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Monte-carlo evidence suggesting a no moment problem of the continuous updating estimator

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  • Patrik Guggenberger

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    (UCLA, Department of Economics)

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    Abstract

    Monte Carlo evidence is provided that suggests that the continuous updating estimator might have a moment problem. In the linear simultaneous equation model, its performance in terms of sample median and standard deviation is virtually identical to the one of the limited information maximum likelihood estimator.

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    File URL: http://www.accessecon.com/pubs/EB/2005/Volume3/EB-04C10027A.pdf
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    Bibliographic Info

    Article provided by AccessEcon in its journal Economics Bulletin.

    Volume (Year): 3 (2005)
    Issue (Month): 13 ()
    Pages: 1-6

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    Handle: RePEc:ebl:ecbull:eb-04c10027

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    1. Kinal, Terrence W, 1980. "The Existence of Moments of k-Class Estimators," Econometrica, Econometric Society, Econometric Society, vol. 48(1), pages 241-49, January.
    2. Guido W. Imbens & Phillip Johnson & Richard H. Spady, 1995. "Information Theoretic Approaches to Inference in Moment Condition Models," NBER Technical Working Papers, National Bureau of Economic Research, Inc 0186, National Bureau of Economic Research, Inc.
    3. Whitney K. Newey & Richard J. Smith, 2004. "Higher Order Properties of Gmm and Generalized Empirical Likelihood Estimators," Econometrica, Econometric Society, Econometric Society, vol. 72(1), pages 219-255, 01.
    4. Imbens, Guido W, 1997. "One-Step Estimators for Over-Identified Generalized Method of Moments Models," Review of Economic Studies, Wiley Blackwell, Wiley Blackwell, vol. 64(3), pages 359-83, July.
    5. Donald, Stephen G. & Newey, Whitney K., 2000. "A jackknife interpretation of the continuous updating estimator," Economics Letters, Elsevier, Elsevier, vol. 67(3), pages 239-243, June.
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    Cited by:
    1. Rachida Ouysse, 2014. "On the performance of block-bootstrap continuously updated GMM for a class of non-linear conditional moment models," Computational Statistics, Springer, Springer, vol. 29(1), pages 233-261, February.

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