Econometric Theory and Methods

Econometric Theory and Methods

Econometric Theory and Methods

Econometric Theory and Methods


Econometric Theory and Methodsprovides 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 Methodsis 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.


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 thebootstrap(Chapter 4),sandwich covariance matrices(Chapter 5), andartificial 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.


This book is the second graduate-level econometrics textbook that we have written. Our first one, Estimation and Inference in Econometrics, appeared eleven years ago and has been quite successful. Why then did we choose to write this book instead of a second edition of the first one? Although it would have been quicker and easier to write a second edition, there were several compelling reasons that drove us to write an entirely new book.

It seems unavoidable that the second edition of a book is longer than its predecessor. Estimation and Inference in Econometrics is by no means short. Indeed, it contains too much material even for most two-course sequences. This book is significantly shorter. The entire book can be taught in a twocourse sequence, as we explain below in detail, and a substantial fraction of it can be taught in a single course, possibly at a somewhat lower level.

The subject of econometrics has evolved as rapidly in the last ten years as it did in the ten years prior to that. This means not only that there are many new things that students of econometrics should learn, but also that there are new and perhaps better ways of understanding older material. Although many parts of Estimation and Inference in Econometrics have held up well, we would have had to reorganize and rewrite it radically if we were to produce a second edition that we could be truly happy with.

Another reason for preferring to write a new book is that the level of our earlier one, especially in several key chapters in the first half, is too high for the first graduate courses at many institutions. With hindsight, this was a mistake. One of our goals in writing this book has been to start at a more modest level and work up from there gradually as the book proceeds. Some of the earlier chapters do contain some fairly advanced material, but much of it is confined to exercises, and the rest is in sections and subsections that can be skipped without serious loss of continuity.

Features of This Book

Cheap personal computers were already a fact of life around 1990. Since then, computers have become vastly more powerful and even less expensive. It is no surprise that econometrics, always a computer-intensive discipline, should have been profoundly affected by the development of computers. Ten years ago, one could have predicted that they would make the practice of econometrics a lot easier, and of course that is what has happened. What was less predictable is that the ability to perform simulations easily and quickly would change many of the directions of econometric theory as well as econometric practice. The use of the computer in econometrics, especially for simulation, has blossomed so quickly that no textbook like this one can reasonably avoid a serious discussion of simulation.

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