The file “wage” presents 526 observations from the Current Population Survey for the year 1986. The variables are in the following order:
wage = average hourly earnings
educ = years of education
exper = years of experience
nonwhite = Y if nonwhite
female = Y if female
married = Y if married
tenure = years with current employer
Use this data to do the following:
- (20 points) a) Carry out the following regression:
wagei = B0 + B1 femalei + ei
And interpret the coefficient B1.
- b) Carry out the following regression:
Ln(wagei) = B0 + B1 femalei + ei
Interpret the coefficient B1.
- (80 points) Run a regression of the natural logarithm of wages on gender, experience, experience squared, tenure and education. That is, you have to carry out the following regression:
Ln(wagei) = B0 + B1 femalei + B2 educi +B3 experi + B4 experi2+ B5 tenurei + ei
- a) Explicitly provide the estimated regression equation for men and the estimated regression equation for women.
- b) Evaluate whether the residuals satisfy the assumptions of homoscedasticity. You have to provide graphical and numerical tests.
Note: If you found heteroscedasticity in the model, you must correct the t and the F tests statistics before answering the following question.
- c) Carry out the hypotheses tests to evaluate whether each parameter associated with each independent variable is zero.
- d) Interpret the coefficient of determination (R2).
- e) Based on this model, determine the expected Ln(wage) for a randomly individual selected in this population with the following information:
Gender: Female; Years of education=10; Years of experience = 10; Years with current employer (tenure)=5
- f) Using the information in part (e), what is the expected effect on her wage if she obtains another year of experience, keeping the other explanatory variables constant?
- g) Using the information in part (e), what is the expected effect on her wage if she obtains another year of formal education, keeping the other explanatory variables constant?
- h) Interpret the estimator of the coefficient associated with the variable female.