Comparing Seasonal Forecasts of Industrial Production
Forecast combination methodologies exploit complementary relations between different types of econometric models and often deliver more accurate forecasts than the individual models on which they are based. This paper examines forecasts of seasonally unadjusted monthly industrial production data for 17 countries and the Euro Area, comparing individual model forecasts and forecast combination methods in order to examine whether the latter are able to take advantage of the properties of different seasonal specifications. In addition to linear models (with deterministic seasonality and with nonstationary stochastic seasonality), more complex models that capture nonlinearity or seasonally varying coefficients (periodic models) are also examined. Although parsimonous periodic models perform well for some countries, forecast combinations provide the best overall performance at short horizons, implying that utilizing the characteristics captured by different models can contribute to improved forecast accuracy.
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- Terui, Nobuhiko & van Dijk, Herman K., 2002.
"Combined forecasts from linear and nonlinear time series models,"
International Journal of Forecasting,
Elsevier, vol. 18(3), pages 421-438.
- N. Terui & Herman K. van Dijk, 2000. "Combined Forecasts from Linear and Nonlinear Time Series Models," Tinbergen Institute Discussion Papers 00-003/4, Tinbergen Institute.
- Terui, N. & van Dijk, H.K., 1999. "Combined forecasts from linear and nonlinear time series models," Econometric Institute Research Papers EI 9949-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Hylleberg, Svend & Jorgensen, Clara & Sorensen, Nils Karl, 1993. "Seasonality in Macroeconomic Time Series," Empirical Economics, Springer, vol. 18(2), pages 321-335.
- Matas-Mir, Antonio & Osborn, Denise R., 2004.
"Does seasonality change over the business cycle? An investigation using monthly industrial production series,"
European Economic Review,
Elsevier, vol. 48(6), pages 1309-1332, December.
- Matas-Mir, Antoni & Denise R Osborn, 2002. "Does Seasonality Change over the Business Cycle? An Investigation using Monthly Industrial Production Series," Royal Economic Society Annual Conference 2002 139, Royal Economic Society.
- A Matas-Mir & D R Osborn, 2001. "Does Seasonality Change Over the Business Cycle? An Investigation Using Monthly Industrial Production Series," The School of Economics Discussion Paper Series 0110, Economics, The University of Manchester.
- D R Osborn & A Matas-Mir, 2001. "Does Seasonality Change over the Business Cycle? An Investigation using Monthly Industrial Production Series," Centre for Growth and Business Cycle Research Discussion Paper Series 09, Economics, The Univeristy of Manchester.
- Ghysels,Eric & Osborn,Denise R., 2001.
"The Econometric Analysis of Seasonal Time Series,"
Cambridge University Press, number 9780521562607, December.
- Dick van Dijk & Philip Hans Franses & Michael P. Clements & Jeremy Smith, 2003.
"On SETAR non-linearity and forecasting,"
Journal of Forecasting,
John Wiley & Sons, Ltd., vol. 22(5), pages 359-375.
- Robert B. Davies, 2002. "Hypothesis testing when a nuisance parameter is present only under the alternative: Linear model case," Biometrika, Biometrika Trust, vol. 89(2), pages 484-489, June.
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