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On the J-test for nonnested hypotheses and Bayesian extension

Author

Listed:
  • Rao, Surekha
  • Ghali, Moheb
  • Krieg, John

Abstract

Abstract Davidson and MacKinnon’s J-test was developed to test non-nested 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 J-test 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.

Suggested Citation

  • Rao, Surekha & Ghali, Moheb & Krieg, John, 2008. "On the J-test for nonnested hypotheses and Bayesian extension," MPRA Paper 14637, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:14637
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    File URL: https://mpra.ub.uni-muenchen.de/14637/1/MPRA_paper_14637.pdf
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    References listed on IDEAS

    as
    1. Russell Davidson & James G. Mackinnon, 1982. "Some Non-Nested Hypothesis Tests and the Relations Among Them," Review of Economic Studies, Oxford University Press, vol. 49(4), pages 551-565.
    2. Davidson, Russell & MacKinnon, James G, 1981. "Several Tests for Model Specification in the Presence of Alternative Hypotheses," Econometrica, Econometric Society, vol. 49(3), pages 781-793, May.
    3. Davidson, Russell & MacKinnon, James G., 1993. "Estimation and Inference in Econometrics," OUP Catalogue, Oxford University Press, number 9780195060119.
    4. Davidson, Russell & MacKinnon, James G., 2002. "Bootstrap J tests of nonnested linear regression models," Journal of Econometrics, Elsevier, vol. 109(1), pages 167-193, July.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    specification testing; non-nested hypotheses; Bayes factor; Bayesian Information Criteria; Marginal likelihood;

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General

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