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Time Varying Coefficient Models; A Proposal for selecting the Coefficient Driver Sets

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journal contribution
posted on 2015-08-21, 09:27 authored by Stephen G. Hall, P. A. V. B. Swamy, G. S. Tavlas
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.

History

Citation

Macroeconomic Dynamics, 2016

Author affiliation

/Organisation/COLLEGE OF SOCIAL SCIENCE/Department of Economics

Source

Third ISCEF (Paris, www.iscef.com)

Version

  • AM (Accepted Manuscript)

Published in

Macroeconomic Dynamics

Publisher

Cambridge University Press (CUP)

issn

1365-1005

eissn

1469-8056

Copyright date

1989

Available date

2017-03-04

Publisher version

https://www.cambridge.org/core/journals/macroeconomic-dynamics/article/div-classtitletime-varying-coefficient-models-a-proposal-for-selecting-the-coefficient-driver-setsdiv/00891C13CCA1A2940FBE7BFACEBBAFB3

Temporal coverage: start date

2014-04-10

Temporal coverage: end date

2014-04-12

Language

en

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