TY  - BOOK
AU  - Gujarati,Damodar N.
TI  - Basic econometrics
SN  - 0072335424
U1  - 330.015195 21
PY  - 2003///]
CY  - Boston
PB  - McGraw Hill
KW  - Econometrics
N1  - Includes bibliographical references (pages 979-982) and indexes; Pt. 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 --
Pt. II. Relaxing the Assumptions of the Classical Model. 10. Multicollinearity: What Happens if the Regressors 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: Model Specification and Diagnostic Testing --
Pt. III. Topics in Econometrics. 14. Nonlinear Regression Models. 15. Qualitative Response Regression Models. 16. Panel Data Regression Models. 17. Dynamic Econometric Models: Autoregressive and Distributed-Lag Models --
Pt. IV. Simultaneous-Equation Models. 18. Simultaneous-Equation Models. 19. The Identification Problem. 20. Simultaneous-Equation Methods. 21. Time Series Econometrics: Some Basic Concepts. 22. Time Series Econometrics: Forecasting --
App. A. A Review of Some Statistical Concepts --
App. B. Rudiments of Matrix Algebra --
App. C. The Matrix Approach to Linear Regression Model --
App. E. Economic Data on the World Wide Web
ER  -