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.
Michael P. Clements is Professor of
Economics at the University of Warwick. His research interests include econometric
modelling and forecasting, with recent publications in the areas of forecast evaluation,
the analysis of high frequency data and mixed data frequency models, real-time vintage
data, and survey expectations. He currently serves as an editor of the International
Journal of Forecasting.
David F. Hendry is a Fellow of
Nuffield College and Professor of Economics, University of Oxford (Chairman, 2001-2007).
He was Knighted in 2009, and holds seven Honorary Doctorates. He is an Honorary
Vice-President and past President, Royal Economic Society; Fellow, British Academy, Royal
Society of Edinburgh, Econometric Society, and Journal of Econometrics; Foreign Honorary
Member, American Economic Association and American Academy of Arts and Sciences; and an
Honorary Fellow, International Institute of Forecasters. He is listed by the ISI as one of
the world's 200 most cited economists, and has published more than 200 papers and 14 books
on econometric methods, theory, modelling, and history; numerical techniques and
computing; empirical economics; and both nowcasting and forecasting.
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
624 pages, Hardcover