What do you think?
Rate this book
Econometric Theory and Methods
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 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 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 These include the bootstrap (Chapter 4), sandwich covariance matrices (Chapter 5), and artificial regressions (Chapter 6).
· Inclusive Treatment of 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 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 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.
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 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 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 These include the bootstrap (Chapter 4), sandwich covariance matrices (Chapter 5), and artificial regressions (Chapter 6).
· Inclusive Treatment of 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 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 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.
768 pages, Hardcover
First published October 16, 2003
1 person is currently reading
60 people want to read
Ratings & Reviews
Friends & Following
Create a free account to discover what your friends think of this book!
Community Reviews
Displaying 1 - 5 of 5 reviews
August 6, 2020
Before reading this textbook, I was effectively lost in the middle of many econometric methods that I could not connect together. In addition to that, my weak background in theoretical mathematics stood as a barrier to understanding econometric theory taught at my university.
This textbook is self-contained and assumes no mathematical knowledge beyond calculus, basic linear algebra and statistics. All mathematical methods that are needed are introduced within chapters in a very intuitive way. The book starts from the basics of econometric theory and progresses to derive and prove common methods used at PhD level. This is done with a rich discussion that leaves little space for confusion.
The book helped me develop my understanding such that I am now able to navigate different methods according to the problem at hand and assumptions that could be made. For example, it helped me have an intuitive understanding of what the weighting matrix should be for the feasible efficient GMM that I could always remember.
I would recommend reading all chapters of the book as they contain a common theme and draw a natural line of progression to help understand how everything connects together.
This textbook is self-contained and assumes no mathematical knowledge beyond calculus, basic linear algebra and statistics. All mathematical methods that are needed are introduced within chapters in a very intuitive way. The book starts from the basics of econometric theory and progresses to derive and prove common methods used at PhD level. This is done with a rich discussion that leaves little space for confusion.
The book helped me develop my understanding such that I am now able to navigate different methods according to the problem at hand and assumptions that could be made. For example, it helped me have an intuitive understanding of what the weighting matrix should be for the feasible efficient GMM that I could always remember.
I would recommend reading all chapters of the book as they contain a common theme and draw a natural line of progression to help understand how everything connects together.
May 11, 2018
it was a hard book to read, especially regarding my not economics background. but after a while, I get used to the language and understanding.
February 9, 2021
Great book! I read it during my MA
June 24, 2013
no applications (that I recall) but very worthwhile piece in your artillery
January 23, 2016
Wonderful maths :D
Displaying 1 - 5 of 5 reviews