Bootstrap Testing in Nonlinear Models

When a model is nonlinear, boostrap testing can be expensive because of the need to perform at least one nonlinear estimation for every bootstrap sample. We show that it may be possible to reduce computational costs by performing only a fixed, small number of Newton steps or artificial regressions for each bootstrap sample.

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Year of publication:	1997
Authors:	Davidson, R. ; Mackinnon, J.G.
Institutions:	Groupement de Recherche en Économie Quantitative d'Aix-Marseille (GREQAM), Aix-Marseille School of Economics (AMSE)
Subject:	TESTING \| ECONOMETRICS

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Series:	G.R.E.Q.A.M..
Type of publication:	Book / Working Paper
Notes:	24 pages
Classification:	C1 - Econometric and Statistical Methods: General
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005479052