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Offering students a unifying theoretical perspective, this innovative text emphasizes nonlinear techniques of estimation, including nonlinear least squares, nonlinear instrumental variables, maximum likelihood and the generalized method of moments, but nevertheless relies heavily on simple geometrical arguments to develop intuition. One theme of the book is the use of artificial regressions for estimation, inference, and specification testing of nonlinear models, including diagnostic tests for parameter constancy, series correlation, heteroskedasticity and other types of misspecification. Other topics include the linear simultaneous equations model, non-nested hypothesis tests, influential observations and leverage, transformations of the dependent variable, binary response models, models for time-series/cross-section data, multivariate models, seasonality, unit roots and cointegration, and Monte Carlo methods, always with an emphasis on problems that arise in applied work. Explaining throughout how estimates can be obtained and tests can be carried out, the text goes beyond a mere algebraic description to one that can be easily translated into the commands of a standard econometric software package. A comprehensive and coherent guide to the most vital topics in econometrics today, this text is indispensable for all levels of students of econometrics, economics, and statistics on regression and related topics.
List of contents
- 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
About the author
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.
