Bootstrap Testing in Nonlinear Models
AbstractWhen 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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Bibliographic InfoPaper provided by Universite Aix-Marseille III in its series G.R.E.Q.A.M. with number 97a39.
Length: 24 pages
Date of creation: 1997
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TESTING ; ECONOMETRICS;
Other versions of this item:
- C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
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