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VAR forecasting using Bayesian variable selection

Korobilis, D (2011) 'VAR forecasting using Bayesian variable selection.' Journal of Applied Econometrics, 28 (2). pp. 204-230. ISSN 0883-7252

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Abstract

This paper develops methods for automatic selection of variables in Bayesian vector autoregressions (VARs) using the Gibbs sampler. In particular, I provide computationally efficient algorithms for stochastic variable selection in generic linear and nonlinear models, as well as models of large dimensions. The performance of the proposed variable selection method is assessed in forecasting three major macroeconomic time series of the UK economy. Data-based restrictions of VAR coefficients can help improve upon their unrestricted counterparts in forecasting, and in many cases they compare favorably to shrinkage estimators.

Item Type: Article
Uncontrolled Keywords: C11; C32; C52; C53; E37; Forecasting; variable selection; time-varying parameters; Bayesian vector autoregression
Subjects: H Social Sciences > HB Economic Theory
Divisions: Faculty of Social Sciences
Faculty of Social Sciences > Essex Business School
Faculty of Social Sciences > Essex Business School > Essex Finance Centre
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 23 Nov 2016 12:35
Last Modified: 06 Jan 2022 14:41
URI: http://repository.essex.ac.uk/id/eprint/17958

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