Estimating Parameters and Structural Change in CGE Models Using a Bayesian Cross-Entropy Estimation Approach
This paper uses a three-step Bayesian cross-entropy estimation approach in an environment of noisy and scarce data to estimate behavioral parameters for a computable general equilibrium model. The estimation also measures how labor-augmenting produ...
| Main Authors: | , , , |
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| Format: | Publications & Research |
| Language: | English en_US |
| Published: |
World Bank Group, Washington, DC
2015
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| Subjects: | |
| Online Access: | http://documents.worldbank.org/curated/en/2015/01/23855951/estimating-parameters-structural-change-cge-models-using-bayesian-cross-entropy-estimation-approach http://hdl.handle.net/10986/21391 |
| Summary: | This paper uses a three-step Bayesian
cross-entropy estimation approach in an environment of noisy
and scarce data to estimate behavioral parameters for a
computable general equilibrium model. The estimation also
measures how labor-augmenting productivity and other
structural parameters in the model may have shifted over
time to contribute to the generation of historically
observed changes in the economic arrangement. In this
approach, the parameters in a computable general equilibrium
model are treated as fixed but unobserved, represented as
prior mean values with prior error mass functions.
Estimation of the parameters involves using an
information-theoretic Bayesian approach to exploit
additional information in the form of new data from a series
of social accounting matrices, which are assumed were
measured with error. The estimation procedure is
"efficient" in the sense that it uses all
available information and makes no assumptions about
unavailable information. As illustration, the methodology is
applied to estimate the parameters of a computable general
equilibrium model using alternative data sets for the
Republic of Korea and Sub-Saharan Africa. |
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