Three essays in applied economics

My dissertation covers areas in applied economics: labor economics, public economics, and the economics of education. I use a variety of econometric tools and other economic analysis to study welfare program rules and regulations as well as assess the efficacy of a high school science curriculum. My first chapter uses data from the Survey of Income and Program Participation (SIPP), spanning 2003-2013, to estimate whether the ABAWD-specific 20 hour per week minimum work requirement influences their labor supply outcomes and SNAP participation. I employ binary response models to estimate average partial effects (APE) and find the work requirement has statistically significant effects: ABAWDs are 1 percentage point (pp) less likely to participate in SNAP and are 2.6 pp more likely to meet the 20-hourwork requirement. This negative effect of the work requirement on SNAP participation is larger among non-white (1.37 pp), specifically blacks (2.09 pp), suggesting that the impacts of a work requirement must be considered in areas with higher percentages of minorities. This paper contributes to the study of ABAWDs, a relatively understudied population in the context of SNAP.Chapter 2 uses the 2014 Survey of Income and Program Participation (SIPP), spanning from January 2013 to December 2016, to study the effect of SNAP and Medicaid expansion on labor market outcomes (income, hours worked and employment status) and SNAP participation. Using a suite of empirical methods, I find no evidence that the interaction of the SNAP and Medicaid expansions has an effect on labor outcomes of the head and second adult in a household. However, I do find that the Medicaid expansion increases SNAP participation in states with the least generous state-level SNAP policy options. These findings demonstrate the importance of analyzing the effect of both expansions jointly, as both SNAP and Medicaid serve low income households that may simultaneously choose their labor supply and program participation.Chapter 3 uses data from the NSF funded project Crafting Engaging Science Environments(CESE), a cluster-randomized controlled trial to study the effect of project-based learning on the scientific achievement of high school chemistry and physics students in Michigan and California during the 2018-2019 school year. I extend the analysis conducted in Schneideret al. (2021) and use pooled OLS with school level fixed effects to estimate the treatment effect. I find sound evidence to support the findings in Schneider et al., 2021 that the CESE intervention had a positive and significant effect on students' scientific learning, even in the presence of multiple levels of attrition. The point estimates range from 0.24 to 0.34 standard deviations. Additionally, I compute the Lee Bounds for the estimates and find the bounds do not contain zero, suggesting that differential attrition alone likely does not drive the entire treatment effect.