Estimation and Inference in Econometrics / Edition 1

by Russell Davidson, James G. MacKinnon

Overview

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.

Product Details

ISBN-13:	9780195060119
Publisher:	Oxford University Press
Publication date:	01/14/1993
Edition description:	New Edition
Pages:	896
Product dimensions:	9.56(w) x 6.38(h) x 1.96(d)

Table of Contents

1. The Geometry of Least Squares2. Nonlinear Regression Models and Nonlinear Least Squares3. Inference in Nonlinear Regression Models4. Introduction to Asymptotic Theory and Methods5. Asymptotic Methods and Nonlinear Least Squares6. The Gauss-Newton Regression7. Instrumental Variables8. The Method of Maximum Likelihood9. Maximum Likelihood and Generalized Least Squares10. Serial Correlation11. Tests Based on the Gauss-Newton Regression12. Interpreting Tests in Regression Directions13. The Classical Hypothesis Tests14. Transforming the Dependent Variable15. Qualitative and Limited Dependent Variables16. Heteroskedasticity and Related Topics17. The Generalized Method of Moments18. Simultaneous Equations Models19. Regression Models for Time-series Data20. Unit Roots and Cointegratiaon21. Monte Carlo ExperimentsA. Matrix AlgebraB. Results from Probability TheoryReferencesAuthor IndexSubject Index