Connectionist-Based Rules Describing the Pass-Through of Individual Goods Prices into Trend Inflation in the United States

Federal Reserve Bank of St. Louis Working Paper No. 2011-007A

32 Pages Posted: 17 Feb 2011

See all articles by Richard G. Anderson

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

Date Written: February 16, 2011

Abstract

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.

Keywords: Consumer prices, Inflation, Neural Network, Data Mining, Rule Generation

JEL Classification: E31, C45

Suggested Citation

Anderson, Richard G. and Binner, Jane M. and Schmidt, Vincent A., Connectionist-Based Rules Describing the Pass-Through of Individual Goods Prices into Trend Inflation in the United States (February 16, 2011). Federal Reserve Bank of St. Louis Working Paper No. 2011-007A. Available at SSRN: https://ssrn.com/abstract=1762716 or http://dx.doi.org/10.2139/ssrn.1762716

Richard G. Anderson (Contact Author)

Federal Reserve Bank of St. Louis - Research Division ( email )

411 Locust St
Saint Louis, MO 63011
United States

Jane M. Binner

University of Birmingham - Department of Accounting and Finance ( email )

Birmingham, B15 2TY
United Kingdom

Vincent A. Schmidt

Government of the United States of America - United States Air Force Research Laboratory WPAFB ( email )

Dayton, OH 45435
United States

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