We examine how migrant workers impact firm performance using administrative data from the United States. Exploiting an unexpected change in firms' likelihood of securing low-wage workers through the H-2B visa program, we find limited crowd-out of other forms of employment and no impact on average pay at the firm. Yet, access to H-2B workers raises firms' annual revenues and survival likelihood. Our results are consistent with the notion that guest worker programs can help address labor shortages without inflicting large losses on incumbent workers.
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The Impact of Immigration on Firms and Workers: Insights from the H-1B Lottery
April 2024
Working Paper Number:
CES-24-19
We study how random variation in the availability of highly educated, foreign-born workers impacts firm performance and recruitment behavior. We combine two rich data sources: 1) administrative employer-employee matched data from the US Census Bureau; and 2) firm level information on the first large-scale H-1B visa lottery in 2007. Using an event-study approach, we find that lottery wins lead to increases in firm hiring of college-educated, immigrant labor along with increases in scale and survival. These effects are stronger for small, skill-intensive, and high-productivity firms that participate in the lottery. We do not find evidence for displacement of native-born, college-educated workers at the firm level, on net. However, this result masks dynamics among more specific subgroups of incumbents that we further elucidate.
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Private Equity and Workers: Modeling and Measuring Monopsony, Implicit Contracts, and Efficient Reallocation
June 2025
Working Paper Number:
CES-25-37
We measure the real effects of private equity buyouts on worker outcomes by building a new database that links transactions to matched employer-employee data in the United States. To guide our empirical analysis, we derive testable implications from three theories in which private equity managers alter worker outcomes: (1) exertion of monopsony power in concentrated markets, (2) breach of implicit contracts with targeted groups of workers, including managers and top earners, and (3) efficient reallocation of workers across plants. We do not find any evidence that private equity-backed firms vary wages and employment based on local labor market power proxies. Wage losses are also very similar for managers and top earners. Instead, we find strong evidence that private equity managers downsize less productive plants relative to productive plants while simultaneously reallocating high-wage workers to more productive plants. We conclude that post-buyout employment and wage dynamics are consistent with professional investors providing incentives to increase productivity and monitor the companies in which they invest.
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Do SBA Loans Create Jobs? Estimates from Universal Panel Data and Longitudinal Matching Methods
September 2012
Working Paper Number:
CES-12-27
This pape reports estimates of the effects of the Small Business Administration (SBA) 7(a) and 504 loan programs on employment. The database links a complete list of all SBA loans in these programs to universal data on all employers in the U.S. economy from 1976 to 2010. Our method is to estimate firm fixed effect regressions using matched control groups for the SBA loan recipients we have constructed by matching exactly on firm age, industry, year, and pre-loan size, plus kernel-based matching on propensity scores estimated as a function of four years of employment history and other variables. The results imply positive average effects on loan recipient employment of about 25 percent or 3 jobs at the mean. Including loan amount, we find little or no impact of loan receipt per se, but an increase of about 5.4 jobs for each million dollars of loans. When focusing on loan recipients and control firms located in high-growth counties (average growth of 22 percent), places where most small firms should have excellent growth potential, we find similar effects, implying that the estimates are not driven by differential demand conditions across firms. Results are also similar regardless of distance of control from recipient firms, suggesting only a very small role for displacement effects. In all these cases, the results pass a "pre-program" specification test, where controls and treated firms look similar in the pre-loan period. Other specifications, such as those using only matching or only regression imply somewhat higher effects, but they fail the pre-program test.
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Starting Up AI
March 2024
Working Paper Number:
CES-24-09R
Using comprehensive administrative data on business applications over the period 2004- 2023, we study business applications (ideas) and the resulting startups that aim to develop AI technologies or produce goods or services that use, integrate, or rely on AI. The annual number of new AI-related business applications is stable between 2004 and 2011, but begins to rise in 2012 with further increases from 2016 onward into the Covid-19 pandemic and beyond, with a large, discrete jump in 2023. The distribution of these applications is highly uneven across states and sectors. AI business applications have a higher likelihood of becoming employer startups compared to other applications. Moreover, businesses originating from these applications exhibit higher revenue, average wage, and labor share, but similar labor productivity and lower survival rate, compared to other businesses. While it is still early in the diffusion of AI, the rapid rise in AI business applications, combined with the better performance of resulting businesses in several key outcomes, suggests a growing contribution from AI-related business formation to business dynamism.
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After the Storm: How Emergency Liquidity Helps Small Businesses Following Natural Disasters
April 2024
Working Paper Number:
CES-24-20
Does emergency credit prevent long-term financial distress? We study the causal effects of government-provided recovery loans to small businesses following natural disasters. The rapid financial injection might enable viable firms to survive and grow or might hobble precarious firms with more risk and interest obligations. We show that the loans reduce exit and bankruptcy, increase employment and revenue, unlock private credit, and reduce delinquency. These effects, especially the crowding-in of private credit, appear to reflect resolving uncertainty about repair. We do not find capital reallocation away from neighboring firms and see some evidence of positive spillovers on local entry.
