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Information Theoretic Alternatives To Traditional Simultaneous Equations Estimators In The Presence Of Heteroskedasticity

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  • Marsh, Thomas L.
  • Mittelhammer, Ronald C.

Abstract

Finite sampling properties of information theoretic estimators of the simultaneous equations model, including maximum empirical likelihood, maximum empirical exponential likelihood, and maximum log Euclidean likelihood, are examined in the presence of selected forms of heteroskedasticity. Extensive Monte Carlo experiments are used to compare finite sample performance of Wald, Likelihood ratio, and Lagrangian multiplier tests constructed from information theoretic estimators to those from traditional generalized method of moments.

Suggested Citation

  • Marsh, Thomas L. & Mittelhammer, Ronald C., 2002. "Information Theoretic Alternatives To Traditional Simultaneous Equations Estimators In The Presence Of Heteroskedasticity," 2002 Annual meeting, July 28-31, Long Beach, CA 19831, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    • Handle: RePEc:ags:aaea02:19831
    DOI: 10.22004/ag.econ.19831
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    References listed on IDEAS

    as
    1. Guido W. Imbens & Richard H. Spady & Phillip Johnson, 1998. "Information Theoretic Approaches to Inference in Moment Condition Models," Econometrica, Econometric Society, vol. 66(2), pages 333-358, March.
    2. Yuichi Kitamura & Michael Stutzer, 1997. "An Information-Theoretic Alternative to Generalized Method of Moments Estimation," Econometrica, Econometric Society, vol. 65(4), pages 861-874, July.
    3. Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers Archive 1488, Iowa State University, Department of Economics.
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