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Title: Time Varying Coefficient Models; A Proposal for selecting the Coefficient Driver Sets
Authors: Hall, Stephen G.
Swamy, P. A. V. B.
Tavlas, G. S.
First Published: 20-Jan-2016
Presented at: Third ISCEF (Paris,
Start Date: 10-Apr-2014
End Date: 12-Apr-2014
Publisher: Cambridge University Press (CUP)
Citation: Macroeconomic Dynamics, 2016
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 of which is correlated 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 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.
DOI Link: 10.1017/S1365100515000279
ISSN: 1365-1005
eISSN: 1469-8056
Version: Post-print
Status: Peer-reviewed
Type: Journal Article
Rights: Archived with reference to SHERPA/RoMEO and publisher website. No embargo. Version of record:
Appears in Collections:Published Articles, Dept. of Economics

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