On the Failure of the Bootstrap for Matching Estimators

Guido Imbens and Alberto Abadie

Scholarly Articles from Harvard University Department of Economics

Abstract: Matching 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).

Date: 2008
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Citations: View citations in EconPapers (385)

Published in Econometrica: journal of the Econometric Society

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http://dash.harvard.edu/bitstream/handle/1/3043415/imbens_bootstrap.pdf (application/pdf)

Related works:
Journal Article: On the Failure of the Bootstrap for Matching Estimators (2008)
Working Paper: On the Failure of the Bootstrap for Matching Estimators (2006)
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Persistent link: https://EconPapers.repec.org/RePEc:hrv:faseco:3043415

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