Introduction to Econometrics

Rating:
Summary: Give me Matrix Algebra!
Review: G.S. Maddala, who held the University Eminent Scholar Professorship in the Department of Economics at Ohio State University, was widely regarded as one of the professions most prolific and influential econometricians of the last forty years. Throughout the 1990s, Maddala was one of most often cited researchers, and he ranked among the top five most cited authors during the years 1988-1994, according to the Social Science Citation Index. His contributions to distributed lags, generalized least squares, panel data, and simultaneous equations have advanced the field tremendously.

Unfortunately, his "Introduction to Econometrics," now in its third edition, is, at best, a mediocre principles textbook. While his explanations of crucial ideas, such as least squares methodology, heteroskedasticity, or autocorrelation, are concise and extremely clear, a student who wants a more rigorous mathematical introduction to econometrics will be searching for another book. Linear algebra, which makes a number of proofs and tests far simpler and less burdensome to follow than calculus, is resigned to pages in the dark recesses of the appendix. Although these incidentals are well written, they remain peripheral, when they should be the focus of any undergraduate econometrics textbook.

To its credit, Maddala's text does an excellent job of explaining concepts and problems in plain English, which would do well to supplement a purely mathematical approach. The book is full of techniques and tricks that might be helpful to reduce problems of serial correlation and heteroskedasticity, and the later chapters do a very good job of introducing students to more advanced topics, such as panel data analysis and vector autoregression. Nevertheless, the book's treatment of time-series analysis is scattered and atrocious, and many students will find themselves searching for other texts especially for information on this area.

For students who do not mind a bit of mathematical simplicity and would rather seek to grasp the general ideas behind linear regression and its difficulties, G.S. Maddala's "Introduction to Econometrics" should be a good read. Yet, for students who want to pursue their knowledge of econometrics further, this book will most likely not be very helpful. As many courses taught at an undergraduate level tend to vary on their level of rigor, it probably will not hurt to have this book, but it may not help.

Rating:
Summary: Very good, but not for everyone
Review: I found this book to be a very useful bridge between my undergraduate statistics class and my graduate econometrics class. However, I would not say that it is an ideal first book on econometrics for the beginner. The best features of Maddala's text are: it's integrated treatment of different estimation methods, including least squares, method of moments and maximum likelihood; an appropriate level of mathematical sophistication, with appendices in several chapters deriving the main results using matrix notation; and a comprehensive coverage of important topics in econometrics for an introductory level text. When Greene's graduate text didn't make sense to me on first reading, Maddala really helped to clear things up. It was much better for this purpose than Kennedy's 'A Guide to Econometrics'.

I would have no reservation recommending this book to other readers. It is certainly better that Gujarati's 'Basic Econometrics.' However, I think Wooldridge's 'Introductory Econometrics' is a better choice for the beginner, especially in it's coverage of cross section and panel data and its abundance of examples. Unfortunately, since Maddala passed away before the third edition was completed the last three chapters, including the chapter on panel data, do not contain any exercises.

To sum up: An excellent text overall, with some minor shortcomings.

Rating:
Summary: Critical, good, but sometimes too advanced for beginners
Review: This is is a comprehensive and critical treatment of standard and modern econometrics. Its main strength is the presentation of recent developments in econometrics in terms accessible to advanced undergraduates (for instance, cointegration, exogeneity, model selection). However, it is too advanced to be used as a book for beginners.

In sum, I think the book is sometimes too elementary to be used for advanced students, while it was too advanced to be used alone as an introductory textbook. I would recommend using/reading selected chapters (such as ch. 12 on model selection), which are accessible as well as dealing with topics not normally included in many textbooks.