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Rating: 
Summary: a good source for quick references
Review: I agree with other reviewers - it's a great book, but I just wanted to add a few comments. The book is well organized and covers many results in asymptotics of linear regression model. The book is also very compact and gets you directly to the point. If you compare it, for example, with "Stochastic Limit Theory" by Davidson, which is the great book by the way, in the last one you have to go through 300 of pages of mathematics and probability background before you get to stochastic convergence. But a large number of results were left without a proof and the author provides references to other books instead, so if you want to go more deeply into the topic you would need another 3-4 books to read with it (or to get Davidson's book). Also, a few very important results for asymptotics of linear regression has not been mentioned. For example, "persistence excitation" result (Lai, Robbins and Wei, 1978) was not mentioned, which is strange, because it can be very useful for proving strong consistency of LS estimators and in many cases is much easier to apply than LLN.
Rating:
Summary: A must-have.
Review: This book is a must-have for serious econometrics students who want to specialize in asymptotic theory. But the price of this book is an outrage (...). The publisher should really consider publishing a paperback version to make it more affordable. I also recommend Davidson's Stochastic Limit Theory and Billingsley's Convergence of Probability Measures.
Rating:
Summary: A must-have.
Review: This book is a must-have for serious econometrics students who want to specialize in asymptotic theory. But the price of this book is an outrage (...). The publisher should really consider publishing a paperback version to make it more affordable. I also recommend Davidson's Stochastic Limit Theory and Billingsley's Convergence of Probability Measures.
Rating:
Summary: The best introduction on Asymptotic Theory for Econometrics
Review: This book provides the basics of asymptotic theory for linear econometric models. It presents very clearly the classical assumptions concerning linear models, and shows the implications from them. Then, it relaxes each assumption, and compares the results with those obtained previously. This makes the book very readable and understandable. Of course, the reader is required to have taken a course in Econometrics, and should be used to matrix notation. I strongly recommend this book for those who wish to deepen their undertanding on Econometric Theory. I think this is the first book to be read. The exercises are proposed in the body of the text and should be solved before going on, because in fact they are part of the text. The solution is in the end of the book.
Rating:
Summary: A very useful resource
Review: This is a must-have for economists who do any work with theoretical econometrics. It is the kind of book I wish I had when I was a graduate student in economics. It provides kind of a theoretical backing to books like Greene and updates the more difficult to read econometrics texts of long ago like Theil. White starts out easy (easy if you do econometrics, that is). The linear model and the consequences of violating the basic assumptions. But from the basic beginning, the book goes far and seems to focus on those issues I consider to be most important (and things I didn't get first time around). And it takes you up to the "cutting edge." Too often, things like Laws of Large Numbers and Central Limit Theory are thrown at you like a tool that you must accept. But reading White's book helps you understand why these things work the way they do. I found this helpful. One more thing: Solutions in the back! perhaps this will start a trend. Some of the items might be difficult if you haven't had a bit of analysis or your understanding of applied econometrics isn't too good. But I guess if you pick up something called "Asympotic Theory" you know what you are getting into. I enjoyed it.
Rating:
Summary: A very useful resource
Review: This is a must-have for economists who do any work with theoretical econometrics. It is the kind of book I wish I had when I was a graduate student in economics. It provides kind of a theoretical backing to books like Greene and updates the more difficult to read econometrics texts of long ago like Theil. White starts out easy (easy if you do econometrics, that is). The linear model and the consequences of violating the basic assumptions. But from the basic beginning, the book goes far and seems to focus on those issues I consider to be most important (and things I didn't get first time around). And it takes you up to the "cutting edge." Too often, things like Laws of Large Numbers and Central Limit Theory are thrown at you like a tool that you must accept. But reading White's book helps you understand why these things work the way they do. I found this helpful. One more thing: Solutions in the back! perhaps this will start a trend. Some of the items might be difficult if you haven't had a bit of analysis or your understanding of applied econometrics isn't too good. But I guess if you pick up something called "Asympotic Theory" you know what you are getting into. I enjoyed it.
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