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An encompassing test for non-nested quantile regression models

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  • Kuan, Chung-Ming
  • Lin, Hsin-Yi

Abstract

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.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ecolet:v:107:y:2010:i:2:p:257-260
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    References listed on IDEAS

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    Cited by:

    1. Hsin-Yi Lin, 2011. "A robust test for non-nested hypotheses," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(1), pages 93-111, March.

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