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Editorial Reviews
Review
"This is a first class book, modern in conception and flawless in execution. The coverage is superb and it does things that many other books do not do or do not do adequately."--Richard E Quandt, Princeton University
"An excellent book that stands on its own in terms of approach."--Thanasis Stengos, University of Guelph, Canada
"This book teaches the core of econometric theory...with all of the fluency and didactic elegance that we have come to expect of its two authors....One of the book's outstanding features is its carefully constructed exercises which serve to reaffirm the concepts expounded it is chapters. The book has an elegant architecture, and it has been written with close attention to detail. In comparison, most other books that have a similar purpose look like mere agglomerations of econometric building materials. This is the best textbook of econometric theory to have emerged in a long while; and it deserves to find a place on the bookshelf of every instructor. It is bound to find favour with the students."--D.S.G. Pollock, University of London, UK
Product Description
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.
See all Editorial Reviews
"This is a first class book, modern in conception and flawless in execution. The coverage is superb and it does things that many other books do not do or do not do adequately."--Richard E Quandt, Princeton University
"An excellent book that stands on its own in terms of approach."--Thanasis Stengos, University of Guelph, Canada
"This book teaches the core of econometric theory...with all of the fluency and didactic elegance that we have come to expect of its two authors....One of the book's outstanding features is its carefully constructed exercises which serve to reaffirm the concepts expounded it is chapters. The book has an elegant architecture, and it has been written with close attention to detail. In comparison, most other books that have a similar purpose look like mere agglomerations of econometric building materials. This is the best textbook of econometric theory to have emerged in a long while; and it deserves to find a place on the bookshelf of every instructor. It is bound to find favour with the students."--D.S.G. Pollock, University of London, UK
Product Description
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.
See all Editorial Reviews
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Inside This Book
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First Sentence:
Regression models form the core of the discipline of econometrics. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
classical normal linear model, asymptotic identification condition, skedastic function, predeterminedness condition, theoretical moment conditions, sandwich covariance matrix estimator, standardized random walk, loglikelihood function, stationarity triangle, information matrix estimator, test regressor, predetermined explanatory variables, artificial regression, tth diagonal element, matrix that projects, asymptotic information matrix, linear simultaneous equations model, nonnested hypothesis tests, information matrix equality, linear simultaneous system, resealed residuals, deterministic regressors, binary response models, classical test statistics, common factor restrictions Key Phrases - Capitalized Phrases (CAPs): (learn more)
Final Remarks, Monte Carlo, Taylor's Theorem, Yule Walker, The Geometry of Linear Regression, Law of Iterated Expectations, Fundamental Theorem of Statistics, Heteroskedasticity-Consistent Covariance Matrices, Security Prices, Parameter Estimators Consistent, Parameter Estimators Unbiased, United States New!
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Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Regression models form the core of the discipline of econometrics. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
classical normal linear model, asymptotic identification condition, skedastic function, predeterminedness condition, theoretical moment conditions, sandwich covariance matrix estimator, standardized random walk, loglikelihood function, stationarity triangle, information matrix estimator, test regressor, predetermined explanatory variables, artificial regression, tth diagonal element, matrix that projects, asymptotic information matrix, linear simultaneous equations model, nonnested hypothesis tests, information matrix equality, linear simultaneous system, resealed residuals, deterministic regressors, binary response models, classical test statistics, common factor restrictions Key Phrases - Capitalized Phrases (CAPs): (learn more)
Final Remarks, Monte Carlo, Taylor's Theorem, Yule Walker, The Geometry of Linear Regression, Law of Iterated Expectations, Fundamental Theorem of Statistics, Heteroskedasticity-Consistent Covariance Matrices, Security Prices, Parameter Estimators Consistent, Parameter Estimators Unbiased, United States New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Citations (learn more)
This book cites 61
books:
See all 61 books this book cites
5
books
cite this book:
- Handbook of Econometrics, Volume 5 (Handbooks in Economics) by J.J. Heckman in Back Matter (1), Back Matter (2), and Back Matter (3)
- Time Series Analysis: Forecasting & Control (3rd Edition) by George Box in Back Matter
- An Introduction to Classical Econometric Theory by Paul A. Ruud in Back Matter
- The Econometric Analysis of Seasonal Time Series (Themes in Modern Econometrics) by Eric Ghysels in Back Matter
- Calculus With Applications by Karl J. Smith in Back Matter
See all 61 books this book cites
- An Introduction to the Structural Econometrics of Auction Data by Harry J. Paarsch in Front Matter, and Back Matter
- The Schur Complement and Its Applications (Numerical Methods and Algorithms) by Fuzhen Zhang in Back Matter
- Statistical Models: Theory and Practice by David Freedman in Back Matter
- Econometric Theory and Practice: Frontiers of Analysis and Applied Research by Dean Corbae on page 80
- An Introduction to Modern Econometrics Using Stata by Christopher F. Baum in Back Matter
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