This Handbook provides up-to-date coverage of both new and well-established fields in the sphere of economic forecasting. The chapters are written by world experts in their respective fields, and provide authoritative yet accessible accounts of the key concepts, subject matter, and techniques in a number of diverse but related areas. It covers the ways in which the availability of ever more plentiful data and computational power have been used in forecasting, in terms of the frequency of observations, the number of variables, and the use of multiple data vintages. Greater data availability has been coupled with developments in statistical theory and economic analysis to allow more elaborate and complicated models to be entertained; the volume provides explanations and critiques of these developments. These include factor models, DSGE models, restricted vector autoregressions, and non-linear models, as well as models for handling data observed at mixed frequencies, high-frequency data, multiple data vintages, methods for forecasting when there are structural breaks, and how breaks might be forecast. Also covered are areas which are less commonly associated with economic forecasting, such as climate change, health economics, long-horizon growth forecasting, and political elections. Econometric forecasting has important contributions to make in these areas along with how their developments inform the mainstream.

Table of Contents:
Introduction, Michael Clements and David Hendry Part 1. Forecasting models and methods 1. VARs, cointegration and common cycle restrictions, Heather Anderson and Farshid Vahid 2. Dynamic factor models, James Stock and Mark Watson 3. Forecasting with non-linear models, Anders Kock and Timo Teräsvirta 4. Forecasting with DSGE models, Kai Christoffel, Günter Coenen and Anders Warne 5. Unobserved components, Siem Jan Koopman and Marius Ooms 6. Judgmental forecasting, Paul Goodwin, Dilek Önkal and Michael Lawrence Part 2. Data issues 7. Nowcasting, Marta Banbura, Domenico Giannone and Lucrezia Reichlin 8. Forecasting with mixed-frequency data, Elena Andreou, Eric Ghysels and Andros Kourtellos 9. Forecasting with real-time data vintages, Dean Croushore Part 3. Forecasting and structural breaks 10. Forecasting and structural breaks, Michael Clements and David Hendry 11. Forecasting breaks and forecasting during breaks, Jennifer Castle, David Hendry, and Nicholas Fawcett 12. Forecast combination, Marco Aiolfi, Carlos Capistrán and Allan Timmermann Part 4. Forecast evaluation 13. Multiple forecast model evaluation, Valentina Corradi and Walter Distaso 14. Testing for unconditional predictive ability, Todd Clark and Michael McCracken 15. Testing for conditional predictive ability, Raffaella Giacomini 16. Interpreting and Combining Heterogeneous Survey Forecasts, Charles Manski 17. Use and Evaluation of Panels of Forecasts, Antony Davies, Kajal Lahiri and Xuguang Sheng Part 5. Financial forecasting 18. Forecasting Financial Time Series, Terence Mills 19. Volatility Forecasting Using High Frequency Data, Peter Hansen and Asger Lunde Part 6. Special interest areas 20. Economic value of weather and climate forecasts, Richard Katz and Jeff Lazo 21. Long-horizon growth forecasting and demography, Thomas Lindh 22. Energy market forecasting, Derek Bunn and Nektaria Karakatsani 23 Models for health care, Andrew Jones 24 Political and election forecasting, Michael Lewis-Beck and Charles Tien 25 Marketing & sales, Philip-Hans Franses