Statistical Identification of Key Parameters of Korean CGE Model
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초록
Although Computable General Equilibrium(CGE) models are now widely used in various fields of economics to assess policy impact, they are often criticized as most key parameters are not econometrically estimated. However, the econometric estimation of parameters may be very costly, since a large database is required for the estimation even for medium-scaled models. Identifying important parameters would be useful, as research resources could be efficiently focused on them. This paper employs a novel approach based on Monte Carlo simulation and regression analysis to identify the important parameters of a CGE model. Using this approach, we illustrate how to identify and rank statistical key parameters of the Korean economy-energy-environment CGE model in impact analysis of an emission reduction policy.
Abstract
Although Computable General Equilibrium(CGE) models are now widely used in various fields of economics to assess policy impact, they are often criticized as most key parameters are not econometrically estimated. However, the econometric estimation of parameters may be very costly, since a large database is required for the estimation even for medium-scaled models. Identifying important parameters would be useful, as research resources could be efficiently focused on them. This paper employs a novel approach based on Monte Carlo simulation and regression analysis to identify the important parameters of a CGE model. Using this approach, we illustrate how to identify and rank statistical key parameters of the Korean economy-energy-environment CGE model in impact analysis of an emission reduction policy.
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