Summary Classical Linear Regression Model

, CLRM – Classical Linear Regression Model

Dummy variables: Distinguish between groups, the average and the slope between groups, that´s all
about Dummy variables.
In empirical finance we have two important concepts
1. Estimations
- We have a group and we look at their salaries. We take the average of the salaries.
- Taking the average is estimation
2. Inference
- We split the group in two. We have two different averages.
- Afterwards we ask ourselves: Are they different? Are they surprisingly different?
H0 = everybody earns the same salary.
H1 = otherwise
- Inference is about interpreting the results.
- When we check at the differences we look coefficients.
Exam Questions: How do I interpret these results?
Notation Issues: What is random and non-random in the linear regression model?




- B/M – book to market  valuation multiple  high book to market  high value
- Gov – governance  better governance is better for valuation  so, lower book to
market
- Lev – leverage  leverage affects valuation
- The slope of the line is β2
- The data is only dots. You have the data and then you infer the slope. That is the
estimation part of β2.
- High governance is a very good variable. Very good governance means high market value
 therefore low book to market. Low book to market means the stock is overvalued.