- Hardcover: 460 pages
- Publisher: South-Western College Pub; 3rd edition edition (Sep 19 2003)
- Language: English
- ISBN-10: 0324163827
- ISBN-13: 978-0324163827
- Product Dimensions: 24.6 x 18.8 x 2.2 cm
- Shipping Weight: 839 g
- Average Customer Review: 1.0 out of 5 stars See all reviews (2 customer reviews)
- Amazon Bestsellers Rank: #596,770 in Books (See Top 100 in Books)
- See Complete Table of Contents
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Product Details |
Product Description
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 alternate Hardcover edition.
"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 alternate Hardcover edition.
Book Description
Written by a leading expert on forecasting, this concise, modern survey of business and economic forecasting methods is intentionally selective and focuses only on the core techniques with the widest applicability. Assuming readers have a limited background in statistics, the book is extremely applications oriented and illustrates all methods with detailed real-world applications - many of them international in flavor - that reflect typical forecasting situations in todayÂ's global marketplace. Offering a practical blend of traditional and contemporary topics, Elements of Forecasting, 3e covers trend, seasonality and cycles, as well as more modern topics such as model selection, volatility models, unit roots and stochastic trends, vector autoregressions and cointegration. It devotes full chapters to volatility, statistical graphics, and evaluating and combining forecasts.
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Most helpful customer reviews
1 of 1 people found the following review helpful
1.0 out of 5 stars
an embarrassingly slapdash and sloppy book,
By Ronald Michener "williamdouglass" (Charlottesville, VA United States) - See all my reviews (REAL NAME)
This review is from: Elements of Forecasting with Disk (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.
1.0 out of 5 stars
Third edition is no better,
By Ronald Michener "williamdouglass" (Charlottesville, VA United States) - See all my reviews (REAL NAME)
This review is from: Elements of Forecasting with Economic Applications (Hardcover)
I posted the unfavorable review of the second edition. I have recently had an opportunity to see the third edition, and find the same errors are still present.
Share your thoughts with other customers: Create your own review
Most Helpful Customer Reviews on Amazon.com (beta) Amazon.com:
3.3 out of 5 stars (7 customer reviews) 33 of 36 people found the following review helpful
1.0 out of 5 stars
an embarrassingly slapdash and sloppy book,
By Ronald Michener "williamdouglass" - Published on Amazon.com
This review is from: Elements of Forecasting with Disk (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. 13 of 16 people found the following review helpful
5.0 out of 5 stars
Excellent introductory guide to forecasting !!!,
By lawong@mbox3.singnet.com.sg - Published on Amazon.com
This review is from: Elements of Forecasting (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.
8 of 10 people found the following review helpful
1.0 out of 5 stars
Third edition is no better,
By Ronald Michener "williamdouglass" - Published on Amazon.com
This review is from: Elements of Forecasting with Economic Applications (Hardcover)
I posted the unfavorable review of the second edition. I have recently had an opportunity to see the third edition, and find the same errors are still present.
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