130 Corwin Hall, Department of Politics
Princeton University, Princeton, NJ 08544
Welcome to my website! I am a PhD candidate in the Department of Politics at Princeton University, where I have been a Quantitative and Analytical Political Science (Q-APS) graduate student fellow since 2015.
I have research and teaching interests in comparative political economy, political sociology, and formal theory and quantitative methods. My research appears or is due to appear in the journals Social Forces and American Sociological Review.
In my spare time, I enjoy spending time with my dog Maggie, whom I adopted from SAVE Animal Shelter in Princeton, NJ.
Papers under Review
"Sensitive Survey Questions with Auxiliary Information." Co-authored with Kosuke Imai and Bryn Rosenfeld.
Scholars increasingly use indirect questioning methods to alleviate social desirability bias and item nonresponse when conducting survey research on sensitive topics. This paper develops methods of improving the efficiency of these methods by incorporating outside information. We apply the methods to survey experiments conducted after an anti-abortion referendum held in the 2011 Mississippi General Election.
Work in Progress
"Bad Times or Bad Types? How Mainstream Politicians Create Opportunities for Radicals." [Draft from 1/20/2017]
This paper develops and tests a theory of why voters support new political parties and politicians. The theory claims that voters will be more likely to support new politicians when they perceive the supply of mainstream politicians to be of lower quality and when they place a greater premium on the honesty of their political representatives relative to their competence. I test these hypotheses in an analysis of the electoral effects of high-risk loans drawn by French mayors in the run-up to the 2007-08 financial crisis.
"Conditioning on Violations of the Exclusion Restriction." [Draft from 2/25/2017]
This paper explains why exclusion restriction violations impede causal inference with instrumental variables and, in particular, why the common practice of conditioning on potential violations does not eliminate the bias. In fact, adjusting for such nonfocal treatments may yield estimates that are less interpretable, and at times more biased, than unadjusted estimates. We provide expressions for the biases of conditional and unadjusted estimates and a simple method for quantifying the sensitivity of the IV estimator to exclusion restriction violations. Attractively, the method "scales" to an arbitrary number of violations under flexible assumptions about the additivity of causal effects.
Assistantships Held at Princeton
POL 245 Visualizing Data
POL 502 Mathematics for Political Science
POL 220/WWS 310 American Politics