Samyam Shrestha

The U.S. farm labor supply depends heavily on foreign-born workers, almost half of whom are unauthorized. Over the past few decades, this labor supply has steadily declined, leading to tighter farm labor markets, widespread reports of worker shortages, and rising wages. At the same time, domestic production of major labor-intensive fruit and vegetable (FV) crops has decreased, while imports and trade deficits have grown substantially. Against this backdrop, this study examines whether intensified immigration enforcement in the U.S. interior, a supply-side shock to farm labor availability affects domestic and international FV trade flows. First, I demonstrate that a state's FV production decreases with the intensification of immigration enforcement. Using reduced-form gravity models, I then show that immigration enforcement reduces FV exports to other U.S. states and foreign trading partners. I also show that a state’s FV imports from other U.S. states increase with enforcement intensity, especially from states with lower enforcement levels. Most of these effects are driven by police-based rather than employment-based enforcement. However, I do not find evidence that immigration enforcement contributes to the rise in international FV imports. These results have important implications for U.S. agricultural and trade policy, food supply systems, and consumer welfare.

We use administrative panel data on the universe of Brazilian formal workers to investigate the labor market effects of the Venezuelan crisis in Brazil, focusing on the border state of Roraima. The results using difference-in-differences show that the monthly wages of Brazilians in Roraima increased by around 2 percent, which was mostly driven by those working in sectors and occupations with no refugee involvement. The study finds negligible job displacement for Brazilians but finds evidence of native workers moving to occupations without immigrants. We also find that immigrants in the informal market offset the substitution effects in the formal market.

Agricultural workers are among the poorest in the United States, with many earning wages at or near the minimum wage. This paper examines the effects of minimum wage increases on their participation in the Supplemental Nutrition Assistance Program (SNAP), the largest federal program addressing food insecurity among low-income households. Using data from the 2003–19 American Community Survey, we find no significant effect of minimum wage increases on SNAP participation among likely-eligible agricultural worker households in the full agricultural sample. However, minimum wage hikes disproportionately increase SNAP enrollment among certain demographic groups, particularly Latino- and immigrant-headed households. We have suggestive evidence that these increases are driven by greater labor supply, enabling these groups to meet the minimum hours worked required to qualify for SNAP benefits. The findings are robust to alternative specifications.

We examine whether reducing the undocumented immigrant population affects business dynamics by leveraging the spatiotemporal variations in the implementation of the Secure Communities (SC) program, which coordinates data sharing between local law enforcement agencies to identify and arrest undocumented immigrants. Using difference-in-differences models with the 2001-12 county-level business dynamics panel data, we find that SC implementation at the commuting-zone level reduced the number of firms, establishments, and employment, increased establishment exits, and decreased establishment entries and job creation in the construction sector, but not in other labor-intensive sectors. We discuss several potential mechanisms, including entrepreneurial out-migration, higher labor costs, and changes in consumption.

This paper examines the effects of crime on firm entry and exit in the Brazilian city of Rio de Janeiro, using data on the universe of firms and establishments in the city from 2007 to 2017. By spatially locating firms and merging this information with granular neighborhood-level crime data, which includes detailed records of crime type, time, and severity, we investigate how crime influences the local business environment. We address endogeneity and simultaneity issues through an instrumental variable approach, leveraging spatiotemporal variations in the Pacifying Police Unit program that deployed the Brazilian military across Rio de Janeiro neighborhoods. Our hypothesis is that firms are more likely to enter areas where crime has been reduced and less likely to exit them. We explore heterogeneity at the level of crime type, firm size, industry, and productivity distribution.