Papers, latest, tagged causal inference clear

  1. Carlson, J., & Dell, M. (2025). A Unifying Framework for Robust and Efficient Inference with Unstructured Data.

    ai: 1causal inference: 1econometrics: 1machine learning: 1

  2. Dell, M., Jones, B. F., & Olken, B. A. (2014). What Do We Learn from the Weather? The New Climate-Economy Literature. Journal of Economic Literature.

    causal inference: 1climate: 1econometrics: 1environmental: 1

  3. Vohra, V. (2026). Identification Under Universal Policy Exposure.

    causal inference: 1econometrics: 1

  4. Chernozhukov, V., Wüthrich, K., & Zhu, Y. (2021). An Exact and Robust Conformal Inference Method for Counterfactual and Synthetic Controls. Journal of the American Statistical Association.

    causal inference: 1econometrics: 1

  5. Imbens, G., & Wager, S. (2019). Optimized Regression Discontinuity Designs. The Review of Economics and Statistics.

    causal inference: 1econometrics: 1

  6. Athey, S., & Imbens, G. W. (2017). The State of Applied Econometrics: Causality and Policy Evaluation. Journal of Economic Perspectives.

    causal inference: 1econometrics: 1

  7. Arkhangelsky, D., Athey, S., Hirshberg, D. A., et al. (2021). Synthetic Difference-in-Differences. American Economic Review.

    causal inference: 1econometrics: 1

  8. Wager, S., & Athey, S. (2018). Estimation and Inference of Heterogeneous Treatment Effects using Random Forests. Journal of the American Statistical Association.

    causal inference: 1econometrics: 1

  9. Słoczyński, T. (2022). Interpreting OLS Estimands When Treatment Effects Are Heterogeneous: Smaller Groups Get Larger Weights. The Review of Economics and Statistics.

    causal inference: 1econometrics: 1

  10. Słoczyński, T., Uysal, S. D., & Wooldridge, J. M. (2025). Abadie’s Kappa and Weighting Estimators of the Local Average Treatment Effect. Journal of Business & Economic Statistics.

    causal inference: 1econometrics: 1

  11. Słoczyński, T. (2026). When Should We (Not) Interpret Linear IV Estimands as LATE?

    causal inference: 1econometrics: 1

  12. Słoczyński, T., Uysal, S. D., & Wooldridge, J. M. (2022). Doubly Robust Estimation of Local Average Treatment Effects Using Inverse Probability Weighted Regression Adjustment. arXiv.org.

    causal inference: 1econometrics: 1

  13. Abadie, A., Athey, S., Imbens, G. W., et al. (2020). Sampling‐Based versus Design‐Based Uncertainty in Regression Analysis. Econometrica.

    causal inference: 1econometrics: 1

  14. Abadie, A., Athey, S., Imbens, G. W., et al. (2022). When Should You Adjust Standard Errors for Clustering? The Quarterly Journal of Economics.

    causal inference: 1econometrics: 1

  15. Wooldridge, J. M. (2023). Simple approaches to nonlinear difference-in-differences with panel data. The Econometrics Journal.

    causal inference: 1econometrics: 1

  16. Wooldridge, J. M. (2025). An Algebraic Equivalence between Generalized Fixed Effects and a Generalized Mundlak Regression with Applications to Heterogeneous Trends and Difference-in-Differences. Seven Decades of Econometrics and Beyond: A Tribute to the Life and Work of Marc Nerlove.

    causal inference: 1econometrics: 1

  17. S{l}oczy'nski, T., Uysal, S. D., & Wooldridge, J. M. (2025). Covariate Balancing and the Equivalence of Weighting and Doubly Robust Estimators of Average Treatment Effects. Papers.

    causal inference: 1econometrics: 1

  18. Solon, G., Haider, S. J., & Wooldridge, J. M. (2015). What Are We Weighting For? Journal of Human Resources.

    econometrics: 2causal inference: 1

  19. Callaway, B., & Sant’Anna, P. H. (2021). Difference-in-Differences with multiple time periods. Journal of Econometrics.

    econometrics: 3causal inference: 1

  20. Chernozhukov, V., Wüthrich, K., & Zhu, Y. (2026). Debiasing and t -Tests for Synthetic Control Inference on Average Causal Effects. Journal of Political Economy.

    causal inference: 1econometrics: 1

  21. Ludwig, J., Mullainathan, S., & Rambachan, A. (2026). Large Language Models: An Applied Econometric Framework. Annual Review of Economics.

    causal inference: 1econometrics: 1llm: 1

  22. Mullainathan, S., & Spiess, J. (2017). Machine Learning: An Applied Econometric Approach. Journal of Economic Perspectives.

    causal inference: 1econometrics: 1llm: 1

  23. Bertanha, M., McCallum, A. H., & Seegert, N. (2023). Better bunching, nicer notching. Journal of Econometrics.

    bunching: 1causal inference: 1econometrics: 1