Consider a data set with the following descriptive statistics.
Table 1. Descriptive Statistics.

Wage is the worker's hourly wage; Black takes on a value of 1 if the worker is Black and a value of 0 otherwise; work experience is actual years of work experience, schooling is measured in years; and % female occupation is the percent of all employees in the worker's occupation who are female. The following table reports the regression results from a log wage regression.

Decompose the raw difference in average wages using the Oaxaca decomposition. Specifically, decompose the raw difference into the portion due to differences in personal characteristics (schooling, race, age, and experience), the portion due to occupation, and the portion left unexplained possibly due to gender discrimination.

Men Mean MinMax Mean 3.562 1.3895.0133.198 0.231 0 42.2 19 18.10 13.9 9 Womern Min Max Ln(wages) Black Age Work experience Schooling %female occupation | 0.182 0.023 .954 0.623 1.213 4.875 68 42 21 0.191 39.2 16.1 14.1 19 63 35 21 0.067 .985 Table 2. Regression Results. Constant Black Age Years of work experience Years of schooling Percent temale in occupation Men 2.314 0.198 0.054 0.042 0.085 0.121 Women 2.556 0.154 0.037 0.059 0.083 0.002 Number of Observations 442 278 R-squared 0.231 0.254