Econometrics

Econometrics has many useful features and covers all the important topics in econometrics in a succinct manner. All the estimation techniques that could possibly be taught in a first-year graduate course, except maximum likelihood, are treated as special cases of GMM (generalized methods of moments). Maximum likelihood estimators for a variety of models (such as probit and tobit) are collected in a separate chapter. This arrangement enables students to learn various estimation techniques in an efficient manner. Eight of the ten chapters include a serious empirical application drawn from labor economics, industrial organization, domestic and international finance, and macroeconomics. These empirical exercises at the end of each chapter provide students a hands-on experience applying the techniques covered in the chapter. The exposition is rigorous yet accessible to students who have a working knowledge of very basic linear algebra and probability theory. All the results are stated as propositions, so that students can see the points of the discussion and also the conditions under which those results hold. Most propositions are proved in the text.

For those who intend to write a thesis on applied topics, the empirical applications of the book are a good way to learn how to conduct empirical research. For the theoretically inclined, the no-compromise treatment of the basic techniques is a good preparation for more advanced theory courses.

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All Customer Reviews
Average Customer Review:
0 of 0 people found the following review helpful:

Excelent Econometrics Book, 2008-03-27
Great book for advanced undergrad and grad students. Personally, I think this book is as good as the Greene, but much cheaper.


20 of 20 people found the following review helpful:

Solid basis for econometric analysis, 2006-04-02
I have a love/hate relationship with this book. Perhaps I should state as a precursor that I was never formally trained in economics before learning econometrics. And, that the last time I'd done matrix algebra or calculus was some 15 years prior.

We used this book as part of a taught graduate course. It took half a semester to go through the first two chapters - an investment of time that proved well worth it for the rest of the topics which were covered in the remainder of the semester.

Basically, if you can understand the first two chapters on ordinary least square regression for finite and large samples, the required assumptions and properties, then the rest of the chapters are a piece of cake:
- generalized method of moments for single and multiple equations
- panel data
- time series analysis (including unit root analysis)
- extremum estimators
- maximum likelihood
- cointegration.

In short, the book covers all major econometrics topics and does so in a succinct, clear manner. The way in which Hayashi builds on each topic, showing that all models are basically different versions of the same method, with slightly different assumptions is just brilliant. It put statistics in a different light for me, and gave me a much deeper, intuitive understanding of it than any other book or class had done before.

There is a caveat however. This book assumes that you have substantial mathematical grounding. In particular, I found the succinct use of notation, without any verbal explanation, irritating at first. I invested quite some time in a mathematical economics book reminding myself what sets were, rules of matrices, calculus functions, expectations and probability.

Without the support and input of our brilliant teacher who (very patiently) took us through the end of chapter exercises step-by-step, I would never have managed to successfully read this book on my own! While those exercises honed my skills and deepened my understanding, I relied heavily on Hayashi's home page notes and hints to complete them.

For those of you that have strong mathematical skills and an economic background, this book is probably one of the best introductions to econometrics. For those of you who do not, it will prove to be a difficult read at best.

What's certain is that after succesfully completing it, your econometrics and statistical skills will provide a solid enough basis for any graduate program.






5 of 6 people found the following review helpful:

Helps you to become a complete econometrician, 2005-07-24
Yes, indeed I also think this one is the best around. Some points I'd add are:

Hayashi's book is the only econometrics textbook I am aware of (IMHO, these are certainly not all, but quite a few) that is truly complete. Not only from a material point of view - it covers both time series and cross section material in a unified framework (as opposed to Wooldridge). The empirical exercises are useful (outperforming, say, Davidson/MacKinnon) and yet you can also go on to read theoretical papers or Amemiya after having read Hayashi's coverage of asymptotic properties of GMM and M estimators. Finally, also more towards the theoretical side, it provides some first training in hands-on programming, as opposed to some books that tell you where to click in eViews.

Furthermore:

- A corollary of the above comments is of course that it's not very detailed in each of the fields covered. E.g., all you find on limited dependent variables is Probit, Logit, Tobit.
- It's well managed: the typo list (which isn't very long, I should emphasize, especially for a 1st ed.) is always up to date
- The typsetting really is debatable. I find it unpleasant to have italics, boldface, boldface italics, verbatim environments etc all on one page. Less is more.


2 of 4 people found the following review helpful:

The best choice, 2005-07-16
Mr. Hayashi has written an excelent textbook, which has become the standard in PhD programs as far as I know. I agree with other recomendants that Hayashi has been original to explain econometrics from a newer and more efficient point of view. But there is more: Hayashi has devoted a lot of effort to create exercises to teach students instead of contributing to some professor's questions data bank.


12 of 14 people found the following review helpful:

A modern and unusal approach, 2005-01-27
This is a fine book, but probably not the one you want to buy if you are looking for ONE all-encompassing reference. The approach is interesting, but unusual, with all the pros and cons that come with originality. It is for graduate students, or very advanced undergraduates, as it requires quite a lot of previous knowledge of linear algebra and statistics.
What is unusual about this book is that it covers most topics within a unifying Generalized Method of Moments (GMM) framework. Many many estimators are treated as special cases of GMM. The book is clear, and the notation is mostly OK, even if the chapters on panel data and systems of simultaneous equations are a notational nightmare, partly because of the choice of treating everything in a GMM framework. Another unusual aspect of this book is the emphasis on certain regularity conditions (such as ergodicity) that are usually used in a time-series framework, but are not commonly seen in cross-section analysis. I studied (also) on this book as a graduate student, and overall I liked it. The only real minus are the exercises, which contain so many hints that they become trivial (really, I am not a genius...). Worse, they only require mindless application of linear algebra.

One UNimporant cons of this book is the fact that (cover aside) it is... ugly! How could the publisher choose the boring "Times New Roman" font for this book!? But this, of course, does not really matter....

Overall, a useful and good book, but if you are looking for ONE textbook in cross-section econometrics Wooldridge is probably a better choice, and if what you are looking for is ONE book in time series, Hamilton is likely to be what you want on your shelf.

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