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Outliers in semi-parametric estimation of treatment effects

Canavire-Bacarreza, Gustavo; Castro, Luis; Ontiveros, … - In: Econometrics 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/10012696324

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/10011445765

New evidence on the finite sample properties of propensity score matching and reweighting estimators

Busso, Matias; DiNardo, John; McCrary, Justin - 2009

Currently available asymptotic results in the literature suggest that matching estimators have higher variance than reweighting estimators. The extant literature comparing the finite sample properties of matching to specific reweighting estimators, however, has concluded that reweighting...

Persistent link: https://www.econbiz.de/10010268994

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/10011494361

The elephant in the corner: A cautionary tale about measurement error in treatment effects models

Millimet, Daniel L. - 2010

Researchers in economics and other disciplines are often interested in the causal effect of a binary treatment on outcomes. Econometric methods used to estimate such effects are divided into one of two strands depending on whether they require the conditional independence assumption (i.e.,...

Persistent link: https://www.econbiz.de/10010274588

New Evidence on Linear Regression and Treatment Effect Heterogeneity

Sloczynski, 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/10011401759

Sensitivity of propensity score methods to the specifications

Zhao, Zhong - 2005

Propensity score matching estimators have two advantages. One is that they overcome the curse of dimensionality of covariate matching, and the other is that they are nonparametric. However, the propensity score is usually unknown and needs to be estimated. If we estimate it nonparametrically, we...

Persistent link: https://www.econbiz.de/10010267689

A martingale representation for matching estimators

Abadie, Alberto; Imbens, Guido W. - 2009

Matching estimators are widely used in statistical data analysis. However, the distribution of matching estimators has been derived only for particular cases (Abadie and Imbens, 2006). This article establishes a martingale representation for matching estimators. This representation allows the...

Persistent link: https://www.econbiz.de/10010269062

Minimizing bias in selection on observables estimators when unconfoundness fails

Millimet, Daniel L.; Tchernis, Rusty - 2008

We characterize the bias of propensity score based estimators of common average treatment effect parameters in the case of selection on unobservables. We then propose a new minimum biased estimator of the average treatment effect. We assess the finite sample performance of our estimator using...

Persistent link: https://www.econbiz.de/10010268598

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/10010481663