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Efficient Estimation of Moment Condition Models with Heterogenous Populations

Author

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  • Zhiguo Xiao

    (School of Management, Fudan University)

Abstract

A wide range of econometric and statistical models are specified through moment conditions. Efficient estimation of such models essentially employs two distinct ideas: optimally combining estimation equations (e.g., the optimal estimating equations of Godambe (1976), the generalized method of moments of Hansen (1982) and the empirical likelihood of Qin and Lawless (1994)), and optimally combining estimators (e.g., the weighted method of moments of Xiao (2010)). This paper extends these methods to moment condition models with heterogeneous populations. Comparison of the finite sample performance of the proposed estimators is conducted through Monte Carlo simulations.

Suggested Citation

  • Zhiguo Xiao, 2011. "Efficient Estimation of Moment Condition Models with Heterogenous Populations," Annals of Economics and Finance, Society for AEF, vol. 12(1), pages 89-107, May.
    • Handle: RePEc:cuf:journl:y:2011:v:12:i:1:p:89-107
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    References listed on IDEAS

    as
    1. Girma, Sourafel, 2000. "A quasi-differencing approach to dynamic modelling from a time series of independent cross-sections," Journal of Econometrics, Elsevier, vol. 98(2), pages 365-383, October.
    2. Yuichi Kitamura, 2006. "Empirical Likelihood Methods in Econometrics: Theory and Practice," Levine's Bibliography 321307000000000307, UCLA Department of Economics.
    3. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    4. Whitney K. Newey & Richard J. Smith, 2004. "Higher Order Properties of Gmm and Generalized Empirical Likelihood Estimators," Econometrica, Econometric Society, vol. 72(1), pages 219-255, January.
    5. Xiao, Zhiguo, 2010. "The weighted method of moments approach for moment condition models," Economics Letters, Elsevier, vol. 107(2), pages 183-186, May.
    6. Altonji, Joseph G & Segal, Lewis M, 1996. "Small-Sample Bias in GMM Estimation of Covariance Structures," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 353-366, July.
    7. Imbens, Guido W, 2002. "Generalized Method of Moments and Empirical Likelihood," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 493-506, October.
    8. Yuichi Kitamura, 2006. "Empirical Likelihood Methods in Econometrics: Theory and Practice," Cowles Foundation Discussion Papers 1569, Cowles Foundation for Research in Economics, Yale University.
    9. K. Jöreskog, 1971. "Simultaneous factor analysis in several populations," Psychometrika, Springer;The Psychometric Society, vol. 36(4), pages 409-426, December.
    10. Bengt Muthén, 1989. "Latent variable modeling in heterogeneous populations," Psychometrika, Springer;The Psychometric Society, vol. 54(4), pages 557-585, September.
    11. Yuichi Kitamura, 2006. "Empirical Likelihood Methods in Econometrics: Theory and Practice," CIRJE F-Series CIRJE-F-430, CIRJE, Faculty of Economics, University of Tokyo.
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    Cited by:

    1. Ting Luo & Zhiguo Xiao, 2015. "Selective Disclosure Associated with Institutional Investors: Evidence Based on Chinese Stock Market," Annals of Economics and Finance, Society for AEF, vol. 16(2), pages 515-542, November.

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    More about this item

    Keywords

    Moment condition models; Heterogenous populations; Optimal estimating equations; Generalized method of moments; Weighted method of moments; Empirical likelihood;
    All these keywords.

    JEL classification:

    • 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

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