Hayashi's Econometrics promises to be the next great synthesis of modern econometrics. It introduces first year Ph.D. students to standard graduate econometrics material from a modern perspective. It covers all the standard material necessary for understanding the principal techniques of econometrics from ordinary least squares through cointegration. The book is also distinctive in developing both time-series and cross-section analysis fully, giving the reader a unified framework for understanding and integrating results.
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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The best introductory book to Graduate Linear Econometric Models and a Fair Treatment of ARIMA models... It is very logical without the use of much words which really speeds up learning.. I have tried a lot of textbooks that are way pricier and I think this is the best although you might wish to try something a little less terse if you background with linear algebra or basic statistics is lacking. His presentation and outline of the book is very methodological and exceptionally well documented with mathematical logic and where need be proofs and the mathematical operator for "therefore" and "because". I went straight from Johnston and DiNardo to this book without any problems at all. It is a good reference even for third course in Econometrics or fourth course in Econometrics where you have to contrast large sample asymptotic assumptions to those of GARCH ARCH ARIMA models etc.
A really good book, both for empirical and theoretical guys. Seriously.
2 LargeSample Theory
3 SingleEquation GMM
4 MultipleEquation GMM
5 Panel Data
6 Serial Correlation
7 Extremum Estimators