Easy Bootstrap-Like Estimation of Asymptotic Variances

15 Pages Posted: 31 Jul 2018 Last revised: 29 Apr 2020

See all articles by Bo E. Honoré

Bo E. Honoré

Princeton University - Department of Economics

Luojia Hu

Federal Reserve Bank of Chicago

Date Written: June, 2018

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

JEL Classification: C10, C15, C18

Suggested Citation

Honore, Bo E. and Hu, Luojia, Easy Bootstrap-Like Estimation of Asymptotic Variances (June, 2018). FRB of Chicago Working Paper No. WP-2018-11, Available at SSRN: https://ssrn.com/abstract=3223387 or http://dx.doi.org/10.21033/wp-2018-11

Bo E. Honore (Contact Author)

Princeton University - Department of Economics ( email )

Princeton, NJ 08544-1021
United States

Luojia Hu

Federal Reserve Bank of Chicago ( email )

230 South LaSalle Street
Chicago, IL 60604
United States

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