Analyzing MSI rules for the USA – Extracted from a feedforward neural network

Abstract

This chapter introduces a mechanism for generating a series of rules that characterize the money-price relationship for the United States, defined as the relationship between the rate of growth of the money supply and inflation. Monetary Services Indicator (MSI) component data is used to train a selection of candidate feedforward neural networks. The selected network is mined for rules, expressed in human-readable and machine-executable form. The rule and network accuracy are compared, and expert commentary is made on the readability and reliability of the extracted rule set. The ultimate goal of this research is to produce rules that meaningfully and accurately describe inflation in terms of the MSI component dataset.11Paper cleared for public release AFRL/WS–07–0848.

Citation

Schmidt, V.A. and Binner, J.M. (2009), "Analyzing MSI rules for the USA – Extracted from a feedforward neural network", Binner, J.M., Edgerton, D.L. and Elger, T. (Ed.) Measurement Error: Consequences, Applications and Solutions (Advances in Econometrics, Vol. 24), Emerald Group Publishing Limited, Leeds, pp. 281-294. https://doi.org/10.1108/S0731-9053(2009)0000024015