Poor (Wo)man's Bootstrap

Bo E. Honoré; Luojia Hu

doi:10.3982/ECTA13465

Poor (Wo)man's Bootstrap

Bo E. Honoré, Luojia Hu

Research output: Contribution to journal › Article › peer-review

5 Scopus citations

Abstract

The bootstrap is a convenient tool for calculating standard errors of the parameter estimates of complicated econometric models. Unfortunately, the fact that these models are complicated often makes the bootstrap extremely slow or even practically infeasible. This paper proposes an alternative to the bootstrap that relies only on the estimation of one-dimensional parameters. We introduce the idea in the context of M and GMM estimators. A modification of the approach can be used to estimate the variance of two-step estimators.

Original language	English (US)
Pages (from-to)	1277-1301
Number of pages	25
Journal	Econometrica
Volume	85
Issue number	4
DOIs	https://doi.org/10.3982/ECTA13465
State	Published - Jul 2017

All Science Journal Classification (ASJC) codes

Economics and Econometrics

Keywords

Standard error
bootstrap
inference
structural models
two-step estimation

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10.3982/ECTA13465

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abstract = "The bootstrap is a convenient tool for calculating standard errors of the parameter estimates of complicated econometric models. Unfortunately, the fact that these models are complicated often makes the bootstrap extremely slow or even practically infeasible. This paper proposes an alternative to the bootstrap that relies only on the estimation of one-dimensional parameters. We introduce the idea in the context of M and GMM estimators. A modification of the approach can be used to estimate the variance of two-step estimators.",

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AU - Hu, Luojia

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AB - The bootstrap is a convenient tool for calculating standard errors of the parameter estimates of complicated econometric models. Unfortunately, the fact that these models are complicated often makes the bootstrap extremely slow or even practically infeasible. This paper proposes an alternative to the bootstrap that relies only on the estimation of one-dimensional parameters. We introduce the idea in the context of M and GMM estimators. A modification of the approach can be used to estimate the variance of two-step estimators.

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KW - bootstrap

KW - inference

KW - structural models

KW - two-step estimation

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IS - 4

ER -

Poor (Wo)man's Bootstrap

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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