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Forecasting Economic Time Series


  • 43 tables
  • Page extent: 392 pages
  • Size: 228 x 152 mm
  • Weight: 0.57 kg

Library of Congress

  • Dewey number: 330/.01/12
  • Dewey version: 21
  • LC Classification: HB3730 .C555 1998
  • LC Subject headings:
    • Economic forecasting--Econometric models
    • Econometrics
    • Microeconomics

Library of Congress Record

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 (ISBN-13: 9780521634809 | ISBN-10: 0521634806)

DOI: 10.2277/0521634806

Manufactured on demand: supplied direct from the printer

 (Stock level updated: 16:52 GMT, 03 September 2015)


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.

• Professor Hendry is perhaps the most distinguished scholar in this field in the world • Clear, accessible and coherent exposition, based on Marshall Lectures • Important original research and analysis, with major policy implications


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.


'Perhaps one of the most appealing features of the book is the systematic way in which it outlines and uncovers problems in forecasting, lays out possible solutions, and uses Monte Carlo, theoretical and empirical evidence to assess the potential solutions. Another appealing feature is that beginning researchers who are generally interested in serious (empirical) scientific investigation can learn much from noting how Clements and Hendry uncover, assess, and examine important issues in the area of economic forecasting. A third feature worth noting is the plethora of insightful and detailed empirical and Monte Carlo evidence. Forecasting Economic Time Series not only elucidates in detailed fashion how to construct macroeconomic forecasts, but also contains many hints on how to construct good macroeconomic forecasts. This makes it a must for forecasters' Journal of the American Statistical Association

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