I am trying to figure out how to interpret the coefficients when using several qualitative independent variables of which some have more than two categories. I found this short article that touches upon that issue (the one page preview is enough to understand what I mean but I will explain here too). The article says that the interpretation is messed up in this case. Let me use the example variables of the article to make it clear what I mean. Wage is my dependent variable. The independent variables are all dummies that can be grouped in:
educational attainment
E1 = postgraduate (value 1 if postgraduate, 0 otherwise)
E2 = bachelor (value 1 if bachelor's degree, 0 otherwise)
E3 = high school (value 1 if high school, 0 otherwise)
marital status
R1 = married/in relationship (value 1 if married, 0 otherwise)
R2 = divorced (value 1 if divorced, 0 otherwise)
R3 = single (value 1 if single, 0 otherwise)
sex
M = male (value 1 if male, 0 otherwise)
F = female (value 1 if female, 0 otherwise)
Now, to avoid the dummy trap I delete E3, R3 and F. My regression equation would then look like this:
wage = b0 + b1*E1 + b2*E2 + b3*R1 + b4*R2 + b5*M
The article states that the baseline to compare against would thus be a single female that went to high school and that would mess up interpreting the individual dummy coefficients. My questions:
- Do I understand it correctly that it is indeed using several qualitative variables that have more than 2 categories (in this case educational attainment and marital status have each 3) that messes up the interpretation? I get that if I for example only used the marital status dummies (again excluding R3 to not face the dummy trap), I could easily state that married people (R1) earn more or less compared to single people (R3). But is this no longer possible as soon as I include the educational attainment dummies in my regression as well?
- Are dummy variables that only have 2 categories and therefore are represented in the regression equation with 1 dummy only (e.g. my sex variable -> M in the equation) affected by this at all or could I still state that men earn more or less compared to females, despite having educational attainment and marital status in my equation?