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 in a single volume a range of contrasting approaches and views. Uniquely surveying forecasting in a single volume, the Companion provides a comprehensive account of the leading approaches and modeling strategies that are routinely employed.
Arvustused
"A Companion to Economic Forecasting offers an insightful and authoritative overview of the diverse issues, methods, and applications falling under the broad umbrella of economic and financial forecasting. It belongs on every practitioner's bookshelf, and on every student's reading list." Francis X. Diebold, University of Pennsylvania "Economic forecasting methods, models, applications, evaluation, and diagnostics, all in one encompassing volume by leaders in the field. This collection of lucid chapters defines where economic forecasting is today. An invaluable addition to the library of anyone working with economic data." Charles Nelson, University of Washington
List of Contributors. Preface. Acknowledgments.
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 Onkal-Atay, Mary E. Thomson and
Andrew C. Pollock.
7. Forecasting for Policy: Adrian R. Pagan and John
Robertson.
8. Forecasting Cointegrated VARMA Processes: Helmut Lutkepohl.
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: Oyvind Eitrheim, Tore Anders Husebo, 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 Terasvirta.
22. Forecasting Financial Variables: Terence
C. Mills.
23. Explaining Forecast Failure in Macroeconomics: Michael P.
Clements and David F. Hendry. Author Index. Subject Index
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.
