Differences in Occupations & EarningsSlide 2Slide 3Slide 4Slide 5Slide 6What about the women?Slide 8Slide 9Slide 10Index of Occupational SegregationExample 1: Complete segregation 100% of all men in blue-collar jobs 100% of all women in pink-collar jobsExample 2: Complete integration 40% of men in blue-collar jobs, 60% in pink-collar jobs 40% of women in blue-collar jobs, 60% in pink-collar jobsExample 3: High integration 60% of men in blue-collar jobs, 40% in pink-collar jobs 40% of women in blue-collar jobs, 60% in pink-collar jobsExample 4: Low integration 80% of men in blue-collar jobs, 20% in pink-collar jobs 20% of women in blue-collar jobs, 80% in pink-collar jobsIndex of Occupational Segregation by Gender, 1999We can also look at the Index of Occupational Segregation by Race/Ethnicity.1999Slide 19Slide 20Slide 21Slide 22Example: University Faculty, 1999Slide 24Slide 25Trends in Occupational SegregationFemale/Male Earnings Ratio2009 ratio of women’s to men’s earnings for full-time, year-round workersSlide 29Female-to-Male Earnings Ratios for Full-Time, Year-Round Workers by Age, 1999Female-to-Male Earnings Ratios for Full-Time, Year-Round Workers by Education, 1999Female-to-Male Earnings Ratios for Full-Time, Year-Round Workers by Race/Ethnicity, 1999Earnings Ratios for Full-Time, Year-Round Workers, 1999Racial/Ethnic TrendsExplaining the trends in the gender wage gapDifferences in Occupations & EarningsHow do occupations differ by race/ethnicity and gender?Let’s first look at men.MenOccupation White Black Hispanic AsianExecutives, managers 16.7 8.8 7.0 15.3Professional specialty 16.2 13.6 6.7 32.9Services 12.5 20.5 22.3 13.9Sales 11.5 8.8 7.6 11.4Administrative support 6.0 9.5 6.0 6.0Farming, forestry, fishing 1.1 .3 2.7 .5Construction, extraction 11.4 7.2 17.8 2.5Installation, repair 6.7 4.9 6.2 3.4Production 8.9 10.5 12.2 8.5Transportation 9.1 16.0 11.6 5.7The highest percentages of white men are in executive and professional specialty occupations. (People in professional specialty occupations include engineers, lawyers, computer scientists, physicians, teachers, nurses, and social workers.)MenOccupation White Black Hispanic AsianExecutives, managers 16.7 8.8 7.0 15.3Professional specialty 16.2 13.6 6.7 32.9Services 12.5 20.5 22.3 13.9Sales 11.5 8.8 7.6 11.4Administrative support 6.0 9.5 6.0 6.0Farming, forestry, fishing 1.1 .3 2.7 .5Construction, extraction 11.4 7.2 17.8 2.5Installation, repair 6.7 4.9 6.2 3.4Production 8.9 10.5 12.2 8.5Transportation 9.1 16.0 11.6 5.7The highest percentages of black men are in services and transportation.MenOccupation White Black Hispanic AsianExecutives, managers 16.7 8.8 7.0 15.3Professional specialty 16.2 13.6 6.7 32.9Services 12.5 20.5 22.3 13.9Sales 11.5 8.8 7.6 11.4Administrative support 6.0 9.5 6.0 6.0Farming, forestry, fishing 1.1 .3 2.7 .5Construction, extraction 11.4 7.2 17.8 2.5Installation, repair 6.7 4.9 6.2 3.4Production 8.9 10.5 12.2 8.5Transportation 9.1 16.0 11.6 5.7The highest percentages of Hispanic men are in services and construction.MenOccupation White Black Hispanic AsianExecutives, managers 16.7 8.8 7.0 15.3Professional specialty 16.2 13.6 6.7 32.9Services 12.5 20.5 22.3 13.9Sales 11.5 8.8 7.6 11.4Administrative support 6.0 9.5 6.0 6.0Farming, forestry, fishing 1.1 .3 2.7 .5Construction, extraction 11.4 7.2 17.8 2.5Installation, repair 6.7 4.9 6.2 3.4Production 8.9 10.5 12.2 8.5Transportation 9.1 16.0 11.6 5.7The highest percentages of Asian men are in professional specialty occupations.What about the women?WomenOccupation White Black Hispanic AsianExecutives, managers 13.6 10.1 6.7 12.9Professional specialty 15.0 21.4 14.5 28.4Services 18.9 26.4 31.0 20.9Sales 12.1 11.1 11.9 10.3Administrative support 23.4 21.6 20.8 16.2Farming, forestry, fishing .4 .1 1.3 .3Construction, extraction .4 - .5 -Installation, repair .3 .4 .8 -Production 4.2 6.3 9.3 9.8Transportation 1.8 2.7 3.3 1.1All groups of women have high percentages in services and administrative support.WomenOccupation White Black Hispanic AsianExecutives, managers 13.6 10.1 6.7 12.9Professional specialty 15.0 21.4 14.5 28.4Services 18.9 26.4 31.0 20.9Sales 12.1 11.1 11.9 10.3Administrative support 23.4 21.6 20.8 16.2Farming, forestry, fishing .4 .1 1.3 .3Construction, extraction .4 - .5 -Installation, repair .3 .4 .8 -Production 4.2 6.3 9.3 9.8Transportation 1.8 2.7 3.3 1.1The percentages are also fairly high for professional specialty occupations, especially for Asian women.We can measure the extent of the differences in the occupational distributions of men and women using the index of occupational segregation.Index of Occupational SegregationThis index measures the percentage of females (or males) that must change jobs in order for the occupational distributions to be equal. It is calculated as follows: ½  |Mi – Fi| Where Mi is the percentage of males in the labor force in occupation i, and Fi is the percentage of females in the labor force in occupation iExample 1: Complete segregation100% of all men in blue-collar jobs100% of all women in pink-collar jobs ½ [|100-0| + |0-100|] = 100This means that 100% of women would have to change to blue-collar jobs or 100% of men would have to change to pink-collar jobs for the occupational distributions to be the same.Occupation Men WomenBlue-Collar100 0Pink-collar0 100Total100 100Example 2: Complete integration 40% of men in blue-collar jobs, 60% in pink-collar jobs40% of women in blue-collar jobs, 60% in pink-collar jobs½ [|40-40| + |60-60|] = 0This means that no one needs to change jobs to make the occupational distributions the same for the two genders.Occupation Men WomenBlue-Collar40 40Pink-collar60 60Total100 100Example 3: High integration60% of men in blue-collar jobs, 40% in pink-collar jobs40% of women in blue-collar jobs, 60% in pink-collar jobs½ [|60-40| + |40-60|] = 20This means that 20% of men would have to change to pink-collar jobs or 20% of women would have to change to blue-collar jobs to make the occupational distributions the same.Occupation Men WomenBlue-Collar60 40Pink-collar40 60Total100 100Example 4: Low integration80% of men in blue-collar jobs, 20% in pink-collar jobs20% of women in blue-collar jobs, 80% in pink-collar jobs½ [|80-20| + |20-80|] = 60This means that 60% of men would have to change to pink-collar jobs or 60% of women would have to change to blue-collar jobs to make the occupational distributions the same.Occupation Men