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Direct and indirect treatment effects–causal chains and mediation analysis with instrumental variables

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  • Markus Frölich
  • Martin Huber

Abstract

This paper discusses the nonparametric identification of causal direct and indirect effects of a binary treatment based on instrumental variables. We identify the indirect effect, which operates through a mediator (i.e. intermediate variable) that is situated on the causal path between the treatment and the outcome, as well as the unmediated direct effect of the treatment using distinct instruments for the endogenous treatment and the endogenous mediator. We examine different settings to obtain nonparametric identification of (natural) direct and indirect as well as controlled direct effects for continuous and discrete mediators and continuous and discrete instruments. We illustrate our approach in two applications: to disentangle the effects (i) of education on health, which may be mediated by income, and (ii) of the Job Corps training program, which may affect earnings indirectly via working longer hours and directly via higher wages per hour.
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  • 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.
  • Handle: RePEc:bla:jorssb:v:79:y:2017:i:5:p:1645-1666
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    Cited by:

    1. Huber, Martin & Steinmayr, Andreas, 2017. "A Framework for Separating Individual Treatment Effects From Spillover, Interaction, and General Equilibrium Effects," Rationality and Competition Discussion Paper Series 21, CRC TRR 190 Rationality and Competition.
    2. Fabian Kosse & Thomas Deckers & Pia Pinger & Hannah Schildberg-Hörisch & Armin Falk, 2020. "The Formation of Prosociality: Causal Evidence on the Role of Social Environment," Journal of Political Economy, University of Chicago Press, vol. 128(2), pages 434-467.
    3. Huber, Martin & Schelker, Mark & Strittmatter, Anthony, 2019. "Direct and Indirect Effects based on Changes-in- Changes," FSES Working Papers 508, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    4. Prifti, Ervin & Daidone, Silvio & Davis, Benjamin, 2019. "Causal pathways of the productive impacts of cash transfers: Experimental evidence from Lesotho," World Development, Elsevier, vol. 115(C), pages 258-268.
    5. Huber Martin & Wüthrich Kaspar, 2019. "Local Average and Quantile Treatment Effects Under Endogeneity: A Review," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-27, January.
    6. Kantorowicz, Jarosław & Köppl–Turyna, Monika, 2019. "Disentangling the fiscal effects of local constitutions," Journal of Economic Behavior & Organization, Elsevier, vol. 163(C), pages 63-87.
    7. Arthur Lewbel, 2019. "The Identification Zoo: Meanings of Identification in Econometrics," Journal of Economic Literature, American Economic Association, vol. 57(4), pages 835-903, December.
    8. Strobl, Renate & Wunsch, Conny, 2018. "Identification of causal mechanisms based on between-subject double randomization designs," CEPR Discussion Papers 13028, C.E.P.R. Discussion Papers.
    9. Denise Hörner & Adrien Bouguen & Markus Frölich & Meike Wollni, 2019. "The Effects of Decentralized and Video-based Extension on the Adoption of Integrated Soil Fertility Management – Experimental Evidence from Ethiopia," NBER Working Papers 26052, National Bureau of Economic Research, Inc.
    10. Christian Dippel & Robert Gold & Stephan Heblich & Rodrigo Pinto, 2017. "Instrumental Variables and Causal Mechanisms: Unpacking the Effect of Trade on Workers and Voters," CESifo Working Paper Series 6816, CESifo.
    11. Tadao Hoshino & Takahide Yanagi, 2018. "Treatment Effect Models with Strategic Interaction in Treatment Decisions," Papers 1810.08350, arXiv.org, revised Aug 2020.
    12. 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.
    13. Lochmann, Alexia & Rapoport, Hillel & Speciale, Biagio, 2019. "The effect of language training on immigrants’ economic integration: Empirical evidence from France," European Economic Review, Elsevier, vol. 113(C), pages 265-296.
    14. Martin Huber, 2016. "Disentangling policy effects into causal channels," IZA World of Labor, Institute of Labor Economics (IZA), pages 259-259, May.
    15. Muhammad Shoukat Malik & Lubna Kanwal, 2018. "Impact of Corporate Social Responsibility Disclosure on Financial Performance: Case Study of Listed Pharmaceutical Firms of Pakistan," Journal of Business Ethics, Springer, vol. 150(1), pages 69-78, June.
    16. Liu, Shilei & Xu, Jintao, 2019. "Livelihood mushroomed: Examining household level impacts of non-timber forest products (NTFPs) under new management regime in China's state forests," Forest Policy and Economics, Elsevier, vol. 98(C), pages 44-53.
    17. Bijwaard, G.E.; & Jones, A.M.;, 2019. "Education and life-expectancy and how the relationship is mediated through changes in behaviour: a principal stratification approach for hazard rates," Health, Econometrics and Data Group (HEDG) Working Papers 19/05, HEDG, c/o Department of Economics, University of York.
    18. Avdeenko, Alexandra & Frölich, Markus, 2020. "Research standards in empirical development economics: What’s well begun, is half done," World Development, Elsevier, vol. 127(C).

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    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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