Generalized maximum entropy (GME) estimator: formulation and a monte carlo study
AbstractThe 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.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 12459.
Date of creation: 26 May 2005
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Entropy; Maximum Entropy; ME; Generalized Maximum Entropy; GME; Monte Carlo Experiment; Shannon’s Entropy; Non-normal disturbances;
Find related papers by 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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- Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers 1488, Iowa State University, Department of Economics.
- 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.
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