Ebook A Guide to Econometrics - 4th Edition
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A Guide to Econometrics - 4th Edition
Ebook A Guide to Econometrics - 4th Edition
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Review
"Peter Kennedy's book, which provides intuitive, narrative explanations for a wide range of topics covered in undergraduate and graduate econometrics courses, occupies a unique position in the econometrics textbook market." —David Ribar, Department of Economics, the George Washington University
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About the Author
The late Peter E. Kennedy was Professor Emeritus of Economics at Simon Fraser University.
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Product details
Paperback: 468 pages
Publisher: The MIT Press; 4 edition (May 8, 1998)
Language: English
ISBN-10: 9780262611404
ISBN-13: 978-0262611404
ASIN: 0262611406
Product Dimensions:
6.2 x 1.2 x 9 inches
Shipping Weight: 1.4 pounds
Average Customer Review:
4.8 out of 5 stars
13 customer reviews
Amazon Best Sellers Rank:
#1,249,651 in Books (See Top 100 in Books)
Buy it. You need it. Stop waiting.For an actual econometric theory text, use Hayashi.Both of these together, along with Kleiber "Applied Econometrics with R," will set you up for really understanding what's going on. Kennedy's emphasis on understanding the sampling distribution of an estimator and laying the groundwork for the basic properties of estimators are fundamental concepts to understand econometric theory and practice.
Kennedy's Guide to Econometrics explains econometrics more clearly than any other book I have read. This book will not make you into an econometrician. But, this is definitely the place to start your education on empirical methods in economics.For a book of this size, he covers a lot of territory. He covers the CLR model and hypothesis testing well, and discusses a few other things too. This guide is hardly encyclopedic. However, it covers the things economists need to know most.Kennedy does more than just explain econometrics. He spells out the limits of econometric analysis. Texts often pay little attention to the 'con in econometrics'. Not Kennedy. He discusses the limitations and defects in standard techniques, as well as their advantages.The only thing wrong with this book is that it does not carry the reader along far enough. After reading this book, most reader's will likely move on to a standard (i.e. badly written) econometrics textbook. In contrast, this book is written so well that it almost makes learning econometrics fun!
Used this book in my advanced stats doctoral course and I enjoyed the content. It is always helpful to have multiple resources to explain a concept for you. Stats can be difficult, but regression is worse!
Very helpful Infomation for a statistical mathematician and economists who want to really understand what is going on in economics.
This is the fourth edition of a very popular text for an introductory graduate level course in econometrics. Although designed for econometricians and economics majors, the book has a lot to offer the statistician (time series analyst). There is good coverage of both the classical econometric models and the classical ARIMA time series models. The difference, as Kennedy points out, is that most univariate statistical time series models use only the past history to model and forecast the future while the econometric models emphasize the inclusion of economic predictor variables and not the past history.However, in recent years, and partly because in fair-fight forecasting competitions the Box-Jenkins time series methods have done better than the econometric models, the econometricians are beginning to incorporate the Box-Jenkins approach in their models. As Kennedy points out,the new theory of multivariate ARIMA models is providing the econometricians with a methodology that is similar to their simultaneous equation models.One nice feature of the book is that it treats classical linear regression theory early, highlights the key assumptions and then provides specific chapters that cover how to deal with the violations of the assumptions taken one by one.The book is clear, up-to-date and has an excellent bibliography. It introduces the structural econometric time series approach along with multivariate Box-Jenkins methodolgy. Advanced topics such as dealing with roots on the unit circle in Box-Jenkins models and cointegration are covered. Also robust estimation procedures are discussed. It even introduces bootstrap methodology and the Bayesian approach to inference.There is some coverage and some warnings about neural networks. Models for count data, duration, linear structural equations and instrumental variables are all presented in an introductory way.Emphasis is placed early on the concept of sampling distributions for estimators. A clear understanding of sampling distributions is essential to understanding classical frequentist statistical approaches. Much confusion can arise when these concepts are glossed over.
I have tried three econometrics textbooks so far (Johnston and DiNardo, Hayashi and Greene) but this is the only one that I can read without having a headache. This is because aside from its technical contents, it also contains lots of anecdotes that make it a pleasure to read. From this book, I could presume that Prof. Kennedy is not only a great researcher but an excellent teacher too. Even the answers to selected problems are explained thoroughly and clearly. Besides, the price is so affordable. Nevertheless, I would prefer to see the geometry of least squares than the Ballantine-Venn diagram utilized in the book. I also agree that GMM should be included in the subsequent editions.
Although it is not necessary to introduce once again a book that is already this well known, I can say that this "guide" has helped me to understand better some fundamental ideas and techniques of econometrics. It should be read before starting with the "books" on econometrics like Greene or Johnston. Like the title says, the book is only a guide, so further study is necessary for a completer understanding. Although the guide is compact and well written, the structure can sometimes be confusing. Because every topic is divided into an introduction, general notes and technical notes, you will have to read a little bit everywhere to get to know everythhing about a certain topic. I suggest you read through it all. I definitely recommend it to everybody who wants to study or teach econometrics.
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