Gujarati: Basic Econometrics, Fourth Edition
Part I – Single-Equation Regression Models
1. The Nature of Regression Analysis
2. Two-Variable Regression Analysis: Some Basic Ideas
3. Two Variable Regression Model: The Problem of Estimation
4. Classical Normal Linear Regression Model (CNLRM)
5. Two-Variable Regression: Interval Estimation and Hypothesis Testing
6. Extensions of the Two-Variable Linear Regression Model
7. Multiple Regression Analysis: The Problem of Estimation
8. Multiple Regression Analysis: The Problem of Inference
9. Dummy Variable Regression Models
Part 2: Relaxing Assumptions of the Classical Model
10. Multicollinearity: What Happens if the Regressions are Correlated?
11. Heteroscedasticity: What Happens if the Error Variance is Nonconstant?
12. Autocorrelation: What Happens if the Error Terms are Correlated?
13. Econometric Modeling I: Model Specification and Diagnostic Testing?
Part 3: Topics in Econometrics
14. Nonlinear Regression Models
15. Qualitative Response Regression Models
16. Panel Data Regression Models
17. Dynamic Econometric Model: Autoregressive and Distributed Lag Models
Part 4: Simultaneous Equation Models
18. Simultaneous-Equation Models
19. The Identification Problem
20. Simultaneous-Equation Methods
Part 5: Time Series Econometrics
21. Time Series Econometrics: Some Basic Concepts
22. Time Series Econometrics: Forecasting
Basic_Econometrics By Gujarati, 2004.pdf
File size:5.70 MB
