Université de Fribourg

The Finite Sample Performance of Inference Methods for Propensity Score Matching and Weighting Estimators

Bodory, Hugo ; Camponovo, Lorenzo ; Huber, Martin ; Lechner, Michael

In: Journal of Business and Economic Statistics, 2020, vol. 38, no. 1, p. 183-200

This article investigates the finite sample properties of a range of inference methods for propensity score-based matching and weighting estimators frequently applied to evaluate the average treatment effect on the treated. We analyze both asymptotic approximations and bootstrap methods for computing variances and confidence intervals in our simulation designs, which are based on German...

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 wild bootstrap algorithm for propensity score matching estimators

Huber, Martin ; Camponovo, Lorenzo ; Bodory, Hugo ; Lechner, Michael

(Working Papers SES ; 470)

We introduce a wild bootstrap algorithm for the approximation of the sampling distribution of pair or one-to-many propensity score matching estimators. Unlike the conventional iid bootstrap, the proposed wild bootstrap approach does not construct bootstrap samples by randomly resampling from the observations with uniform weights. Instead, it fixes the covariates and constructs the bootstrap...

Université de Fribourg

The finite sample performance of inference methods for propensity score matching and weighting estimators

Bodory, Hugo ; Huber, Martin ; Camponovo, Lorenzo ; Lechner, Michael

(Working Papers SES ; 466)

This paper investigates the finite sample properties of a range of inference methods for propensity score-based matching and weighting estimators frequently applied to evaluate the average treatment effect on the treated. We analyse both asymptotic approximations and bootstrap methods for computing variances and confidence intervals in our simulation design, which is based on large scale labor...