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

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

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.

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Paper provided by American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association) in its series 2002 Annual meeting, July 28-31, Long Beach, CA with number 19831.

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Date of creation: 2002
Date of revision:
Handle: RePEc:ags:aaea02:19831
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  1. Guido W Imbens, Phillip Johnson & Richard H Spady, . "Information theoretic approaches to inference in moment condition model," Economics Papers W12., Economics Group, Nuffield College, University of Oxford.
  2. Imbens, G.W. & Johnson, P. & Spady, R.H., 1995. "Information Theoretic Approaches to Inference in Movement Condition Models," Economics Papers 99, Economics Group, Nuffield College, University of Oxford.
  3. Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers 1488, Iowa State University, Department of Economics.
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