Journal Publications |
| Identifying Prediction Mistakes in Observational Data. 2024. The Quarterly Journal of Economics. [ Published Version ] |
| A More Credible Approach to Parallel Trends (with Jonathan Roth). 2023. The Review of Economic Studies. [ Published Version | R package ] |
| Panel Experiments and Dynamic Causal Effects: A Finite Population Perspective (with Iavor Bojinov and Neil Shephard). 2021. Quantitative Economics. [ Published Version ] |
Conference Papers |
| Evaluating the World Model Implicit in a Generative Model (with Keyon Vafa, Justin Chen, Jon Kleinberg and Sendhil Mullainathan). 2024. Conference on Neural Information Processing Systems (NeurIPS 2024) (Spotlight). [ Draft ] |
| Do Large Language Models Generalize the Way People Expect? Measuring the Human Generalization Function (with Keyon Vafa and Sendhil Mullainathan). 2024. International Conference on Machine Learning (ICML 2024). [ Draft ] |
| The Unreasonable Effectiveness of Algorithms (with Jens Ludwig and Sendhil Mullainathan). 2024. AEA Papers and Proceedings, 114, Pp. 623-627. Non-refereed. [ Published Version ] |
| Characterizing Fairness over the Set of Good Models under Selective Labels (with Amanda Coston and Alexandra Chouldechova). 2021. International Conference on Machine Learning (ICML 2021). [ Published Version ] |
| An Economic Perspective on Algorithmic Fairness (with Jon Kleinberg, Jens Ludwig and Sendhil Mullainathan). 2020. AEA Papers and Proceedings, 110, Pp. 91-95. Non-refereed. [ Published Version ] |
| Bias In, Bias Out? Evaluating the Folk Wisdom (with Jonathan Roth). 2020. 1st Symposium on the Foundations of Responsible Computing (FORC 2020), LIPIcs, 156, Pp. 6:1-6:15. [ Published Version ] |
| Algorithmic Fairness (with Jon Kleinberg, Jens Ludwig and Sendhil Mullainathan). 2018. AEA Papers and Proceedings, 108, Pp. 22-27. Non-refereed. [ Published Version ] |