ECONOMICS 671
LECTURE NOTES
SET OF NOTES
FILE
DESCRIPTION
#1
Regression #1
Linear regression model basic framework. Matrix / Vector representation. Assumptions.
#2
Regression #2
The OLS estimator. Interpretation of multiple regression coefficients. R-square
#3
Regression #3
Consistency, Unbiasedness of OLS estimator, estimation of variance parameter.
#4
Regression #4
Sampling distribution of OLS estimator. Asymptotics. Gauss-Markov Theorem.
#5
Regression #5
Introduction to Confidence Intervals and Hypothesis Testing under normality.
#6
Regression #6
Scalar and Joint Testing
#7
Regression #7
Asymptotic distributions of test statistics. Hypothesis testing in practice.
#8
Regression #8
Loose ends: interpretation of regression coefficients with various transformations. Multicollinearity, dummy variables, interactions.
Thursday, Feb 1
In-Class Midterm Examination
Solutions
#9
Heteroscedasticity
Consequences for OLS estimation. GLS estimation. Aitken's Theorem.
(Missing Material Here)
#10
GLS/FGLS
Generalized Least Squares, Feasible Generalized Least Squares
#11
Mean Independence Violations
Omitted Variables, simultaneity, endogeneity.
#12
Instrumental Variables
Introduction to the Instrumental Variables Estimator
#13
Instrumental Variables #2
IV and Control Function Approaches
#14
IV Examples
Thursday, March 1
Final Examination, In class
