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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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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Unemployment Insurance, Wage Pass-Through, and Endogenous Take-Up
September 2025
Working Paper Number:
CES-25-59
This paper studies how unemployment insurance (UI) generosity affects reservation wages, re-employment wages, and benefit take-up. Using Benefit Accuracy Measurement (BAM) data, we estimate a cross-sectional elasticity of reservation wages with respect to weekly UI benefits of 0.014. Exploiting state variation in Pandemic Unemployment Assistance (PUA) intensity and the timing of federal supplements, we find that expanded benefits during COVID-19 increased reservation wages by 8'12 percent. Using CPS rotation data, we also document a 9 percent rise in re-employment wages for UI-eligible workers relative to ineligible workers. Over the same period, the UI take-up rate rose from roughly 30 to 40 percent; Probit estimates indicate that higher benefit levels, rather than changes in observables, account for this increase. A directed search model with an endogenous filing decision replicates these facts: generosity primarily operates through the extensive margin of take-up, which mutes the pass-through from benefits to wages.
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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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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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The Impact of Minimum Wages on Job Training: An Empirical Exploration with Establishment Data
February 2003
Working Paper Number:
CES-03-04
Human capital theory suggests that workers may finance on-the-job training by accepting lower wages during the training period. Minimum wage laws could reduce job training, then, to the extent they prevent low-wage workers from offering sufficient wage cuts to finance training. Empirical findings on the relationship between minimum wages and job training have failed to reach a consensus. Previous research has relied primarily on survey data from individual workers, which typically lack both detailed measures of job training and important information about the characteristics of firms. This study addresses the issue of minimum wages and on-the-job training with a unique employer survey. We find no evidence indicating that minimum wages reduce the average hours of training of trained employees, and little to suggest that minimum wages reduce the percentage of workers receiving training.
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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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The Impact of Immigration on the Labor Market Outcomes of Native Workers: Evidence using Longitudinal Data from the LEHD
January 2016
Working Paper Number:
CES-16-56
Empirical estimates of the effect of immigration on native workers that rely on spatial comparisons have generally found small effects, but have been subject to the criticism that out-migration by native workers dampens the observed effect by spreading it over a larger area. In contrast, studies that rely on variation in immigration across industries, occupations, or education-based skill-levels often report large negative effects, but rely primarily on repeated cross-sectional data sets which also cannot account for the adjustment of native workers over time. In this paper, we use a newly available data set, the Longitudinal Employer Household Data (LEHD), which provides quarterly earnings records, geographic location, and firm and industry identifiers for 97% of all privately employed workers in 29 states. We use this data to analyze the impact of immigration on earnings changes and the mobility response of native workers. Overall, we find that although immigration has a negative effect on the earnings and employment of native workers, and positive effects on their firm, industry, and cross-state mobility, the overall size of the effects is small.
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Locate Your Nearest Exit: Mass Layoffs and Local Labor Market Response
September 2015
Working Paper Number:
CES-15-25
Large shocks to local labor markets cause lasting changes to communities and their residents. We examine four main channels through which the local labor force adjusts following mass layoffs: in- and out-migration, retirement, and disability insurance enrollment. We show that these channels account for over half of the labor force reductions following a mass layoff event. By measuring the residual difference between these channels and labor force change, we also show that labor force non-participation grew in the period during and after the Great Recession. This result highlights the growing importance of non-participation as a response to labor demand shocks.
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Taken by Storm: Hurricanes, Migrant Networks, and U.S. Immigration
January 2017
Working Paper Number:
CES-17-50
How readily do potential migrants respond to increased returns to migration? Even if origin areas become less attractive vis-'-vis migration destinations, fixed costs can prevent increased migration. We examine migration responses to hurricanes, which reduce the attractiveness of origin locations. Restricted-access U.S. Census data allows precise migration measures and analysis of more migrant-origin countries. Hurricanes increase U.S. immigration, with the effect increasing in the size of prior migrant stocks. Large migrant networks reduce fixed costs by facilitating legal immigration from
hurricane-affected source countries. Hurricane-induced immigration can be fully accounted for by new legal permanent residents ('green card' holders).
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