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Testing for Non-nested Conditional Moment Retrictions via Conditional Empirical Likelihood

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We propose non-nested tests for competing conditional moment resctriction models using a method of empirical likelihood. Our tests are based on the method of conditional empirical likelihood developed by Kitamura, Tripathi and Ahn (2004) and Zhang and Gijbels (2003). By using the conditional implied probabilities, we develop three non-nested tests: the moment encompassing, Cox-type, and effcient score encompassing tests. Compared to the existing non-nested tests which mainly focus on testing unconditional moment restrictions, our approach directly tests conditional moment restrictions which imply the infinite number of unconditional moment restrictions. We derive the null distributions and power properties of the proposed tests. Simulation experiments show that our tests have reasonable finite sample properties.

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  • Taisuke Otsu & Yoon-Jae Whang, 2005. "Testing for Non-nested Conditional Moment Retrictions via Conditional Empirical Likelihood," Cowles Foundation Discussion Papers 1533, Cowles Foundation for Research in Economics, Yale University.
    • Handle: RePEc:cwl:cwldpp:1533
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    1. Wooldridge, Jeffrey M., 1990. "An encompassing approach to conditional mean tests with applications to testing nonnested hypotheses," Journal of Econometrics, Elsevier, vol. 45(3), pages 331-350.
    2. Jian Zhang & Irène Gijbels, 2003. "Sieve Empirical Likelihood and Extensions of the Generalized Least Squares," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 30(1), pages 1-24, March.
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    8. Yuichi Kitamura & Gautam Tripathi & Hyungtaik Ahn, 2004. "Empirical Likelihood-Based Inference in Conditional Moment Restriction Models," Econometrica, Econometric Society, vol. 72(6), pages 1667-1714, November.
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    16. 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.
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    Cited by:

    1. Marmer, Vadim & Otsu, Taisuke, 2012. "Optimal comparison of misspecified moment restriction models under a chosen measure of fit," Journal of Econometrics, Elsevier, vol. 170(2), pages 538-550.
    2. Sueishi, Naoya, 2016. "A simple derivation of the efficiency bound for conditional moment restriction models," Economics Letters, Elsevier, vol. 138(C), pages 57-59.
    3. 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.
    4. Yuichi Kitamura, 2006. "Empirical Likelihood Methods in Econometrics: Theory and Practice," CIRJE F-Series CIRJE-F-430, CIRJE, Faculty of Economics, University of Tokyo.
    5. Yu‐Chin Hsu & Xiaoxia Shi, 2017. "Model‐selection tests for conditional moment restriction models," Econometrics Journal, Royal Economic Society, vol. 20(1), pages 52-85, February.
    6. Xiaoxia Shi, 2015. "A nondegenerate Vuong test," Quantitative Economics, Econometric Society, vol. 6(1), pages 85-121, March.
    7. Komunjer, Ivana, 2013. "Quantile Prediction," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 961-994, Elsevier.

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    More about this item

    Keywords

    Empirical likelihood; Non-nested tests; Encompassing tests; Cox-type tests; Conditional moment restrictions;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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