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Elements of Econometrics: Second Edition, by Jan Kmenta
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This classic text has proven its worth in university classrooms and as a tool kit in research--selling over 40,000 copies in the United States and abroad in its first edition alone. Users have included undergraduate and graduate students of economics and business, and students and researchers in political science, sociology, and other fields where regression models and their extensions are relevant. The book has also served as a handy reference in the "real world" for people who need a clear and accurate explanation of techniques that are used in empirical research.
Throughout the book the emphasis is on simplification whenever possible, assuming the readers know college algebra and basic calculus. Jan Kmenta explains all methods within the simplest framework, and generalizations are presented as logical extensions of simple cases. And while a relatively high degree of rigor is preserved, every conflict between rigor and clarity is resolved in favor of the latter. Apart from its clear exposition, the book's strength lies in emphasizing the basic ideas rather than just presenting formulas to learn and rules to apply.
The book consists of two parts, which could be considered jointly or separately. Part one covers the basic elements of the theory of statistics and provides readers with a good understanding of the process of scientific generalization from incomplete information. Part two contains a thorough exposition of all basic econometric methods and includes some of the more recent developments in several areas.
As a textbook, Elements of Econometrics is intended for upper-level undergraduate and master's degree courses and may usefully serve as a supplement for traditional Ph.D. courses in econometrics. Researchers in the social sciences will find it an invaluable reference tool.
A solutions manual is also available for teachers who adopt the text for coursework.
Jan Kmenta is Professor Emeritus of Economics and Statistics, University of Michigan.
- Sales Rank: #942501 in Books
- Published on: 1997-09-10
- Original language: English
- Number of items: 1
- Dimensions: 9.00" h x 1.80" w x 6.00" l, 2.60 pounds
- Binding: Hardcover
- 800 pages
Most helpful customer reviews
3 of 3 people found the following review helpful.
An excellent reference but a very difficult read
By not a natural
I did an independent study in econometrics as a doctoral student in educational policy studies, and some of the readings were taken from the first edition of Kmenta's Elements of Econometrics. At the time, I recognized that Kmenta's text was long and difficult, but it was also clear that some topics that were simply unreadable in other econometric accounts, especially Jack Johnston's Econometric Methods, were presented with greater clarity and less mathematical density by Kmenta. For me, the fact that most of Kmenta's account did not require a working knowledge of matrix algebra was a definite plus.
That was thirty years ago, and I have since bought a copy of the second edition of Kmenta's book. No less demanding than the first edition, Kmenta's updated text remains comprehensive and wonderfully informative. As with the first edition, moreover, the second edition avoids undue reliance on matrix algebra.
I have learned, however, that for my purposes this book serves best as a reference. When I was having trouble understanding maximum likelihood methods for the estimation of regression coefficients, I turned to Kmenta and found an accessible explanation, as well as a graphical account that brought the notion of maximum likelihood to life, making it seem almost commonsensical. Similarly, when I struggled to learn why procedures such as tobit were useful as an antidote to certain forms of sample selection bias, I turned to Kemnta and found what I needed. This included a clearer understanding of just what sample selection bias means in this context.
I have read substantial chunks of Kmenta's book, but I doubt that I will ever sit down and undertake the daunting task of reading it from start to finish. Nevertheless, Kmenta's second edition occupies a conspicuous and important place on my book shelf precisely because it serves so usefully as a reference. For those of us who are often forced to work on or just beyond the borders of our readily available statistical knowledge, this text is well worth the price.
As an afterthought, I was recently gratified when Kmenta gave a very mixed, not particularly flattering review to Angrist and Pische's Mostly Harmless Econometrics. The title of the book is misleading, as is the subtitle ("An Empiricist's Companion"), inviting the reader to surmise that it is a general introduction to econometrics. As Kmenta makes clear in his review, this is definitely not the case. The book presupposes a good deal of econometric knowledge, and is narrowly focused on the work of labor economists. Kmenta also takes issue with some technical details.
1 of 1 people found the following review helpful.
Walks through proofs of basic concepts
By (d)avid
Previewing textbooks to teach my political science graduate students, I have noticed that econometrics textbooks generally fall into two broad categories:
1) Basic introductions that rely more heavily on examples than proofs
2) Books on advanced topics that provide proofs.
There are very few texts that provide proofs of basic econometric techniques. Kmenta's Elements of Econometrics is one of those few books. In roughly 700 pages, it provides a thorough introduction to linear regression and supports this introduction with exceptionally clear proofs. The book is far from exhaustive in the topics it covers and there are texts with better examples, but you will be hard pressed to find a text with a better presentation of the proofs underlying these foundational building blocks.
0 of 0 people found the following review helpful.
A Classic.
By PruneCandy
I had the fortune of taking two undergraduate statistics courses under Professor Kmenta just prior to his retirement at the University of Michigan. The first was a standard introductory statistics course for economics majors, the second a more advanced class for honors students. Of course, this was the text assigned for those courses.
Since then, I have read other Statistics textbooks, and few, if any, will provide you with a more fundamental understanding of what statistics is and how it works than "Elements of Econometrics".
As other reviewers have noted, this textbook may not be the best introduction to statistics for people without a solid mathematical background. But even if your mathematical skills are on the rusty side, if you are willing to put forth the effort, I think that you will find yourself well rewarded with a more profound knowledge of statistics than you will find elsewhere. If on the other hand, you are looking for a quick primer on how to do simple regressions, for example, then you may be better off looking elsewhere.
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