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Forecasting Economic Time Series

Paperback / softback

Main Details

Title Forecasting Economic Time Series
Authors and Contributors      By (author) Michael Clements
By (author) David Hendry
Physical Properties
Format:Paperback / softback
Pages:392
Dimensions(mm): Height 229,Width 152
Category/GenreEconometrics
Economic forecasting
ISBN/Barcode 9780521634809
ClassificationsDewey:330.0112
Audience
Professional & Vocational
Illustrations 43 Tables, unspecified

Publishing Details

Publisher Cambridge University Press
Imprint Cambridge University Press
Publication Date 8 October 1998
Publication Country United Kingdom

Description

David Hendry is one of the world's leading econometricians, and in this major new work he and Michael Clements provide an extended formal analysis of economic forecasting with econometric models: their analysis builds in many of the features of the real world that are often overlooked in traditional, textbook analyses of forecasting. Consequently, Clements and Hendry are able to suggest ways in which existing forecasting practices can be improved, as well as providing a rationale for some of the habitual practices of forecasters that have hitherto lacked a scientific foundation.

Reviews

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