Easy bootstrap-like estimation of asymptotic variances

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.

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Year of publication:	2018
Authors:	Honoré, Bo E. ; Hu, Luojia
Publisher:	Chicago, IL : Federal Reserve Bank of Chicago
Subject:	standard error \| bootstrap \| inference \| censored regression \| two-step estimation

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Series:	Working Paper ; 2018-11
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Working Paper
Language:	English
Other identifiers:	10.21033/wp-2018-11 [DOI] 1027871348 [GVK] hdl:10419/200581 [Handle]
Classification:	C10 - Econometric and Statistical Methods: General. General ; c18 ; C15 - Statistical Simulation Methods; Monte Carlo Methods
Source:	EconStor

Persistent link: https://ebvufind01.dmz1.zbw.eu/10012030354