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

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Author Info
J M C Santos Silva (ISEG, Universidade Técnica de Lisboa)

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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.

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Publisher Info
Paper provided by University College London, Department of Economics in its series Discussion Papers with number 96-28 ISSN 1350-6722.

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Length: 25 pages
Date of creation: Nov 1996
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Handle: RePEc:wuk:ucloec:9628

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Related research
Keywords: Non-nested hypotheses; Score tests; Cox test; Linear mixtures.;

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Find related papers by JEL classification:
C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

  1. Gordon Fisher & Michael McAleer, 1980. "The Interpretation of the Cox Test in Econometrics," Working Papers 371, Queen's University, Department of Economics.
  2. Tse, Y K, 1987. "A Diagnostic Test for the Multinomial Logit Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(2), pages 283-86, April.
  3. Lechner, Michael, 1991. "Testing Logit Models in Practice," Empirical Economics, Springer, vol. 16(2), pages 177-98.
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  4. Gaundry, Marc J. I. & Dagenais, Marcel G., 1979. "The dogit model," Transportation Research Part B: Methodological, Elsevier, vol. 13(2), pages 105-111, June. [Downloadable!] (restricted)
  5. Fry, Tim R. L. & Harris, Mark N., 1996. "A Monte Carlo study of tests for the independence of irrelevant alternatives property," Transportation Research Part B: Methodological, Elsevier, vol. 30(1), pages 19-30, February. [Downloadable!] (restricted)
  6. Pesaran, M. H., 1981. "Pitfalls of testing non-nested hypotheses by the lagrange multiplier method," Journal of Econometrics, Elsevier, vol. 16(1), pages 158-158, May. [Downloadable!] (restricted)
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  7. Bahram Pesaran & M. Hashem Pesaran, 1995. "A non-nested test of level-differenced versus log-differenced stationary models," Econometric Reviews, Taylor and Francis Journals, vol. 14(2), pages 213-227. [Downloadable!] (restricted)
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  8. Davidson, Russell & MacKinnon, James G., 1984. "Convenient specification tests for logit and probit models," Journal of Econometrics, Elsevier, vol. 25(3), pages 241-262, July. [Downloadable!] (restricted)
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  9. Quandt, Richard E, 1974. "A Comparison of Methods for Testing Nonnested Hypotheses," The Review of Economics and Statistics, MIT Press, vol. 56(1), pages 92-99, February. [Downloadable!] (restricted)
  10. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-33, March. [Downloadable!] (restricted)
  11. Cameron, A Colin & Trivedi, Pravin K, 1986. "Econometric Models Based on Count Data: Comparisons and Applications of Some Estimators and Tests," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 1(1), pages 29-53, January. [Downloadable!] (restricted)
  12. Godfrey, L. G. & Pesaran, M. H., 1983. "Tests of non-nested regression models: Small sample adjustments and Monte Carlo evidence," Journal of Econometrics, Elsevier, vol. 21(1), pages 133-154, January. [Downloadable!] (restricted)
  13. Godfrey, L. G., 1998. "Tests of non-nested regression models some results on small sample behaviour and the bootstrap," Journal of Econometrics, Elsevier, vol. 84(1), pages 59-74, May. [Downloadable!] (restricted)
  14. James MacKinnon, 1983. "Model specification tests against non-nested alternatives," Econometric Reviews, Taylor and Francis Journals, vol. 2(1), pages 85-110. [Downloadable!] (restricted)
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  15. Fisher, Gordon R. & McAleer, Michael, 1981. "Alternative procedures and associated tests of significance for non-nested hypotheses," Journal of Econometrics, Elsevier, vol. 16(1), pages 103-119, May. [Downloadable!] (restricted)
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  16. Gurmu, Shiferaw & Trivedi, Pravin K, 1996. "Excess Zeros in Count Models for Recreational Trips," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(4), pages 469-77, October.
  17. Gourieroux, C. & Monfort, A., 1986. "Testing non-nested hypotheses," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 44, pages 2583-2637 Elsevier. [Downloadable!] (restricted)
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. 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). [Downloadable!]
  2. R. Paap & P.F. Franses, 2002. "Common large innovations across nonlinear time series," Econometric Institute Report 262, Erasmus University Rotterdam, Econometric Institute. [Downloadable!]
    Other versions:
  3. Nakatani, Tomoaki & Sato, Kazuo, 2005. "Truncation and Endogenous Stratification in Various Count Data Models for Recreation Demand Analysis," Working Paper Series in Economics and Finance 615, Stockholm School of Economics. [Downloadable!]
  4. Taisuke Otsu & Myung Hwan Seo & Yoon-Jae Whang, 2008. "Testing for Non-Nested Conditional Moment Restrictions Using Unconditional Empirical Likelihood," Cowles Foundation Discussion Papers 1660, Cowles Foundation, Yale University. [Downloadable!]
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