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A Score Test for Non-nested Hypotheses with Applications to Discrete Data Models

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  • J M C Santos Silva

    (ISEG, Universidade Técnica de Lisboa)

Abstract

This paper suggests that a convenient score test against non- nested alternatives can be constructed from the linear combination of the likelihood functions of the competing models. It is shown that this procedure is essentially a test for the correct specification of the conditional distribution of the variable of interest. As in Models for discrete data it is often necessary to fully specify the conditional distribution of the variate of interest, the test proposed here is particularly attractive in this context. The usefulness of the proposed tests is illustrated with applications to discrete choice and count data models.

Suggested Citation

  • J M C Santos Silva, 1996. "A Score Test for Non-nested Hypotheses with Applications to Discrete Data Models," Discussion Papers 96-28 ISSN 1350-6722, University College London, Department of Economics.
    • Handle: RePEc:wuk:ucloec:9628
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    3. Silva João M. C. Santos & Tenreyro Silvana & Windmeijer Frank, 2015. "Testing Competing Models for Non-negative Data with Many Zeros," Journal of Econometric Methods, De Gruyter, vol. 4(1), pages 29-46, January.
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    8. Juan Mora & Ana I. Moro, 2006. "Consistent Specification Test For Ordered Discrete Choice Models," Working Papers. Serie AD 2006-17, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    9. Esmeralda A. Ramalho & Joaquim J. S. Ramalho, 2012. "Alternative Versions of the RESET Test for Binary Response Index Models: A Comparative Study," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(1), pages 107-130, February.
    10. Esmeralda A. Ramalho & Joaquim J. S. Ramalho & José M. R. Murteira, 2014. "A Generalized Goodness-of-functional Form Test for Binary and Fractional Regression Models," Manchester School, University of Manchester, vol. 82(4), pages 488-507, July.
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    19. M. T. Aparicio & I. Villan�a, 2012. "Selection criteria for overlapping binary Models," Documentos de Trabajo dt2012-01, Facultad de Ciencias Económicas y Empresariales, Universidad de Zaragoza.
    20. Kuan, Chung-Ming & Lin, Hsin-Yi, 2010. "An encompassing test for non-nested quantile regression models," Economics Letters, Elsevier, vol. 107(2), pages 257-260, May.
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    More about this item

    Keywords

    Non-nested hypotheses; Score tests; Cox test; Linear mixtures.;
    All these keywords.

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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