
Regression models
Just a little confused what's being asked.. So...
I have these variables to play with:
Y: Wage is the annual Wage of an employee (response variable)
X1: Starting Wage (StWage) is the employee’s Starting Wage
X2: Years of Experience (YrsExp) is the number of years the employee has been in the workforce
X3: Previous Experience (PrevExp) an employee’s Years of Previous Experience.
X4: Years of Education (YrsEd) is the total number of years of education.
G: Gender is coded M if employee is male, F if the employee is female.
D: Education Level is one of five categories, 1: Post Graduate, 2: Bachelor’s Degree, 3: TAFE,
4: Completed High School, 5: High School dropout.
I am asked 2 questions (of which confuse me a little)
1)Estimate equation Y = β_{0} + β_{1}X_{1} + β_{2}X_{2} + β_{3}X_{3} + ε with the addition of M as an explanatory variable (i.e., use Females as the base). Write out the equation, with its standard errors. Now estimate the same equation, with F as an explanatory variable (i.e., use Males as the base). Write out this equation and its standard errors also. Compare these two estimations.
Here, I just filtered for either 'only' male or 'only' female data.. Then the regression. model  blah blah
2)Now estimate without the Gender variable, but with the Education dummy variables (dropping D5). Also estimate this equation, but this time dropping Education level 4 (D4) instead of level 5. Write out both equations with their standard errors. Compare these two estimations.
Now, I just used filtered 'all' data except for D5, then 'all' except D4... Then the regression model  blah blah.
Is that wrong, for 2 it seems to make extra no sense to me.
Thank you !