Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/200581
Authors: 
Honoré, Bo E.
Hu, Luojia
Year of Publication: 
2018
Series/Report no.: 
Working Paper 2018-11
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, 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.
Subjects: 
standard error
bootstrap
inference
censored regression
two-step estimation
JEL: 
C10
C18
C15
Persistent Identifier of the first edition: 
Document Type: 
Working Paper
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