 Bootstrap Testing in Nonlinear ModelsRussell Davidson and James MacKinnon International Economic Review, 1999, vol. 40, issue 2, 487-508 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. Date: 1999 There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ier:iecrev:v:40:y:1999:i:2:p:487-508 Ordering information: This journal article can be ordered from Access Statistics for this article International Economic Review is currently edited by Harold L. Cole More articles in International Economic Review from Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association 160 McNeil Building, 3718 Locust Walk, Philadelphia, PA 19104-6297. Contact information at EDIRC. |
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