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Can forecasting performance be improved by considering the steady state? An application to Swedish inflation and interest rate

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Author Info
Pär Österholm (Sveriges Riksbank and Department of Economics, Uppsala University, Uppsala, Sweden)

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Abstract

This paper investigates whether the forecasting performance of Bayesian autoregressive and vector autoregressive models can be improved by incorporating prior beliefs on the steady state of the time series in the system. Traditional methodology is compared to the new framework-in which a mean-adjusted form of the models is employed-by estimating the models on Swedish inflation and interest rate data from 1980 to 2004. Results show that the out-of-sample forecasting ability of the models is practically unchanged for inflation but significantly improved for the interest rate when informative prior distributions on the steady state are provided. The findings in this paper imply that this new methodology could be useful since it allows us to sharpen our forecasts in the presence of potential pitfalls such as near unit root processes and structural breaks, in particular when relying on small samples. Copyright © 2008 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/for.1041
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Publisher Info
Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

Volume (Year): 27 (2008)
Issue (Month): 1 ()
Pages: 41-51
Download reference. The following formats are available: HTML, plain text, BibTeX, RIS (EndNote), ReDIF
Handle: RePEc:jof:jforec:v:27:y:2008:i:1:p:41-51

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Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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  1. Lisandro Abrego & Pär Österholm, 2008. "External Linkages and Economic Growth in Colombia: Insights from A Bayesian VAR Model," IMF Working Papers 08/46, International Monetary Fund. [Downloadable!]
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This page was last updated on 2008-6-10.


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