Econ

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:

1. (20 points) a) Carry out the following regression:

wage_i = B₀ + B₁ female_i + e_i
And interpret the coefficient B₁.

1. b) Carry out the following regression:

Ln(wage_i) = B₀ + B₁ female_i + e_i
Interpret the coefficient B₁.
 

2. (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(wage_i) = B₀ + B₁ female_i + B₂ educ_i +B₃ exper_i +  B₄ exper_i²+ B₅ tenure_i + e_i

1. a) Explicitly provide the estimated regression equation for men and the estimated regression equation for women.
2. 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.

1. c) Carry out the hypotheses tests to evaluate whether each parameter associated with each independent variable is zero.
2. d) Interpret the coefficient of determination (R²).
3. 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

1. 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?
2. 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?
3. h) Interpret the estimator of the coefficient associated with the variable female.