In: Journal of Business and Economic Statistics, 2019, vol. 37, no. 4, p. 710-720
We propose a difference-in-differences approach for disentangling a total treatment effect within specific subpopulations into a direct effect and an indirect effect operating through a binary mediating variable. Random treatment assignment along with specific common trend and effect homogeneity assumptions identify the direct effects on the always and never takers, whose mediator is not...
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(Working Papers SES ; 515)
This paper combines causal mediation analysis with double machine learning to control for observed confounders in a data-driven way under a selection-on- observables assumption in a high-dimensional setting. We consider the average indirect effect of a binary treatment operating through an intermediate variable (or mediator) on the causal path between the treatment and the outcome, as well as...
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In: Theory and Decision, 2006, vol. 60, no. 1, p. 17-33
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In: Economic Policy, 2001, vol. 16, no. 33, p. 330-367
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In: Health Policy and Planning, 2008, vol. 23, no. 4, p. 252-263
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In: Socio-Economic Review, 2015, vol. 13, no. 2, p. 189-213
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(Working Papers SES ; 473 (revised))
This paper proposes a difference-in-differences approach for disentangling a total treatment effect on some outcome into a direct effect as well as an indirect effect operating through a binary intermediate variable – or mediator – within strata defined upon how the mediator reacts to the treatment. Imposing random treatment assignment along with specific common trend (and further)...
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(Working Papers SES ; 473)
This study empirically evaluates the impact of the war in eastern Ukraine on the political attitudes aThis paper proposes a difference-in-differences approach for disentangling a total treatment effect on some outcome into a direct impact as well as an indirect effect operating through a binary intermediate variable – or mediator – within strata defined upon how the mediator reacts to the...
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(Working Papers SES ; 453)
Many instrumental variable (IV) regressions include control variables to justify (conditional) independence of the instrument and the potential outcomes. The plausibility of conditional IV independence crucially depends on the timing when the control variables are determined. This paper systemically works through different IV models and discusses the (conditions for the) satisfaction of...
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In: Legal Republicanism - National and International Perspectives, 2009, p. 3-36
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