Rao, Surekha and Ghali, Moheb and Krieg, John (2008): On the Jtest for nonnested hypotheses and Bayesian extension.

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Abstract
Abstract Davidson and MacKinnon’s Jtest was developed to test nonnested model specification. In empirical applications, however, when the alternate specifications fit the data well the J test may fail to distinguish between the true and false models: the J test will either reject, or fail to reject both specifications. In such cases we show that it is possible to use the information generated in the process of applying the Jtest to implement a Bayesian approach that provides an unequivocal and acceptable solution. Jeffreys’ Bayes factors offer ways of obtaining the posterior probabilities of the competing models and relative ranking of the competing hypotheses. We further show that by using approximations of Schwarz Information Criterion and Bayesian Information Criterion we can use the classical estimates of the log of the maximum likelihood which are available from the estimation procedures used to implement the J test to obtain Bayesian posterior odds and posterior probabilities of the competing nested and non nested specifications without having to specify prior distributions and going through the rigorous Bayesian computations.
Item Type:  MPRA Paper 

Original Title:  On the Jtest for nonnested hypotheses and Bayesian extension 
Language:  English 
Keywords:  specification testing, nonnested hypotheses, Bayes factor, Bayesian Information Criteria, Marginal likelihood 
Subjects:  C  Mathematical and Quantitative Methods > C5  Econometric Modeling > C52  Model Evaluation, Validation, and Selection C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C12  Hypothesis Testing: General C  Mathematical and Quantitative Methods > C0  General > C01  Econometrics C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C11  Bayesian Analysis: General 
Item ID:  14637 
Depositing User:  surekha Rao 
Date Deposited:  14 Apr 2009 00:38 
Last Modified:  27 Sep 2019 14:02 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/14637 