Using data from 50 workers, a labour economist runs a multiple regression of Y (hourly wage in $) on X1 (years of education), X2 (gender) and X3 (an interaction between X1 and X2), and obtains the following regression results.
Coefficients  Standard error  
Intercept  16.78  2.14 
Years of education  2.77  0.16 
Gender (coded 1 for female and 0 for male)  8.84  3.01 
Interaction between years of education and gender  1.02  0.22 
Based on the above information, the estimated effect of X1 (years of education) on Y (hourly wage) for female employees is ___________.
a. 
11.61 

b. 
8.84 

c. 
1.02 

d. 
1.75 
Given:
Using data from 50 workers, a labour economist runs a multiple regression of Y (hourly wage in $) on X1 (years of education), X2 (gender) and X3 (an interaction between X1 and X2), and obtains the following regression results.
Coefficients  Standard error  
Intercept  16.78  2.14 
Years of education  2.77  0.16 
Gender (coded 1 for female and 0 for male)  8.84  3.01 
Interaction between years of education and gender  1.02  0.22 
Based on the above information, the estimated effect of X1 (years of education) on Y (hourly wage) for female employees is
Estimated effect = 2.77 + 8.84 = 11.61........ ( for female employees, X2 = 1).
So the estimated effect of X1 (years of education) on Y (hourly wage) for female employees is 11.61.
Answer  option a
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