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Elements of Forecasting Paperback – September 2, 1997

ISBN-13: 978-0538862448 ISBN-10: 0538862440 Edition: 1st

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Product Details

  • Paperback: 392 pages
  • Publisher: Cengage Learning; 1 edition (September 2, 1997)
  • Language: English
  • ISBN-10: 0538862440
  • ISBN-13: 978-0538862448
  • Product Dimensions: 0.8 x 7.5 x 9.5 inches
  • Shipping Weight: 1.8 pounds
  • Average Customer Review: 3.6 out of 5 stars  See all reviews (11 customer reviews)
  • Amazon Best Sellers Rank: #2,357,999 in Books (See Top 100 in Books)

Editorial Reviews

Review

"The text is excellent from instructor's perspective. It is focused and comprehensive. The text is empirically oriented. It covers major issues of time-series econometrics at the undergraduate level. Including several comprehensive applications is a unique and outstanding feature of this book."

"I will adopt the new edition. Coverage and organization of the book are excellent and focused on the student while giving many pointers and references to advanced material and even current research."

"The strength of the Diebold text is that it covers sufficiently diverse topics related to forecasting methods (compared with other books in the market). Also, its nicely organized flow of the topics should be very accessible to many readers, which is the primary reason why I assigned this book to my students." --This text refers to an out of print or unavailable edition of this title.

About the Author

Francis X. Diebold is William Polk Carey Professor of Economics, and Professor of Finance and Statistics, at the University of Pennsylvania and its Wharton School, and Faculty Research Associate at the National Bureau of Economic Research in Cambridge, Mass. He is a leader in forecasting, econometrics, risk management, quantitative finance, and macroeconomics, with extensive experience simultaneously in academic, corporate, and policy circles. Dr. Diebold has published more than one hundred articles and ten books and edited volumes. He has received widespread recognition for his work, including election to Fellowship in the Econometric Society, Sloan and Guggenheim Fellowships, and election to advisory and editorial boards of numerous leading journals, including Econometrica and Review of Economics and Statistics. Dr. Diebold is equally active in corporate and policy affairs, and he is consulted regularly by financial firms, governments and multilateral organizations, worldwide. His latest book is Measuring and Forecasting Financial Market Volatilities and Correlations. Dr. Diebold is a popular lecturer, both in the U.S. and internationally. He has held visiting appointments in Economics and Finance at Princeton University, Cambridge University, the University of Chicago, the London School of Economics, and New York University. He is also active in executive education; his ongoing annual courses include those at the International Monetary Fund (Washington, DC) and FAME (Geneva). He has received several prizes for outstanding teaching. Dr. Diebold received his B.S. from the Wharton School in 1981 and his Ph.D. in 1986. Before returning to the University of Pennsylvania in 1989, he worked as an economist under Paul Volcker and Alan Greenspan at the Board of Governors of the Federal Reserve System in Washington DC. He is married with three children and lives in Wayne, Pennsylvania.

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Customer Reviews

3.6 out of 5 stars
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Most Helpful Customer Reviews

43 of 49 people found the following review helpful By Ronald Michener on September 27, 2002
Format: Hardcover
There were a considerable number of errors in the first edition that I pointed out to the author shortly after its publication. The second edition seems to have corrected few if any of them. Let me cite two egregious examples.
In the chapter on ARMA models, the example analyzed is Canadian Employment data. One of the models that is fit is an MA(4) -- see pages 164-6. When I tried to reproduce these results using software other than EVIEWS, using the data disk in the 1st edition, I couldn't. I contacted EVIEWS and they discovered a programming error in the estimation routine. They released a patch to fix EVIEWS. However, the author never re-estimated his model, and the estimates in the second edition are the same as in the first. However, my copy of the 2nd edition has no data disk! Was that thought to be an adequate solution?!
Chapter 9 ("Putting it all together") is a capstone chapter that analyzes liquor sales data using the techniques introduced in earlier chapters. After several pages (pp. 207-19) a model is selected. On pages 220-2, the residuals are examined using the Box-Ljung statistic, and deemed acceptable. However, as a careful examination of table 9.6 makes clear, the p-values for the Box-Ljung statistic were computed as if the input data were a raw series. The model generating the residuals (p. 219) had 3 autoregressive terms! This changes the d.f. in the chi-square distribution of the statistic. If you make the appropriate correction using the data in table 9.6, and compute the p-values correctly, you will see that the model residuals apparently ARE NOT white noise. One reason is a calendar effect in liquor sales: months that contain more than a usual number of Fridays and Saturdays result in more liquor sales; ones with more Sundays result in lower liquor sales. However, the author doesn't discover this, but accepts his inappropriate model on the basis of faulty distribution theory.
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13 of 16 people found the following review helpful By lawong@mbox3.singnet.com.sg on January 25, 1999
Format: Paperback
The use of practical examples (using the Eviews software) and the availability of a data disk makes this a very relevant guide for practitioners. There is a good section on graphical analysis and modelling of cycles using AR and MA processes. The mathematics is kept simple and clear, intuitive explanations are given throughout. The treatment of unit roots, cointegration and other advanced materials is quite sketchy but I guess that is to be expected in an introductory text. With the level of clarity evident throughout this book, I certainty hope Diebold follows up with another book on more advanced forecasting techniques.
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2 of 2 people found the following review helpful By Sebastian Krynski on January 3, 2007
Format: Hardcover
The book starts with talking about forecasting deterministic trends, then seasonalities, later chapters 6,7,8 talk about forecasting cycles. Finally in the end chapters the author puts it all together and talks about multivariable forecasting models. The book is on an introductory level, so if you're looking for indepth discussion of these topics this is not for you. Anoter drawback is that this book does not integrate into its discussion of the topics any examples of code that would show how to forecast with any popular software package (Eviews or SAS).
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11 of 16 people found the following review helpful By John on November 26, 1999
Format: Paperback
If the purpose of using this book is to get a brief idea of what certain concepts are then it is a good book. Unfortunately, many people using this book are going to be those who do not have much background with the concepts inside and they will be looking for clearer explanations of what the author is talking about. I think that is the book's weakness: the fact that many times I didn't feel that his definitions and explanations were complete enough.
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By jeydutra on February 18, 2014
Format: Hardcover Verified Purchase
I purchased the book for ECON 716 at The University of Kansas.
It is very didactic, very pedagogical , goes with you not only through the calculus, but also the reason behind them. Very good to get started into more serious time-series forecasting. However, too limited for advanced users. It serves its purpose as an introductory to intermediate book for time-series.
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By Blackdawn on July 11, 2013
Format: Hardcover Verified Purchase
I used this for one of my masters classes, it was decent. Came on time and in good condition which is always nice
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