Welcome. I am a political methodologist specializing in statistical text analysis with applications to legislative politics (ideal point estimation, government opposition conflict), political economy (central banker preferences, determinants of inflation expectations), and public policy (the causal inference of racial bias in policing). Some of that stuff is below and in the trusty CV.
I’m a Lecturer in the Department of Politics at Princeton. Last semester I helped teach POL 345 (Intro to Quantitative Social Science) and every summer I teach POL 245 (Visualizing Data) at the Freshman Scholars Institute where a select cohort of first generation and low income students meet an awful lot of causal inference, statistics, and R. I’m also the ‘Senior Research Specialist’ in the Politics Department’s Program in Quantitative and Analytical Politics (QAPS), which hosts a statistical consulting service, methods and tools workshops that run parallel to the graduate methods sequence, and holds all our lovely data.
You can sometimes find me answering questions on stats.stackexchange.com, writing code on GitHub, or wittering on Twitter. There’s a blog here too. Alternatively you can ponder some biographical stuff. Here’s a picture of how I used to look and still do in my head.
Baerg, Duell and Lowe ‘Central Bank Communication as Public Opinion: Experimental Evidence’ has won the 2018 David A. Lake Award for the best paper presented at IPES. (Apparently some other paper also won, but we don’t feel the need to talk about that.)
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