Part 1. Forecasting methodology. <br>1. Bayesian forecasting (J. Geweke, C. Whiteman). <br><br>2. Forecasting and decision theory (C.W.J.Granger, M.J. Machina). <br><br>3. Forecast evaluation (K.D. West). <br><br>4. Forecast combinations (A. Timmermann). <br><br>5. Predictive density evaluation (V. Corradi, N.R. Swanson).<br><br>Part 2. Forecasting models. <br>6. Forecasting with VARMA models (H. Lutkepohl).<br><br>7. Forecasting with unobserved components time series models (A. Harvey).<br><br>8. Forecasting economic variables with nonlinear models (T. Terasvirta).<br><br>9. Approximate nonlinear forecasting models (H. White). <br><br>Part 3. Forecasting with different data structures. <br>10. Forecasting with many predictors (J.H. Stock, M.W. Watson).<br><br>11. Forecasting with trending data (G. Elliott). <br><br>12. Forecasting with breaks (M.P. Clements, D.F. Hendry). <br><br>13. Forecasting seasonal time series (E. Ghysels, D.R. Osborn, P.M.M. Rodrigues).<br><br>14. Survey expectations (M.H. Pesaran, M. Weale). <br><br>Part 4. Applications of forecasting methods. <br>15.Volatility and correlation forecasting (T.G. Andersen, T. Bollerslev, P.F. Christoffersen, F.X. Diebold).<br><br>16. Leading Indicators (M. Marcellino). <br><br>17. Forecasting with real-time macroeconomic data (D. Croushore).<br><br>18. Forecasting in marketing (P.H. Franses).