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 ; 516)
Using a survey on wage expectations among students at two Swiss institutions of higher education, we examine the wage expectations of our respondents along two main lines. First, we investigate the rationality of wage expectations by comparing average expected wages from our sample with those of similar graduates; we further examine how our respondents revise their expectations when provided...
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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: Mathematical Methods of Operations Research, 2013, vol. 77, no. 3, p. 357-370
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In: Journal of Occupational Rehabilitation, 2011, vol. 21, no. 2, p. 134-146
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In: PLOS ONE, 2018, vol. 13, no. 4, p. e0195781
We investigated how visual and kinaesthetic/efferent information is integrated for speed perception in running. Twelve moderately trained to trained subjects ran on a treadmill at three different speeds (8, 10, 12 km/h) in front of a moving virtual scene. They were asked to match the visual speed of the scene to their running speed–i.e., treadmill’s speed. For each trial, participants...
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(Working Papers SES ; 493)
We describe R package “causalweight” for causal inference based on inverse probability weighting (IPW). The “causalweight” package offers a range of semiparametric methods for treatment or impact evaluation and mediation analysis, which incorporates intermediate outcomes for investigating causal mechanisms. Depending on the method, identification relies on selection on observables ...
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In: Oxford Economic Papers, 2000, vol. 52, no. 3, p. 497-520
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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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