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Model Specification Tests Based on Artificial Linear Regressions

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Author Info

  • Russell Davidson
  • James G. MacKinnon

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

Paper provided by Queen's University, Department of Economics in its series Working Papers with number 426.

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Length: 31
Date of creation: 1981
Date of revision:
Publication status: Published in International Economic Review, 25, 1984
Handle: RePEc:qed:wpaper:426

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