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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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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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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Remote 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.
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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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Industry Shakeouts after an Innovation Breakthrough
November 2024
Working Paper Number:
CES-24-70
Conventional wisdom suggests that after a technological breakthrough, the number of active firms first surges, and then sharply declines, in what is known as a 'shakeout'. This paper challenges that notion with new empirical evidence from across the U.S. economy, revealing that shakeouts are the exception, not the rule. I develop a statistical strategy to detect breakthroughs by isolating sustained anomalies in net firm entry rates, offering a robust alternative to narrative-driven approaches that can be applied to all industries. The results of this strategy, which reliably align with well-documented breakthroughs and remain consistent across various validation tests, uncover a novel trend: the number of entry-driven breakthroughs has been declining over time. The variability and frequent absence of shakeouts across breakthrough industries are consistent with breakthroughs primarily occurring in industries with low returns to scale and with modest learning curves, shifting the narrative on the nature of innovation over the past forty years in the U.S.
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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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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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Compositional Nature of Firm Growth and Aggregate Fluctuations
March 2020
Working Paper Number:
CES-20-09
This paper studies firm dynamics over the business cycle. I present evidence from the United Kingdom that more rapidly growing firms are born in expansions than in recessions. Using administrative records from Census data, I find that this observation also holds for the last four recessions in the United States. I also present suggestive evidence that financial frictions play an important role in determining the types of firms that are born at different stages of the business cycle. I then develop a general equilibrium model in which firms choose their managers' span of control at birth. Firms that choose larger spans of control grow faster and eventually get to be larger, and in this sense have a larger target size. Financial frictions in the form of collateral constraints slow the rate at which firms reach their target size. It takes firms longer to get up to scale when collateral constraints tighten; therefore, businesses with the largest target size are affected disproportionately more. Thus, fewer entrepreneurs find it profitable to choose larger projects when financial conditions deteriorate. Using Bayesian methods, I estimate the model using micro and aggregate data from the United Kingdom. I find that financial shocks account for over 80% of fluctuations in the formation of businesses with a large target size, and TFP and labor wedge shocks account for the remaining 20%. An independently estimated version of the model with no choice over the span of control needs larger aggregate shocks in order to account for the same data series, suggesting that the intensive margin of business formation is important at business cycle frequencies. The model with the choice over the span of control generates an empirically relevant and non-targeted collapse in the right tail of the cumulative growth distribution among firms started in recessions, while the model without such a choice does not. The paper also discusses implications for micro-targeted government stimulus policies.
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