Easy bootstrap-like estimation of asymptotic variances

Bo E. Honoré and Luojia Hu

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, Illinois] : Federal Reserve Bank of Chicago
Subject:	standard error \| bootstrap \| inference \| censored regression \| two-step estimation \| Schätztheorie \| Estimation theory \| Regressionsanalyse \| Regression analysis \| Bootstrap-Verfahren \| Bootstrap approach

Extent:	1 Online-Ressource (circa 15 Seiten) Illustrationen
Series:	Working papers / Federal Reserve Bank of Chicago. - Chicago, Ill. : [Verlag nicht ermittelbar], ISSN 1936-5276, ZDB-ID 2186680-6. - Vol. WP 2018, 11 (June 29, 2018) FRB of Chicago Working Paper ; No. WP-2018-11
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Graue Literatur ; Non-commercial literature ; Arbeitspapier ; Working Paper
Language:	English
Other identifiers:	hdl:10419/200581 [Handle]
Classification:	C10 - Econometric and Statistical Methods: General. General ; c18 ; C15 - Statistical Simulation Methods; Monte Carlo Methods
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://ebvufind01.dmz1.zbw.eu/10011879253