Connectionist-Based Rules Describing the Pass-Through of Individual Goods Prices into Trend Inflation in the United States
Richard G. Anderson
Federal Reserve Bank of St. Louis - Research Division
Jane M. Binner
University of Birmingham - Department of Accounting and Finance
Vincent A. Schmidt
Government of the United States of America - United States Air Force Research Laboratory WPAFB
February 16, 2011
Federal Reserve Bank of St. Louis Working Paper No. 2011-007A
This paper examines the inflation "pass-through" problem in American monetary policy, defined as the relationship between changes in the growth rates of individual goods and the subsequent economy-wide rate of growth of consumer prices. Granger causality tests robust to structural breaks are used to establish initial relationships. Then, feedforward artificial neural network (ANN) is used to approximate the functional relationship between selected component subindexes and the headline CPI. Moving beyond the ANN "black box," we illustrate how decision rules can be extracted from the network. Our custom decompositional extraction algorithm generates rules in human-readable and machine-executable form (Matlab code). Our procedure provides an additional route, beyond direct Bayesian estimation, for empirical econometric relationships to be embedded in DSGE models. A topic for further research is embedding decision rules within such models.
Number of Pages in PDF File: 32
Keywords: Consumer prices, Inflation, Neural Network, Data Mining, Rule Generation
JEL Classification: E31, C45working papers series
Date posted: February 17, 2011
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