A Guide to Econometrics, 5th Edition 5th Edition

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ISBN-13: 978-0262611831
ISBN-10: 026261183X
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Editorial Reviews


Peter Kennedy's A Guide to Econometrics is a superb text. I first used it as a student, and now I find it indispensable as a professor. I would not dream of teaching an econometrics course without it.

(Lisa A. Keister, Department of Sociology, The Ohio State University)

A Guide to Econometrics is an excellent book that is, or at least should be, essential reading for all undergraduate and graduate students with an interest in the subject, as well as scholars engaged in applied econometric work.

(Anders Olofsgård, Georgetown University)

This revised version is a worthy successor to the fourth edition, which was already the most useful applied econometrics book on the market. It is an excellent complement to standard econometrics textbooks, which tend to be heavy on mathematics and technique, and light on practical advice.

(T.H. Gindling, Department of Economics, University of Maryland Baltimore County)

This has been an excellent book in the past and the revisions for the fifth edition include some new subjects and bring the material up to date. The text is clearly written and shows the author's excellent understanding of the material covered. And his clever insights and witty comments make the book fun to read.

(Jan Kmenta, Professor Emeritus of Economics, University of Michigan)


"Peter Kennedy's Guide to Econometrics is a superb text. I first used it as a student, and now I find it indispensable as a professor. I would not dream of teaching an econometrics course without it." --Lisa A. Keister, Department of Sociology, The Ohio State University --This text refers to an out of print or unavailable edition of this title.

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Product Details

  • Paperback: 500 pages
  • Publisher: The MIT Press; 5th edition (August 1, 2003)
  • Language: English
  • ISBN-10: 026261183X
  • ISBN-13: 978-0262611831
  • Product Dimensions: 6 x 1.5 x 9 inches
  • Shipping Weight: 1.9 pounds (View shipping rates and policies)
  • Average Customer Review: 4.6 out of 5 stars  See all reviews (49 customer reviews)
  • Amazon Best Sellers Rank: #674,695 in Books (See Top 100 in Books)

Customer Reviews

Most Helpful Customer Reviews

53 of 57 people found the following review helpful By Dr. Lee D. Carlson HALL OF FAMEVINE VOICE on April 14, 2006
Format: Paperback Verified Purchase
Econometrics is now a respectable topic, both in the financial industry, where it is used extensively, and in academia. Like most efforts to model phenomena in the real world, especially those that attempt to model the behavior of human agents, econometrics has had its share of critics. These critics pointed out some of the failures of the econometric models, and some of their criticism was justified. However, there have been successes as well, if one realizes that the success of a model should be determined by what a model is actually developed for.

The author of this book is fully aware of what modeling is all about, and gives a very interesting overview of the major mathematical techniques used in econometrics. He characterizes econometrics as a study of how to obtain a good estimator in a situation or problem at hand that must be estimated. He recognizes that any criteria for what is "good" is somewhat subjective, but a "good" estimator it is generally believed must be computationally cost effective, unbiased, efficient, and robust. The author gives detailed discussions of these criteria in the book, and throughout most of the book more detailed mathematical derivations take place in the notes at the end of each chapter. The discussions can be a bit wordy at times in places outside of the notes for this reason. The book includes of course discussions on least squares, nonlinear regression, and Bayesian estimation of parameters. These are all topics that are fairly standard in the literature, but the author also includes discussions on topics such as neural networks and kernel estimation. An extensive list of exercises is included at the end of the book.
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28 of 29 people found the following review helpful By not a natural on November 2, 2009
Format: Paperback Verified Purchase
Throughout the 1970's, big-name sociologists with impeccable methodological and statistical credentials sought to persuade the discipline's journeymen that they should learn econometrics. The two most influential proponents of this view were the social statistics luminaries Hubert Blalock and Otis Dudley Duncan. Blalock was more optimistic than Duncan with regard to the ultimate payoff, but Duncan was more arrogantly dismissive of those who failed to heed his admonition.

In response, sociology and related social science journals became much more densely quantitative. Many social scientists, as a result, felt as if they had been reduced to obslescence. After all, econometrics and the other new quantitative tools, especially path analysis, which had come to dominate the discipline were difficult topics under the best of circumstances, and most social scientists lacked the mathematical training to tackle the best known econometrics texts, such as those by Jack Johnston, Jan Kmenta, and Arthur Goldberger. Many social scientists had been introduced to the econometrics mainstay, regression analysis, but not in this highly technical form.

Fortunately, the decade of the '70's also saw publication of Damodar Gujarati's introductory econometrics text, as well as the first edition of Peter Kennedy's Guide to Econometrics. Gujarati's book presented much the same material as his more insistently mathematical colleagues, but in a much more accessible form. His book could actually be used for self-instructional purposes, enabling less methodologically astute social scientists to finally figure out what was going on.
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22 of 23 people found the following review helpful By nels_tomlinson@mgmt.purdue.edu on December 13, 1997
Format: Paperback
This book doesn't pretend to be a text. It answers the questions a text usually doesn't: like how does it all fit together? and what do we do when our assumptions don't hold? The author points out that econometrics texts are usually "cookbooks", and aim to tell you how to use their collection of receipes. This book explains the assumptions behind regression, and what happens when we violate them, and what we can do about it. It also gives a good overview of the topic. This book shows the connection between the receipes in a text. It doesn't pretend to teach econometrics, so the reader isn't innundated with equations. Instead, you get a discussion of why you would want to do (or not do) the things your text would teach you. Anyone who is taking an econometrics course (graduate or undergraduate) should get this book. After reading a chapter in your text, read the corresponding chapter in Kennedy to add some depth to your understanding.
I would also suggest this to graduate students who are facing preliminary or comprehensive exams in econometrics. This will help you to "bring it all together", and answer those vague, conceptual questions which seem to cause the most grief. The book has sufficient references to the literature so that you can easily follow up anything you want to explore in more depth, but it's clear and self-contained enough that only an econometrician is likely to feel the need. Each chapter is organized in three parts: a discussion of the topic, an appendix of long footnotes which add details which would obstruct the flow of the discussion, and finally, a technical appendix, where you can find a few of those equations if you really want them. This makes it easy to read the book at the level you need.
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