The forecasting performance of various models for seasonality and nonlinearity for quarterly industrial production
AbstractSeasonality often accounts for the major part of quarterly or monthly movements in detrended macro-economic time series. In addition, business cycle nonlinearity is a prominent feature of many such series too. A forecaster can nowadays consider a wide variety of time series models which describe seasonal variation and regime-switching behaviour. In this paper we examine the forecasting performance of various models for seasonality and nonlinearity using quarterly industrial production series for 17 OECD countries. We find that forecasting performance varies widely across series, across forecast horizons and across seasons. However, in general, linear models with fairly simple descriptions of seasonality outperform at short forecast horizons, whereas nonlinear models with more elaborate seasonal components dominate at longer horizons.
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Bibliographic InfoPaper provided by Erasmus University Rotterdam, Econometric Institute in its series Econometric Institute Report with number EI 2001-14.
Date of creation: 26 Apr 2001
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seasonality; industrial production; forecasting; nonlinearity;
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- Dijk, D.J.C. van & Strikholm, B. & Terasvirta, T., 2001.
"The effects of institutional and technological change and business cycle fluctiations on seasonal patterns in quarterly industrial production series,"
Econometric Institute Report
EI 2001-12, Erasmus University Rotterdam, Econometric Institute.
- Dick van Dijk 1 & Birgit Strikholm & Timo Ter�svirta, 2003. "The effects of institutional and technological change and business cycle fluctuations on seasonal patterns in quarterly industrial production series," Econometrics Journal, Royal Economic Society, vol. 6(1), pages 79-98, 06.
- van Dijk, Dick & Strikholm, Birgit & Teräsvirta, Timo, 2001. "The effects of institutional and technological change and business cycle fluctuations on seasonal patterns in quarterly industrial production series," Working Paper Series in Economics and Finance 0429, Stockholm School of Economics, revised 16 May 2002.
- De Gooijer, Jan G. & Kumar, Kuldeep, 1992. "Some recent developments in non-linear time series modelling, testing, and forecasting," International Journal of Forecasting, Elsevier, vol. 8(2), pages 135-156, October.
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