Skip to main content

States Taking the Reins? Employment Verification Requirements and Local Labor Market Outcomes (No. w26676) (Ayromloo et al., 2020)

Review Guidelines

There is no conflict of interest.

Citation

Ayromloo, S., Feigenberg, B., & Lubotsky, D. (2020). States Taking the Reins? Employment Verification Requirements and Local Labor Market Outcomes (No. w26676). National Bureau of Economic Research.

Highlights

  • The study’s objective was to examine the impact of state mandates requiring E-Verify for new hires on employment and compliance outcomes.
  • The study used a difference-in-differences analysis to examine the effects of E-Verify mandates on outcomes in states with and without the mandates. The authors used administrative data from the Department of Homeland Security, the Quarterly Workforce Indicators (QWI), the American Community Survey (ACS), County Business Patterns (CBP), and from the U.S. Citizenship and Immigration Service (USCIS).
  • The study found a significant relationship between state E-Verify mandates and declines in employment for Hispanic workers overall, especially for undocumented workers, in states with E-Verify mandates compared to Hispanic workers in states without mandates.
  • This study receives a low evidence rating. This means we are not confident that the estimated effects are attributable to state E-Verify mandates; other factors are likely to have contributed.

This page has been updated to comply with Executive Order 14168.

Intervention Examined

State E-Verify Mandates

Features of the Intervention

The 1952 Immigration and Nationality Act requires employers to verify their employees' legal eligibility to work in the United States. The E-Verify system, created by the United States Immigration and Naturalization Service (INS) in 1997, is a voluntary electronic tool for this verification. Employers can use E-Verify to confirm if new hires are authorized to work, but there is no federal mandate to use it. If a business chooses to use E-Verify, it must apply the system uniformly to all employees. While E-Verify is free to use, businesses must train and pay employees to use the system. As of this study, 22 states have implemented some type of E-Verify mandate. Some states require that nearly all employers use it, while others have less strict rules. Some requirements were introduced gradually, starting with larger firms before smaller firms. Non-compliance with state E-Verify mandates has a range of penalties, from fines to suspension of a business license.

Features of the Study

The study used a difference-in-differences analysis to examine the effects of state E-Verify mandates on outcomes for businesses and different groups of workers in states with and without the mandates. The authors identified when various states enacted laws requiring businesses to use E-Verify and the timeline for enforcement of the mandates across firms of varying sizes from 2004 to 2015. They used data from the Department of Homeland Security, the Quarterly Workforce Indicators (QWI, created by the U.S. Census Bureau), the American Community Survey (ACS), County Business Patterns (CBP), and the U.S. Citizenship and Immigration Services (USCIS).

The authors compared the employment, separation, and hiring rates of different groups of workers (i.e., Hispanic, non-Hispanic, likely undocumented, and native-born individuals) before and after state E-Verify laws were enacted. They examined separations and hires, as undocumented workers may experience "job lock," meaning they remain in their current jobs since E-Verify applies only to new hires. The study also investigated if more businesses started using E-Verify after the mandate was passed and whether compliance with the mandate differed based on the size of the business.

Findings

Employment

  • The study found a significant relationship between E-Verify mandates and employment outcomes in states with E-Verify mandates compared to states without mandates. The study found significant declines in employment, job separations, and hires among both Hispanic workers and non-Hispanic workers after the passage of a state E-Verify mandate, but the decline was smaller among non-Hispanic workers.
  • The study found that a state E-Verify mandate reduced employment by a small but significant amount among young, male, native-born workers without college degrees; however, employment among older workers with the same characteristics was not significant.

Compliance

  • The study found that businesses were significantly more likely to use E-Verify after the passage of a state mandate.
  • After a state mandate was passed, the use of E-Verify increased among larger firms (those with 20 or more employees), while smaller firms with fewer employees demonstrated smaller increases in their use of E-Verify.

Considerations for Interpreting the Findings

The authors examined employment outcomes among Hispanic and non-Hispanic workers, and among young male native-born workers and older male native-born workers after the passage of state E-Verify mandates, but did not otherwise control for the effects of age, race/ethnicity, or sex in their models as required by CLEAR. These preexisting differences between workers could explain some or all of the observed differences in employment outcomes. Also, while the authors examined the impact of state E-Verify mandates based on business size, they did not explore how different sectors (like manufacturing or construction) might vary in their compliance. It is possible that businesses in various sectors have different rates of E-Verify usage and react differently to state mandates. Therefore, the study is not eligible for a moderate causal evidence rating, the highest rating available for nonexperimental designs.

Causal Evidence Rating

The quality of causal evidence rating presented in this report is low because the authors did not include sufficient controls for pre-existing differences between the study groups in their analysis. This means we are not confident that the estimated effects are attributable to state E-Verify mandates; other factors are likely to have contributed.

Reviewed by CLEAR

May 2026