Efficient Inference of Average Treatment Effects in High Dimensions via Approximate Residual Balancing
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- Nikolay Doudchenko & Guido W. Imbens, 2016. "Balancing, Regression, Difference-In-Differences and Synthetic Control Methods: A Synthesis," NBER Working Papers 22791, National Bureau of Economic Research, Inc.
- Dmitry Arkhangelsky & Guido Imbens, 2018. "Fixed Effects and the Generalized Mundlak Estimator," Papers 1807.02099, arXiv.org, revised Aug 2023.
- Keyon Vafa & Susan Athey & David M. Blei, 2024.
"Estimating Wage Disparities Using Foundation Models,"
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2409.09894, arXiv.org.
- Vafa, Keyon & Athey, Susan & Blei, David M., 2024. "Estimating Wage Disparities Using Foundation Models," Research Papers 4206, Stanford University, Graduate School of Business.
- Soumajyoti Sarkar & Hamidreza Alvari, 2020. "Mitigating Bias in Online Microfinance Platforms: A Case Study on Kiva.org," Papers 2006.12995, arXiv.org.
- Susan Athey & Guido Imbens & Thai Pham & Stefan Wager, 2017.
"Estimating Average Treatment Effects: Supplementary Analyses and Remaining Challenges,"
American Economic Review, American Economic Association, vol. 107(5), pages 278-281, May.
- Susan Athey & Guido Imbens & Thai Pham & Stefan Wager, 2017. "Estimating Average Treatment Effects: Supplementary Analyses and Remaining Challenges," Papers 1702.01250, arXiv.org.
- Susan Athey & Mohsen Bayati & Nikolay Doudchenko & Guido Imbens & Khashayar Khosravi, 2021.
"Matrix Completion Methods for Causal Panel Data Models,"
Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(536), pages 1716-1730, October.
- Susan Athey & Mohsen Bayati & Nikolay Doudchenko & Guido Imbens & Khashayar Khosravi, 2017. "Matrix Completion Methods for Causal Panel Data Models," Papers 1710.10251, arXiv.org, revised Apr 2022.
- Susan Athey & Mohsen Bayati & Nikolay Doudchenko & Guido Imbens & Khashayar Khosravi, 2018. "Matrix Completion Methods for Causal Panel Data Models," NBER Working Papers 25132, National Bureau of Economic Research, Inc.
- Susan Athey & Guido W. Imbens, 2017.
"The State of Applied Econometrics: Causality and Policy Evaluation,"
Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 3-32, Spring.
- Susan Athey & Guido Imbens, 2016. "The State of Applied Econometrics - Causality and Policy Evaluation," Papers 1607.00699, arXiv.org.
- Wang, Xin (Shane) & Ryoo, Jun Hyun (Joseph) & Bendle, Neil & Kopalle, Praveen K., 2021. "The role of machine learning analytics and metrics in retailing research," Journal of Retailing, Elsevier, vol. 97(4), pages 658-675.
- Matthias Huber & Simone Schüller & Marc Stöckli & Klaus Wohlrabe, 2018. "Maschinelles Lernen in der ökonomischen Forschung," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 71(07), pages 50-53, April.
- Dmitry Arkhangelsky & Guido W. Imbens, 2019.
"Doubly Robust Identification for Causal Panel Data Models,"
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1909.09412, arXiv.org, revised Feb 2022.
- Dmitry Arkhangelsky & Guido W. Imbens, 2021. "Double-Robust Identification for Causal Panel Data Models," NBER Working Papers 28364, National Bureau of Economic Research, Inc.
- Thai T. Pham & Yuanyuan Shen, 2017. "A Deep Causal Inference Approach to Measuring the Effects of Forming Group Loans in Online Non-profit Microfinance Platform," Papers 1706.02795, arXiv.org.
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This paper has been announced in the following NEP Reports:- NEP-ECM-2016-10-02 (Econometrics)
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