29 citations · 52 across the 19 of their papers we have counts for
9 papers · 1 filter
Assessing the effects of seasonal tariff-rate quotas on vegetable prices in Switzerland
Daria Loginova, Marco Portmann, Martin Huber
Causal estimation of the short-term effects of tariff-rate quotas (TRQs) on vegetable producer prices is hampered by the large variety and different growing seasons of vegetables a…
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…
Evaluating (weighted) dynamic treatment effects by double machine learning
Hugo Bodory, Martin Huber, Lukáš Lafférs
We consider evaluating the causal effects of dynamic treatments, i.e. of multiple treatment sequences in various periods, based on double machine learning to control for observed,…
The Impact of Response Measures on COVID-19-Related Hospitalization and Death Rates in Germany and Switzerland
Martin Huber, Henrika Langen
We assess the impact of COVID-19 response measures implemented in Germany and Switzerland on cumulative COVID-19-related hospitalization and death rates. Our analysis exploits the…
On the plausibility of the latent ignorability assumption
Martin Huber
The estimation of the causal effect of an endogenous treatment based on an instrumental variable (IV) is often complicated by attrition, sample selection, or non-response in the ou…
A Machine Learning Approach for Flagging Incomplete Bid-rigging Cartels
Hannes Wallimann, David Imhof, Martin Huber
We propose a new method for flagging bid rigging, which is particularly useful for detecting incomplete bid-rigging cartels. Our approach combines screens, i.e. statistics derived…
Gender Differences in Wage Expectations
Ana Fernandes, Martin Huber, Giannina Vaccaro
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, w…
Causal mediation analysis with double machine learning
Helmut Farbmacher, Martin Huber, Lukáš Lafférs +2
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…
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…