Hannah To, 22, Class of 2022
To earned a bachelor’s degree from the Department of Economics. She also earned two certificates: one from the Center for Statistics and Machine Learning (CSML) and another in Latin American Studies.
For her CSML independent work project, To worked on a study to see how gangs in El Salvador impacted labor, and was advised by Thomas Fujiwara, associate professor of economics and international affairs. This project also fulfilled her senior thesis requirement.
“When I was starting my CSML project, I knew I wanted to explore questions in labor economics and social problems by using data science and statistics” she said.
Her ideas for this project were first sparked in her Latin American Studies classes. She started to read research papers on gangs in El Salvador and became intrigued on how they impacted different aspects of the country, from the build up of criminal capital to migration patterns.
For her CSML project, she focused on the impact of gang presence and violence on labor force participation, particularly at the differences between men and women. To said El Salvador, still reeling from the 12-year civil war in the late 20th Century, is plagued with high rates of gender-based violence and impunity for these crimes. She wanted to understand how extra-legal organizations, like gangs, may compound existing struggles women face.
To used data science methodologies such as difference-in-differences and multivariate linear regression models, while tapping data sets centered on El Salvador. These data sets included a survey of 20,000 households taken every year from 1995 to 2016, homicide logs from 2003 to 2016, various population data, and a data set that analyzed gang presence. To was particularly interested in any patterns resulting from the increased deportation of gang members back to El Salvador after the passage of the U.S. immigration policy, the Illegal Immigration Reform and Immigrant Responsibility Act (IIRIRA) of 1996. This legislation increased border militarization, reduced due process and expanded criteria for deportation, among other impacts. Prior to IIRIRA, gangs like MS-13 did not exist in El Salvador.
At the conclusion of her study, she found some surprising patterns: In areas of gang presence, people have relatively high incomes and women actually worked at a higher rate than women in areas without gang presence; the opposite was true for men. At the onset of her project, she thought she would find the opposite.
“Based on my results, I hypothesize that in areas where there are gangs and a higher work rate for women, men are pressured to join gangs and leave the formal labor market,” she said. “And these same families with gang members still want a stable source of income, so the women in these households enter the formal labor market.”
To said her hypothesis is based on studies on post-conflict zones from other parts of the world. A qualitative survey that follows up her work would complement and complete the picture hinted at by her CSML project.
“I’m interested in this research because while there is some discussion on the immediate impacts of immigration and deportation policy, we should also understand the long term and often devastating, unintended consequences of these policies,” To added.
After her graduation in May, To will be an economic and litigation analyst in New York City. She hopes to later attend law school or graduate school for economics or data science.
To was vice president of the Princeton University Energy Association and was a member of the Princeton Debate Panel, Princeton Pianists Ensemble and Federal Reserve Challenge Team. She was also a peer academic advisor and an editor on TigerTrends.
To enjoys reading, hiking, cooking, and hanging out with her friends.