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Status 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.
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Neighborhood 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.
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Positioned at Extremes: Future Job Placements of Immigrant Students at U.S. Colleges
January 2026
Working Paper Number:
CES-26-08
Immigrant students who attend U.S. colleges are disproportionately employed in either large firms'especially multinationals'or small firms and self-employment. Using linked Census and longitudinal employment data, we trace the jobs taken by college students in 2000 during the 2001-20 period and evaluate four mechanisms shaping sector and firm size placement: geographic clustering, degree specialization, firm capabilities/visas, and ethnic self-employment specialization. Degree fields predict large firm and MNE placement, while ethnic specialization explains small firm sorting. Immigrant students who remain in the U.S. earn more than their native peers, suggesting the segmentation reflects productive sorting rather than blocked opportunity.
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Careers of Minimum Wage Workers
January 2026
Working Paper Number:
CES-26-07
We characterize the careers of minimum wage workers by merging SIPP panels covering 1992-2016 into the LEHD. A long-run analysis shows strong earnings growth for these workers in subsequent decades, becoming indistinguishable from peers earning modestly more initially. Most of this growth is due to the steep earnings trajectories of young workers. Older workers earning minimum wages show a modest dip in earnings at that moment compared to earlier and later periods. Increases in state minimum wages do not significantly alter the future careers of workers who are on the minimum wage when the increases occur.
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Kids to School and Moms to Work: New York City's Universal Pre-K Expansion and Mother's Employment
September 2025
Working Paper Number:
CES-25-62
Using the restricted data from American Community Survey from 2011 to 2017, this paper examines the impact of New York City's (NYC) expansion of universal pre-kindergarten (UPK) on labor force participation of mothers with the youngest child of 4 years of age. Starting in Fall of 2014, any child who is 4 years old and residing in NYC for the past year is eligible for UPK for the academic year, for example all children born in 2010 would qualify for the academic year 2014-15. It uses a triple-difference approach - first compare mothers in NYC with the youngest child of 4-year-olds (treated mothers) to mothers with the youngest child of 5 and 6-year-olds (control mothers) before and after the program. Next, it compares this difference with mothers living in adjacent counties in the New York Metropolitan Area (NMA) in New York to NYC. I find that the program increased mothers' labor force participation by 5 percentage points (a 7.5 percent impact) in NYC. The results are robust to various robustness checks like comparing with mothers living in all of NMA and mothers in Philadelphia.
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Receipt of Public and Private Food Assistance Across the Rural-Urban Continuum Before and During the COVID-19 Pandemic: Analysis of Current Population Survey Data
August 2025
Working Paper Number:
CES-25-51
Background: The nutrition safety net in the United States is critical to supporting food security among households in need. Food assistance in the United States includes both government-funded food programs and private community-based providers who distribute food to in need households. The COVID-19 pandemic impacted experiences of food security and use of private and public food assistance resources. However, this may have differed for households residing in urban versus rural areas. We explored receipt of Supplemental Nutrition Assistance Program (SNAP) benefits or food from community-based emergency food providers across a detailed measure of the rural-urban continuum before and during the COVID-19 pandemic.
Methods: We linked restricted use Current Population Survey Food Security Supplement data to census-tract level United States Department of Agriculture Rural-Urban Commuting Area codes to estimate prevalence of self-reported SNAP participation and receipt of emergency food support across temporal (2015-2019 versus 2020-2021) and socio-spatial (urban, large rural city/town, small rural town, or isolated rural town/area) dimensions. We report prevalences as point estimates with 95% confidence intervals, all weighted for national representation.
Results:
The weighted prevalence of self-reported SNAP participation was 8.9% (8.7-9.2%) in 2015-2019 and 9.1% (8.5-9.5%) in 2020-2021 in urban areas, 11.4% (10.8-12.2%) in 2015-2019 and 11.6% (10.5-12.9%) in 2020-2021 in large rural towns/cities, 13.4% (12.3-14.6%) in 2015-2019 and 12.3% (10.5-14.5%) in 2020-2021 in small rural towns, and 9.7% (8.6-10.9%) in 2015-2019 and 10.9% (8.8-13.4% )in 2020-2021 isolated rural towns. The weighted prevalence of self-reported receipt of emergency food was 4.9% (4.8-5.1%) in 2015-2019 and 6.2% (5.8-6.5%) in 2020-2021 in urban areas, 6.8% (6.2-7.4%) in 2015-2019 and 7.6% (6.6-8.6%) in 2020-2021 in large rural towns/cities, 8.1% (7.3-9.1%) in 2015-2019 and 7.1% (5.7-8.8%) in 2020-2021 in small rural towns, and 6.8% (5.9-7.7%) in 2015-2019 and 8.5% (6.7-10.6%) in 2020-2021 isolated rural towns.
