MALE is the indicator whether the student is a male or a female. Based on the gender of the student, the model becomes the following:
1) For Females, MALE=0
using OLS, we have
i.e., it is just the mean schooling for all the girls.
2) For Males: MALE=1,
using
5.4 Consider the rudimentary educational attainment model S = B. + B, MALE+ Demonstrate that, if...
Question 4 We will look at the possible effects of gender of an individual on educationol attainment. In the dataset is S years of schooling, ASVABC is composite score on the cognitive tests, SM is years of schooling of the respondent's mother, SF is years of schooling of the respondent's father, MALE is a dummy variable equal to 1 if the respondent was a male Some of the regression output has been deliberately hidden. Source I df MS Number of...
Consider the relationship between hourly wage rate and education attainment. A random sample of 21 male workers was collected to estimate the following model Y; = Bo + B1X; + uj, for i = 1,..., 21. Here, Y; is the logarithm of hourly wage rate, log(wage), for the i-th worker. Xi is the education level, husedu, of the i-th worker, which is measured as the years of schooling, and uị is the error term for the i-th worker. The ordinary...
Imagine that you regressed the earnings of individuals on a constant, a binary variable (“Male”) which takes on the value of 1 for males and is 0 otherwise, and another binary variable (“Female”) which takes on the value of 1 for female and is 0 otherwise. Because females typically earn less than males, you would expect: Group of answer choices autocorrelation or serial correlation to be a serious problem. the estimated coefficient for Male to have a positive sign, and...