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Causal Mediation Analysis in Economics: objectives, assumptions, models

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  • Viviana Celli

    (Department of Methods and Models for Economics, Territory and Finance.)

Abstract

The aim of mediation analysis is to identify and evaluate the mechanisms through which a treatment affects an outcome. The goal is to disentangle the total treatment effect into two components: the indirect effect that operates through one or more intermediate variables, called mediators, and the direct effect that captures the other mechanisms. This paper reviews the methodological advancements in causal mediation literature in economics, in particular focusing on quasi-experimental designs. It defines the parameters of interest under the counterfactual approach, the assumptions and the identification strategies, presenting the Instrumental Variables (IV), Difference-in-Differences (DID) and the Synthetic Control (SC) methods.

Suggested Citation

  • Viviana Celli, 2019. "Causal Mediation Analysis in Economics: objectives, assumptions, models," Working Papers 12/19, Sapienza University of Rome, DISS.
  • Handle: RePEc:saq:wpaper:12/19
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    File URL: http://www.diss.uniroma1.it/sites/default/files/allegati/DiSSE_Celli_wp12_2019.pdf
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    References listed on IDEAS

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    1. Constantine E. Frangakis & Donald B. Rubin, 2002. "Principal Stratification in Causal Inference," Biometrics, The International Biometric Society, vol. 58(1), pages 21-29, March.
    2. Keele, Luke & Tingley, Dustin & Teppei Yamamoto, "undated". "Identifying Mechanisms behind Policy Interventions via Causal Mediation Analysis," Working Paper 135661, Harvard University OpenScholar.
    3. Powdthavee, Nattavudh & Lekfuangfu, Warn N. & Wooden, Mark, 2013. "The Marginal Income Effect of Education on Happiness: Estimating the Direct and Indirect Effects of Compulsory Schooling on Well-Being in Australia," IZA Discussion Papers 7365, Institute of Labor Economics (IZA).
    4. Imai, Kosuke & Keele, Luke & Tingley, Dustin & Yamamoto, Teppei, 2011. "Unpacking the Black Box of Causality: Learning about Causal Mechanisms from Experimental and Observational Studies," American Political Science Review, Cambridge University Press, vol. 105(4), pages 765-789, November.
    5. Cerqua, Augusto & Pellegrini, Guido, 2014. "Do subsidies to private capital boost firms' growth? A multiple regression discontinuity design approach," Journal of Public Economics, Elsevier, vol. 109(C), pages 114-126.
    6. Martin Huber, 2015. "Causal Pitfalls in the Decomposition of Wage Gaps," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(2), pages 179-191, April.
    7. Andrew Gelman & Guido Imbens, 2013. "Why ask Why? Forward Causal Inference and Reverse Causal Questions," NBER Working Papers 19614, National Bureau of Economic Research, Inc.
    8. Stacey H. Chen & Yen-Chien Chen & Jin-Tan Liu, 2019. "The Impact of Family Composition on Educational Achievement," Journal of Human Resources, University of Wisconsin Press, vol. 54(1), pages 122-170.
    9. Alberto Abadie & Javier Gardeazabal, 2003. "The Economic Costs of Conflict: A Case Study of the Basque Country," American Economic Review, American Economic Association, vol. 93(1), pages 113-132, March.
    10. Luke Keele & Dustin Tingley & Teppei Yamamoto, 2015. "Identifying Mechanisms Behind Policy Interventions Via Causal Mediation Analysis," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 34(4), pages 937-963, September.
    11. Gardner, Jonathan & Oswald, Andrew J., 2007. "Money and mental wellbeing: A longitudinal study of medium-sized lottery wins," Journal of Health Economics, Elsevier, vol. 26(1), pages 49-60, January.
    12. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-475, March.
    13. Rosenzweig, Mark R & Wolpin, Kenneth I, 1980. "Testing the Quantity-Quality Fertility Model: The Use of Twins as a Natural Experiment," Econometrica, Econometric Society, vol. 48(1), pages 227-240, January.
    14. Markus Frölich & Martin Huber, 2017. "Direct and indirect treatment effects–causal chains and mediation analysis with instrumental variables," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(5), pages 1645-1666, November.
    15. James Heckman & Rodrigo Pinto & Peter Savelyev, 2013. "Understanding the Mechanisms through Which an Influential Early Childhood Program Boosted Adult Outcomes," American Economic Review, American Economic Association, vol. 103(6), pages 2052-2086, October.
    16. Joshua Angrist & Victor Lavy & Analia Schlosser, 2010. "Multiple Experiments for the Causal Link between the Quantity and Quality of Children," Journal of Labor Economics, University of Chicago Press, vol. 28(4), pages 773-824, October.
    17. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    18. Martin Huber & Michael Lechner & Giovanni Mellace, 2017. "Why Do Tougher Caseworkers Increase Employment? The Role of Program Assignment as a Causal Mechanism," The Review of Economics and Statistics, MIT Press, vol. 99(1), pages 180-183, March.
    19. Guido W. Imbens, 2004. "Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 4-29, February.
    20. Philip Oreopoulos, 2006. "Estimating Average and Local Average Treatment Effects of Education when Compulsory Schooling Laws Really Matter," American Economic Review, American Economic Association, vol. 96(1), pages 152-175, March.
    21. Jeffrey M. Albert & Suchitra Nelson, 2011. "Generalized Causal Mediation Analysis," Biometrics, The International Biometric Society, vol. 67(3), pages 1028-1038, September.
    22. Eva Deuchert & Martin Huber & Mark Schelker, 2019. "Direct and Indirect Effects Based on Difference-in-Differences With an Application to Political Preferences Following the Vietnam Draft Lottery," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(4), pages 710-720, October.
    23. VanderWeele, Tyler J., 2008. "Simple relations between principal stratification and direct and indirect effects," Statistics & Probability Letters, Elsevier, vol. 78(17), pages 2957-2962, December.
    24. Abadie, Alberto & Diamond, Alexis & Hainmueller, Jens, 2010. "Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California’s Tobacco Control Program," Journal of the American Statistical Association, American Statistical Association, vol. 105(490), pages 493-505.
    25. Kosuke Imai & Dustin Tingley & Teppei Yamamoto, 2013. "Experimental designs for identifying causal mechanisms," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(1), pages 5-51, January.
    26. Huber, Martin, 2019. "A review of causal mediation analysis for assessing direct and indirect treatment effects," FSES Working Papers 500, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    27. Lars Skipper & Marianne Simonsen, 2006. "The costs of motherhood: an analysis using matching estimators," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(7), pages 919-934.
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    More about this item

    Keywords

    mediation; policy evaluation; direct effect; indirect effect; sequential conditional independence; quasi-experimental designs.;
    All these keywords.

    JEL classification:

    • B41 - Schools of Economic Thought and Methodology - - Economic Methodology - - - Economic Methodology
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • D04 - Microeconomics - - General - - - Microeconomic Policy: Formulation; Implementation; Evaluation

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