Easy Bootstrap-Like Estimation of Asymptotic Variances

Bo E. Honore and Luojia Hu

No WP-2018-11, Working Paper Series from Federal Reserve Bank of Chicago

Abstract: 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, Honor 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.

Keywords: standard error; bootstrap; inference; censored regression; two-step estimation (search for similar items in EconPapers)
JEL-codes: C10 C15 C18 (search for similar items in EconPapers)
Pages: 15 pages
Date: 2018-06-29
New Economics Papers: this item is included in nep-ecm
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Journal Article: Easy bootstrap-like estimation of asymptotic variances (2018)
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DOI: 10.21033/wp-2018-11

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