Table of Contents

Part I: Single-Equation Regression Model 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: Interval 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 Regressor 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 Part III: Topics in Econometrics Chapter 14: Nonlinear Regression Models Chapter 15: Qualitative Response Regression Models Chapter 16: Panel Data Regression Models Chapter 17: Dynamic Econometric Model: Autoregressive and Distributed-Lag Models. Part IV: Simultaneous-Equation Models 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: Review of Some Statistical Concepts Appendix B: Rudiments of Matrix Algebra Appendix C: The Matrix Approach to Linear Regression Model Appendix D: Statistical Tables Appendix E: Computer Output of EViews, MINITAB, Excel, and STATA Appendix F: Economic Data on the World Wide Web