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Bootstrap Testing in Nonlinear Models
Author(s) -
Davidson Russell,
MacKin James G.
Publication year - 1999
Publication title -
international economic review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.658
H-Index - 86
eISSN - 1468-2354
pISSN - 0020-6598
DOI - 10.1111/1468-2354.00026
Subject(s) - tobit model , nonlinear system , mathematics , sample (material) , newton's method , sample size determination , work (physics) , statistics , econometrics , computer science , engineering , physics , chemistry , chromatography , quantum mechanics , mechanical engineering
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.