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Bootstrap Testing in Nonlinear Models

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  • Davidson, Russell
  • MacKinnon, James G

Abstract

Bootstrap testing of nonlinear models normally requires at least one nonlinear estimation for every bootstrap sample. We show how to reduce computational costs by performing only a fixed, small number of Newton or quasi-Newton steps for each bootstrap sample. The number of steps is smaller for likelihood ratio tests than for other types of classical tests and smaller for Newton's method than for quasi-Newton methods. The suggested procedures are applied to tests of slope coefficients in the Tobit model and to tests of common factor restrictions. In both cases, bootstrap tests work well, and very few steps are needed. Copyright 1999 by Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association.

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Bibliographic Info

Article provided by Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association in its journal International Economic Review.

Volume (Year): 40 (1999)
Issue (Month): 2 (May)
Pages: 487-508
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Handle: RePEc:ier:iecrev:v:40:y:1999:i:2:p:487-508

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  1. Gregory, Allan W & Veall, Michael R, 1987. "Formulating Wald Tests of the Restrictions Implied by the Rational Expectations Hypothesis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 2(1), pages 61-68, January.
  2. Orme, Chris, 1995. "On the Use of Artificial Regressions in Certain Microeconometric Models," Econometric Theory, Cambridge University Press, vol. 11(02), pages 290-305, February.
  3. Gregory, Allan W & Veall, Michael R, 1985. "Formulating Wald Tests of Nonlinear Restrictions," Econometrica, Econometric Society, vol. 53(6), pages 1465-68, November.
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