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 logoORCID: https://orcid.org/0000-0002-6091-378X and Korobilis, Dimitris;
  • Item type:Article
    ID code:65705
    Dates:
    Date
    Event
    1 October 2019
    Published
    28 February 2019
    Published Online
    2 October 2018
    Accepted
    Notes:© 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:11 Nov 2024 12:07
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/65705
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