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On the Failure of the Bootstrap for Matching Estimators / Alberto Abadie, Guido W. Imbens.
Author
Abadie, Alberto
[Browse]
Format
Book
Language
English
Published/​Created
Cambridge, Mass. National Bureau of Economic Research 2006.
Description
1 online resource: illustrations (black and white);
Details
Related name
National Bureau of Economic Research
[Browse]
Imbens, Guido W.
[Browse]
Series
Technical Working Paper Series (National Bureau of Economic Research) no. t0325.
[More in this series]
NBER technical working paper series no. t0325
Summary note
Matching estimators are widely used for the evaluation of programs or treatments. Often researchers use bootstrapping methods for inference. However, no formal justification for the use of the bootstrap has been provided. Here we show that the bootstrap is in general not valid, even in the simple case with a single continuous covariate when the estimator is root-N consistent and asymptotically normally distributed with zero asymptotic bias. Due to the extreme non-smoothness of nearest neighbor matching, the standard conditions for the bootstrap are not satisfied, leading the bootstrap variance to diverge from the actual variance. Simulations confirm the difference between actual and nominal coverage rates for bootstrap confidence intervals predicted by the theoretical calculations. To our knowledge, this is the first example of a root-N consistent and asymptotically normal estimator for which the bootstrap fails to work.
Notes
June 2006.
Source of description
Print version record
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