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on 14 January 2004
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. (page numbers refer to the second US edition.) In the US, the book is now in its third edition, and the mistakes STILL have not been corrected. 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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on 22 November 2010
This is the kind of book you read and you think "gosh I must be really slow, because I can't understand a thing"!

The sentences are long, the grammar is convoluted, the wording isn't simple, and there are many errors and sloppy ommissions as per other reviews.

Shame because this could be an excellent book with some proper editing, proof-reading and fixing the obvious mistakes. However it just drifts from one edition to another with none of this being done.
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on 3 November 2012
Not the most fun book in the world but is useful to get an idea of forecasting. I would not recommend this to anyone who has not studied econometrics or at least stats in the past but if you have it is a useful starting point to learn from. The learning style is easy but a bit too wordy for me while the example data and questions are very useful to get a grip on the subject.
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on 10 January 2013
I am pretty satisfied. It is a clean and new book. There is no sign inside the book.
Thank you very much!
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