Joint Tests of Non-Nested Models and General Error Specifications

Anil K. Bera, Michael McAleer, M. Hashem Pesaran, Mann J. Yoon

Research output: Contribution to journalArticlepeer-review


This paper is concerned with joint tests of non-nested models and simultaneous departures from homoskedasticity, serial independence and normality of the disturbance terms. Locally equivalent alternative models are used to construct joint tests since they provide a convenient way to incorporate more than one type of departure from the classical conditions. The joint tests represent a simple asymptotic solution to the “pre-testing” problem in the context of non-nested linear regression models. Our simulation results indicate that the proposed tests have good finite sample properties.

Original languageEnglish (US)
Pages (from-to)97-117
Number of pages21
JournalEconometric Reviews
Issue number1
StatePublished - 1992

ASJC Scopus subject areas

  • Economics and Econometrics


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