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Technology Use and Worker Outcomes: Direct Evidence from Linked Employee-Employer Data
August 2000
Working Paper Number:
CES-00-13
We investigate the impact of technology adoption on workers' wages and mobility in U.S. manufacturing plants by constructing and exploiting a unique Linked Employee-Employer data set containing longitudinal worker and plant information. We first examine the effect of technology use on wage determination, and find that technology adoption does not have a significant effect on high-skill workers, but negatively affects the earnings of low-skill workers after controlling for worker-plant fixed effects. This result seems to support the skill-biased technological change hypothesis. We next explore the impact of technology use on worker mobility, and find that mobility rates are higher in high-technology plants, and that high-skill workers are more mobile than their low and medium-skill counterparts. However, our technology-skill interaction term indicates that as the number of adopted technologies increases, the probability of exit of skilled workers decreases while that of unskilled workers increases.
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Does Federally-Funded Job Training Work? Nonexperimental Estimates of WIA Training Impacts Using Longitudinal Data on Workers and Firms
January 2018
Working Paper Number:
CES-18-02
We study the job training provided under the US Workforce Investment Act (WIA) to adults and dislocated workers in two states. Our substantive contributions center on impacts estimated non-experimentally using administrative data. These impacts compare WIA participants who do and do not receive training. In addition to the usual impacts on earnings and employment, we link our state data to the Longitudinal Employer-Household Dynamics (LEHD) data at the US Census Bureau, which allows us to estimate impacts on the characteristics of the firms at which participants find employment. We find moderate positive impacts on employment, earnings and desirable firm characteristics for adults, but not for dislocated workers. Our primary methodological contribution consists of assessing the value of the additional conditioning information provided by the LEHD relative to the data available in state Unemployment Insurance (UI) earnings records. We find that value to be zero.
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Impact Investing and Worker Outcomes
May 2025
Working Paper Number:
CES-25-30
Impact investors claim to distinguish themselves from traditional venture capital and growth equity investors by also pursuing environmental, social, and governance (ESG) objectives. Whether they successfully do so in practice is unclear. We use confidential Census Bureau microdata to assess worker outcomes across portfolio companies. Impact investors are more likely than other private equity firms to fund businesses in economically disadvantaged areas, and the performance of these companies lags behind those held by traditional private investors. We show that post-funding impact-backed firms are more likely to hire minorities, unskilled workers, and individuals with lower historical earnings, perhaps reflecting the higher representation of minorities in top positions. They also allocate wage increases more favorably to minorities and rank-and-file workers than VC-backed firms. Our results are consistent with impact investors and their portfolio companies acting according to non-pecuniary social goals and thus are not consistent with mere window dressing or cosmetic changes.
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Antitrust Enforcement Increases Economic Activity
October 2023
Working Paper Number:
CES-23-50
We hand-collect and standardize information describing all 3,055 antitrust law suits brought by the Department of Justice (DOJ) between 1971 and 2018. Using restricted establishment-level microdata from the U.S. Census, we compare the economic outcomes of a non-tradable industry in states targeted by DOJ antitrust lawsuits to outcomes of the same industry in other states that were not targeted. We document that DOJ antitrust enforcement actions permanently increase employment by 5.4% and business formation by 4.1%. Using an event-study design, we find (1) a sharp increase in payroll that exceeds the increase in employment, meaning that DOJ antitrust enforcement increases average wages, (2) an economically smaller increase in sales that is statistically insignificant, and (3) a precise increase in the labor share. While we cannot separately measure the quantity and price of output, the increase in production inputs (employment), together with a proportionally smaller increase in sales, strongly suggests that these DOJ antitrust enforcement actions increase the quantity of output and simultaneously decrease the price of output. Our results show that government antitrust enforcement leads to persistently higher levels of economic activity in targeted industries.
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Estimation of Job-to-Job Flow Rates under Partially Missing Geography
September 2012
Working Paper Number:
CES-12-29
Integration of data from different regions presents challenges for the calculation of entitylevel longitudinal statistics with a strong geographic component: for example, movements between employers, migration, business dynamics, and health statistics. In this paper, we consider the estimation of worker-level employment statistics when the geographies (in our application, US states) over which such measures are defined are partially missing. We focus on the recent pilot set of job-to-job flow statistics produced by the US Census Bureau's Longitudinal Employer- Household Dynamics (LEHD) program, which measure the frequency of worker movements between jobs and into and out of nonemployment. LEHD's coverage of the labor force gradually increases during the 1990s and 2000s because some states have a longer time series than others, so employment transitions involving missing states are only partially or not at all observed. We propose and implement a method for estimating national-level job-to-job flow statistics that involves dropping observed states to recover the relationship between missing states and directly tabulated job-to-job flow rates. Using the estimated relationship between the observable characteristics of the missing states and changes in the employment measures, we provide estimates of the rates of job-to-job, and job-to-nonemployment, job-to-nonemploymentto- job flows were all states uniformly available.
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