Author ORCID Identifier

Date of Award

Spring 5-4-2020

Degree Type


Degree Name

Doctor of Philosophy (PhD)



First Advisor

Alberto Chong

Second Advisor

Daniel Kreisman

Third Advisor

Pierre Nguimkeu

Fourth Advisor

Charles Courtemanche


This dissertation comprises three chapters on applied microeconomics that study different economic aspects around the intersection between street violence and nutrition in the context of Mexico. The first and pivot chapter, titled “Military Interventions and Obesity: Evidence from Mexico’s Drug War”, studies the relationship street violence and body weight. This chapter examines if exposure to street violence originated in the military interventions against the drug trafficking organizations (DTOs) that started in 2006 in Mexico had an impact on weight using longitudinal data from a household survey. My results indicate that military operations affect weight positively, increasing overweight although not to the extent of inducing obesity.

The second chapter, titled “Will Violent Crime Incentivize the Hiding of Small Firms?”, explores the impact from street violence on a different outcome: tax compliance. This chapter examines the relationship between crime exposure and informality of businesses using a rotating panel survey matched to municipal homicide rates. My hypothesis is that losses derived from crime may take away income that could otherwise be used to afford formality. Also, firms may prefer to stay underground to avoid disclosing their existence to criminals. I find that exposure to violent crime promotes informality. These results are further corroborated by using temperature as an instrumental variable.

The third chapter, “Fighting Against Hunger: A Country-Wide Intervention and its Impact on Birth Outcomes,” steps away from the crime scene to focus on nutrition again. This chapter studies the impact of Sin Hambre (SH), a food assistance program introduced in Mexico in 2013, on birth weight. I use a difference in difference approach exploiting timing and regional variations in exposure to evaluate the impact of the overall program on birthweight. Since municipalities were not randomly assigned, linear regression methodologies may lead to biased estimates. In order to address these concerns and obtain causal estimates, I employ a multiperiod difference-in-difference matching method. I find that exposure to SH leads to moderate impacts on birth weight at best.