Add to ORKGThe 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
The method of Generalized Maximum Entropy (GME), proposed in Golan, Judge and Miller (1996), is an i...
We study a parametric estimation problem related to moment condition models. As an alternative to th...
The concept and the mathematical properties of entropy play an im- portant role in statistics, cyber...
The origin of entropy dates back to 19th century. In 1948, the entropy concept as a measure of uncer...
Maximum entropy estimation is a relatively new estimation technique in econometrics. We carry out se...
The generalized maximum entropy (GME) estimator was introduced by Golan et al. as a way to overcome ...
Currently we are witnessing the revaluation of huge data recourses that should be analyzed carefully...
The maximum entropy principle (MEP) is a powerful statistical inference tool that provides a rigorou...
In this study we illustrate a Maximum Entropy (ME) methodology for modeling incomplete information a...
Multicollinearity hampers empirical econometrics. The remedies proposed to date suffer from pitfalls...
This paper estimates von Neumann and Morgenstern utility functions using the generalized maximum ent...
Multicollinearity hampers empirical econometrics. The remedies proposed to date suffer from pitfalls...
Methodologies related to information theory have been increasingly used in studies in economics and ...
Multicollinearity hampers empirical econometrics. The remedies proposed to date suffer from pitfall...
A generalized maximum entropy estimator is developed for the linear simultaneous equations systems m...
The method of Generalized Maximum Entropy (GME), proposed in Golan, Judge and Miller (1996), is an i...
We study a parametric estimation problem related to moment condition models. As an alternative to th...
The concept and the mathematical properties of entropy play an im- portant role in statistics, cyber...
The origin of entropy dates back to 19th century. In 1948, the entropy concept as a measure of uncer...
Maximum entropy estimation is a relatively new estimation technique in econometrics. We carry out se...
The generalized maximum entropy (GME) estimator was introduced by Golan et al. as a way to overcome ...
Currently we are witnessing the revaluation of huge data recourses that should be analyzed carefully...
The maximum entropy principle (MEP) is a powerful statistical inference tool that provides a rigorou...
In this study we illustrate a Maximum Entropy (ME) methodology for modeling incomplete information a...
Multicollinearity hampers empirical econometrics. The remedies proposed to date suffer from pitfalls...
This paper estimates von Neumann and Morgenstern utility functions using the generalized maximum ent...
Multicollinearity hampers empirical econometrics. The remedies proposed to date suffer from pitfalls...
Methodologies related to information theory have been increasingly used in studies in economics and ...
Multicollinearity hampers empirical econometrics. The remedies proposed to date suffer from pitfall...
A generalized maximum entropy estimator is developed for the linear simultaneous equations systems m...
The method of Generalized Maximum Entropy (GME), proposed in Golan, Judge and Miller (1996), is an i...
We study a parametric estimation problem related to moment condition models. As an alternative to th...
The concept and the mathematical properties of entropy play an im- portant role in statistics, cyber...