A researcher wonders whether males get paid more, on average, than females at a large firm. She interviews 50 employees and collects data on each employee’s hourly wage (Wage in $), years of higher education (Educ), years of experience (Exper), age (Age), and a Male dummy variable that equals 1 if male, 0 otherwise. A portion of the data is shown in the accompanying table. Wage Educ Exper Age Male
37.95 9.00 8.00 59.00 0.00
21.27 7.00 21.00 67.00 0.00
⋮ ⋮ ⋮ ⋮ ⋮
24.08 9.00 9.00 62.00 0.00

Click here for the Excel Data File

a. Estimate: Wage = β0 + β1Educ + β2Exper + β3Age + β4Male + ε. (Negative values should be indicated by a minus sign. Round your answers to 2 decimal places.)

b. Predict the hourly wage of a 34-year-old male and female employee with 16 years of higher education and 9 years experience. (Do not round intermediate calculations. Round final answers to 2 decimal places.)

c-1. Interpret the estimated coefficient for Male.

multiple choice 1
The male coefficient implies that males earn $0.22 per hour more than females at the firm, holding everything else the same.
The male coefficient implies that males earn $0.22 per hour less than females at the firm, holding everything else the same.
The male coefficient implies that males earn $0.90 per hour more than females at the firm, holding everything else the same.
The male coefficient implies that males earn $0.90 per hour less than females at the firm, holding everything else the same.

c-2. Is the variable Male significant at the 5% level? Do the data suggest that sex discrimination exists at this firm?

multiple choice 2
Yes, since we reject the null hypothesis of discrimination.
Yes, since we reject the null hypothesis of no discrimination.
No, since we do not reject the null hypothesis of discrimination.
No, since we do not reject the null hypothesis of no discrimination.