SUMARY: 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).