Forecasting with high dimensional panel VARs
Koop, Gary and Korobilis, Dimitris (2019) Forecasting with high dimensional panel VARs. Oxford Bulletin of Economics and Statistics, 81 (5). pp. 937-959. ISSN 1468-0084 (https://doi.org/10.1111/obes.12303)
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Abstract
This paper develops methods for estimating and forecasting in Bayesian panel vector autoregressions of large dimensions with time-varying parameters and stochastic volatility. We exploit a hierarchical prior that takes into account possible pooling restrictions involving both VAR coefficients and the error covariance matrix, and propose a Bayesian dynamic learning procedure that controls for various sources of model uncertainty. We tackle computational concerns by means of a simulation-free algorithm that relies on an analytical approximation of the posterior distribution. We use our methods to forecast inflation rates in the eurozone and show that forecasts from our flexible specification are superior to alternative methods for large vector autoregressions.
ORCID iDs
Koop, Gary ORCID: https://orcid.org/0000-0002-6091-378X and Korobilis, Dimitris;-
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Item type: Article ID code: 65705 Dates: DateEvent1 October 2019Published28 February 2019Published Online2 October 2018AcceptedNotes: © 2019 The Department of Economics, University of Oxford and John Wiley & Sons Ltd. Koop, G. and Korobilis, D. (2019), Forecasting with High-Dimensional Panel VARs. Oxf Bull Econ Stat, 81: 937-959. https://doi.org/10.1111/obes.12303 Subjects: Social Sciences > Economic Theory Department: Strathclyde Business School > Economics Depositing user: Pure Administrator Date deposited: 08 Oct 2018 10:52 Last modified: 05 Sep 2024 00:58 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/65705