I study money in politics, with a focus on how legislators’ investment portfolios and firm lobbying interact to shape trade and immigration policy. Methodologically, I’m interested in Bayesian statistics, and machine learning methods as a way to fit complex models with high parameter-to-observation ratios, as well as using cross validation and information criteria to optimally select among models. I apply these methods to more traditional sources of data (e.g. legislators’ investments) as well as text, harnessing breakthroughs in natural language processing. My research has been funded by UCLA’s Graduate Research Mentorship Fellowship and UCLA’s Dissertation Fellowship.
https://polisci.ucla.edu/wp-content/uploads/2019/10/Uxd_Blk_PoliticalScience_A.png 0 0 webteam https://polisci.ucla.edu/wp-content/uploads/2019/10/Uxd_Blk_PoliticalScience_A.png webteam2019-10-16 14:41:512020-10-20 09:42:06Caleb Ziolkowski