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Causal Estimands for Policy Evaluation and Beyond

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  • Sokolov, Boris

    (HSE University)

Abstract

This paper reviews various estimands used in modern scientific and applied research to operationalize causal inquiries within the Rubin Causal Model framework. I first introduce the most widely utilized average treatment effects, such as ATE, ATT, and ATC. I then describe their popular extensions, including those targeting local and conditional treatment effects; causal interactions and mediation; effects for non-continuous outcomes, as well as for multi-valued and continuous treatments; and longitudinal treatment effects. For each of these estimands, a substantive explanation is provided, along with examples of research questions they can address. The key assumptions necessary for the identification of the most widely used effects are also discussed.

Suggested Citation

  • Sokolov, Boris, 2025. "Causal Estimands for Policy Evaluation and Beyond," SocArXiv 4vtpk_v1, Center for Open Science.
    • Handle: RePEc:osf:socarx:4vtpk_v1
    DOI: 10.31219/osf.io/4vtpk_v1
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    1. Guido W. Imbens, 2020. "Potential Outcome and Directed Acyclic Graph Approaches to Causality: Relevance for Empirical Practice in Economics," Journal of Economic Literature, American Economic Association, vol. 58(4), pages 1129-1179, December.
    2. Gaurav Khanna & Wenquan Liang & Ahmed Mushfiq Mobarak & Ran Song, 2025. "The Productivity Consequences of Pollution-Induced Migration in China," American Economic Journal: Applied Economics, American Economic Association, vol. 17(2), pages 184-224, April.
    3. James J. Heckman, 2008. "Econometric Causality," International Statistical Review, International Statistical Institute, vol. 76(1), pages 1-27, April.
    4. Matias D. Cattaneo & Rocío Titiunik, 2022. "Regression Discontinuity Designs," Annual Review of Economics, Annual Reviews, vol. 14(1), pages 821-851, August.
    5. Gary King & Christopher Lucas & Richard A. Nielsen, 2017. "The Balance‐Sample Size Frontier in Matching Methods for Causal Inference," American Journal of Political Science, John Wiley & Sons, vol. 61(2), pages 473-489, April.
    6. Jiehan Liu & Ziyi Liu & Yiqing Xu, 2025. "A Practical Guide to Estimating Conditional Marginal Effects: Modern Approaches," Papers 2504.01355, arXiv.org.
    7. Stefan Wager & Susan Athey, 2018. "Estimation and Inference of Heterogeneous Treatment Effects using Random Forests," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(523), pages 1228-1242, July.
    8. Joshua D. Angrist & Jörn-Steffen Pischke, 2009. "Mostly Harmless Econometrics: An Empiricist's Companion," Economics Books, Princeton University Press, edition 1, number 8769.
    9. Abadie, Alberto, 2003. "Semiparametric instrumental variable estimation of treatment response models," Journal of Econometrics, Elsevier, vol. 113(2), pages 231-263, April.
    10. Akhter Ahmed & Melissa Hidrobo & John Hoddinott & Bastien Kolt & Shalini Roy & Salauddin Tauseef, 2025. "Sustainable Poverty Reduction through Social Assistance: Modality, Context, and Complementary Programming in Bangladesh," American Economic Journal: Applied Economics, American Economic Association, vol. 17(2), pages 102-126, April.
    11. Riccardo Di Francesco & Giovanni Mellace, 2025. "Causal Inference for Qualitative Outcomes," Papers 2502.11691, arXiv.org.
    12. Matias D. Cattaneo & Nicolas Idrobo & Rocio Titiunik, 2023. "A Practical Introduction to Regression Discontinuity Designs: Extensions," Papers 2301.08958, arXiv.org, revised Mar 2024.
    13. Clément de Chaisemartin & Xavier D’Haultfœuille, 2023. "Two-way fixed effects and differences-in-differences with heterogeneous treatment effects: a survey," The Econometrics Journal, Royal Economic Society, vol. 26(3), pages 1-30.
