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A Companion to Economic Forecasting


A Companion to Economic Forecasting provides an accessible and comprehensive account of recent developments in economic forecasting. Each of the chapters has been specially written by an expert in the field, bringing together a range of contrasting approaches and views. Forecasting is a practical venture, so many of the chapters are aimed at practitioners and nonspecialists.

This book surveys a field that has expanded rapidly in recent years. There are no other up-to-date treatments that survey forecasting in a single volume. The Companion provides a comprehensive account of the leading approaches and modeling strategies that are routinely employed. An extensive editorial overview places the contributions in context, and shows their interconnections and commonalities.

Michael P. Clements is a Reader in Economics at the University of Warwick. He is co-author with David Hendry of Forecasting Economic Time Series (1998) and Forecasting Non-stationary Economic Time Series (1999), and has published in academic journals on a variety of time-series econometrics topics.

David F. Hendry, Professor of Economics at Oxford University, is a past President and Honorary Vice-President of the Royal Economic Society, Fellow of the British Academy and Econometric Society, and a Foreign Honorary Member of both the American Academy of Arts and Sciences and the American Economic Association. He has published more than twenty books, as well as over 150 articles and papers on time-series econometrics, econometric modeling, economic forecasting, the history of econometrics, Monte Carlo methods, econometric computing and empirical applications.

List of Contributors.



1. An Overview of Economic Forecasting: Michael P. Clements and David H. Hendry.

2. Predictable Uncertainty in Economic Forecasting: Neil R. Ericsson.

3. Density Forecasting: A Survey: Anthony S. Tay and Kenneth F. Wallis.

4. Statistical Approaches to Modelling and Forecasting Time Series: Diego J. Pedregal and Peter C. Young.

5. Forecasting with Structural Time-Series Models: Tommaso Proietti.

6. Judgemental Forecasting: Dilek Önkal-Atay, Mary E. Thomson and Andrew C. Pollock.

7. Forecasting for Policy: Adrian R. Pagan and John Robertson.

8. Forecasting Cointegrated VARMA Processes: Helmut Lütkepohl.

9. Multi-Step Forecasting: Raj Bhansali.

10. The Rationality and Efficiency of Individuals’ Forecasts: Herman O. Stekler.

11. Decision-Theoretic Methods for Forecast Evaluation: M. Hashem Pesaran and Spyros Skouros.

12. Forecast Combination and Encompassing: Paul Newbold and David I. Harvey.

13. Testing Forecast Accuracy: Roberto S. Mariano.

14. Inference About Predictive Ability: Michael W. McCracken and Kenneth D. West.

15. Forecasting Competitions: Their Role in Improving Forecasting Practice and Research: Robert Fildes and Keith Ord.

16. Empirical Comparisons of Inflation Models' Forecast Accuracy: Øyvind Eitrheim, Tore Anders Husebø, and Ragnar Nymoen.

17. The Forecasting Performance of the OECD Composite Leading Indicators for France, Germany, Italy, and the UK: Gonzalo Camba-Mendez, George Kapetanios, Martin R. Weale and Richard J. Smith.

18. Unit Root Versus Deterministic Representations of Seasonality for Forecasting: Denise R. Osborn.

19. Forecasting with Periodic Autoregressive Time Series Models: Philip Hans Franses and Richard Paap.

20. Non-Linear Models and Forecasting: Ruey S. Tsay.

21. Forecasting with Smooth Transition Autoregressive Models: Stefan Lundbergh and Timo Teräsvirta.

22. Forecasting Financial Variables: Terence C. Mills.

23. Explaining Forecast Failure in Macroeconomics: Michael P. Clements and David F. Hendry.

Author Index.

Subject Index