An encompassing test for non-nested quantile regression models
We propose an encompassing test for non-nested linear quantile regression models and show that it has an asymptotic [chi]2 distribution. It is also shown that the proposed test is a regression rank score test in a comprehensive model under conditional homogeneity. Our simulation results indicate that the proposed test performs very well in finite samples.
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- Wooldridge, Jeffrey M., 1990.
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- Christophe Bontemps & Grayham E. Mizon, 2008. "Encompassing: Concepts and Implementation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(s1), pages 721-750, December.
- Ramalho, Joaquim J. S. & Smith, Richard J., 2002. "Generalized empirical likelihood non-nested tests," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 99-125, March.
- Chen, Yi-Ting & Kuan, Chung-Ming, 2002. "The pseudo-true score encompassing test for non-nested hypotheses," Journal of Econometrics, Elsevier, vol. 106(2), pages 271-295, February.
- Yi-Ting Chen & Chung-Ming Kuan, 2000. "The Pseudo-True Score Encompassing Test for Non-Nested Hypothesis," Econometric Society World Congress 2000 Contributed Papers 1723, Econometric Society.
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- Mizon, Grayham E & Richard, Jean-Francois, 1986. "The Encompassing Principle and Its Application to Testing Non-nested Hypotheses," Econometrica, Econometric Society, vol. 54(3), pages 657-678, May.
- Otsu, Taisuke, 2008. "Conditional empirical likelihood estimation and inference for quantile regression models," Journal of Econometrics, Elsevier, vol. 142(1), pages 508-538, January. Full references (including those not matched with items on IDEAS)
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