Causal mediation analysis in economics: Objectives, assumptions, models

Mediation analysis aims at identifying and evaluating the mechanisms through which treatment affects an outcome. The goal is to disentangle the total treatment effect into two components: the indirect effect that occurs due to one or more intermediate variables, known as mediators, and the direct effect that captures all other possible explanations for why a treatment works. This paper reviews the methodological advancements in the literature on causal mediation in economics, specifically quasi-experimental designs. I define the parameters of interest, the main assumptions and the identification strategies under the counterfactual approach, and present the Instrumental Variables (IV), Difference-in-Differences (DID), and Synthetic Control (SC) methods.

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This paper reviews methodological advancements in the literature on causal mediation in economics, specifically quasi-experimental designs, defining parameters of interest, main assumptions, and identification strategies under the counterfactual approach, and presenting Instrumental Variables (IV), Difference-in-Differences (DID), and Synthetic Control (SC) methods.