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Université de Fribourg

Direct and indirect effects under sample selection and outcome attrition

Huber, Martin ; Solovyeva, Anna

(Working Papers SES ; 496)

This paper considers the evaluation of direct and indirect treatment effects, also known as mediation analysis, when outcomes are only observed for a subpopulation due to sample selection or outcome attrition. For identification, we combine sequential conditional independence assumptions on the assignment of the treatment and the mediator, i.e. the variable through which the indirect effect...

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),...

Université de Fribourg

Machine learning with screens for detecting bid-rigging cartels

Huber, Martin ; Imhof, David

(Working Papers SES ; 494)

We combine machine learning techniques with statistical screens computed from the distribution of bids in tenders within the Swiss construction sector to predict collusion through bid-rigging cartels. We assess the out of sample performance of this approach and find it to correctly classify more than 80% of the total of bidding processes as collusive or non-collusive. As the correct...

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

Instrument-based estimation with binarized treatments : issues and tests for the exclusion restriction

Andresen, Martin Eckhoff ; Huber, Martin

(Working Papers SES ; 492)

When estimating local average and marginal treatment effects using instrumental variables (IV), multivalued endogenous treatments are frequently binarized based on a specific threshold in treatment support. However, such binarization introduces a violation of the IV exclusion if (i) the IV affects the multivalued treatment within support areas below and/or above the threshold and (ii) such...

Université de Fribourg

Including covariates in the regression discontinuity design

Frölich, Markus ; Huber, Martin

(Working Papers SES ; 489)

This paper proposes a fully nonparametric kernel method to account for observed covariates in regression discontinuity designs (RDD), which may increase precision of treatment effect estimation. It is shown that conditioning on covariates reduces the asymptotic variance and allows estimating the treatment effect at the rate of one-dimensional nonparametric regression, irrespective of the...

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 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

Nonparametric estimation of natural direct and indirect effects based on inverse probability weighting

Hsu, Yu-Chin ; Huber, Martin ; Lai, Tsung Chih

(Working Papers SES ; 482)

Using a sequential conditional independence assumption, this paper discusses fully nonparametric estimation of natural direct and indirect causal effects in causal mediation analysis based on inverse probability weighting. We propose estimators of the average indirect effect of a binary treatment, which operates through intermediate variables (or mediators) on the causal path between the...

Université de Fribourg

A framework for separating individual treatment effects from spillover, interaction, and general equilibrium effects

Huber, Martin ; Steinmayr, Andreas

(Working Papers SES ; 481)

This paper suggests a causal framework for disentangling individual level treatment effects and interference effects, i.e., general equilibrium, spillover, or interaction effects related to treatment distribution. Thus, the framework allows for a relaxation of the Stable Unit Treatment Value Assumption (SUTVA), which assumes away any form of treatment-dependent interference between study...