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Econometric Theory and Methods

$49.50 each

Russell Davidson and James G. MacKinnon
Publisher: Oxford University Press
Copyright: 2004
ISBN-13: 978-0-19-512372-2
Pages: 750; hardcover
Price: $49.50

Comment from the Stata technical group

Davidson and MacKinnon’s Econometric Theory and Methods provides an excellent introduction to modern methods of estimation and inference used in econometrics. The first-principles approach, which allows readers new to the material to develop a deep understanding of the topics, makes this book a valuable resource for both students and applied researchers.

Over the years, Davidson and MacKinnon have become known for their geometrical explanations, use of augmented regressions, and attention to numerical methods. This new book lives up to their well-deserved reputation. For instance, in a refreshing departure from the usual presentation, Davidson and MacKinnon introduce bootstrap and simulation techniques early on in their presentation of inference, rather than waiting until a later chapter to introduce these now-common techniques.

Throughout the book, they present material at a rigorous yet very approachable level. For each topic considered, the authors provide an introduction and then ease the reader into advanced topics that are not always covered in other books. For instance, while hypothesis testing and confidence-interval estimation could be collapsed into a matter of pages, Davidson and MacKinnon take the time to explain such important concepts as the power of a test, exact versus approximate confidence regions, asymptotically pivotal statistics, and the advantages of bootstrapping studentized statistics. Also included in chapter five is a discussion of heteroskedasticity-consistent covariance matrices.

The authors provide detailed introductions to six of the major methods of estimation used in econometrics: ordinary least squares, nonlinear regression, generalized least squares, instrumental variables, the generalized method of moments (GMM), and maximum likelihood. Chapter nine contains one of the best introductions to GMM currently available, covering both simulated GMM and simulated maximum likelihood are covered in detail. Plenty of references are given so that readers can pursue more advanced topics; for example, chapter eight briefly discusses the “weak instruments” problem and then provides no fewer than fifteen references.

While this book provides an excellent introduction to the general methods of estimation and inference used in econometrics, the standard topics are covered very quickly. As in their 1993 book, Davidson and MacKinnon condense their treatment of limited dependent variables into a single chapter, and panel data get only a few pages. Readers who want a detailed discussion of specific models will want to supplement the material in this book with Jeffrey Wooldridge’s Econometric Analysis of Cross Section and Panel Data.

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