Using restricted Census business records, I explore how banning affirmative action in state contracting affects minority- and women-owned business enterprises (MWBEs). I find that ending affirmative action led MWBE contractors to gradually downsize, with the most pronounced reductions in force experienced by Black-owned businesses and larger MWBEs. Despite these workforce changes, existing MWBEs were no more likely to shut down than other businesses. New MWBEs were relatively less common after a state's ban, highlighting how bans can shift the demographic composition of new contractors. A calibrated model suggests bans are equivalent to considerable reductions in MWBE productivity and scrap values.
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Same Shock, Separate Channels: House Prices and Firm Performance in the Great Recession
January 2026
Working Paper Number:
CES-26-03
Combining confidential business-level microdata with housing and banking data, I document large and persistent effects of local house prices on employment at small businesses, and particularly young businesses, during the Great Recession. I show that the effect on entry is important for explaining the disproportionate effect on young businesses, while young firm exit is also disproportionately affected. I then explore the channels through which house prices affect business outcomes. I use survey data to show that reliance on either personal assets or home equity is associated with increased sensitivity to house prices. I then use local bank balance sheet information to show both young and old firms are sensitive to local credit shocks, with some evidence of a larger effect on young businesses. I develop a macroeconomic model that is consistent with these findings where house prices work through two channels: a bank credit supply channel and a housing collateral channel.
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Resilience After Climate Shocks: Evidence From SBA Disaster Loans
September 2026
Working Paper Number:
CES-26-58
We show that natural disasters generate persistent declines in U.S. county employment and net job creation. We then examine whether emergency credit can mitigate these effects. Linking the universe of SBA disaster-loan applications to Census Bureau records, we exploit a credit-score screening rule introduced in 2016 and implement a fuzzy regression discontinuity design around the score cutoff. Firms just above the threshold are substantially more likely to receive government-backed loans, and approval increases employment relative to declined applicants, with effects persisting over subsequent years. The adjustment operates primarily through lower job destruction, while reduced firm exit and stronger job creation also contribute. Overall, SBA lending preserved an estimated 9.8% of the jobs that would otherwise have been lost in disaster-affected counties.
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Cleansing Floods? Creative Destruction and Government Spending After Disasters
August 2026
Working Paper Number:
CES-26-52
Disasters devastate economies, yet productivity can improve in their wake. Why? Using confidential plant-level microdata from the US Census Bureau and an event study design, I trace the creative destruction process that follows large federally declared floods. Exits are concentrated among the least productive plants, whose used machines are then acquired by high-productivity entrants. Survivors upgrade their machinery as they rebuild and see productivity gains. Federal disaster spending facilitates this process by expanding financing access for nimble young and small firms that disproportionately fuel productive reallocation. Without it, financing constraints stifle creative destruction and productivity declines. Ultimately, the relative income gains from federal disaster assistance generate tax revenues far exceeding the policy's upfront cost, making it both efficiency-enhancing and fiscally sound. My findings reveal a novel allocative efficiency channel through which government spending supports post-disaster recovery, with critical implications for a warming world.
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Labor Market Concentration, Earnings Inequality, and Earnings Mobility
September 2018
Working Paper Number:
carra-2018-10
Using data from the Longitudinal Business Database and Form W-2, I document trends in local industrial concentration from 1976 through 2015 and estimate the effects of that concentration on earnings outcomes within and across demographic groups. Local industrial concentration has generally been declining throughout its distribution over that period, unlike national industrial concentration, which declined sharply in the early 1980s before increasing steadily to nearly its original level beginning around 1990. Estimates indicate that increased local concentration reduces earnings and increases inequality, but observed changes in concentration have been in the opposite direction, and the magnitude of these effects has been modest relative to broader trends; back-of-the-envelope calculations suggest that the 90/10 earnings ratio was about six percent lower and earnings were about one percent higher in 2015 than they would have been if local concentration were at its 1976 level. Within demographic subgroups, most experience mean earnings reductions and all experience increases in inequality. Estimates of the effects of concentration on earnings mobility are sensitive to specification.
