On Forecasting Cointegrated Seasonal Time Series
AbstractWe analyze periodic and seasonal cointegration models for bivariate quarterly observed time series in an empirical forecasting study. We include both single equation and multiple equation methods. A VAR model in first differences with and without cointegration restrictions is also included in the analysis, where it serves as a benchmark. Our empirical results indicate that the VAR model in first differences without cointegration is best if one-step and four-step ahead forecasts are considered. For longer forecast horizons, however, the periodic and seasonal cointegration models are better. When comparing periodic versus seasonal cointegration models, we find that the seasonal cointegration models tend to yield better forecasts. Finally, there is no clear indication that multiple equation methods improve on single equation methods.
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Bibliographic InfoPaper provided by Stockholm School of Economics in its series Working Paper Series in Economics and Finance with number 350.
Length: 28 pages
Date of creation: 14 Jan 2000
Date of revision:
Publication status: Forthcoming in International Journal of Forecasting.
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Periodic Cointegration; Seasonal cointegration; Forecasting;
Other versions of this item:
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
This paper has been announced in the following NEP Reports:
- NEP-ALL-2000-01-24 (All new papers)
- NEP-ECM-2000-01-24 (Econometrics)
- NEP-ETS-2000-01-24 (Econometric Time Series)
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- Cubadda, Gianluca & Omtzigt, Pieter, 2003.
"Small Sample Improvements in the Statistical Analysis of Seasonally Cointegrated Systems,"
Economics & Statistics Discussion Papers
esdp03012, University of Molise, Dept. SEGeS.
- Cubadda, Gianluca & Omtzigt, Pieter, 2005. "Small-sample improvements in the statistical analysis of seasonally cointegrated systems," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 333-348, April.
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