EconPapers    
Economics at your fingertips  
 

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

H. Ozan Eruygur

MPRA Paper from University Library of Munich, Germany

Abstract: 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.

Keywords: Entropy; Maximum Entropy; ME; Generalized Maximum Entropy; GME; Monte Carlo Experiment; Shannon’s Entropy; Non-normal disturbances (search for similar items in EconPapers)
JEL-codes: C01 C10 C15 (search for similar items in EconPapers)
Date: 2005-05-26
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/12459/1/MPRA_paper_12459.pdf original version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:12459

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().

 
Page updated 2025-03-19
Handle: RePEc:pra:mprapa:12459