Similar Search Results

Outliers in semi-parametric estimation of treatment effects

Ontiveros, Darwin Ugarte; Canavire-Bacarreza, Gustavo; … - 2017

Average treatment effects estimands can present significant bias under the presence of outliers. Moreover, outliers can … outliers. Bad and good leverage points outliers are considered. The bias arises because bad leverage points completely change … the propensity score. We provide some clues to diagnose the presence of outliers and propose a reweighting estimator that …

Persistent link: https://www.econbiz.de/10011778870

Outliers in semi-parametric estimation of treatment effects

Canavire-Bacarreza, Gustavo; Castro, Luis; Ontiveros, … - In: Econometrics : open access journal 9 (2021) 2, pp. 1-32

Outliers can be particularly hard to detect, creating bias and inconsistency in the semi-parametric estimates. In this … presence of outliers. Bad and good leverage point outliers are considered. Bias arises in the case of bad leverage points … correct for the effects of outliers following a reweighting strategy in the spirit of the Stahel-Donoho (SD) multivariate …

Persistent link: https://www.econbiz.de/10012547410

Model averaging in semiparametric estimation of treatment effects

Kitagawa, Toru; Muris, Chris - 2015

In the practice of program evaluation, choosing the covariates and the functional form of the propensity score is an important choice that the researchers make when estimating treatment effects. This paper proposes a data-driven way of averaging the estimators over the candidate specifications...

Persistent link: https://www.econbiz.de/10011309717

The value of knowing the propensity score for estimating average treatment effects

Rothe, Christoph - 2016

In a treatment effect model with unconfoundedness, treatment assignments are not only independent of potential outcomes given the covariates, but also given the propensity score alone. Despite this powerful dimension reduction property, adjusting for the propensity score is known to lead to an...

Persistent link: https://www.econbiz.de/10011486511

New evidence on linear regression and treatment effect heterogeneity

Słoczyński, Tymon - 2015

It is standard practice in applied work to rely on linear least squares regression to estimate the effect of a binary variable ("treatment") on some outcome of interest. In this paper I study the interpretation of the regression estimand when treatment effects are in fact heterogeneous. I show...

Persistent link: https://www.econbiz.de/10011387124

The finite sample performance of semi- and nonparametric estimators for treatment effects and policy evaluation

Frölich, Markus; Huber, Martin; Wiesenfarth, Manuel - 2015

This paper investigates the finite sample performance of a comprehensive set of semi- and nonparametric estimators for treatment and policy evaluation. In contrast to previous simulation studies which mostly considered semiparametric approaches relying on parametric propensity score estimation,...

Persistent link: https://www.econbiz.de/10010467808

A general weighted average representation of the ordinary and two-stage least squares estimands

Słoczyński, Tymon - 2018

It is standard practice in applied work to study the effect of a binary variable ("treatment") on an outcome of interest using linear models with additive effects. In this paper I study the interpretation of the ordinary and two-stage least squares estimands in such models when treatment effects...

Persistent link: https://www.econbiz.de/10011924924

Does the estimation of the propensity score by machine learning improve matching estimation? : the case of Germany's programmes for long term unemployed

Goller, Daniel; Lechner, Michael; Moczall, Andreas; … - 2020

Matching-type estimators using the propensity score are the major workhorse in active labour market policy evaluation. This work investigates if machine learning algorithms for estimating the propensity score lead to more credible estimation of average treatment effects on the treated using a...

Persistent link: https://www.econbiz.de/10012165548

Interpreting OLS estimands when treatment effects are heterogeneous : smaller groups get larger weights

Słoczyński, Tymon - 2020

Applied work often studies the effect of a binary variable (“treatment”) using linear models with additive effects. I study the interpretation of the OLS estimands in such models when treatment effects are heterogeneous. I show that the treatment coefficient is a convex combination of two...

Persistent link: https://www.econbiz.de/10012223869

Interpreting OLS estimands when treatment effects are heterogeneous: smaller groups get larger weights

Słoczyński, Tymon - 2020

Applied work often studies the effect of a binary variable ("treatment") using linear models with additive effects. I study the interpretation of the OLS estimands in such models when treatment effects are heterogeneous. I show that the treatment coefficient is a convex combination of two...

Persistent link: https://www.econbiz.de/10012227296