- Hardcover: 896 pages
- Publisher: Oxford University Press; 1 edition (January 14, 1993)
- Language: English
- ISBN-10: 0195060113
- ISBN-13: 978-0195060119
- Product Dimensions: 9.6 x 2 x 6.4 inches
- Shipping Weight: 3 pounds (View shipping rates and policies)
- Average Customer Review: 11 customer reviews
- Amazon Best Sellers Rank: #879,829 in Books (See Top 100 in Books)
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Estimation and Inference in Econometrics 1st Edition
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"An important reference source for both the theoretical and applied researcher....More importantly, the authors' view of the areas presented is cohesive, and they provide an open-ended discussion, so that the book can serve as a source of research topics as well as a reference. From this
standpoint, it is very good reading for a doctoral student....Davidson and MacKinnon's book is sure to have an impact on the way econometrics is taught; my hope is that the geometric approach, widely and quite consistently used by the authors, will be adopted in the exposition of regression,
illustration of the classical test statistics, and examination of test power. Certainly, the tool of projection orthogonally to part of the regression space (the Frisch-Waugh-Lovell theorem) should be adopted more widely for its convenience in simplifying many derivations."--Econometric
"Well-written advanced textbook in econometrics, suitable for seminar courses. With its lucid analysis, it emerges as an extremely useful tool for applied econometricians."--Madhu Mohanty, California State University
"Clearly written and makes clear a lot of links between different estimation procedures."--Curtis J. Simon, Clemson University
"Good coverage of standard econometric theory."--M.M. Ali, University of Kentucky
"Coverage of the geometry of least squares is excellent."--Doug Steigerwald, University of California, Santa Barbara
"This is a unique and fascinating book. It's the only econometrics textbook that has ever given me the urge to read it from cover to cover."--Stratford Douglas, West Virginia University
"A wonderful text. The book is comprehensive and has a most authoritative discussion of topics of current interest such as cointegration, nonlinear simultaneous equation models, specification testing, etc."--Sunil Sapra, California State University at Los Angeles
"Great book! Good reference for anyone wishing to get an overview of the state of the art. Good pace, topic selection, level of difficulty. Also, good use of notation."--Dean Allen Schiffman, University of California, San Diego
"This is the most up-to-date econometrics textbook. It deals with topics which were so far discussed only in journal articles....A must book for any higher level graduate econometrics course."--Professor Anil K. Bera, University of Illinois
"Extremely valuable in the sense that it balances the coverage between test of hypothesis and estimation. Most books treat test of hypothesis as a side issue. The book is well-contained and easy to read. An excellent textbook."--Choon-Geol Moon, Rutgers University
From the Back Cover
Offering a unifying theoretical perspective not readily available in any other text, this innovative book uses simple geometrical arguments to develop students' intuitive understanding of basic and advanced topics in econometrics, emphasizing throughout the practical applications of modern theory and nonlinear techniques of estimation.
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I think I would have found the exposition here rather challenging had this been my initial text. A few comparisons between the two books:
H - GMM as organizing principle.
D&M - Least squares as organizing principle.
I think the latter was in many ways a more intuitive way of viewing these techniques (for me), but perhaps provides a less fully integrated view of the estimators.
H - Matrix algebra and first order conditions as justifying estimation techniques.
D&M - Geometric projection as justifying estimation techniques.
The geometry is a powerful tool for understanding these concepts, but I think serves me better as a complement rather than a primary motivator.
H - Treats homoskedasticity and lack of serial correlation as special cases.
D&M - Treats heteroskedasticity and serial correlation as extensions of iid models.
H - Treats nonlinear models as extensions.
D&M - Treats linear models as special cases.
H - Offers a large number of economic applications.
D&M - Basically entirely theoretical in its justification of theorems and techniques.
This would be among the most frustrating things about using D&M as a primary text.
Just a few thoughts that might be useful to someone considering this book. The organization around least squares is very useful, I think, and a geometric intuition for econometrics must be a powerful tool as one progresses in the field.
Overall the book is very well written and relatively easy to understand, considering its subject. However, if you have not been introduced to linear econometrics, the book can become very hard, mainly if the reader is not acquainted with matrix algebra.
The first chapter on the geometrics of regression is simply marvelous, although a better picture is in Ruud's.
The style is someway formal, but different from the traditional lemma-theorem-proof-corollary way. This makes the book easier to read.
Future improvements include:
a. More examples (please);
b. Make the early 2 chapters on asymptotics clearer;
c. Extend the GMM approach interconnecting it with other chapters (it's more general);
d. Put exercises, with solutions, with selected solutions, whatever, but exercises, including computational ones;
e. Some economics - this does not mean applications per se, but it means to explain where and why such techniques are necessary in the real world.
There is no one like this.
The only problem is the way the contents are presented. There is no a logical order that help us in a course. I agree that there is not a clear structured inside the chapters or in the entire work. But this is the book that reach the deepest point being readable. Another books are better structured or more intutive but too superficial or old-fashioned.
With the modern computers and software the old classical books based on small sample theory are unsuitable. Davidson and MacKinnon point us to the econometry of the future.
It would be a good idea to combine this book with Berndt's one on applied econometrics, plus a good software like Stata 8 or matrix-based programming software like MATLAB.
That's the best way to access the econometry.
Davidson and MacKinnon is different. Both expositions and explanations are clear and easy to follow. I was so delighted after picking up a copy from the libarary. This is the one econometrics students should have. The price is also hard to beat. The reason I think it is not widely adopted is because of the geometric analysis of regression (Chapter 2). But if you don't like geometrics, you can simply skip it.
An improved version of this book is just published under the new title "Econometric Theory and Methods". This new version contains a chapter on unit-root and cointegration, as well as some new numerical methods. I urge interested buyers to take a look at the new version.