Forecasting economic time series
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Forecasting economic time series
Cambridge University Press, 1998
- : pbk
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Note
Includes bibliographical references (p. 339-358) and indexes
Description and Table of Contents
Description
This book provides a formal analysis of the models, procedures, and measures of economic forecasting with a view to improving forecasting practice. David Hendry and Michael Clements base the analyses on assumptions pertinent to the economies to be forecast, viz. a non-constant, evolving economic system, and econometric models whose form and structure are unknown a priori. The authors find that conclusions which can be established formally for constant-parameter stationary processes and correctly-specified models often do not hold when unrealistic assumptions are relaxed. Despite the difficulty of proceeding formally when models are mis-specified in unknown ways for non-stationary processes that are subject to structural breaks, Hendry and Clements show that significant insights can be gleaned. For example, a formal taxonomy of forecasting errors can be developed, the role of causal information clarified, intercept corrections re-established as a method for achieving robustness against forms of structural change, and measures of forecast accuracy re-interpreted.
Table of Contents
- 1. An introduction to economic forecasting
- 2. First principles
- 3. Evaluating forecast accuracy
- 4. Forecasting in univariate processes
- 5. Monte Carlo techniques
- 6. Forecasting in co-intergrated systems
- 7. Forecasting with large-scale macro-econometric models
- 8. A theory of intercept corrections: beyond mechanistic forecasts
- 9. Forecasting using leading indicators
- 10. Combining forecasts
- 11. Multi-step estimation
- 12. Parsimony
- 13. Testing forecast accuracy
- 14. Postscript.
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