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Stochastic Limit Theory: An Introduction for Econometricicans (Advanced Texts in Econometrics)
 
 

Stochastic Limit Theory: An Introduction for Econometricicans (Advanced Texts in Econometrics) [Paperback]

James Davidson (Author)
4.7 out of 5 stars  See all reviews (3 customer reviews)

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Book Description

0198774036 978-0198774037 December 8, 1994
This major new econometrics text surveys recent developments in the rapidly expanding field of asymptotic distribution theory, with a special emphasis on the problems of time dependence and heterogeneity. Designed for econometricians and advanced students with limited mathematical training, the book clearly lays out the necessary math and probability theory and uses numerous examples to make its data useful and comprehensible. It also includes original new material from Davidson's own research on central limit theorems.

About the Series
Advanced Texts in Econometrics is a distinguished and rapidly expanding series in which leading econometricians assess recent developments in such areas as stochastic probability, panel and time series data analysis, modeling, and cointegration. In both hardback and affordable paperback, each volume explains the nature and applicability of a topic in greater depth than possible in introductory textbooks or single journal articles. Each definitive work is formatted to be as accessible and convenient for those who are not familiar with the detailed primary literature.

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Editorial Reviews

Review


"An excellent text."--W.G. Park, Assistant Professor of Economics, American University


"The chapters on the law of large numbers are superb. This book lays the foundation for serious econometrics. I wish I had spent a year studying it before graduate school. Well done!"--Henry Thompson, Auburn University


About the Author

James Davidson is at University of Wales, Aberystwyth.

Product Details

  • Paperback: 568 pages
  • Publisher: Oxford University Press, USA (December 8, 1994)
  • Language: English
  • ISBN-10: 0198774036
  • ISBN-13: 978-0198774037
  • Product Dimensions: 9.2 x 6.1 x 1.2 inches
  • Shipping Weight: 1.7 pounds (View shipping rates and policies)
  • Average Customer Review: 4.7 out of 5 stars  See all reviews (3 customer reviews)
  • Amazon Best Sellers Rank: #1,122,980 in Books (See Top 100 in Books)

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Average Customer Review
4.7 out of 5 stars (3 customer reviews)
 
 
 
 
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10 of 10 people found the following review helpful:
4.0 out of 5 stars Get ready for a hard time, September 13, 2005
This review is from: Stochastic Limit Theory: An Introduction for Econometricicans (Advanced Texts in Econometrics) (Paperback)
Yes, I know it's a standard game of reviewers to show off by describing books as "a good introduction", implying one's capability of easily absorbing the material.

I shall try to judge the book by its stated mission, viz. to be an "introduction for econometricians". In my view it isn't, the material doesn't resemble much of what you are likely to have encountered in your econometrics education. If anything it is a course in applied measure theory. I should add that I don't know how the original sources look like (e.g. Billingsley), perhaps they're even worse. I just don't see where the book is supposed to be tailored to the background and needs of econometricians (with the exception of convergence to stochastic integrals at the very end, relevant for unit root econometrics etc.). Motivation and relevant examples (e.g. links to econometrics which one might reasonably expect in view of the title) are scarce, or to put it in Davidson's words, they occur on a set with measure zero. The book is thus extremely terse. It's Theorem - Proof - Corollary at its best. The back cover even recommends the book to business econometricians also (whatever that may be). This must be a marketing gag by the publisher, as far as I can judge the business world.

On the other hand it is quite self contained, which means most concepts you need in the later parts of the book are developed (if briefly) in the introductory chapters. Davidson frequently helps you with the task of understanding the proofs (which cover an estimated 2/3 of the book) by referring you to the relevant places.

It is only fair to acknowledge that Davidson does a remarkable job of explaining the material rigorously, but just don't be fooled by the title. It's hard work, you have to spend time on each word and (there is a lot more of that obviously) (in)equality.

Happily, it's worth it. Once you're through this, some of these obscure appendices in Econometrica may at last become more accessible to you. (The converse also holds: if you have never been interested in the details of the proofs save your money.)
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5.0 out of 5 stars Fantastic introductdory reference book, August 12, 2007
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G. Calhoun (Ames, IA United States) - See all my reviews
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This review is from: Stochastic Limit Theory: An Introduction for Econometricicans (Advanced Texts in Econometrics) (Paperback)
As another reviewer noted, there are absolutely no "real world" examples in this book. But that's not really the point. This book covers many of the theorems and techniques you would need to prove asymptotic results for time series, and I refer to it almost daily. The book would be extremely difficult for someone who hasn't taken a graduate sequence in econometrics or had similar mathematical preparation.

It's the first book I look at when I want to understand the details of a concept (mixing, for example), and I wish that Davidson had included some more topics that are related to my current research... that combination should make this an ideal introductory book, even though the material is inherently difficult.
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1 of 6 people found the following review helpful:
5.0 out of 5 stars Stochastic limit theory for beginners, June 8, 2005
By 
Vito (London, UK) - See all my reviews
This review is from: Stochastic Limit Theory: An Introduction for Econometricicans (Advanced Texts in Econometrics) (Paperback)
This is a very good book on stochastics as it covers a lot of advanced topics in detail. I particularly found helpful the coverage of weak convergence. If you want to master the realm of stochastic processes, this could be a great place to start.
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