Customer Reviews

An Introduction to Classical Econometric Theory

5 star:		(4)
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1 star:		(1)

 

 

I have just completed reading Professor Ruud's textbook from cover to cover. It is the clearest, most insightful graduate-level econometrics book I have read. Whereas many texts seem to be compendiums of theorems and proofs with little in the way of explanation, Ruud takes the time to explain things thoroughly. At over 800 pages, however, Ruud's book is never verbose. A good explanation takes time, but Ruud never takes more time than is needed. Yet, in addition to all concepts being thoroughly explained, they are introduced with practical examples, and--what is most amazing--the proofs are built up systematically in such a way that you can actually read though them and be enlightened rather than convinced.

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.

This is the best text I have encountered for an advanced graduate text in econometrics. The style is less terse than Amemiya, but Ruud does not skimp on content. There are many (useful) details, particularly on some subjects other authors assume (in my experience, incorrectly) the student knows. Finally, the geometric approach Ruud frequently espouses is somewhat unique in econometric presentation, and one I find quite useful.

Econometrics seemed to me a technically demanding subject with results that are either magic (stated without derivation) or based on some arcane mathematical tricks. But after reading Ruud's textbook, econometrics finally makes sense. It provides a great exposition of graduate econometrics with all the main results and techniques clearly spelled out. Furthermore, it actually has derivations of the results. I also really like the emphasis on the geometry behind econometrics; it provides a systematic approach and the results even become intuitive.

So, if you want more than just a recipe book and actually understand econometrics, read this book!

This is another good, modern textbook on parametric, cross-sectional econometrics (don't look for non/semi-parametric or time-series econometrics in here). It is, I think, in the same league as Wooldridge, which is however less technical and spends more time describing empirical applications. I think Ruud is a very nice addition to an econometric shelf. The notation is good, and the math/stat appendix is one of the best I have ever seen (the section on multivariate differentiation in particular is outstanding and very useful). Overall, if you want to have 3 *relatively* basic books on parametric cross-section econometrics, I think this is a good companion to Wooldridge and Cameron and Trivedi (a nice compendium of applied tools, which also includes some non-parametrics, for which the best introduction is likely Pagan and Ullah). If time-series is important to you, Hayashi is a good choice. As you may have guessed, I am not a big fan of Greene, which I do own but never look at.

I gave it a one-star to balance those biased 5 stars. The first part of the book is pretty good, intuitively explains what an OLS regression is really like geometrically. The second part of the book is just horrible. The author just goes on and on and on without being able to clearly explain the theories. The book is used in my program for one year and then stopped. Now we use Yamashi's book, which is much better.