We introduce a maximum entropy approach to parameter estimation for computable general equilibrium (CGE) models. The approach applies information theory to estimating a system of nonlinear simultaneous equations. It has a number of advantages. First, it imposes all general equilibrium constraints. Second, it permits incorporation of prior information on parameter values. Third, it can be applied in the absence of copious data. Finally, it supplies measures of the capacity of the model to reproduce the historical record and the statistical significance of parameter estimates. The method is applied to estimating a CGE model of Mozambique.Non-PRIFPRI1TM
Maximum entropy estimation is a relatively new estimation technique in econometrics. We carry out se...
In this letter, we elaborate on some of the issues raised by a recent paper by Neapolitan and Jiang ...
The method of Generalized Maximum Entropy (GME), proposed in Golan, Judge and Miller (1996), is an i...
We introduce a maximum entropy approach to parameter estimation for computable general equilibrium (...
The authors introduce a maximum entropy approach to parameter estimation for computable general equi...
We introduce a maximum entropy approach to parameter estimation for computable general equilibrium (...
Given the objective of estimating the unknown parameters of a possibly nonlinear dynamic model using...
In this study we illustrate a Maximum Entropy (ME) methodology for modeling incomplete information a...
In the present communication entropy optimization principles namely maximum entropy principle and mi...
In this article, we describe the gmentropylogit command, which implements the generalized maximum en...
The generalized maximum entropy (GME) estimator was introduced by Golan et al. as a way to overcome ...
This paper proposes a generalized maximum entropy (GME) approach to estimate nonlinear dynamic stoch...
A generalized maximum entropy estimator is developed for the linear simultaneous equations systems m...
In this paper, we continue our efforts to show how maximum relative entropy (MrE) can be used as a u...
The maximum entropy principle (MEP) is a powerful statistical inference tool that provides a rigorou...
Maximum entropy estimation is a relatively new estimation technique in econometrics. We carry out se...
In this letter, we elaborate on some of the issues raised by a recent paper by Neapolitan and Jiang ...
The method of Generalized Maximum Entropy (GME), proposed in Golan, Judge and Miller (1996), is an i...
We introduce a maximum entropy approach to parameter estimation for computable general equilibrium (...
The authors introduce a maximum entropy approach to parameter estimation for computable general equi...
We introduce a maximum entropy approach to parameter estimation for computable general equilibrium (...
Given the objective of estimating the unknown parameters of a possibly nonlinear dynamic model using...
In this study we illustrate a Maximum Entropy (ME) methodology for modeling incomplete information a...
In the present communication entropy optimization principles namely maximum entropy principle and mi...
In this article, we describe the gmentropylogit command, which implements the generalized maximum en...
The generalized maximum entropy (GME) estimator was introduced by Golan et al. as a way to overcome ...
This paper proposes a generalized maximum entropy (GME) approach to estimate nonlinear dynamic stoch...
A generalized maximum entropy estimator is developed for the linear simultaneous equations systems m...
In this paper, we continue our efforts to show how maximum relative entropy (MrE) can be used as a u...
The maximum entropy principle (MEP) is a powerful statistical inference tool that provides a rigorou...
Maximum entropy estimation is a relatively new estimation technique in econometrics. We carry out se...
In this letter, we elaborate on some of the issues raised by a recent paper by Neapolitan and Jiang ...
The method of Generalized Maximum Entropy (GME), proposed in Golan, Judge and Miller (1996), is an i...