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.
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'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
Book 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 which 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 which have hitherto lacked a scientific foundation.
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19 of 22 people found the following review helpful:
5.0 out of 5 stars
Good strategies for macro economic forecasting,
By A Customer
This review is from: Forecasting Economic Time Series (Paperback)
This is a unique text that treats economic time series forecasting with emphasis on the recent advances in econometric theory such as cointegration as well as other practical strategies such as combination forecasts. Usual text books do not have the breadth of coverage this one attempts, successfully, to achieve. In short, this one text replaces many books and papers on one's shelf.
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Inside This Book
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First Sentence:
Our objective is to develop an econometric theory applicable to macroeconomic forecasting. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
comparing mean squared forecast errors, intercept corrections, assessing forecast accuracy, rival forecasts, forecast encompassing tests, intercept correcting, model evaluation techniques, cointegrating combinations, parameter estimation uncertainty, forecast origin, empirical econometric models, cointegrating space, progressive research strategy, mean stationarity, forecast confidence intervals, variance formulae, econometric systems, forecast tests, antithetic pair, unconditional forecasts, correctly specified model, composite predictor, antithetic variates, zero forecast, forecast uncertainty Key Phrases - Capitalized Phrases (CAPs): (learn more)
Monte Carlo, Central Statistical Office, Macroeconomic Modelling Bureau, Mean Variance New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Our objective is to develop an econometric theory applicable to macroeconomic forecasting. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
comparing mean squared forecast errors, intercept corrections, assessing forecast accuracy, rival forecasts, forecast encompassing tests, intercept correcting, model evaluation techniques, cointegrating combinations, parameter estimation uncertainty, forecast origin, empirical econometric models, cointegrating space, progressive research strategy, mean stationarity, forecast confidence intervals, variance formulae, econometric systems, forecast tests, antithetic pair, unconditional forecasts, correctly specified model, composite predictor, antithetic variates, zero forecast, forecast uncertainty Key Phrases - Capitalized Phrases (CAPs): (learn more)
Monte Carlo, Central Statistical Office, Macroeconomic Modelling Bureau, Mean Variance New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Citations (learn more)
This book cites 47
books:
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35
books
cite this book:
See all 35 books citing this book
- Econometrics and Quantitative Economics by David F. Hendry in Back Matter (1), and Back Matter (2)
- Economic Trends December 2003 (No. 601) by Office for National Statistics in Back Matter (1), and Back Matter (2)
- Money, Inflation and Employment: Essays in Honour of James Ball by Sean Holly in Front Matter, and Back Matter
- Contributions to Operations Research and Economics (papers, 1987) by Bernard Cornet in Back Matter
- Econometric Models and Methods by Carl F. Christ in Back Matter
See all 47 books this book cites
- A Companion to Economic Forecasting (Blackwell Companions to Contemporary Economics) by Michael P. Clements on 12 pages
- Practical Business Forecasting by Michael K. Evans on page 5, page 159, and page 273
- Econometric Modelling: Techniques and Applications (National Institute of Economic and Social Research Economic and Social Studies) by Sean Holly on page 35, and page 36
- An Introduction to Time Series Analysis and Forecasting: With Applications of SAS® and SPSS® by Robert A. Yaffee on page 102, and page 266
- Nonlinear Time Series Analysis of Business Cycles, Volume 276 (Contributions to Economic Analysis) by Costas Milas on page 172, and page 245
See all 35 books citing this book
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