I'm an Economics PhD candidate at the University of Chicago's Booth School of Business. I will be on the job market in the 2023-24 academic year.
My primary fields are behavioral and labor economics.
Feel free to reach out to me at firstname.lastname@example.org or take a look at my CV.
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I document that experienced decision makers can be influenced by irrelevant events in a high stakes setting, felony sentencing in Cook County. Using a stacked difference-in-differences design, I estimate that judges hand down sentences that are 13% longer after sentencing a first degree murder. The effect is twice as large for defendants who resemble the murderer along the dimensions of race and charge severity. The bias affects 6% of defendants on an ongoing basis and temporarily increases the Black sentencing penalty by 91%.
I study the scope of a principle-agent problem in the field. I analyze news firms and journalists with possibly misaligned preferences over the partisan slant of content, and find that the firm's ability to exert control is limited. I construct a dataset that links 2,700 journalists to firms, news articles, and Twitter profiles. I measure article slant with a machine learning algorithm I train to identify partisan phrases. Using a movers design, I find firm ideology does not change the slant of a journalist’s writing. In contrast, journalist ideology, estimated using the following decisions of Twitter users, is strongly correlated with article slant.
Math Camp Instructor (2020, 2021, 2022) [Lecture Notes]
I taught an intensive math camp to incoming Booth PhD students. I collaborated with my co-instructor Walter Zhang to design all course materials including lecture notes and problem sets. The course is comprised of 36 hours of lectures reviewing calculus, linear algebra, real analysis, probability, statistical inference, optimization and dynamic programming.