Date of Award




Document Type


Degree Name

Doctor of Philosophy (PhD)


Department of Economics

Content Description

1 online resource (ii, viii, 128 pages) : illustrations (some color)

Dissertation/Thesis Chair

Baris K. Yoruk

Committee Members

Pinka Chatterji, Zhongwen Liang


applied microeconometrics, health economics, public policy, Public health administration, Medical policy, Health insurance, Health care reform, Young adults

Subject Categories

Economics | Public Policy


This dissertation consists of three essays on public program evaluation in health economics. This dissertation explores the estimation of treatment effects of public programs on risky behaviors, health insurance status, labor market outcomes or other health-related outcomes among adolescents or young adults and addresses causality inferences based on empirical modeling, analysis and applications. The first chapter in this dissertation identifies the causal treatment effects of keg registration laws on underage alcohol consumption and related outcomes: alcohol-related traffic fatalities, by exploiting the substantial variations in the timing of the introduction of these laws across different states at different times. Using the matched sample that created, I conduct difference-in-difference analysis and suggest that the introduction of the KR laws is associated with a reduction in the probability of binge drinking among minors. In the second chapter, I explore the effect of “ride-sharing” economy on traffic fatalities in the United States using the case of Uber. I evaluate the treatment effects of this recent controversial debating public program, “ride-sharing”, on traffic fatalities by investigating Uber’s expansion during 2010-2015 and exploiting the variations in Uber launch dates across different counties in United States. Using different-in-difference methodology, I identify that the launch of Uber service reduces total fatality by 0.113 and alcohol-involved traffic fatality by 0.032 per 100,000 population. These results are robust to different model specifications and placebo tests. The last chapter identifies the effect of the Affordable Care Act’s (hereafter, ACA’s) dependent coverage mandate on health insurance coverage and labor market outcomes among young adults by exploiting an exogenous variation in additional access to health insurance coverage at age 26. I exploit the discrete jump in health insurance coverage at age 26 using a fuzzy regression discontinuity (RD) design. I find that aging out from the ACA’s dependent coverage mandate is associated with up to 4.2 and 6.1 percentage points decreases in private insurance coverage and coverage from someone living outside the reporting unit, when young adults turn 26. These results are robust to different model specifications and different bandwidths.