Fuzzy modelling and estimation of economic relationships

Authors:
David Shepherd;Francis K. C. Shi
Affiliations:
Tanaka Business School, Imperial College London, South Kensington Campus, London SW7 2AZ, UK;Tanaka Business School, Imperial College London, South Kensington Campus, London SW7 2AZ, UK
Venue:
Computational Statistics & Data Analysis
Year:
2006

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Abstract

A modelling strategy based on the application of fuzzy logic is shown to provide a powerful and efficient method for the estimation of non-linear and linear economic relationships. The procedure is particularly suitable for the estimation of ill-defined systems in which there is considerable uncertainty about the nature and range of key input variables. In addition, no prior knowledge is required about the form of the underlying relationships, and trend, cyclical and irregular components of the model can all be estimated in a single pass. The potential benefits of the fuzzy logic approach are illustrated using a model of real-wage behaviour in the United States over the period 1960-1995. The results suggest that the relationships in the model are basically non-linear.