author
Guido W. Imbens
also written as Guido Imbens
9 papers here · 2 people have them
tags: econometrics: 9causal inference: 5machine learning: 3
lists: stats.club
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Athey, S., & Imbens, G. W. (2019). Machine Learning Methods That Economists Should Know About. Annual Review of Economics.
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Athey, S., Bayati, M., Doudchenko, N., et al. (2021). Matrix Completion Methods for Causal Panel Data Models. Journal of the American Statistical Association.
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Imbens, G., & Wager, S. (2019). Optimized Regression Discontinuity Designs. The Review of Economics and Statistics.
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Athey, S., & Imbens, G. (2016). Recursive partitioning for heterogeneous causal effects. Proceedings of the National Academy of Sciences.
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Abadie, A., Athey, S., Imbens, G. W., et al. (2020). Sampling‐Based versus Design‐Based Uncertainty in Regression Analysis. Econometrica.
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Arkhangelsky, D., Athey, S., Hirshberg, D. A., et al. (2021). Synthetic Difference-in-Differences. American Economic Review.
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Athey, S., & Imbens, G. W. (2017). The State of Applied Econometrics: Causality and Policy Evaluation. Journal of Economic Perspectives.
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Abadie, A., Athey, S., Imbens, G. W., et al. (2022). When Should You Adjust Standard Errors for Clustering? The Quarterly Journal of Economics.
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Imbens, G. W., & Xu, Y. (2025). Comparing Experimental and Nonexperimental Methods: What Lessons Have We Learned Four Decades after LaLonde (1986)? Journal of Economic Perspectives.
None of these papers is tagged [machine learning].
popular ↓yearaddedtitlepopular ↑yearaddedtitlepopularyear ↓addedtitlepopularyear ↑addedtitlepopularyearadded ↓titlepopularyearadded ↑titlepopularyearaddedtitle a–zpopularyearaddedtitle z–a