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A BAYESIAN CLASSIFICATION APPROACH TO MONETARY AGGREGATION

Published online by Cambridge University Press:  01 April 2009

Apostolos Serletis
Apostolos Serletis*
Affiliation:
University of Calgary
*
Address correspondence to: Apostolos Serletis, Department of Economics, University of Calgary, Calgary, Alberta T2N 1N4, Canada; e-mail: serletis@ucalgary.ca.
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Abstract

In this article we use Bayesian classification and finite mixture models to extract information from the MSI database (maintained by the Federal Reserve Bank of St. Louis) and construct a new set of non-nested monetary aggregates (under the Divisia aggregation procedure) based on statistical similarities and multidimensional structures. We also use recent advances in the fields of applied econometrics, dynamical systems theory, and statistical physics to investigate the relationship between the new money measures and economic activity. The empirical results offer practical evidence in favor of this approach to monetary aggregation.

Keywords

Monetary AggregationMonetary Policy
Type
Articles
Information
Macroeconomic Dynamics , Volume 13 , Issue 2 , April 2009 , pp. 200 - 219
Copyright
Copyright © Cambridge University Press 2009

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