
Susan Athey
@susan_athey
Economist.
ID: 945284660
https://athey.people.stanford.edu/ 13-11-2012 06:28:52
916 Tweet
31,31K Followers
1,1K Following

Real world challenges demand consistent innovation. Learn how Susan Athey and colleagues at Stanford Graduate School of Business are pushing the boundaries of experimental design and analysis to tackle them. gsb.stanford.edu/insights/ab-teā¦

Join us for 'Promoting Competition in Artificial Intelligence' on May 30th, 2024. Speakers include Jonathan Kanter, Condoleezza Rice, and Susan Athey. Register for the free live stream: stanford.io/3Vid5Yh



š£2024 NBER Methods Lectures by Susan Athey guido imbens on advances in designing complex experiments available. Topics: staggered rollouts, learning targeted treatment policies, bandits & interference. Some highlights š§µ 1/23 youtube.com/watch?v=I6GyDWā¦

Hi #EconTwitter! š Interested in experimental designs and the use of experimental data in #economics? Check out these amazing slides by Susan Athey and guido imbens (@stanford)! Lots of very interesting material and guidelines - don't miss out! āļø Link:


We were thrilled to welcome students & faculty from Spelman College Spelman Economics Morehouse College for the 2nd annual Stanford-Spelman-Sloan Summer Institute last week. Big thank you to Stanford University, Sloan Foundation, & Stanford Institute for Economic Policy Research for making this possible. Hereās our amazing visit. [1/ 15]
![Stanford Economics (@stanfordecon) on Twitter photo We were thrilled to welcome students & faculty from <a href="/SpelmanCollege/">Spelman College</a> <a href="/Spelman_Econ/">Spelman Economics</a> <a href="/Morehouse/">Morehouse College</a> for the 2nd annual Stanford-Spelman-Sloan Summer Institute last week. Big thank you to <a href="/Stanford/">Stanford University</a>, <a href="/SloanFoundation/">Sloan Foundation</a>, & <a href="/SIEPR/">Stanford Institute for Economic Policy Research</a> for making this possible. Hereās our amazing visit. [1/ 15] We were thrilled to welcome students & faculty from <a href="/SpelmanCollege/">Spelman College</a> <a href="/Spelman_Econ/">Spelman Economics</a> <a href="/Morehouse/">Morehouse College</a> for the 2nd annual Stanford-Spelman-Sloan Summer Institute last week. Big thank you to <a href="/Stanford/">Stanford University</a>, <a href="/SloanFoundation/">Sloan Foundation</a>, & <a href="/SIEPR/">Stanford Institute for Economic Policy Research</a> for making this possible. Hereās our amazing visit. [1/ 15]](https://pbs.twimg.com/media/GVnbwy-bgAIKE4_.jpg)

Susan Athey delivered today the Stamp Memorial Lecture at LSE Events, in which she presented the tech toolkit for incremental innovation: a data-driven cycle to develop and evaluate interventions for social impact.


NEW research in The BMJ investigated whether health insurance generated improvements in cardiovascular risk factors for identifiable subpopulations, Kosuke Inoue Susan Athey Yusuke Tsugawa bmj.com/content/386/bmā¦


Health insurance might be more beneficial to health than average effects suggests. Re-examination of evidence suggests that the lack of consistent improvements on average masks substantial improvements for some, Kosuke Inoue Susan Athey Yusuke Tsugawa bmj.com/content/386/bmā¦

Dear #econtwitter, Re: Teaching at a SLAC (Small Liberal Arts College) vs. an R1 (Top-Tier Research University). Using this š§µ to share my experiences at Vassar College and Cornell, while sharing our job ad for a TT (tenure-track) Public Econ AP (Asst Prof) Vassar College year.

The tech industry is growing, but transitioning from other fields is hard. Find out how the Golub Capital Social Impact Lab partnered with @DareIT to develop & evaluate a digital program that helps Polish and Ukrainian women get tech jobs. medium.com/@gsb_silab/darā¦

Foundation models make great predictions. How should we use them for estimation problems in social science? New PNAS paper Susan Athey & @KeyonV & @Blei_Lab: Bad news: Good predictions ā good estimates. Good news: Good estimates are possible by fine-tuning models differently.


If we know someoneās career history, how well can we predict which jobs theyāll have next? Read our profile of @gcsilab & Harvard Data Science Initiative fellow @KeyonV to learn how ML models can be used to predict workersā career trajectories & understand labor markets medium.com/@gsb_silab/keyā¦