“The Hidden Costs of Mass Deportations: Early-Life Consequences of the 1930s Mexican Repatriation” joint with Jesse McDevitt-Irwin
Presented at the NBER SI, Development of the American Economy (poster session)
Nativism and anti-immigrant sentiment have been a common thread throughout US history, leading to exclusionary policies and deportation campaigns designed to expel immigrant groups. From 1928 to 1935, the US government implemented a deportation campaign based on fear and pushed between 330,000 and one million Mexicans to leave the country. We study the effect of this campaign on early-life mortality and educational attainment of children born to Mexican-immigrant families that remained in the US. In order to study the impact of this repatriation campaign on health, we overcome the lack of disaggregated stillbirth and infant mortality data by leveraging the fact that, in utero and in infancy, males are more frail than females. We proxy early-life mortality using childhood sex ratios and leverage the rollout of the campaign, which started in Texas in 1928 and didn't move to the rest of the country until 1931. Using a triple-differences estimator, we find a large increase in the childhood sex ratio for Mexican-immigrant households in Texas in 1930, equivalent to moving from the early-life mortality rates of the white population in 1931 to those of the Black population. We also study the effects of the campaign on educational attainment for children of Mexican-immigrant households and find a $16\%-20\%$ reduction in years of schooling. Finally, we find evidence that the deportation campaign led to lower healthcare utilization and public services more broadly, which helps explain our results on health and human capital accumulation.
"Overnight Americans: Economic Assimilation of Mexican[s] Crossed by the Border" (Draft available upon request)
Presented at Economic History Association, 2026
Inter-country conflicts usually lead to annexations and occupations, yet we don’t know much about how the populations that get absorbed assimilate both socially and in the labor market. This paper studies the economic and social outcomes of Mexicans that were absorbed by the US annexation of the American Southwest in the mid 19th century. I find achievement gaps in the labor market that get passed along to their children, as well as low intermarriage rates. These gaps are much bigger than the gaps observed for Latin American migrants and free Black Americans. One of the main drivers of these differences seems to be geography, since adding state X year fixed effects greatly reduces them.
“Acquisitions and Relational Management Practices”, joint with Ameet Morjaria, Michael Powell, and Rocco Macchiavello.
“US Border Wall and Organized Crime in Mexico”
“Gender Stereotypes in Job Advertisements: What Do They Imply for the Gender Salary Gap?” with Raymundo Campos Vázquez, Eva Arceo Gómez, and Raquel Badillo Salas. (Journal of Labor Research, 2022, vol. 43, issue 1, No 3, 65-102)
Gender stereotypes, the assumptions concerning appropriate social roles for men and women, permeate the labor market. Analyzing information from over 2.5 million job advertisements on three different employment search websites in Mexico, exploiting approximately 235,00 that are explicitly gender-targeted, we find evidence that advertisements seeking “communal” characteristics, stereotypically associated with women, specify lower salaries than those seeking “agentic” characteristics, stereotypically associated with men. Given the use of gender-targeted advertisements in Mexico, we use a random forest algorithm to predict whether non-targeted ads are in fact directed toward men or women, based on the language they use. We find that the non-targeted ads for which we predict gender show larger salary gaps (8–35 percent) than explicitly gender-targeted ads (0–13 percent). If women are segregated into occupations deemed appropriate for their gender, this pay gap between jobs requiring communal versus agentic characteristics translates into a gender pay gap in the labor market.
“Big Data, Google, and Unemployment” (Spanish) with Raymundo Campos Vázquez. (Estudios Económicos 9-vol. 35, no. 1, January-June, 2020)
We use Google Trends data for employment opportunities related queries in order to nowcast the unemployment rate in Mexico. We begin by discussing the literature related to big data and nowcasting in which user generated data is used to forecast unemployment. Afterwards, we explain the basics of several machine learning algorithms. Finally, we implement such algorithms in order to find the best model to predict unemployment using both Google Trends queries and unemployment lags.
“The Status of Mexico’s Economic Science” (Spanish) with Raymundo Campos Vázquez. (El Trimestre Económico vol. 85-340)
We study both the authors and subjects discussed in Mexico’s six main economic journals from 2000 to 2017. We study how the presence of female authors has evolved in Mexican economic journals and, also, the interactions among scholars from different institutions using network analysis. On the other hand, we use text analysis on the abstracts to determine if certain keywords related to Mexico’s main economic problems or vulnerable groups were mentioned.