Handbook of Economic Forecasting part 3. Research on forecasting methods has made important progress over recent years and these developments are brought together in the Handbook of Economic Forecasting. The handbook covers developments in how forecasts are constructed based on multivariate time-series models, dynamic factor models, nonlinear models and combination methods. The handbook also includes chapters on forecast evaluation, including evaluation of point forecasts and probability forecasts and contains chapters on survey forecasts and volatility forecasts. Areas of applications of forecasts covered in the handbook include economics, finance and marketing | xx Contents of Volume 1 . GARCH model forecast-error taxonomy 616 4. Forecasting when there are breaks 617 . Cointegrated vector autoregressions 617 . VECM forecast errors 618 . DVAR forecast errors 620 . Forecast biases under location shifts 620 . Forecast biases when there are changes in the autoregressive parameters 621 . Univariate models 622 5. Detection of breaks 622 . Tests for structural change 622 . Testing for level shifts in ARMA models 625 6. Model estimation and specification 627 . Determination of estimation sample for a fixed specification 627 . Updating 630 7. Ad hoc forecasting devices 631 . Exponential smoothing 631 . Intercept corrections 633 . Differencing 634 . Pooling 635 8. Non-linear models 635 . Testing for non-linearity and structural change 636 . Non-linear model forecasts 637 . Empirical evidence 639 9. Forecasting UK unemployment after three crises 640 . Forecasting 1992-2001 643 . Forecasting 1919-1938 645 . Forecasting 1948-1967 645 . Forecasting 1975-1994 647 . Overview 647 10. Concluding remarks 648 Appendix A Taxonomy derivations for Equation 10 648 Appendix B Derivations for Section 650 References 651 Chapter 13 Forecasting Seasonal Time Series ERIC GHYSELS DENISE R. OSBORN AND PAULO . RODRIGUES 659 Abstract 660 Keywords 661 1. Introduction 662 2. Linear models 664 . SARIMA model 664 . Seasonally integrated model 666 Contents of Volume 1 xxi . Deterministic seasonality model 669 . Forecasting with misspecified seasonal models 672 . Seasonal cointegration 677 . Merging short-and long-run forecasts 681 3. Periodic models 683 . Overview of PAR models 683 . Modelling procedure 685 . Forecasting with univariate PAR models 686 . Forecasting with misspecified models 688 . Periodic cointegration 688 . Empirical forecast comparisons 690 4. Other specifications 691 . Nonlinear models 691 . Seasonality in variance 696 5. .
