This text prepares first-year graduate students and advanced undergraduates for empirical research in economics, and also equips them for specialization in econometric theory, business, and sociology.
A Course in Econometrics is likely to be the text most thoroughly attuned to the needs of your students. Derived from the course taught by Arthur S. Goldberger at the University of Wisconsin–Madison and at Stanford University, it is specifically designed for use over two semesters, offers students the most thorough grounding in introductory statistical inference, and offers a substantial amount of interpretive material. The text brims with insights, strikes a balance between rigor and intuition, and provokes students to form their own critical opinions.
A Course in Econometrics thoroughly covers the fundamentals—classical regression and simultaneous equations—and offers clear and logical explorations of asymptotic theory and nonlinear regression. To accommodate students with various levels of preparation, the text opens with a thorough review of statistical concepts and methods, then proceeds to the regression model and its variants. Bold subheadings introduce and highlight key concepts throughout each chapter.
Each chapter concludes with a set of exercises specifically designed to reinforce and extend the material covered. Many of the exercises include real microdata analyses, and all are ideally suited to use as homework and test questions.
This book is an excellent choice for first year graduate econometrics courses because it provides a solid foundation in statistical reasoning in a manner that is both clear and concise. It addresses a number of issues that are of central importance to developing practitioners and theorists alike and achieves this in a fairly nontechnical manner… The topics addressed here are rarely given such a thorough treatment in econometrics textbooks. For example, in discussions of bivariate distributions, Goldberger points out that two uncorrelated normal random variables may not be independent, since a nonnormal bivariate distribution can generate normal marginal distributions. Other texts typically leave readers with the impression that two uncorrelated normal random variables are independent without reference to their joint distribution… A Course in Econometrics is rigorous, it makes students think hard about important issues, and it avoids a cookbook approach. For these reasons, I strongly recommend it as a basic text for all first year graduate econometrics courses.
[A Course in Econometrics] strike[s] the right balance between mathematical rigour and intuitive feel. It aims to prepare students for empirical research but also those who go on to more advanced econometrics… The book is very clear and very precise. It is built on just a few very simple concepts. I think that students will like it very much. I congratulate Professor Goldberger with having written a very useful book.
Undoubtedly the best Ph.D. level econometrics textbook available today. The analogy principle of estimation serves to unify the treatment of a wide range of topics that are at the foundation of empirical economics. The notation is concise and consistently used throughout the text… Students have expressed delight in unraveling the proofs and lemmas. It’s a pleasure to teach from this book. Recommended for any serious economics student or anyone interested in studying the principles underlying applied economics.
- 432 pages
- 1 x 6-1/8 x 9-1/4 inches
- Harvard University Press
From this author
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