Bootstrap Testing in Nonlinear Models

Russell Davidson and James MacKinnon

No 273378, Queen's Institute for Economic Research Discussion Papers from Queen's University - Department of Economics

Abstract: When a model is nonlinear bootstrap 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 xed small number of articial regressions or Newton steps for each bootstrap sample The number of iterations needed is smaller for likelihood ratio tests than for other types of classical tests The suggested procedures are applied to tests of slope coe cients in the tobit model where asymptotic procedures often work surprisingly poorly In contrast bootstrap tests work remarkably well and very few iterations are needed to compute them

Keywords: Farm; Management (search for similar items in EconPapers)
Pages: 27
Date: 1997-02
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Citations: View citations in EconPapers (1)

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Related works:
Journal Article: Bootstrap Testing in Nonlinear Models (1999)
Working Paper: Bootstrap Testing in Nonlinear Models (1997)
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Persistent link: https://EconPapers.repec.org/RePEc:ags:queddp:273378

DOI: 10.22004/ag.econ.273378

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