Easy bootstrap-like estimation of asymptotic variances

Bo E. Honoré, Luojia Hu

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


The bootstrap is a convenient tool for calculating standard errors of the parameter estimates of complicated econometric models. Unfortunately, the bootstrap can be very time-consuming. In a recent paper, Honoré and Hu (2017), we propose a “Poor (Wo)man's Bootstrap” based on one-dimensional estimators. In this paper, we propose a modified, simpler method and illustrate its potential for estimating asymptotic variances.

Original languageEnglish (US)
Pages (from-to)46-50
Number of pages5
JournalEconomics Letters
StatePublished - Oct 2018

All Science Journal Classification (ASJC) codes

  • Finance
  • Economics and Econometrics


  • Bootstrap
  • Censored regression
  • Inference
  • Standard error
  • Two-step estimation


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