Specifying parameters in computable general equilibrium models using optimal fingerprint detection methods

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.