Large time-varying parameter VARs

Koop, Gary and Korobilis, Dimitris (2013) Large time-varying parameter VARs. Journal of Econometrics, 177 (2). pp. 185-198. ISSN 0304-4076 (https://doi.org/10.1016/j.jeconom.2013.04.007)

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Abstract

In this paper, we develop methods for estimation and forecasting in large time-varying parameter vector autoregressive models (TVP-VARs). To overcome computational constraints, we draw on ideas from the dynamic model averaging literature which achieve reductions in the computational burden through the use forgetting factors. We then extend the TVP-VAR so that its dimension can change over time. For instance, we can have a large TVP-VAR as the forecasting model at some points in time, but a smaller TVP-VAR at others. A final extension lies in the development of a new method for estimating, in a time-varying manner, the parameter(s) of the shrinkage priors commonly-used with large VARs. These extensions are operationalized through the use of forgetting factor methods and are, thus, computationally simple. An empirical application involving forecasting inflation, real output and interest rates demonstrates the feasibility and usefulness of our approach.

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• Item metadata

  Item type:	Article
  ID code:	42735
  Dates:	Date Event December 2013 Published 17 April 2013 Published Online
  Notes:	NOTICE: this is the author’s version of a work that was accepted for publication in Journal of Econometrics. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Econometrics, VOL 117, ISSUE 2, (December 2013) DOI 10.1016/j.jeconom.2013.04.007
  Subjects:	Social Sciences > Economic Theory
  Department:	Strathclyde Business School > Economics
  Depositing user:	Pure Administrator
  Date deposited:	05 Feb 2013 14:39
  Last modified:	23 Apr 2024 00:10
  Related URLs:	Scopus publication Journal or Publication
  URI:	https://strathprints.strath.ac.uk/id/eprint/42735