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Klappentext 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. *Addresses economic forecasting methodology! forecasting models! forecasting with different data structures! and the applications of forecasting methods *Insights within this volume can be applied to economics! finance and marketing disciplines Zusammenfassung Covers developments in how forecasts are constructed based on multivariate time-series models! dynamic factor models! nonlinear models and combination methods. This handbook addresses economic forecasting methodology! forecasting models! forecasting with different data structures! and the applications of forecasting methods. Inhaltsverzeichnis Part 1. Forecasting methodology. 1. Bayesian forecasting (J. Geweke, C. Whiteman). 2. Forecasting and decision theory (C.W.J.Granger, M.J. Machina). 3. Forecast evaluation (K.D. West). 4. Forecast combinations (A. Timmermann). 5. Predictive density evaluation (V. Corradi, N.R. Swanson). Part 2. Forecasting models. 6. Forecasting with VARMA models (H. Lutkepohl). 7. Forecasting with unobserved components time series models (A. Harvey). 8. Forecasting economic variables with nonlinear models (T. Terasvirta). 9. Approximate nonlinear forecasting models (H. White). Part 3. Forecasting with different data structures. 10. Forecasting with many predictors (J.H. Stock, M.W. Watson). 11. Forecasting with trending data (G. Elliott). 12. Forecasting with breaks (M.P. Clements, D.F. Hendry). 13. Forecasting seasonal time series (E. Ghysels, D.R. Osborn, P.M.M. Rodrigues). 14. Survey expectations (M.H. Pesaran, M. Weale). Part 4. Applications of forecasting methods. 15.Volatility and correlation forecasting (T.G. Andersen, T. Bollerslev, P.F. Christoffersen, F.X. Diebold). 16. Leading Indicators (M. Marcellino). 17. Forecasting with real-time macroeconomic data (D. Croushore). 18. Forecasting in marketing (P.H. Franses)....
List of contents
Part 1. Forecasting methodology.
1. Bayesian forecasting (J. Geweke, C. Whiteman).
2. Forecasting and decision theory (C.W.J.Granger, M.J. Machina).
3. Forecast evaluation (K.D. West).
4. Forecast combinations (A. Timmermann).
5. Predictive density evaluation (V. Corradi, N.R. Swanson).
Part 2. Forecasting models.
6. Forecasting with VARMA models (H. Lutkepohl).
7. Forecasting with unobserved components time series models (A. Harvey).
8. Forecasting economic variables with nonlinear models (T. Terasvirta).
9. Approximate nonlinear forecasting models (H. White).
Part 3. Forecasting with different data structures.
10. Forecasting with many predictors (J.H. Stock, M.W. Watson).
11. Forecasting with trending data (G. Elliott).
12. Forecasting with breaks (M.P. Clements, D.F. Hendry).
13. Forecasting seasonal time series (E. Ghysels, D.R. Osborn, P.M.M. Rodrigues).
14. Survey expectations (M.H. Pesaran, M. Weale).
Part 4. Applications of forecasting methods.
15.Volatility and correlation forecasting (T.G. Andersen, T. Bollerslev, P.F. Christoffersen, F.X. Diebold).
16. Leading Indicators (M. Marcellino).
17. Forecasting with real-time macroeconomic data (D. Croushore).
18. Forecasting in marketing (P.H. Franses).
