Informational Complexity Criteria For Regression Models

H. Bozdogan and D. Haughton

Working Papers from Toulouse - GREMAQ

Abstract: This paper pursues three objectives in the context of multiple regression models: 1) To give a rationale for model selection criteria which combine a badness of fit term (such as minus twice the log likelihood) with a measure of complexity of a model. 2) To investigate the asymptotic consistency properties of the class of ICOMP criteria first in the case when one of the models considered is the true model and to introduce and establish a consistency property for the case when none of the models is the true model. 3) To investigate the finite sample behavior of ICOMP criteria by means of a simulation study where none of the models considered is the true model.

Keywords: ECONOMETRICS (search for similar items in EconPapers)
JEL-codes: C51 C52 (search for similar items in EconPapers)
Pages: 32 pages
Date: 1996
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Persistent link: https://EconPapers.repec.org/RePEc:fth:gremaq:96.414

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