# Econometric Theory and Methods

Oxford University Press, 2004 - Business & Economics - 750 pages
Econometric Theory and Methods provides a unified treatment of modern econometric theory and practical econometric methods. The geometrical approach to least squares is emphasized, as is the method of moments, which is used to motivate a wide variety of estimators and tests. Simulation methods, including the bootstrap, are introduced early and used extensively.
The book deals with a large number of modern topics. In addition to bootstrap and Monte Carlo tests, these include sandwich covariance matrix estimators, artificial regressions, estimating functions and the generalized method of moments, indirect inference, and kernel estimation. Every chapter incorporates numerous exercises, some theoretical, some empirical, and many involving simulation.
Econometric Theory and Methods is designed for beginning graduate courses. The book is suitable for both one- and two-term courses at the Masters or Ph.D. level. It can also be used in a final-year undergraduate course for students with sufficient backgrounds in mathematics and statistics.
FEATURES

.Unified Approach: New concepts are linked to old ones whenever possible, and the notation is consistent both within and across chapters wherever possible.

.Geometry of Ordinary Least Squares: Introduced in Chapter 2, this method provides students with valuable intuition and allows them to avoid a substantial amount of tedious algebra later in the text.

.Modern Concepts Introduced Early: These include the bootstrap (Chapter 4), sandwich covariance matrices (Chapter 5), and artificial regressions (Chapter 6).

.Inclusive Treatment of Mathematics: Mathematical and statistical concepts are introduced as they are needed, rather than isolated in appendices or introductory chapters not linked to the main body of the text.

.Advanced Topics: Among these are models for duration and count data, estimating equations, the method of simulated moments, methods for unbalanced panel data, a variety of unit root and cointegration tests, conditional moment tests, nonnested hypothesis tests, kernel density regression, and kernel regression.

.Chapter Exercises: Every chapter offers numerous exercises, all of which have been answered by the authors in the Instructor's Manual. Particularly challenging exercises are starred and their solutions are available at the authors' website, providing a way for instructors and interested students to cover advanced material.
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A good geometrical introduction to first graduate (or serious undergraduate) course in econometrics.

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The first 5 chapter deal with fundamentals of econometrics, from geometry of OLS to hypothesis test and confidence region. From
Chapter 6 to 10, variants of estimation methods are discussed, such as NLS, GLS, ML, IV, GMM. The rest of 5 chapters deal with discrete dependent variable, time series, model specification, etc.
Students who are determinant to study this book should be fully prepared with mathematics, esp. linear algebra and calculus. Basic econometrics and statistics previous course are highly recommended. The whole book heavily use linear algebra skills which students are suppose to be familiar with in their undergraduate courses, which means this book is not appropriate for weak mathematics backgrounds students.