Conclusion: Households in rural communities use public and private food assistance at higher rates than urban areas, but there is variation across communities depending on the level of rurality.
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Dynamics of High-Growth Young Firms and the Role of Venture Capitalists
June 2025
Working Paper Number:
CES-25-38
Motivated by the substantial growth and upfront investments of venture capital (VC) backed firms observed in administrative US Census data, this paper develops a firm dynamics model over the life cycle. In the model, startups choose the source of financing from VC, Angel investors, or banks, depending on their growth potential, and invest in innovation. The calibrated model explains the life-cycle dynamics of firms with different sources of financing and implies that venture capitalists' advice accounts for around 22% of the growth of VC-backed firms. A counterfactual economy without VC financing would lose aggregate consumption by around 0.4%.
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Work Organization and Cumulative Advantage
March 2025
Working Paper Number:
CES-25-18
Over decades of wage stagnation, researchers have argued that reorganizing work can boost pay for disadvantaged workers. But upgrading jobs could inadvertently shift hiring away from those workers, exacerbating their disadvantage. We theorize how work organization affects cumulative advantage in the labor market, or the extent to which high-paying positions are increasingly allocated to already-advantaged workers. Specifically, raising technical skill demands exacerbates cumulative advantage by shifting hiring towards higher-skilled applicants. In contrast, when employers increase autonomy or skills learned on-the-job, they raise wages to buy worker consent or commitment, rather than pre-existing skill. To test this idea, we match administrative earnings to task descriptions from job posts. We compare earnings for workers hired into the same occupation and firm, but under different task allocations. When employers raise complexity and autonomy, new hires' starting earnings increase and grow faster. However, while the earnings boost from complex, technical tasks shifts employment toward workers with higher prior earnings, worker selection changes less for tasks learned on-the-job and very little for high autonomy tasks. These results demonstrate how reorganizing work can interrupt cumulative advantage.
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Food Security Status Across the Rural-Urban Continuum Before and During the COVID-19 Pandemic
January 2025
Working Paper Number:
CES-25-01
Background: Food security, defined as consistent access to sufficient food to support an active life, is a crucial social determinant of health. A key dimension affecting food security is position along the rural-urban continuum, as there are important socio-economic and environmental differences between communities related to urbanicity or rurality that impact food access. The COVID-19 pandemic created social and economic shocks that altered financial and food security, which may have had differential effects by rurality and urbanicity. However, there has been limited research on how food security differs across the shades of the rural-urban community spectrum, as most often researchers have characterized communities as either urban or rural.
Methods: In this study, which linked restricted use Current Population Survey Food Security Supplement data to census-tract level United States Department of Agriculture Rural-Urban Commuting Area codes, we estimated the prevalence of household food security across temporal (2015-2019 versus 2020-2021) and socio-spatial (urban, large rural city/town, small rural town, or isolated rural town/area) dimensions in order to characterize variations before and during the COVID-19 pandemic by urbanicity/rurality. We report prevalences as point estimates with 95% confidence intervals.
Results: The prevalence of food security was 87.7% (87.5-88.0%) in 2015-2019 and 88.8% (88.4-89.3%) in 2020-2021 for urban areas, 85.5% (84.7-86.2%) in 2015-2019 and 87.1% (85.7-88.3%) in 2020-2021 for large rural towns/cities, 82.8% (81.5-84.1%) in 2015-2019 and 87.3% (85.7-89.2%) in 2020-2021 for small rural towns, and 87.6% (86.3-88.8%) in 2015-2019 and 90.9% (88.7-92.7%) in 2020-2021 for isolated rural towns/areas.
Conclusion: These findings show that rural communities experiences of food security vary and aggregating households in these environments may mask areas of concern and concentrated need.
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Empirical Distribution of the Plant-Level Components of Energy and Carbon Intensity at the Six-digit NAICS Level Using a Modified KAYA Identity
September 2024
Working Paper Number:
CES-24-46
Three basic pillars of industry-level decarbonization are energy efficiency, decarbonization of energy sources, and electrification. This paper provides estimates of a decomposition of these three components of carbon emissions by industry: energy intensity, carbon intensity of energy, and energy (fuel) mix. These estimates are constructed at the six-digit NAICS level from non-public, plant-level data collected by the Census Bureau. Four quintiles of the distribution of each of the three components are constructed, using multiple imputation (MI) to deal with non-reported energy variables in the Census data. MI allows the estimates to avoid non-reporting bias. MI also allows more six-digit NAICS to be estimated under Census non-disclosure rules, since dropping non-reported observations may have reduced the sample sizes unnecessarily. The estimates show wide variation in each of these three components of emissions (intensity) and provide a first empirical look into the plant-level variation that underlies carbon emissions.
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