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Direct and indirect effects under sample selection and outcome attrition

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  • Huber, Martin
  • Solovyeva, Anna

Abstract

This paper considers the evaluation of direct and indirect treatment effects, also known as mediation analysis, when outcomes are only observed for a subpopulation due to sample selection or outcome attrition. For identification, we combine sequential conditional independence assumptions on the assignment of the treatment and the mediator, i.e. the variable through which the indirect effect operates, with either selection on observables/missing at random or instrumental variable assumptions on the outcome attrition process. We derive expressions for the effects of interest that are based on inverse probability weighting by specific treatment, mediator, and/or selection propensity scores. We also provide a brief simulation study and an empirical illustration based on U.S. Project STAR data that assesses the direct effect and indirect effect (via absenteeism) of smaller kindergarten classes on math test scores.

Suggested Citation

  • Huber, Martin & Solovyeva, Anna, 2018. "Direct and indirect effects under sample selection and outcome attrition," FSES Working Papers 496, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    • Handle: RePEc:fri:fribow:fribow00496
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    Cited by:

    1. Martin Huber & Anna Solovyeva, 2020. "On the Sensitivity of Wage Gap Decompositions," Journal of Labor Research, Springer, vol. 41(1), pages 1-33, June.
    2. Martin Huber & Lukáš Lafférs, 2022. "Bounds on direct and indirect effects under treatment/mediator endogeneity and outcome attrition," Econometric Reviews, Taylor & Francis Journals, vol. 41(10), pages 1141-1163, November.

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    More about this item

    Keywords

    Causal mechanisms; direct effects; indirect effects; causal channels; mediation analysis; causal pathways; sample selection; attrition; outcome nonresponse; inverse probability weighting; propensity score;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education

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