Specifying Parameters in Computable General Equilibrium Models Using Optimal Fingerprint Detection Methods

31 Pages Posted: 13 Nov 2014

See all articles by Simon Koesler

Simon Koesler

ZEW – Leibniz Centre for European Economic Research - Environmental and Resource Economics, Environmental Management Research

Date Written: October 23, 2014

Abstract

The specification of parameters is a crucial task in the development of economic models. The objective of this paper is to improve the standard parameter specification of computable general equilibrium (CGE) models. On that account, we illustrate how Optimal Fingerprint Detection Methods (OFDM) can be used to identify appropriate values for various parameters. This method originates from climate science and combines a simple model validation exercise with a structured sensitivity analysis. The new approach has three main benefits: 1) It uses a structured optimisation procedure and does not revert to ad-hoc model improvements. 2) It allows to account for uncertainty in parameter estimates by using information on the distribution of parameter estimates from the literature. 3) It can be applied for the specification of a range of parameters required in CGE models, for example for the definition of elasticities or productivity growth rates.

Keywords: CGE modelling, sensitivity analysis, model validation parameter specification, substitution elasticities

JEL Classification: C52, C68, D58

Suggested Citation

Koesler, Simon, Specifying Parameters in Computable General Equilibrium Models Using Optimal Fingerprint Detection Methods (October 23, 2014). ZEW - Centre for European Economic Research Discussion Paper No. 14-092, Available at SSRN: https://ssrn.com/abstract=2523357 or http://dx.doi.org/10.2139/ssrn.2523357

Simon Koesler (Contact Author)

ZEW – Leibniz Centre for European Economic Research - Environmental and Resource Economics, Environmental Management Research ( email )

P.O. Box 10 34 43
L 7,1
D-68034 Mannheim
Germany

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
39
Abstract Views
437
PlumX Metrics