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A Simple Derivation of the Efficiency Bound for Conditional Moment Restriction Models

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  • Naoya Sueishi

    (Graduate School of Economics, Kobe University)

Abstract

This study gives a simple derivation of the efficiency bound for conditional moment restriction models. The Fisher information is obtained by deriving a least favorable submodel in an explicit form. The proposed method also suggests an asymptotically efficient estimator, which can be viewed as an empirical likelihood estimator for conditional moment restriction models.

Suggested Citation

  • Naoya Sueishi, 2015. "A Simple Derivation of the Efficiency Bound for Conditional Moment Restriction Models," Discussion Papers 1531, Graduate School of Economics, Kobe University.
    • Handle: RePEc:koe:wpaper:1531
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    File URL: http://www.econ.kobe-u.ac.jp/RePEc/koe/wpaper/2015/1531.pdf
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    References listed on IDEAS

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    1. Manuel A. Domínguez & Ignacio N. Lobato, 2004. "Consistent Estimation of Models Defined by Conditional Moment Restrictions," Econometrica, Econometric Society, vol. 72(5), pages 1601-1615, September.
    2. 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.
    3. Newey, Whitney K, 1990. "Efficient Instrumental Variables Estimation of Nonlinear Models," Econometrica, Econometric Society, vol. 58(4), pages 809-837, July.
    4. Lavergne, Pascal & Patilea, Valentin, 2013. "Smooth minimum distance estimation and testing with conditional estimating equations: Uniform in bandwidth theory," Journal of Econometrics, Elsevier, vol. 177(1), pages 47-59.
    5. Carrasco, Marine & Florens, Jean-Pierre, 2000. "Generalization Of Gmm To A Continuum Of Moment Conditions," Econometric Theory, Cambridge University Press, vol. 16(6), pages 797-834, December.
    6. 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.
    7. Donald, Stephen G. & Imbens, Guido W. & Newey, Whitney K., 2003. "Empirical likelihood estimation and consistent tests with conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 117(1), pages 55-93, November.
    8. 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.
    9. Chamberlain, Gary, 1987. "Asymptotic efficiency in estimation with conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 34(3), pages 305-334, March.
    10. Severini, Thomas A. & Tripathi, Gautam, 2001. "A simplified approach to computing efficiency bounds in semiparametric models," Journal of Econometrics, Elsevier, vol. 102(1), pages 23-66, May.
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    Cited by:

    1. Tomohiro Ando & Naoya Sueishi, 2019. "On the Convergence Rate of the SCAD-Penalized Empirical Likelihood Estimator," Econometrics, MDPI, vol. 7(1), pages 1-14, March.
    2. Yaroslav Mukhin, 2018. "Sensitivity of Regular Estimators," Papers 1805.08883, arXiv.org.

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    More about this item

    Keywords

    Conditional moment restrictions; Empirical likelihood; Fisher information; Least favorable submodel.;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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