December 2, 2025
Adapted from a Yale SOM Faculty Seminar on November 19, 2025 by Kyle Jensen. Kyle is a magician and I deserve almost no credit for this post.
November 29, 2025
November 26, 2025
November 24, 2025
As we reach mid-November in the 2024-2025 academic hiring cycle, the data from JOE (Job Openings for Economists) paints a concerning picture: this year is shaping up to be the worst economics job market on record since at least 2015.
November 22, 2025
November 17, 2025
November 15, 2025
November 15, 2025
I’ve been working on a side project that I think might be useful to other applied folks: a full-text search engine for econ/finance journals and NBER working papers.
November 15, 2025
I just posted a draft of a new paper with the amazing Peter Hull and Michal Kolesár: Leniency Designs: An Operator’s Manual. I will post a longer summary later, but hope you’ll take a look!
November 14, 2025
November 13, 2025
November 12, 2025
October 8, 2025
The interactive visualizations below show how the economics job market has evolved from 2015 to 2025 using data downloaded from JOE on the AEA website. This is following work done by lots of folks, most notably John Cawley’s reports on thr state of the market.
November 6, 2024
Economists love using linear regression to estimate treatment effects — it turns out that there are perils to this method, but also amazing perks. [-0-] [-0-] This post is a synthesis of a Twitter/Bluesky thread.
November 6, 2024
Editors Note: This summmary was created using Claude AI. Please send me any comments or corrections.
November 6, 2024
Editors Note: This summmary was created using Claude AI. Please send me any comments or corrections.
November 6, 2024
Ben Golub had the idea of summarizing technical papers (such as in Econometrica) using AI to be more easily approached by non-technical economists. These papers were selected from the list of the most prominent recent papers in Econometrica by Google Scholar. This is the second post, for an economic theory paper. I also posted one for an econometrics paper.
November 6, 2024
Ben Golub had the idea of summarizing technical papers (such as in Econometrica) using AI to be more easily approached by non-technical economists. These papers were selected from the list of the most prominent recent papers in Econometrica by Google Scholar. First, an econometrics paper. I will also post one for a theory paper.
June 24, 2024
[N.B. I gave a version of this post for an internal discussion at SOM. I’ve modified it for general consumption. Many of the examples I walked through live – I will try to add videos for those, in the future, but for now they will just sit as “examples” in the text.]
November 23, 2023
I wanted to put together a list of AEA (and other Economics groups) Presidential speeches for my own perusal. I thought I’d share it here in case it’s useful for others.
May 27, 2021
Gary Chamberlain’s family granted approval for me to post the collected set of lecture notes from the late Gary Chamberlain’s 2010 Econometrics class (EC2120) that I took during my economics Ph.D. at Harvard University. Gary was a remarkable teacher and this class was an amazing experience for me as a young economist. I hope you find these lectures as enthralling as I did!
April 30, 2018
I recently wrote up some tips and tricks for beamer. You can find the slides here and the source code on Github.
March 12, 2018
Matt Notowidigdo prompted a great thread of peoples’ suggestions of their favorite figures. I thought I would give a resting place for the nominees:
July 9, 2017
I recently put together a maptile geography to incorporate the NPR hex tile map for state maps to be used in Michael Stepner’s excellent Stata maptile ado program (which is a wrapper for spmap). It should be up soon on Michael’s website, but you can grab it here for now.
July 9, 2017
I spent some time this weekend learning tidyverse, a set of R libraries inspired by tidyr by Hadley Wickham. I have a lot of friends who swear by R – I used it in college quite a bit, but once I switched to Stata I never went back. The main reason for this was that the base R language (which is how I learned R) is quite clunky – it’s painful to do basic data cleaning. However, I recently read through a nice post by David Robinson on the values of tidyverse and I decided to give a shot.