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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Publisher Info
Paper provided by Queen's University, Department of Economics in its series Working Papers with number
426.
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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Russell Davidson & James G. MacKinnon, 2001.
"Artificial Regressions,"
Working Papers
1038, Queen's University, Department of Economics.
[Downloadable!]
Other versions:
Russell Davidson & James G. MacKinnon, 1999.
"Artificial Regressions,"
Working Papers
978, Queen's University, Department of Economics.
[Downloadable!]