Bootstrap Testing in Nonlinear Models

Russell Davidson and James MacKinnon ()

G.R.E.Q.A.M. from Universite Aix-Marseille III

Abstract: 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.

Keywords: TESTING; ECONOMETRICS (search for similar items in EconPapers)
JEL-codes: C1 (search for similar items in EconPapers)
Date: 1997
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Related works:
Working Paper: Bootstrap Testing in Nonlinear Models (1997)
Journal Article: Bootstrap Testing in Nonlinear Models (1999)
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Persistent link: http://EconPapers.repec.org/RePEc:fth:aixmeq:97a39

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