Essays in Applied Microeconomics
My dissertation focuses on understanding whether and how institutions, policies and norms lead to an inefficient allocation of human capital - with specific focus on marginalized individuals - and what kind of interventions can be used to reduce such inefficiencies. In Pink Work: Same-Sex Marriage, Employment and Discrimination, I analyze how the legalization of same-sex marriage in the U.S. affected employment levels among gay and lesbian couples. I compare same-sex couples living in different states over time to show increases in the individual and joint probabilities of being employed following the introduction of same-sex marriage in their state. I then provide empirical evidence suggesting that a decrease in discrimination towards sexual minorities was the driving mechanism.In my second dissertation chapter, I analyze the relationship between teacher demographic characteristics and student educational outcomes. In Why Does Teacher Gender Matter?, I show that the effect of high school math and science teacher gender on student interest and self-efficacy in these subjects becomes insignificant once teacher behaviors and attitudes are taken into account, thus pointing towards an omitted variable bias. Teacher beliefs about male and female ability in math and science – as well as how teachers treat boys and girls in the classroom – matter more than teacher's own gender.My last chapter reiterates my research philosophy of using state-of-the-art quantitative methods to analyze topics with important ramifications in the real world. Failing to graduate from high school has high individual and social costs. And yet, high schools in the U.S. tend to rely on few indicators in order to identify students at risk of dropping out. In Beyond Early Warning Indicators: High School Dropout and Machine Learning, I show that this parsimonious approach leads to identifying only a small subset of students who ends up dropping out. I show how schools can obtain more precise predictions by exploiting the available high-dimensional data jointly with machine learning techniques. I incorporate economic theory into machine learning: the algorithms are calibrated not by selecting an ad-hoc goodness-of-fit criterion, but by considering the goal of minimizing the expected dropout rate while respecting the school’s budget constraint.
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Savchenko, Yevgeniya (Georgetown University, 2014)The first chapter of the dissertation investigates whether remittances affect child's schooling and labor outcomes in Bangladesh, specifically enrollment in school, labor and household chores participation and performance ...