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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

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...