Working papers SES

Working papers SES
La collection des Working Papers SES est une série de cahiers de recherche présentant les différents travaux menés au sein de la Faculté des sciences économiques et sociales de l'Université de Fribourg (Suisse). Cette collection existe depuis 1980 et les thèmes abordés reflètent les différentes orientations scientifiques des membres de la Faculté: économie politique, gestion d'entreprise, informatique de gestion, méthodes quantitatives, sciences sociales et sciences des médias et de la communication. Le contenu de ces travaux n'engage que la responsabilité de leurs auteurs.

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Université de Fribourg

Assessing the effects of seasonal tariff-rate quotas on vegetable prices in Switzerland

Loginova, Daria ; Portmann, Marco ; Huber, Martin

(Working Papers SES ; 521)

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 and is therefore rarely performed. We quantify the effects of Swiss seasonal TRQs on domestic producer prices of a variety of vegetables based on a difference-indifferences estimation using a novel dataset of weekly...

Université de Fribourg

Bounds on direct and indirect effects under treatment/mediator endogeneity and outcome attrition

Huber, Martin ; Lafférs, Lukáš

(Working Papers SES ; 514)

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 the treatment on the outcome of interest. However, the evaluation of direct and indirect effects is frequently complicated by non-ignorable selection into the treatment and/or mediator, even after controlling for...

Université de Fribourg

Causal mediation analysis with double machine learning

Farbmacher, Helmut ; Huber, Martin ; Langen, Henrika ; Spindler, Martin

(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...

Université de Fribourg

The causalweight package for causal inference in R

Bodory, Hugo ; Huber, Martin

(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 ...

Université de Fribourg

A cautionary tale about control variables in IV estimation

Deuchert, Eva ; Huber, Martin

(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...

Université de Fribourg

Combining experimental evidence with machine learning to assess anti-corruption educational campaigns among Russian university students

Denisova-Schmidt, Elena ; Huber, Martin ; Leontyeva, Elvira ; Solovyeva, Anna

(Working Papers SES ; 487)

This paper examines how anti-corruption educational campaigns affect the attitudes of Russian university students towards corruption and academic integrity. About 2,000 survey participants were randomly assigned to one of four different information materials (brochures or videos) about the negative consequences of corruption or to a control group. Using machine learning to detect effect...

Université de Fribourg

Direct and indirect effects based on changes-in-changes

Huber, Martin ; Schelker, Mark ; Strittmatter, Anthony

(Working Papers SES ; 508)

We propose a novel approach for causal mediation analysis based on changes-in- changes assumptions restricting unobserved heterogeneity over time. This allows disentangling the causal effect of a binary treatment on a continuous outcome into an indirect effect operating through a binary intermediate variable (called mediator) and a direct effect running via other causal mechanisms. We...

Université de Fribourg

Direct and indirect effects based on difference-in-differences with an application to political preferences following the Vietnam draft lottery

Deuchert, Eva ; Huber, Martin ; Schelker, Mark

(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)...

Université de Fribourg

Direct and indirect effects based on difference-in-differences with an application to political preferences following the Vietnam draft lottery

Deuchert, Eva ; Huber, Martin ; Schelker, Mark

(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...

Université de Fribourg

Direct and indirect effects of continuous treatments based on generalized propensity score weighting

Hsu, Yu-Chin ; Huber, Martin ; Lee, Ying-Ying ; Pipoz, Layal

(Working papers SES ; 495)

This paper proposes semi- and nonparametric methods for disentangling the total causal effect of a continuous treatment on an outcome variable into its natural direct effect and the indirect effect that operates through one or several intermediate variables or mediators. Our approach is based on weighting observations by the inverse of two versions of the generalized propensity score (GPS),...