Easy bootstrap-like estimation of asymptotic variances - Bo E. Honoré; Luojia Hu (Federal Reserve Bank of Chicago, 2018)
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.
Keywords: C10; C18; C15; 330; standard error; bootstrap; inference; censored regression; two-step estimation