Parameter Estimation for a Computable General Equilibrium Model: A Maximum Entropy Approach

Publikation: Working paperForskning

Standard

Parameter Estimation for a Computable General Equilibrium Model : A Maximum Entropy Approach. / Arndt, Channing; Robinson, Sherman; Tarp, Finn.

Washington, D.C. : International Food Policy Research Institute (IFPRI), 1999.

Publikation: Working paperForskning

Harvard

Arndt, C, Robinson, S & Tarp, F 1999 'Parameter Estimation for a Computable General Equilibrium Model: A Maximum Entropy Approach' International Food Policy Research Institute (IFPRI), Washington, D.C.

APA

Arndt, C., Robinson, S., & Tarp, F. (1999). Parameter Estimation for a Computable General Equilibrium Model: A Maximum Entropy Approach. Washington, D.C.: International Food Policy Research Institute (IFPRI).

Vancouver

Arndt C, Robinson S, Tarp F. Parameter Estimation for a Computable General Equilibrium Model: A Maximum Entropy Approach. Washington, D.C.: International Food Policy Research Institute (IFPRI). 1999.

Author

Arndt, Channing ; Robinson, Sherman ; Tarp, Finn. / Parameter Estimation for a Computable General Equilibrium Model : A Maximum Entropy Approach. Washington, D.C. : International Food Policy Research Institute (IFPRI), 1999.

Bibtex

@techreport{6cee970074c011dbbee902004c4f4f50,
title = "Parameter Estimation for a Computable General Equilibrium Model: A Maximum Entropy Approach",
abstract = "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",
author = "Channing Arndt and Sherman Robinson and Finn Tarp",
note = "JEL Classification: C51, C68",
year = "1999",
language = "English",
publisher = "International Food Policy Research Institute (IFPRI)",
type = "WorkingPaper",
institution = "International Food Policy Research Institute (IFPRI)",

}

RIS

TY - UNPB

T1 - Parameter Estimation for a Computable General Equilibrium Model

T2 - A Maximum Entropy Approach

AU - Arndt, Channing

AU - Robinson, Sherman

AU - Tarp, Finn

N1 - JEL Classification: C51, C68

PY - 1999

Y1 - 1999

N2 - 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

AB - 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

M3 - Working paper

BT - Parameter Estimation for a Computable General Equilibrium Model

PB - International Food Policy Research Institute (IFPRI)

CY - Washington, D.C.

ER -

ID: 45480