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econ.EM2024
Testing identification in mediation and dynamic treatment models
Martin Huber, Kevin Kloiber, Lukas Laffers
We propose a test for the identification of causal effects in mediation and dynamic treatment models that is based on two sets of observed variables, namely covariates to be contro…
econ.EM2020★ 3 cited
Double machine learning for sample selection models
Michela Bia, Martin Huber, Lukáš Lafférs
This paper considers the evaluation of discretely distributed treatments when outcomes are only observed for a subpopulation due to sample selection or outcome attrition. For ident…
econ.EM2020
Bounds on direct and indirect effects under treatment/mediator endogeneity and outcome attrition
Martin Huber, Lukáš Lafférs
Causal mediation analysis aims at disentangling a treatment effect into an indirect mechanism operating through an intermediate outcome or mediator, as well as the direct effect of…