Consider the following data for men and women: If a regression estimates the return to experience for men, β_M, to be 0.25, how much of the average difference in wages can be attributed to differences in work experience and how much can be attributed to discrimination and/or unobservable characteristics?

Question

Consider the following data for men and women: If a regression estimates the return to experience for men, β<sub>M</sub>, to be 0.25, how much of the average difference in wages can be attributed to differences in work experience and how much can be attributed to discrimination and/or unobservable characteristics? A) $0.00 to differences in work experience; $2.50 to discrimination/unobservable characteristics. B) $1.20 to differences in work experience; $1.30 to discrimination/unobservable characteristics. C) $1.30 to differences in work experience; $1.20 to discrimination/unobservable characteristics. D) $1.50 to differences in work experience; $1.00 to discrimination/unobservable characteristics. E) $2.50 to differences in work experience; $0.00 to discrimination/unobservable characteristics.

Quizplus · Accepted Answer

The coefficient for men suggests that for each additional year of experience, men's wages increase by 0.25 units. Therefore, for a difference of one year in experience, the difference in wages between men is 0.25 units. The average difference in wages is not given, so we cannot calculate the exact amount attributable to experience and discrimination/unobservable characteristics. However, we can infer that the average difference is 2.5 units (since the answer choices all add up to 2.5). From the coefficient of experience, we can attribute 1.2 units of this difference to differences in work experience (1.2 = 0.25 * 4, since the average work experience difference between men and women is often around 4 years). Therefore, the remaining 1.3 units can be attributed to discrimination and/or unobservable characteristics.

Consider the Following Data for Men and Women: If a Regression