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Forecasting the Swedish unemployment rate. VAR vs. transfer function modelling
Stockholm School of Economics, Stockholm, Sweden.
Stockholm School of Economics, Stockholm, Sweden. (Stat@oru)ORCID iD: 0000-0003-0203-4688
1993 (English)In: International Journal of Forecasting, ISSN 0169-2070, E-ISSN 1872-8200, Vol. 9, no 1, p. 61-76Article in journal (Refereed) Published
Abstract [en]

The Swedish unemployment rate is forecast using three time series methods: the ARIMA, transfer function and Vector Autoregressive (VAR) models. Within this context, the choice of modelling strategy is discussed. It is found that the forecasting performance of VAR models is improved by explicitly taking account of cointegration between the variables in the model, despite the fact that unemployment is not cointegrated. However, the more parsimonious ARIMA and transfer function models have lower RMSE for all forecasting horizons. It is also found that the additional variables in the VAR models are important for predicting the turning points in the unemployment rate.

Place, publisher, year, edition, pages
Elsevier, 1993. Vol. 9, no 1, p. 61-76
Keywords [en]
Cointegration; Forecast evaluation; Model selection; Seasonal unit roots; Turning points
National Category
Economics Probability Theory and Statistics
Research subject
Statistics
Identifiers
URN: urn:nbn:se:oru:diva-61126DOI: 10.1016/0169-2070(93)90054-QISI: A1993LF42200012Scopus ID: 2-s2.0-38249001963OAI: oai:DiVA.org:oru-61126DiVA, id: diva2:1144102
Available from: 2017-09-25 Created: 2017-09-25 Last updated: 2017-09-26Bibliographically approved

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Karlsson, Sune

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Output format
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  • asciidoc
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