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A nondegenerate Vuong test

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  • Xiaoxia Shi

Abstract

In this paper, I propose a one‐step nondegenerate test as an alternative to the classical Vuong (1989) tests. I show that the new test achieves uniform asymptotic size control in both the overlapping and the non‐overlapping cases, while the classical Vuong tests do not. Meanwhile, the power of the new test can be substantially better than the two‐step classical Vuong test and is not dominated by the one‐step classical Vuong test. An extension to moment‐based models is also developed. I apply the new test to the voter turnout data set of Coate and Conlin (2004) and find that it can yield model comparison conclusions different from those of the classical tests. The implementation of the new test is straightforward and can be done using the MATLAB and STATA routines that accompany this paper.

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  • Xiaoxia Shi, 2015. "A nondegenerate Vuong test," Quantitative Economics, Econometric Society, vol. 6(1), pages 85-121, March.
  • Handle: RePEc:wly:quante:v:6:y:2015:i:1:p:85-121
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    1. Gouriéroux, Christian & Monfort, Alain, 1995. "Testing, Encompassing, and Simulating Dynamic Econometric Models," Econometric Theory, Cambridge University Press, vol. 11(2), pages 195-228, February.
    2. Andrews, Donald W.K. & Cheng, Xu & Guggenberger, Patrik, 2020. "Generic results for establishing the asymptotic size of confidence sets and tests," Journal of Econometrics, Elsevier, vol. 218(2), pages 496-531.
    3. Susanne M. Schennach & Daniel Wilhelm, 2017. "A Simple Parametric Model Selection Test," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(520), pages 1663-1674, October.
    4. Otsu, Taisuke & Whang, Yoon-Jae, 2011. "Testing For Nonnested Conditional Moment Restrictions Via Conditional Empirical Likelihood," Econometric Theory, Cambridge University Press, vol. 27(1), pages 114-153, February.
    5. Li, Tong, 2009. "Simulation based selection of competing structural econometric models," Journal of Econometrics, Elsevier, vol. 148(2), pages 114-123, February.
    6. Andrews, Donald W.K., 1992. "Generic Uniform Convergence," Econometric Theory, Cambridge University Press, vol. 8(2), pages 241-257, June.
    7. Chen, Xiaohong & Hong, Han & Shum, Matthew, 2007. "Nonparametric likelihood ratio model selection tests between parametric likelihood and moment condition models," Journal of Econometrics, Elsevier, vol. 141(1), pages 109-140, November.
    8. Smith, Richard J, 1997. "Alternative Semi-parametric Likelihood Approaches to Generalised Method of Moments Estimation," Economic Journal, Royal Economic Society, vol. 107(441), pages 503-519, March.
    9. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-333, March.
    10. Otsu, Taisuke & Seo, Myung Hwan & Whang, Yoon-Jae, 2012. "Testing for non-nested conditional moment restrictions using unconditional empirical likelihood," Journal of Econometrics, Elsevier, vol. 167(2), pages 370-382.
    11. Stephen Coate & Michael Conlin, 2004. "A Group Rule–Utilitarian Approach to Voter Turnout: Theory and Evidence," American Economic Review, American Economic Association, vol. 94(5), pages 1476-1504, December.
    12. Douglas Rivers & Quang Vuong, 2002. "Model selection tests for nonlinear dynamic models," Econometrics Journal, Royal Economic Society, vol. 5(1), pages 1-39, June.
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