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Generalized maximum entropy (GME) estimator: formulation and a monte carlo study


  • Eruygur, H. Ozan


The origin of entropy dates back to 19th century. In 1948, the entropy concept as a measure of uncertainty was developed by Shannon. A decade after in 1957, Jaynes formulated Shannon’s entropy as a method for estimation and inference particularly for ill-posed problems by proposing the so called Maximum Entropy (ME) principle. More recently, Golan et al. (1996) developed the Generalized Maximum Entropy (GME) estimator and started a new discussion in econometrics. This paper is divided into two parts. The first part considers the formulation of this new technique (GME). Second, by Monte Carlo simulations the estimation results of GME will be discussed in the context of non-normal disturbances.

Suggested Citation

  • Eruygur, H. Ozan, 2005. "Generalized maximum entropy (GME) estimator: formulation and a monte carlo study," MPRA Paper 12459, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:12459

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    References listed on IDEAS

    1. 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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    Cited by:

    1. Álvaro Montenegro, 2011. "Información y entropía en economía," Revista de Economía Institucional, Universidad Externado de Colombia - Facultad de Economía, vol. 13(25), pages 199-221, July-Dece.

    More about this item


    Entropy; Maximum Entropy; ME; Generalized Maximum Entropy; GME; Monte Carlo Experiment; Shannon’s Entropy; Non-normal disturbances;

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics


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