The deadline to submit your work to the Machine Learning in Economics Summer Conference (MLESC) is in one week! Send us your work!
www.chicagobooth.edu/research/cen...
@jannspiess.bsky.social
I integrate insights and techniques from machine learning into the econometric toolbox. https://gsb-faculty.stanford.edu/jann-spiess
The deadline to submit your work to the Machine Learning in Economics Summer Conference (MLESC) is in one week! Send us your work!
www.chicagobooth.edu/research/cen...
Reminder to submit your papers to the Machine Learning in Economics Summer Conference (MLESC) at Chicago Booth. The deadline is May 9th. We would love to read your work!
www.chicagobooth.edu/research/cen...
Our research affiliate @sendhil.bsky.social spoke with @jdlahart.bsky.social of @wsj.com about the critical choices we face in developing AI. Instead of setting benchmarks to encourage automation of human tasks, he argues, we should develop AI as a "bicycle for the mind."
www.wsj.com/tech/ai/ai-j...
Last chance to apply to this year's Machine Learning in Economics Summer Institute, our AI/ML summer school for graduate students, co-organized with @sendhil.bsky.social @asheshrambachan.bsky.social @aleximas.bsky.social @lindseyraymond.bsky.social: www.chicagobooth.edu/research/cen... #econsky
08.04.2025 03:36 — 👍 12 🔁 9 💬 0 📌 0we are looking for an Associate Professor (tenure track) in applied Economics, pls share: www.timeshighereducation.com/unijobs/list...
06.03.2025 08:55 — 👍 11 🔁 14 💬 0 📌 1Coming soon to Zoom rooms near you!
We're excited to announce a reboot of the Chamberlain Seminar, five years after its 2020 debut
We'll kick things off on 3/21 with a tribute to Gary. More info and future seminars here:
chamberlainseminar.org
Register here: stanford.zoom.us/meeting/regi...
A very interesting new working paper by the greats Ashesh Rambachan, Rahul Singh, and @vivianodavide.bsky.social: arxiv.org/pdf/2411.10959
It seems that this is another area where the empirical common practice was "too fast,'' and econometrics is catching up!
Cool and empirically relevant stuff!