Causal Estimands for Policy Evaluation and Beyond

Boris Sokolov
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Boris Sokolov: HSE University

No 4vtpk_v1, SocArXiv from Center for Open Science

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.

Date: 2025-04-24
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Persistent link: https://EconPapers.repec.org/RePEc:osf:socarx:4vtpk_v1

DOI: 10.31219/osf.io/4vtpk_v1

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