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Optimizing in the class of Fuller modified limited information maximum likelihood estimators

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  • Kadiyala, K. R.
  • Oberhelman, Dennis

Abstract

A general class of Fuller modified maximum likelihood estimators are considered. It is shown that this class possesses finite moments. Asymptotic bias and asymptotic mean squared error are derived using small-[sigma] expansions. A simulation study is carried out to compare different estimators in this class with standard estimators.

Suggested Citation

  • Kadiyala, K. R. & Oberhelman, Dennis, 1992. "Optimizing in the class of Fuller modified limited information maximum likelihood estimators," Journal of Multivariate Analysis, Elsevier, vol. 43(2), pages 218-236, November.
    • Handle: RePEc:eee:jmvana:v:43:y:1992:i:2:p:218-236
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    Cited by:

    1. Mercado, Rogelio, 2020. "Are capital inflows expansionary or contractionary in the Philippines?," Journal of Asian Economics, Elsevier, vol. 67(C).
    2. Oberhelman, Dennis & Rao Kadiyala, K., 2000. "Asymptotic probability concentrations and finite sample properties of modified LIML estimators for equations with more than two endogenous variables," Journal of Econometrics, Elsevier, vol. 98(1), pages 163-185, September.

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