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Tests for general error specifications and non-nested models : a simultaneous approach PDF

36 Pages·1991·1.9 MB·English
by  BeraAnil K
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Preview Tests for general error specifications and non-nested models : a simultaneous approach

UNIVERSITY OF ILLINOIS LIBRARY AT URBANA CHAMPAIGN BOOKSTACKS Digitized by the Internet Archive in 2012 with funding from University of Illinois Urbana-Champaign http://www.archive.org/details/testsforgenerale91136bera Faculty Working Paper 91-0136 330 B385 1991:136 COPY 2 The Library or the MAY b 1 i^yj Universityof Illinois of Urbana-Chanipiiigr. Tests for General Error Specifications A and Non-Nested Models: Simultaneous Approach AnilK. Bera MichaelMcAleer UniversityofIllinois University ofWesternAustralia M. Hashem Pesaran Mann Yoon J. University ofCalifornia, LosAngeles University ofIllinois Department ofEconomics Bureau ofEconomic and Business Research College ofCommerce and Business Administration University ofIllinois at Urbana-Champaign BEBR FACULTY WORKING PAPER NO. 91-0136 College of Commerce and Business Administration University of Illinois at Urbana-Champaign May 1991 Tests for General Error Specifications and Non-Nested Models: A Simultaneous Approach Anil K. Bera University of Illinois Michael McAleer University of Western Australia M. Hashem Pesaran University of California, Los Angeles Mann Yoon J. University of Illinois Department of Economics ABSTRACT This paper is concerned with joint test of non-nested models and simultaneous departures from homoskedasticity, serial independence and normality of the disturbance terms. Locally equivalent alternative models are used to constructjoint tests since they provide a convenient way to incorporate more than one type of departures from the classical conditions, the joint tests represent a simple asymptotic solution tothe "pre-testing" problem in the context ofnon-nested linear regression models. Our simulation results indicate that the proposed tests have good finite sample properties. KeyWordsandPhrases: locally equivalentalternative models; non-normal errors; non-spherical errors; pre-testing problem; simulation study

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