Multiple Regression Model
Multiple Regression Model: Files
- Lecture: Multiple Regression Model.pdf
- Stata program: Multiple Regression Model.do
- Data files: wage1.dta, ceosal1.dta, HTV.dta, elemapi2.dta
- R script: Multiple Regression Model.R
- Data files: wage1.csv, ceosal1.csv, HTV.csv, elemapi2.csv
Multiple Regression Model: Lecture Topics
- Multiple regression terminology
- Examples and interpretation of coefficients
- Derivation of OLS estimates, OLS properties, partialling out
- Goodness of fit: R-squared and adjusted R-squared
- Gauss Markov assumptions
- 5 assumptions
- Perfect collinearity vs multicollinearity
- Unbiasedness of OLS estimators (omitted variable bias)
- Variance of OLS estimators (variance in misspecified models)
- Gauss-Markov theorem (BLUE)
Multiple Regression Model in Stata/R: Topics
- Multiple regression
- Partialling out
- Goodness of fit (R-squared and adjusted R-squared)
- Perfect collinearity
- Multicollinearity using VIF
- Omitted variable bias
- Variance in misspecified models
- Homoscedasticity and heteroscedasticity