Estimation and Inference in Econometrics / Edition 1

by Russell Davidson, James G. MacKinnon

Overview

Offering a unifying theoretical perspective not readily available in any other text, this innovative book uses simple geometrical arguments to develop students' intuitive understanding of basic and advanced topics in econometrics, emphasizing throughout the practical applications of modern theory and nonlinear techniques of estimation.

Product Details

ISBN-13:	9780195060119
Publisher:	Oxford University Press, USA
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 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 Cointegratiaon
21. Monte Carlo Experiments
A. Matrix Algebra
B. Results from Probability Theory
References
Author Index
Subject Index