- Hardcover: 820 pages
- Publisher: Princeton University Press; 1 edition (January 11, 1994)
- Language: English
- ISBN-10: 0691042896
- ISBN-13: 978-0691042893
- Product Dimensions: 7 x 2.2 x 10.1 inches
- Shipping Weight: 3.6 pounds (View shipping rates and policies)
- Average Customer Review: 48 customer reviews
- Amazon Best Sellers Rank: #119,798 in Books (See Top 100 in Books)
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Time Series Analysis 1st Edition
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"A carefully prepared and well written book. . . . Without doubt, it can be recommended as a very valuable encyclopedia and textbook for a reader who is looking for a mainly theoretical textbook which combines traditional time series analysis with a review of recent research areas."--Journal of Economics
From the Inside Flap
"I am extremely enthusiastic about this book. I think it will quickly become a classic. Like Sargent's and Varian's texts, it will be a centerpiece of the core cirriculum for graduate students."--John H. Cochrane, University of Chicago
Top customer reviews
This is a great book. Given that it has 799 pages, you must expect a lot of detail, and none of it is fluff. Not only are the procedures for constructing every kind of time series spelled out completely, but several times the author points out potential pitfalls and gives tips and tricks for circumventing them. One of them worked for me in another context and meant the difference success and failure in that project. Another benefit of the abundant detail is that, while there are recipes for each time series type, they are not written as a series of steps, but in paragraphs of detailed text. The result is you tend to understand the material, rather than just mindlessly carrying out a series of instructions. People have performed near miracles with maximum likelihood estimators, and this book tells you how it is done.
Obviously, the book is long, but another Amazon reviewer wrote that he knew exactly what kind of time series he needed, found the instructions to build it in the text, and was done in a day. Because the book has been carefully divided into chapters, sections, and sub-sections, all with clear titles and sub-titles, it is relatively quick and easy to find something, if you know what you need.
There are more recent books for sale at Amazon that claim to contain the results of the latest research on multivariate time series. While this book contains material on multivariate problems, it is presented only as an extension of single-variable situations (in what I have read; I have not finished the book). Since it is hard to avoid having several variables in a complex time series, you may want to consider the newer material.
It was an amazing purchase (suggested by my lecturer of "Time Series and Forecasting")
that can work both as a learning book and as reference. Despite its (indeed not small !) size,
I am still amazed by how many contents the author managed to cover, always with good depth.
It is a technical book, no doubts about it, and requires the reader to have a good
familiarity with the basic mathematical tools and a certain pleasure in using them.
A reader interested only to the conceptual aspects of the field might find "Time Series Analysis"
challenging and might prefer other books that go in less depth into the mathematical
foundations of the subject.
"Time Series Analysis" by Hamilton is definitely a master reference for the entire field.
Despite being 20 years old, it covers all the tools and concepts that are widely used
in econometrics nowadays, being still very up-to-date. A recommended purchase.
I would definitely not start out into econometrics with this book though. You probably will not be able to appreciate how good this book is until you have tried to read something as atrocious as Greene.
As is typical with almost every upper level econometrics book, it assumes you have a wide mathematical and statistical knowledge base that you may or may not have. I would not recommend it as a beginning graduate econometrics book but it is a great reintroduction to time series methods. I will say that I haven't found a single book yet in intermediate econometrics that I felt was written clearly or concisely.
Still, overall, this has been by far the best among the worst and I would highly recommend reading it to anyone who is beginning to study time series econometrics in some detail.