Damodar Gujarati,
West Point Military Academy Sangeetha, Formerly with XLRI,
Jamshedpur
ISBN: 0070660050 Copyright year: 2007
Table of Contents
Preface
Introduction
Part I Single-Equation Regression Models
Chapter 1 The Nature of Regression Analysis
Chapter 2 Two-Variable Regression Analysis: Some Basic Ideas
Chapter 3 Two-Variable Regression Model: The Problem of Estimation
Chapter 4 Classical Normal Linear Regression Model (CNLRM)
Chapter 5 Two-Variable Regression: Estimation and Hypothesis Testing
Chapter 6 Extensions of the Two-Variable Linear Regression Model
Chapter 7 Multiple Regression Analysis: The Problem of Estimation
Chapter 8 Multiple Regression Analysis: The Problem of Inference
Chapter 9 Dummy Variable Regression Models
Part II Relaxing the Assumptions of the Classical Model
Chapter 10 Multicollinearity: What Happens if the Regressors Are Correlated
Chapter 11 Heteroscedasticity: What Happens if the Error Variance Is Nonconstant?
Chapter 12 Autocorrelation: What Happens if the Error Terms Are Correlated
Chapter 13 Econometric Modeling: Model Specification and Diagnostic Testing
Chapter 18 Simultaneous-Equation Models
Chapter 19 The Identification Problem
Chapter 20 Simultaneous-Equation Methods
Chapter 21 Time Series Econometrics: Some Basic Concepts
Chapter 22 Time Series Econometrics: Forecasting
Appendix A: A Review of Some Statistical Concepts
Appendix B: Rudiments of Matrix Algebra
Appendix C: The Matrix Approach to Linear Regression Model
2007
Tata McGraw-Hill