemployment, labor force non-participation, sectors, and regions. Empirically, we apply these insights to measure changes in welfare between 2000-2007 across workers who start in different commuting zones (CZs) in the U.S. in the year 2000. Finally, we identify the differential impact across CZs of a particular trade shock: granting China permanent normal trade relations.View Full Paper PDF
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Working PaperCollege Majors and Earnings Growth
February 2026
Working Paper Number:
CES-26-14
We estimate major-specific earnings profiles using matched American Community Survey (ACS) and Longitudinal Employer-Household Dynamics (LEHD) data. Building on Deming and Noray (2020), we exploit a long earnings panel to overcome key limitations of cross-sectional approaches to lifecycle estimation. We find that engineering and computer science majors experience earnings growth that is comparable to or faster than that of other majors, a category including humanities, education, psychology, and similar fields. In contrast, Deming and Noray (2020) use a crosscohort approach and find that earnings for engineering and computer science majors decline relative to other fields over the lifecycle.View Full Paper PDF
