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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.

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Bibliographic 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
Date of revision:
Handle: RePEc:wuk:ucloec:9628

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Postal: Gower Street, London WC1E 6BT
Web page: http://www.ucl.ac.uk/economics/
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Keywords: Non-nested hypotheses; Score tests; Cox test; Linear mixtures.;

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References

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  1. Christine Seller & John R. Stoll & Jean-Paul Chavas, 1985. "Validation of Empirical Measures of Welfare Change: A Comparison of Nonmarket Techniques," Land Economics, University of Wisconsin Press, vol. 62(2), pages 156-175.
  2. Lechner, Michael, 1991. "Testing Logit Models in Practice," Empirical Economics, Springer, vol. 16(2), pages 177-98.
  3. White, Halbert, 1982. "Regularity conditions for cox's test of non-nested hypotheses," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 301-318, August.
  4. 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.
  5. Pesaran, M. H., 1981. "Pitfalls of testing non-nested hypotheses by the lagrange multiplier method," Journal of Econometrics, Elsevier, vol. 17(3), pages 323-331, December.
  6. Gordon Fisher & Michael McAleer, 1981. "Alternative Procedures and Associated Tests of Significance for Non-Nested Hypotheses," Working Papers 420, Queen's University, Department of Economics.
  7. 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.
  8. Gaundry, Marc J. I. & Dagenais, Marcel G., 1979. "The dogit model," Transportation Research Part B: Methodological, Elsevier, vol. 13(2), pages 105-111, June.
  9. 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.
  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.
  11. Pasaran, M.H. & Pasaran, B., 1989. "A Simulation Approach To The Problem Of Computing Cox'S Statistic For Testing Non-Nested Models," Papers 7, California Los Angeles - Applied Econometrics.
  12. Pesaran, M. H., 1982. "On the comprehensive method of testing non-nested regression models," Journal of Econometrics, Elsevier, vol. 18(2), pages 263-274, February.
  13. 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.
  14. 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.
  15. Mullahy, John, 1986. "Specification and testing of some modified count data models," Journal of Econometrics, Elsevier, vol. 33(3), pages 341-365, December.
  16. 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.
  17. 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.
  18. 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.
  19. 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.
  20. James G. MacKinnon, 1983. "Model Specification Tests Against Non-Nested Alternatives," Working Papers 573, Queen's University, Department of Economics.
  21. Gordon Fisher & Michael McAleer, 1980. "The Interpretation of the Cox Test in Econometrics," Working Papers 371, Queen's University, Department of Economics.
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Citations

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Cited by:
  1. 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 for Research in Economics, Yale University.
  2. M. T. Aparicio & I. Villanúa, 2012. "Selection criteria for overlapping binary Models," Documentos de Trabajo dt2012-01, Facultad de Ciencias Económicas y Empresariales, Universidad de Zaragoza.
  3. 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, 02.
  4. J.M.C. Santos Silva & Silvana Tenreyro & Kehai Wei, 2012. "Estimating the Extensive Margin of Trade," Economics Discussion Papers 721, University of Essex, Department of Economics.
  5. Esmeralda A. Ramalho & Joaquim J.S. Ramalho & José M.R. Murteira, 2013. "A generalized goodness-of-functional form test for binary and fractional regression models," CEFAGE-UE Working Papers 2013_09, University of Evora, CEFAGE-UE (Portugal).
  6. 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).
  7. 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.
  8. Isabel Mendes & Isabel Proença, 2009. "Measuring the Social Recreation Per-Day Net Benefit of Wildlife Amenities of a National Park: A Count-Data Travel Cost Approach," Working Papers Department of Economics 2009/35, ISEG - School of Economics and Management, Department of Economics, University of Lisbon.
  9. Franses, Ph.H.B.F. & Paap, R., 2002. "Common large innovations across nonlinear time series," Econometric Institute Research Papers EI 2002-09, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  10. J. M. C. Santos Silva & Silvana Tenreyro & Frank Windmeijer, 2010. "Is it different for zeros? Discriminating between models for non-negative data with many zeros," CeMMAP working papers CWP20/10, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  11. 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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