Estimation and Inference in Econometrics
Published on 1. July 1993
Book
Hardback
896 pages
978-0-19-506011-9 (ISBN)
Description
Offering a unifying theoretical perspective not readily available in any other text, this innovative guide to econometrics uses simple geometrical arguments to develop students' intuitive understanding of basic and advanced topics, emphasizing throughout the practical applications of modern theory and nonlinear techniques of estimation.
One theme of the text is the use of artificial regressions for estimation, reference, and specification testing of nonlinear models, including diagnostic tests for parameter constancy, serial correlation, heteroscedasticity, and other types of mis-specification. Explaining how estimates can be obtained and tests can be carried out, the authors go beyond a mere algebraic description to one that can be easily translated into the commands of a standard econometric software package.
Covering an unprecedented range of problems with a consistent emphasis on those that arise in applied work, this accessible and coherent guide to the most vital topics in econometrics today is indispensable for advanced students of econometrics and students of statistics interested in regression and related topics. It will also suit practising econometricians who want to update their skills. Flexibly designed to accommodate a variety of course levels, it offers both complete coverage of the basic material and separate chapters on areas of specialized interest.
One theme of the text is the use of artificial regressions for estimation, reference, and specification testing of nonlinear models, including diagnostic tests for parameter constancy, serial correlation, heteroscedasticity, and other types of mis-specification. Explaining how estimates can be obtained and tests can be carried out, the authors go beyond a mere algebraic description to one that can be easily translated into the commands of a standard econometric software package.
Covering an unprecedented range of problems with a consistent emphasis on those that arise in applied work, this accessible and coherent guide to the most vital topics in econometrics today is indispensable for advanced students of econometrics and students of statistics interested in regression and related topics. It will also suit practising econometricians who want to update their skills. Flexibly designed to accommodate a variety of course levels, it offers both complete coverage of the basic material and separate chapters on areas of specialized interest.
Reviews / Votes
`Excellent reference text on econometrics.'Ron Smith, Birkbeck College, London `This is a very good overall post-graduate textbook in econometrics.'
Dr Offer Lieberman, University of Bristol `a welcome addition to the long bookshelf of choices available to those teaching graduate econometrics ... the book is remarkably self-contained and internally integrated ... the Davidson and Mackinnon volume represents an excellent choice from a range of fine texts. I look forward to using it in my classes as an extension of the Gujarati text'
Kyklos
More details
Language
English
Place of publication
New York
United States
Target group
College/higher education
Illustrations
line figures, tables
Dimensions
Height: 240 mm
Width: 161 mm
Thickness: 52 mm
Weight
1494 gr
ISBN-13
978-0-19-506011-9 (9780195060119)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
Russell Davidson was born in Johnstone, Scotland, and studied at the University of Glasgow, where he gained a PhD. in Physics in 1966. He was a Faculty Associate at the University of Texas, Austin from 1967-70. He turned to economics in the early 1970s and took a PhD. in economics at the University of British Columbia in 1977 and was a Post-doctoral Fellow there from 1972-3. He was Assistant Professor at Queen's University, Canada, from 1977-82 and Associate Professor there from 1982-5.
James MacKinnon studied at York University, Toronto, and Princeton University. He was Assistant Professor at Queen's University, Canada, from 1975-8 and Associate Professor from 1982-91. He has been a Fellow of the Econometric Society since 1990.
James MacKinnon studied at York University, Toronto, and Princeton University. He was Assistant Professor at Queen's University, Canada, from 1975-8 and Associate Professor from 1982-91. He has been a Fellow of the Econometric Society since 1990.
Content
1. The Geometry of Least Squares ; 2. Nonlinear Regression Models and Nonlinear Least Squares ; 3. Inference in Nonlinear Regression Models ; 4. Introduction to Asymptotic Theory and Methods ; 5. Asymptotic Methods and Nonlinear Least Squares ; 6. The Gauss-Newton Regression ; 7. Instrumental Variables ; 8. The Method of Maximum Likelihood ; 9. Maximum Likelihood and Generalized Least Squares ; 10. Serial Correlation ; 11. Tests Based on the Gauss-Newton Regression ; 12. Interpreting Tests in Regression Directions ; 13. The Classical Hypothesis Tests ; 14. Transforming the Dependent Variable ; 15. Qualitative and Limited Dependent Variables ; 16. Heteroskedasticity and Related Topics ; 17. The Generalized Method of Moments ; 18. Simultaneous Equations Models ; 19. Regression Models for Time-Series Data ; 20. Unit Roots and Cointegration ; 21. Monte Carlo Experiments