Just now noticing a very interesting write-up by @ryanburge which makes use of our #VRscores data from the Politics at Work project with @JustinFrake @ReubenHurst2. Tremendously exciting to see how people are making use of the data to uncover new insights!

Republicans are more upbeat about the economy than Democrats are, but the industries Republicans are more likely to work in are losing jobs.

🎉 Tremendously excited to announce the release of VRscores—an open-source dataset for researchers and journalists interested in studying the political lean of different employers.

Wow. This is wild. Researchers from Columbia, Michigan, and Maryland released VRscores. VRscores is a dataset linking voter registrations to online worker profiles that allow you to measure the partisan leanings of U.S. employers. 24.5M workers. 500k employers. 2012–2024.

Wow! This project looks amazing. In it, three scientists at Columbia, Michigan, and Maryland introduce VRscores: a measure of the partisan leanings of employers in the United States. The dataset is constructed by linking U.S. voter registrations to online worker profiles. The dataset covers the 2012-2022 period. VRscores capture the political affiliations of 21.8 million workers across 2.6 million employers. Wow!

1/ Excited to share our new paper on measuring workforce politics with @ReubenHurst2 and @JustinFrake , where we measure the partisan composition (Democrats and Republicans) for over 3.5 million companies and nearly 28 million workers.

My cousin’s artisan wood furniture business in Asheville, NC was completely destroyed by Hurricane Helene. Please consider donating to help him rebuild, or read his story and share with others. 🙏 gofundme.com/f/help-matt-chr…

Nice writeup of my work with Ronnie Lee and @JustinFrake in HBR:

Excited to see our paper published in JPE Micro! “Do Pre-Registration and Pre-Analysis Plans Reduce p-Hacking and Publication Bias?: Evidence from 15,992 Test Statistics and Suggestions for Improvement” w/ Abel Brodeur, Nikolai Cook (@nikolaimcook), and Anthony Heyes. A thread🧵

Very interesting data on segregation by gender in the US workforce. In a working paper with @ReubenHurst2 and @JustinFrake we use administrative data and find that gender segregation is about the same size as segregation by political partisanship. hq.ssrn.com/submissions/Abst…

How much data do you need to conduct an informative staggered diff-in-diff? In our new working paper @fhollenbach and I simulate the power of #DiD estimators, and find that you might need *a lot*, even to detect large effects. We also provide suggestions for improving power 1/

Find my co-authored paper "Are Firms Gerrymandered", forthcoming at @apsrjournal, in open-access pre-print online. In it we provide the first evidence that firms, not jut voters, are gerrymandered. #gerrymandering

In this #APSRNewIssue article, @lpargyle & @mbarber83 introduce a new machine learning influenced method to correct for misclassification in Bayesian Improved Surname Geocoding (BISG), reducing the misclassification error by up to 50 percent. ow.ly/9xwe50RIzQi

Polarization is a rising issue. We worry about political sorting in social media and in real life. But what about at work? Is work a place where we are exposed to partisan diversity, or just another echo chamber? Read on for a 🧵about our working paper… papers.ssrn.com/sol3/papers.…

Join us at the inaugural *Equitable Opportunity Conference* at @MichiganRoss on June 6-7, 2024. Theme: Organizations shape socioeconomic opportunities in ways that more/less align w/notions of fairness & justice. Submission/registration link below. tinyurl.com/UMRSB-EOC

Important work by my colleague Ronnie Lee, @ReubenHurst2, & @JustinFrake

People who favor a policy do not always care about it to the same degree. In this paper, forthcoming at PSRM, we examine alternative ways of measuring differences in "preference intensity" (1/5) charlottecavaille.wordpress.…

Nice write-up by @SmithBrainTrust of my recent research on why firms speak up on social issues.