Model Specification Tests Based on Artificial Linear Regressions
AbstractThis paper develops an extremely general procedure for performing a wide variety of model specification tests by running artificial linear regressions. Inference may then be based either on a Lagrange Multiplier statistic from the procedure, or on conventional asymptotic t or F tests based on the artificial regressions. This procedure allows us to develop non-nested hypothesis tests for any set of models which attempt to explain the same dependent variable(s), even when the error specifications of the competing models differ.
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Bibliographic InfoArticle 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): 25 (1984)
Issue (Month): 2 (June)
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Other versions of this item:
- Russell Davidson & James G. MacKinnon, 1981. "Model Specification Tests Based on Artificial Linear Regressions," Working Papers 426, Queen's University, Department of Economics.
- Russell Davidson & James G. MacKinnon, 1980. "Model Specification Tests Based on Artificial Linear Regressions," Working Papers 390, Queen's University, Department of Economics.
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