1. 1 Econometrics 1 Lecture 7 Multicollinearity

2. 2 What is multicollinearity

3. 3 OLS Estimates in a Multiple Regression Model

4. 4 Mutlicollinearity

5. 5 Multicollinearity: A Numerical Example

6. 6 Mutlicollinearity: In Matrix Notation

7. 7 Mutlicollinearity: Cramer’s Rule for Estimation OLS Parameters

8. 8 Breakdown of OLS Estimation In Case of Multicollinearity in Matrix

9. 9 General Formula for the OLS Parameters in Matrix Notation

10. 10 Variance in Algebra and in Matrix Notation

11. 11 Variance in Algebra and in Matrix Notation

12. 12 Consequences of Multicollinearity

13. 13 Detection of Multicollinearity

14. 14 Remedial Measures

15. 15 Remedial Measure

16. 16

17. 17 Likelihood and Log-Likelihood Functions Parameter Set, Value of Likelihood function

18. 18 Similarity Between the OLS and Maximum Likelihood Estimators

19. 19 Large Sample Tests