    14. Laetitia Renée, 2025. "The Long-Term Effects of Career Guidance in High School and Student Financial Aid: Evidence from a Randomized Experiment," American Economic Journal: Applied Economics, American Economic Association, vol. 17(2), pages 165-183, April.
    15. Guido W. Imbens, 2010. "Better LATE Than Nothing: Some Comments on Deaton (2009) and Heckman and Urzua (2009)," Journal of Economic Literature, American Economic Association, vol. 48(2), pages 399-423, June.
    16. Marianne Bertrand & Sendhil Mullainathan, 2004. "Are Emily and Greg More Employable Than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination," American Economic Review, American Economic Association, vol. 94(4), pages 991-1013, September.
    17. Luna Bellani & Michela Bia, 2019. "The long‐run effect of childhood poverty and the mediating role of education," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 182(1), pages 37-68, January.
    18. Tingley, Dustin & Yamamoto, Teppei & Hirose, Kentaro & Keele, Luke & Imai, Kosuke, 2014. "mediation: R Package for Causal Mediation Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 59(i05).
    19. James J. Heckman, 2008. "Causalidad econométrica," Monetaria, CEMLA, vol. 0(3), pages 291-338, julio-sep.
    20. Markus, Keith A., 2021. "Causal effects and counterfactual conditionals: contrasting Rubin, Lewis and Pearl," Economics and Philosophy, Cambridge University Press, vol. 37(3), pages 441-461, November.
    21. Naoki Egami & Kosuke Imai, 2019. "Causal Interaction in Factorial Experiments: Application to Conjoint Analysis," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(526), pages 529-540, April.
    22. J.J. Heckman & E.E. Leamer (ed.), 2007. "Handbook of Econometrics," Handbook of Econometrics, Elsevier, edition 1, volume 6, number 6b.
    23. Bansak, Kirk & Hainmueller, Jens & Hopkins, Daniel J. & Yamamoto, Teppei, 2023. "Using Conjoint Experiments to Analyze Election Outcomes: The Essential Role of the Average Marginal Component Effect," Political Analysis, Cambridge University Press, vol. 31(4), pages 500-518, October.
    24. Hainmueller, Jens & Hopkins, Daniel J. & Yamamoto, Teppei, 2014. "Causal Inference in Conjoint Analysis: Understanding Multidimensional Choices via Stated Preference Experiments," Political Analysis, Cambridge University Press, vol. 22(1), pages 1-30, January.
    25. Donald B. Rubin, 2005. "Causal Inference Using Potential Outcomes: Design, Modeling, Decisions," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 322-331, March.
    26. Kosuke Imai & David A. van Dyk, 2004. "Causal Inference With General Treatment Regimes: Generalizing the Propensity Score," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 854-866, January.
    27. J.J. Heckman & E.E. Leamer (ed.), 2007. "Handbook of Econometrics," Handbook of Econometrics, Elsevier, edition 1, volume 6, number 6a.
    28. Victor Chernozhukov & Christian Hansen, 2005. "An IV Model of Quantile Treatment Effects," Econometrica, Econometric Society, vol. 73(1), pages 245-261, January.
    29. Matias D. Cattaneo & Luke Keele & Rocio Titiunik, 2021. "Covariate Adjustment in Regression Discontinuity Designs," Papers 2110.08410, arXiv.org, revised Aug 2022.
    30. Baker, Andrew C. & Larcker, David F. & Wang, Charles C.Y., 2022. "How much should we trust staggered difference-in-differences estimates?," Journal of Financial Economics, Elsevier, vol. 144(2), pages 370-395.
    31. Imbens,Guido W. & Rubin,Donald B., 2015. "Causal Inference for Statistics, Social, and Biomedical Sciences," Cambridge Books, Cambridge University Press, number 9780521885881, June.
    32. King, Gary & Zeng, Langche, 2006. "The Dangers of Extreme Counterfactuals," Political Analysis, Cambridge University Press, vol. 14(2), pages 131-159, April.
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