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TIME-VARYING COEFFICIENT MODELS: A PROPOSAL FOR SELECTING THE COEFFICIENT DRIVER SETS

Published online by Cambridge University Press:  20 January 2016

Stephen G. Hall
Affiliation:
Leicester University, Bank of Greece and NIESR
P. A. V. B. Swamy
Affiliation:
Federal Reserve Board (Retired)
George S. Tavlas*
Affiliation:
Bank of Greece and Leicester University
*
Address correspondence to: George S. Tavlas, Member, Monetary Policy Council, Bank of Greece, 21 El. Venizelos Avenue, 102 50 Athens, Greece; e-mail: [email protected].

Abstract

Coefficient drivers are observable variables that feed into time-varying coefficients (TVCs) and explain at least part of their movement. To implement the TVC approach, the drivers are split into two subsets, one of which is correlated with the bias-free coefficient that we want to estimate and the other with the misspecification in the model. This split, however, can appear to be arbitrary. We provide a way of splitting the drivers that takes account of any nonlinearity that may be present in the data, with the aim of removing the arbitrary element in driver selection. We also provide an example of the practical use of our method by applying it to modeling the effect of ratings on sovereign-bond spreads.

Type
Articles
Copyright
Copyright © Cambridge University Press 2016 

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Footnotes

This paper was presented at the third ISCEF (Paris, April 10–12, 2014, www.iscef.com). The views expressed in this paper are the authors' own and do not necessarily represent those of their respective institutions.

References

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