- Hardcover: 976 pages
- Publisher: Oxford University Press; 1 edition (March 23, 2000)
- Language: English
- ISBN-10: 0195111648
- ISBN-13: 978-0195111644
- Product Dimensions: 9.4 x 1.7 x 7.6 inches
- Shipping Weight: 4.2 pounds (View shipping rates and policies)
- Average Customer Review: 5 customer reviews
- Amazon Best Sellers Rank: #1,433,182 in Books (See Top 100 in Books)
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An Introduction to Classical Econometric Theory 1st Edition
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"A number of interesting topics found here are common in backroom talk but are not as easily found treated systematically as they are here."--David A. Belsley, Boston College
"The author provides an elegant, unified presentation of the material which forms the core of econometrics."--Richard T. Carson, University of California, San Diego
"Ruud is a fine scholar and he is well known as an outstanding teacher. His pedagogical style is certainly evident in the book."--Francis X. Diebold, New York University
"This book fills an important need for a clear and precise graduate textbook in econometrics. Its theoretical discussions are first rate and it includes nice empirical examples, making it a useful resource for any graduate student."--Whitney Newey, Massachusetts Institute of Technology
"This book has the same breadth of coverage as competing texts, with remarkably clear and compelling explanations and motivation of the theoretical concepts."--James L. Powell, University of California, Berkeley
"Paul Ruud's text combines clarity with rigor and is an excellent text for students and professionals alike. The strengths are apparent in every chapter. The author consistently tackles problems in more depth than any other text on the market."--Douglas Steigerwald, University of California,
"The book covers least squares, methods of moments (GMM), and maximum likelihood which are three major frameworks for estimation and inference. Within the subset of chapters relating to each major topic, the key results are developed and given due prominence and subsequently used in further
developments."--Pravin K. Trivedi, Indiana University
"This textbook is rigorous yet accessible. I believe it is destined to become the standard against which all other econometrics textbooks will be measured. Superb!"--Dr. James J. Jozefowicz, Indiana University of Pennsylvania
About the Author
Paul A. Ruud is at University of California, Berkeley.
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Previous econometrics texts have a "Losing sight of the forest for the trees" sort of feel to them. Ruud's text, however, works like the old drill Seargent in the Kipling poem who explained his teaching method as "Firsts I tells 'em what I'ms goings to tells em; then I tells 'em; and then I tells 'em what's I tolds 'em." Ruud does this by first building up the fundamental concept of matrix projection. Then he demonstrates how that can be used to explain Ordinary Least Squares regression. Then he adds onto that all the common assumptions: independent, identically distributed errors; normality of the errors, etc. He builds things up one assumption at a time. And all the while he tells you what he's doing and why the content of each chapter matters and how it is related to what has come before and to what will come afterwards.
But, then--in a master stroke of pedagogy--he tears it all down. He starts taking away, one at a time, all the assumptions like normality that he just spent chapters building up and shows how econometricians deal with matters when they *do* in fact remove the standard assumptions. In this way he can introduce consistent estimators, non-linear regression, latent variables, and so on as what they were historically: practical solutions needed when the assumptions of the classical model fail to hold.
By systematically showing which assumptions imply which results and then showing how to deal with things when a given assumption fails to hold, Ruud's book produces a better econometrician. Too often have previous books left previous readers unable to really understand the art of data analysis, which involves taking a data set, seeing what assumptions can be fairly made about it, and then analyzing it given those fairly made assumptions.
Professor Ruud deserves many plaudits for writing what will surely become the standard text for the next generation of graduate students.