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Who Hires Whom? Entrepreneurial Backgrounds and Labor Market Opportunities
July 2026
Working Paper Number:
CES-26-45
What are the implications of unequal access to entrepreneurial careers for labor markets? Using data from the U.S. Census and LinkedIn profiles, we document that entrepreneurs are significantly more likely to hire workers from similar social backgrounds (gender, race, age, education, etc.). These effects are quantitatively large across several demographic dimensions. For example, female employee share at female-founded startups is 36.4pp higher after controlling for industry-by-metro area-by-cohort fixed effects, with corresponding estimates of 51.2pp for Blacks, 37.3pp for Hispanics, and 11.3pp for non-college individuals. Large effects are present in high-growth startups, across industries and occupations, and remain stable across new firm cohorts. In addition, we find that these differences persist out to at least 20 years. We use wage data and an AKM research design to untangle whether the relative differences are driven by labor demand or labor supply effects. We find that demand drives the differences: group-specific wage decompositions show that new firms pay higher relative wages to individuals from similar backgrounds to the entrepreneur. Using these estimates, we calibrate a model of entrepreneurship with heterogeneous ability and production functions, and assess the impacts on relative wage from reducing access barriers to entrepreneurship.
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Food Fight: U.S. Exporters' Adjustments to Russia's 2014 Agricultural Import Ban
December 2025
Working Paper Number:
CES-25-79
This paper examines the impact of Russia's 2014 food-import ban on U.S. firms that exported banned products to Russia. Using confidential customs transaction data, we implement triple-difference and dosage-response approaches to identify how firms adjust to the sudden loss of a market. Following the ban, treated firms experienced a 30 percentage-point decrease in the probability of exporting banned food to Russia relative to control firms. However, there is substantial heterogeneity by pre-ban reliance on the Russian market: heavily reliant firms were significantly less likely to survive once the ban was in place, and survivors experienced large reductions in revenue (19%) and total export value (49%) for each standard deviation increase in Russian market exposure. We find evidence of export redirection to neighboring countries, though it is insufficient to offset losses. Any negative impacts on survivors dissipate by five years post-ban.
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Garage Entrepreneurs or just Self-Employed? An Investigation into Nonemployer Entrepreneurship
October 2024
Working Paper Number:
CES-24-61
Nonemployers, businesses without employees, account for most businesses in the U.S. yet are poorly understood. We use restricted administrative and survey data to describe nonemployer dynamics, overall performance, and performance by demographic group. We find that eventual outcome ' migration to employer status, continuing as a nonemployer, or exit ' is closely related to receipt growth. We provide estimates of employment creation by firms that began as nonemployers and become employers (migrants), estimating that relative to all firms born in 1996, nonemployer migrants accounted for 3-17% of all net jobs in the seventh year after startup. Moreover, we find that migrants' employment creation declined by 54% for the cohorts born between 1996 to 2014. Our results are consistent with increased adjustment frictions in recent periods, and suggest accessibility to transformative entrepreneurship for everyday Americans has declined.
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You'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.
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Fresh Start or Fresh Water: The impact of Environmental Lender Liability
January 2026
Working Paper Number:
CES-26-05
I study the impact of lenders' environmental responsibility. The empirical setting exploits the U.S. Lender Liability Act of 1996, which reduced lenders' exposure to the environmental clean-up costs attached to some of their debtors' collateral, and employs difference-indifferences specifications estimated using EPA and U.S. Census microdata. Firms whose lenders face lower environmental liability risks increase pollution, reduce investment in abatement technologies by 14.7%, while experiencing small production and employment distortions. Lenders facing higher liability risks offer loans with less favorable pricing, thus financially incentivizing firms to become more environmentally responsible, and potentially monitor borrowers via shorter debt maturity.
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Screening Out the Needy: the Effects of SNAP Work Requirements
July 2026
Working Paper Number:
CES-26-46
We examine the effectiveness of work requirements as a screening device in the Supplemental Nutrition Assistance Program (SNAP). Work requirements for 'able-bodied adults without dependents' were suspended after the Great Recession and gradually reinstated across counties and states in the 2010s. Using linked administrative SNAP and employment data from five states and a triple-differences design, we find that work requirements reduce SNAP participation by seven percent without increasing labor supply and disproportionately screen out low-income individuals. We develop a welfare framework to interpret these results and find that the social costs of work requirements exceed budget savings.
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