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
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ix | |
| Preface |
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xi | |
| Acknowledgments |
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xiii | |
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An Overview of Economic Forecasting |
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1 | (18) |
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Predictable Uncertainty in Economic Forecasting |
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19 | (26) |
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Density Forecasting: A Survey |
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45 | (24) |
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Statistical Approaches to Modeling and Forecasting Time Series |
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69 | (36) |
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Forecasting with Structural Time-Series Models |
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105 | (28) |
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133 | (19) |
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152 | (27) |
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Forecasting Cointegrated VARMA Processes |
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179 | (27) |
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206 | (16) |
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The Rationality and Efficiency of Individuals' Forecasts |
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222 | (19) |
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Decision-Based Methods for Forecast Evaluation |
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241 | (27) |
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Forecast Combination and Encompassing |
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268 | (16) |
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Testing Forecast Accuracy |
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284 | (15) |
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Inference About Predictive Ability |
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299 | (23) |
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Forecasting Competitions: Their Role in Improving Forecasting Practice and Research |
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322 | (32) |
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Empirical Comparisons of Inflation Models' Forecast Accuracy |
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354 | (32) |
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The Forecasting Performance of the OECD Composite Leading Indicators for France, Germany, Italy, and the U.K. |
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386 | (23) |
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Unit-Root Versus Deterministic Representations of Seasonality for Forecasting |
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409 | (23) |
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Forecasting with Periodic Autoregressive Time-Series Models |
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432 | (21) |
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Nonlinear Models and Forecasting |
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453 | (32) |
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Forecasting with Smooth Transition Autoregressive Models |
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485 | (25) |
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Forecasting Financial Variables |
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510 | (29) |
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Explaining Forecast Failure in Macroeconomics |
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539 | (33) |
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| Author Index |
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572 | (11) |
| Subject Index |
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583 | |
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.
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