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.
All Science Journal Classification (ASJC) codes
- Economics and Econometrics
- Censored regression
- Standard error
- Two-step estimation