Rating: 
Summary: An excellent bridge to advanced econometrics
Review: As an economist,before taking PhD lectures, I used to think that this book was too complicated. It is not for undergraduate students. Once you acquire some level in mathematics, this book becomes the best reference for time series econometricians. It covers a wide array of themes, the text is clear and understandable, even if, from time to time, you get lost in the mathematical explanations (but it's not the usual). I particularly liked the non-stationary chapters. The spectral analysis is a little bit confusing and there is no non-parametric section. I think this is one of the best books in the field. Mathematicians will find it extremely clear and graduate economists understandable. "Time series Analysis" it's an unavoidable book for those seeking to understand specialised papers.
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Summary: The most careful ecmtx textbook I know
Review: As you may guess from the title, I loved Hamilton's book. I must definitely disagree with all those who find it too technical. Rather on the contrary, I would say. Admittedly, entire pages with greek letters look intimidating at first glance. But what Hamilton actually does is making a huge effort (unlike most of his competitors) to actually explain the details of the derivations, thereby helping the reader a lot. You'll learn to appreciate this a lot by the time you start developing sth. on your own rather than simply applying existing techniques.
By now, I've been through most of the chapters and I'm yet to find a typo, let alone a major mistake. Whenever I wanted to learn sth. about Time Series Analysis, Hamilton provided a good starting point, if not more.
I am waiting for the second edition!
Rating:
Summary: the best book in time series econometrics
Review: gives details on all areas of time series econometrics. the best overall book i know of in this subject.
Rating:
Summary: A good reference book
Review: I bought it as a reference book since it contains a lot of materials. It lacks details on some new materials, such as, GARCH model. It also has less real life example explaining the use of the methodology as the usual statistics books do. This makes difficult for reader to judge the usefulness of the material he is not familiar with.
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Summary: this book rules
Review: I bought this book when i studied econometrics in grad school. now i work at an investment bank, and i use the book practically every day. the derivations (which rely solely on calculus and linear algebra) are always clear, and most of the subjects are covered thoroughly but concisely. using this book, for example, i learned gmm in one day and implemented it on the next day. moreover, most of the chapters are self-contained (if you already know a bit about regression analysis), so you won't have to read a bunch of preliminary stuff before you get to what you need to learn.btw, the author seems like a nice guy, too. one time, i had a question about his treatment of the kalman filter, and he actually responded to my email.
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Summary: Quite some beach read
Review: I got this book at the beginning of the summer and have been reading it everyday by the pool. This is not to say that you can read it mindlessly - you definitely can not - it is simply so interesting that every time I try to decide what to bring to the pool I would magically turn down Cosmo and Vogue and drag Hamilton along instead. As a rising junior in econonomics and mathematics at Duke, I find this book challenging yet doable. I have previously had an undergraduate course in econometrics and this book answers a lot of the questions I was casually wondering about when I took the class. One more thing I love about this book is that it is vey self-contained. I have a solid background in matrix algebra but not nearly enough in probability (only one undergrad course); I do not so far find it a problem at all. I recommend this book to everyone who liked his/her first econometrics course, even if you are an undergrad.
Rating: 
Summary: Should not be your first look at time series analysis
Review: I used this book for a financial econmetrics class and would not recommend it unless you actually know a bit about time series analysis. The math is not too bad for someone with an engineering/physics background, but there isn't much about application or context and there are few worked examples of anything. The problems don't seem too instructive and are included almost as an afterthought. The book pretty much assumes you know what you're doing and need to see all the details.
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Summary: Not mathematically rigorous enough
Review: If you're coming to time series without a fairly strong background, this is not the book. Others are much more comprehensible as introductory texts, even I think at the graduate level. If you are working in time series and need a great reference book, it's indispensable. Nobody else comes close in comprehensiveness.
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Summary: Excellent book in the right hands
Review: If you're coming to time series without a fairly strong background, this is not the book. Others are much more comprehensible as introductory texts, even I think at the graduate level. If you are working in time series and need a great reference book, it's indispensable. Nobody else comes close in comprehensiveness.
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Summary: Great for Math PhD's but Useless for Everyone Else
Review: This book assumes that the reader already has a Ph.D. in math. As a student, this book fails to do a good job explaining the material covered and makes too many assumptions about what the reader knows.
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