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Open AccessArticle

Outliers in Semi-Parametric Estimation of Treatment Effects

1
Centro de Investigaciones Económicas y Empresariales (CIEE), Universidad Privada Boliviana, La Paz, Bolivia
2
División de Economía, Centro de Investigación y Docencia Económicas, A.C. (CIDE), Aguascalientes CP20313, Mexico
3
Banco Central de Bolivia (BCB), La Paz, Bolivia
*
Author to whom correspondence should be addressed.
Academic Editor: In Choi
Econometrics 2021, 9(2), 19; https://doi.org/10.3390/econometrics9020019
Received: 17 December 2020 / Revised: 11 March 2021 / Accepted: 20 March 2021 / Published: 30 April 2021
Outliers can be particularly hard to detect, creating bias and inconsistency in the semi-parametric estimates. In this paper, we use Monte Carlo simulations to demonstrate that semi-parametric methods, such as matching, are biased in the presence of outliers. Bad and good leverage point outliers are considered. Bias arises in the case of bad leverage points because they completely change the distribution of the metrics used to define counterfactuals; good leverage points, on the other hand, increase the chance of breaking the common support condition and distort the balance of the covariates, which may push practitioners to misspecify the propensity score or the distance measures. We provide some clues to identify and correct for the effects of outliers following a reweighting strategy in the spirit of the Stahel-Donoho (SD) multivariate estimator of scale and location, and the S-estimator of multivariate location (Smultiv). An application of this strategy to experimental data is also implemented. View Full-Text
Keywords: treatment effects; outliers; propensity score; mahalanobis distance treatment effects; outliers; propensity score; mahalanobis distance
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MDPI and ACS Style

Canavire-Bacarreza, G.; Castro Peñarrieta, L.; Ugarte Ontiveros, D. Outliers in Semi-Parametric Estimation of Treatment Effects. Econometrics 2021, 9, 19. https://doi.org/10.3390/econometrics9020019

AMA Style

Canavire-Bacarreza G, Castro Peñarrieta L, Ugarte Ontiveros D. Outliers in Semi-Parametric Estimation of Treatment Effects. Econometrics. 2021; 9(2):19. https://doi.org/10.3390/econometrics9020019

Chicago/Turabian Style

Canavire-Bacarreza, Gustavo; Castro Peñarrieta, Luis; Ugarte Ontiveros, Darwin. 2021. "Outliers in Semi-Parametric Estimation of Treatment Effects" Econometrics 9, no. 2: 19. https://doi.org/10.3390/econometrics9020019

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