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Direct and Indirect Effects Based on Changes-in-Changes

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  • Martin Huber
  • Mark Schelker
  • Anthony Strittmatter

Abstract

We propose a novel approach for causal mediation analysis based on changes-in-changes assumptions restricting unobserved heterogeneity over time. This allows disentangling the causal effect of a binary treatment on a continuous outcome into an indirect effect operating through a binary intermediate variable (called mediator) and a direct effect running via other causal mechanisms. We identify average and quantile direct and indirect effects for various subgroups under the condition that the outcome is monotonic in the unobserved heterogeneity and that the distribution of the latter does not change over time conditional on the treatment and the mediator. We also provide a simulation study and two empirical applications regarding a training programme evaluation and maternity leave reform.

Suggested Citation

  • Martin Huber & Mark Schelker & Anthony Strittmatter, 2019. "Direct and Indirect Effects Based on Changes-in-Changes," CESifo Working Paper Series 7855, CESifo.
    • Handle: RePEc:ces:ceswps:_7855
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    References listed on IDEAS

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    1. Martin Huber & Michael Lechner & Anthony Strittmatter, 2018. "Direct and indirect effects of training vouchers for the unemployed," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(2), pages 441-463, February.
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    4. Keele, Luke & Tingley, Dustin & Teppei Yamamoto, "undated". "Identifying Mechanisms behind Policy Interventions via Causal Mediation Analysis," Working Paper 135661, Harvard University OpenScholar.
    5. Martin Huber, 2014. "Identifying Causal Mechanisms (Primarily) Based On Inverse Probability Weighting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(6), pages 920-943, September.
    6. 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).
    7. 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.
    8. Govert E. Bijwaard & Andrew M. Jones, 2019. "An IPW estimator for mediation effects in hazard models: with an application to schooling, cognitive ability and mortality," Empirical Economics, Springer, vol. 57(1), pages 129-175, July.
    9. Flores, Carlos A. & Flores-Lagunes, Alfonso, 2009. "Identification and Estimation of Causal Mechanisms and Net Effects of a Treatment under Unconfoundedness," IZA Discussion Papers 4237, Institute of Labor Economics (IZA).
    10. 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.
    11. 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.
    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. 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.
    14. 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.
    15. 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.
    16. Strittmatter, Anthony, 2019. "Heterogeneous earnings effects of the job corps by gender: A translated quantile approach," Labour Economics, Elsevier, vol. 61(C).
    17. Jeffrey M. Albert & Suchitra Nelson, 2011. "Generalized Causal Mediation Analysis," Biometrics, The International Biometric Society, vol. 67(3), pages 1028-1038, September.
    18. Imai, Kosuke & Yamamoto, Teppei, 2013. "Identification and Sensitivity Analysis for Multiple Causal Mechanisms: Revisiting Evidence from Framing Experiments," Political Analysis, Cambridge University Press, vol. 21(2), pages 141-171, April.
    19. 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.
    20. 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.
    21. 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.
    22. Anthony Strittmatter, 2019. "Heterogeneous Earnings Effects of the Job Corps by Gender Earnings: A Translated Quantile Approach," Papers 1908.08721, arXiv.org.
    23. 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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    Cited by:

    1. Doerr Annabelle & Strittmatter Anthony, 2021. "Identifying Causal Channels of Policy Reforms with Multiple Treatments and Different Types of Selection," Journal of Econometric Methods, De Gruyter, vol. 10(1), pages 67-88, January.
    2. Masayuki Sawada, 2019. "Noncompliance in randomized control trials without exclusion restrictions," Papers 1910.03204, arXiv.org, revised Jun 2021.
    3. Hannes Wallimann & David Imhof & Martin Huber, 2023. "A Machine Learning Approach for Flagging Incomplete Bid-Rigging Cartels," Computational Economics, Springer;Society for Computational Economics, vol. 62(4), pages 1669-1720, December.

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    More about this item

    Keywords

    direct effects; indirect effects; mediation analysis; changes-in-changes; causal mechanisms; treatment effects;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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