Poor (Wo)man's Bootstrap

Bo E. Honoré, Luojia Hu

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


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 languageEnglish (US)
Pages (from-to)1277-1301
Number of pages25
Issue number4
StatePublished - Jul 2017

All Science Journal Classification (ASJC) codes

  • Economics and Econometrics


  • Standard error
  • bootstrap
  • inference
  • structural models
  • two-step estimation


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