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Further Results on the Limiting Distribution of GMM Sample Moment Conditions

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  • Nikolay Gospodinov
  • Raymond Kan
  • Cesare Robotti

Abstract

In this article, we examine the limiting behavior of generalized method of moments (GMM) sample moment conditions and point out an important discontinuity that arises in their asymptotic distribution. We show that the part of the scaled sample moment conditions that gives rise to degeneracy in the asymptotic normal distribution is T -consistent and has a nonstandard limiting distribution. We derive the appropriate asymptotic (weighted chi-squared) distribution when this degeneracy occurs and show how to conduct asymptotically valid statistical inference. We also propose a new rank test that provides guidance on which (standard or nonstandard) asymptotic framework should be used for inference. The finite-sample properties of the proposed asymptotic approximation are demonstrated using simulated data from some popular asset pricing models.

Suggested Citation

  • Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2012. "Further Results on the Limiting Distribution of GMM Sample Moment Conditions," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(4), pages 494-504, May.
    • Handle: RePEc:taf:jnlbes:v:30:y:2012:i:4:p:494-504
    DOI: 10.1080/07350015.2012.694743
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    Cited by:

    1. Gospodinov, Nikolay & Kan, Raymond & Robotti, Cesare, 2013. "Chi-squared tests for evaluation and comparison of asset pricing models," Journal of Econometrics, Elsevier, vol. 173(1), pages 108-125.
    2. Khalaf, Lynda & Schaller, Huntley, 2016. "Identification and inference in two-pass asset pricing models," Journal of Economic Dynamics and Control, Elsevier, vol. 70(C), pages 165-177.
    3. Fletcher, Jonathan, 2014. "Benchmark models of expected returns in U.K. portfolio performance: An empirical investigation," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 30-46.

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