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Model Specification Tests Based on Artificial Linear Regressions

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  • Davidson, Russell
  • MacKinnon, James G

Abstract

This 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 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): 25 (1984)
Issue (Month): 2 (June)
Pages: 485-502

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Handle: RePEc:ier:iecrev:v:25:y:1984:i:2:p:485-502

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