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 InfoPaper provided by Queen's University, Department of Economics in its series Working Papers with number 426.
Date of creation: 1981
Date of revision:
Publication status: Published in International Economic Review, 25, 1984
Other versions of this item:
- Davidson, Russell & MacKinnon, James G, 1984. "Model Specification Tests Based on Artificial Linear Regressions," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 25(2), pages 485-502, June.
- 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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