IDENTIFYING MECHANISMS BEHIND POLICY INTERVENTIONS VIA CAUSAL MEDIATION ANALYSIS
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mediationPolicy.pdf
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Author(s)
Keele, Luke
Tingley, Dustin
Yamamoto, Teppei
Date Issued
May 2015
Journal
Journal of Policy Analysis and Management
Publisher
Wiley Blackwell
Citation
Keele, Luke, Dustin Tingley, and Teppei Yamamoto. “IDENTIFYING MECHANISMS BEHIND POLICY INTERVENTIONS VIA CAUSAL MEDIATION ANALYSIS.” Journal of Policy Analysis and Management 34, no. 4 (May 20, 2015): 937–963.
Version
Author's final manuscript
Abstract
Causal analysis in program evaluation has primarily focused on the question about whether or not a program, or package of policies, has an impact on the targeted outcome of interest. However, it is often of scientific and practical importance to also explain why such impacts occur. In this paper, we introduce causal mediation analysis, a statistical framework for analyzing causal mechanisms that has become increasingly popular in social and medical sciences in recent years. The framework enables us to show exactly what assumptions are sufficient for identifying causal mediation effects for the mechanisms of interest, derive a general algorithm for estimating such mechanism-specific effects, and formulate a sensitivity analysis for the violation of those identification assumptions. We also discuss an extension of the framework to analyze causal mechanisms in the presence of treatment noncompliance, a common problem in randomized evaluation studies. The methods are illustrated via applications to two intervention studies on pre-school classes and job-training workshops.
MIT Department
Massachusetts Institute of Technology. Department of Political Science
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DOI of Published Version
https://doi.org/10.1002/pam.21853
