On the Failure of the Bootstrap for Matching Estimators
AbstractMatching estimators are widely used in empirical economics for the evaluation of programs or treatments. Researchers using matching methods often apply the bootstrap to calculate the standard errors. However, no formal justification has been provided for the use of the bootstrap in this setting. In this article, we show that the standard bootstrap is, in general, not valid for matching estimators, even in the simple case with a single continuous covariate where the estimator is root-N consistent and asymptotically normally distributed with zero asymptotic bias. Valid inferential methods in this setting are the analytic asymptotic variance estimator of Abadie and Imbens (2006a) as well as certain modifications of the standard bootstrap, like the subsampling methods in Politis and Romano (1994). Copyright 2008 The Econometric Society.
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Bibliographic InfoArticle provided by Econometric Society in its journal Econometrica.
Volume (Year): 76 (2008)
Issue (Month): 6 (November)
Other versions of this item:
- Alberto Abadie & Guido W. Imbens, 2006. "On the Failure of the Bootstrap for Matching Estimators," NBER Technical Working Papers 0325, National Bureau of Economic Research, Inc.
- Imbens, Guido & Abadie, Alberto, 2008. "On the Failure of the Bootstrap for Matching Estimators," Scholarly Articles 3043415, Harvard University Department of Economics.
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
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