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Bootstrap Testing in Nonlinear Models

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Author Info
Davidson, R.
Mackinnon, J.G.

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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.

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Publisher Info
Paper provided by Universite Aix-Marseille III in its series G.R.E.Q.A.M. with number 97a39.

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Length: 24 pages
Date of creation: 1997
Date of revision:
Handle: RePEc:fth:aixmeq:97a39

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Related research
Keywords: TESTING ; ECONOMETRICS;

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C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General

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