TY  - BOOK
AU  - Wooldridge, Jeffrey M
TI  -  Econometrics
SN  - 8131509609
U1  - 658.4033 WOO 
PY  - 2009///
CY  - New Delhi
PB  -  Cengage
KW  - Econometrics
KW  - Regression analysis
KW  - Economics - Inference
N1  - Gratis; 1. The Nature of Econometrics and Economic Data.
Part 1: Regression Analysis with Cross-Sectional Data.
2. The Simple Regression Model
3. Multiple Regression Analysis: Estimation
4. Multiple Regression Analysis: Inference
5. Multiple Regression Analysis: OLS Asymptotic
6. Multiple Regression Analysis: Further Issues
7. Multiple Regression Analysis with Qualitative Information: Binary (or Dummy) Variables
8. Heteroskedasticity
9. More on Specification and Data Problems
Part 2: Regression Analysis with Time Series Data.
10. Basic Regression Analysis with Time Series Data
11. Further Issues in Using OLS with Time Series Data. 12. Serial Correlation and Heteroskedasticity in Time Series Regressions
Part 3: Advanced Topics.
13. Pooling Cross Sections across Time: Simple Panel Data Methods
14. Advanced Panel Data Methods
15. Instrumental Variables Estimation and Two Stage Least Squares
16. Simultaneous Equations Models
17. Limited Dependent Variable Models and Sample Selection Corrections
18. Advanced Time Series Topics
19. Carrying out an Empirical Project
APPENDICES Appendix A: Basic Mathematical Tools.
Appendix B: Fundamentals of Probability.
Appendix C: Fundamentals of Mathematical Statistics.
Appendix D: Summary of Matrix Algebra.
Appendix E: The Linear Regression Model in Matrix Form.
Appendix F: Answers to Chapter Questions.
Appendix G: Statistical Tables.
References.
Index
N2  - Econometrics illustrates how empirical researchers think about and apply econometric methods in real-world practice. The systematic approach, which reduces clutter by introducing assumptions only as they are needed, makes absorbing the material easier and leads to better econometric practices
ER  -