Education and Life time wage potential Chapter 9 Part 2

Human Capital Human Capital is similar to Physical Capital but there are some Important Differences –Nonpecuniary (non-monetary) issues The utility derived from attending School The utility of working in an office vs. outdoors

Human Capital –It is more difficult to finance human capital than it is to finance physical capital Why?

Educational Attainment of the Population by Gender: 1970, 1999, and 2003 (Ages 26-64)* Education Level Male (%) Female (%) Male (%) Female (%) Male (%) Female (%) < 4 yrs of H.S H. S Some College >4 yrs of College Total * 2003 is for figures 25 or older

Educational Attainment of the Population by Gender, Race, and Hispanic Origin 1999 (ages 26-64) Education Level Percent WhitesBlacksHispanic MaleFemaleMaleFemaleMaleFemale < 4 yrs of H.S H. S Some College >4 yrs of College Total 100.0

Distribution of Employment by Gender/Race by Education Achievement: Male (percent) Total Employed Mgmt/ Pro. Tech/ Sales/ Admin Service Precision Prod. Oper. Fabric. Farm Forst Fish Male %18.83%8.54%19.73%18.27%3.46% <HS %7.04%13.12%27.63%37.03%9.73% HS %16.37%10.20%28.84%28.66%4.03% <CL %25.01%10.38%22.91%15.15%2.60% CL %20.67%3.54%4.69%3.06%1.23% White %18.84%7.47%20.49%17.18%3.68% <HS %7.13%11.82%28.99%36.12%10.22% HS %16.47%8.58%30.65%27.36%4.25% <CL %24.84%9.31%23.75%13.90%2.90% CL %20.63%3.25%4.48%2.67%1.34% Black %17.38%16.13%15.92%29.48%2.16% <HS %5.32%18.35%19.55%46.28%7.31% HS %14.51%19.17%18.54%38.85%2.45% <CL %24.53%17.10%17.22%24.23%0.73% CL %20.68%6.99%6.25%6.80%0.28%

Distribution of Employment by Gender/Race by Education Achievement: Male (percent) Total Employed Mgmt/ Pro. Tech/ Sales/ Admin Service Precision Prod. Oper. Fabric. Farm Forst Fish Male %18.83%8.54%19.73%18.27%3.46% <HS %7.04%13.12%27.63%37.03%9.73% HS %16.37%10.20%28.84%28.66%4.03% <CL %25.01%10.38%22.91%15.15%2.60% CL %20.67%3.54%4.69%3.06%1.23% White %18.84%7.47%20.49%17.18%3.68% <HS %7.13%11.82%28.99%36.12%10.22% HS %16.47%8.58%30.65%27.36%4.25% <CL %24.84%9.31%23.75%13.90%2.90% CL %20.63%3.25%4.48%2.67%1.34% Black %17.38%16.13%15.92%29.48%2.16% <HS %5.32%18.35%19.55%46.28%7.31% HS %14.51%19.17%18.54%38.85%2.45% <CL %24.53%17.10%17.22%24.23%0.73% CL %20.68%6.99%6.25%6.80%0.28%

Distribution of Employment by Gender/Race by Education Achievement: Male (percent) Total Employed Mgmt/ Pro. Tech/ Sales/ Admin Service Precision Prod. Oper. Fabric. Farm Forst Fish Male %18.83%8.54%19.73%18.27%3.46% <HS %7.04%13.12%27.63%37.03%9.73% HS %16.37%10.20%28.84%28.66%4.03% <CL %25.01%10.38%22.91%15.15%2.60% CL %20.67%3.54%4.69%3.06%1.23% White %18.84%7.47%20.49%17.18%3.68% <HS %7.13%11.82%28.99%36.12%10.22% HS %16.47%8.58%30.65%27.36%4.25% <CL %24.84%9.31%23.75%13.90%2.90% CL %20.63%3.25%4.48%2.67%1.34% Black %17.38%16.13%15.92%29.48%2.16% <HS %5.32%18.35%19.55%46.28%7.31% HS %14.51%19.17%18.54%38.85%2.45% <CL %24.53%17.10%17.22%24.23%0.73% CL %20.68%6.99%6.25%6.80%0.28%

Distribution of Employment by Gender/Race by Education Achievement: Female (percent) Total Employ ed Mgmt/ Pro. Tech/ Sales/ Admin Service Precision Prod. Oper. Fabric. Farm Forst Fish Female %38.88%15.45%2.15%7.51%1.03% <HS %20.71%40.32%4.48%25.50%3.00% HS %47.46%21.60%3.12%11.75%1.25% <CL %50.18%13.73%1.88%4.30%0.78% CL %23.35%3.49%0.71%1.03%0.48% White %39.51%13.98%2.04%6.82%1.17% <HS %22.16%37.77%4.60%25.54%3.58% HS %49.65%19.44%2.97%10.64%1.43% <CL %50.12%12.86%1.81%3.81%0.90% CL %22.76%3.26%0.61%0.95%0.54% Black %36.32%24.65%2.23%10.79%0.25% <HS %16.30%53.73%3.45%20.86%1.10% HS %36.37%33.62%3.02%17.21%0.27% <CL %50.45%18.01%1.82%6.64%0.10% CL %24.85%4.31%0.83%1.06%0.08%

MGT/PRO TEC/SAL/ADM SERVICE PRE/PROD OP/FAB F/F/F <HS HS <CL CL 0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00% Percent Job Type Education Level All Females Employment Distribution According To Education Level <HS HS <CL CL

Distribution of Employment by Gender/Race by Education Achievement: Female (percent) Total Employ ed Mgmt/ Pro. Tech/ Sales/ Admin Service Precision Prod. Oper. Fabric. Farm Forst Fish Female %38.88%15.45%2.15%7.51%1.03% <HS %20.71%40.32%4.48%25.50%3.00% HS %47.46%21.60%3.12%11.75%1.25% <CL %50.18%13.73%1.88%4.30%0.78% CL %23.35%3.49%0.71%1.03%0.48% White %39.51%13.98%2.04%6.82%1.17% <HS %22.16%37.77%4.60%25.54%3.58% HS %49.65%19.44%2.97%10.64%1.43% <CL %50.12%12.86%1.81%3.81%0.90% CL %22.76%3.26%0.61%0.95%0.54% Black %36.32%24.65%2.23%10.79%0.25% <HS %16.30%53.73%3.45%20.86%1.10% HS %36.37%33.62%3.02%17.21%0.27% <CL %50.45%18.01%1.82%6.64%0.10% CL %24.85%4.31%0.83%1.06%0.08%

Distribution of Employment by Gender/Race by Education Achievement: Female (percent) Total Employ ed Mgmt/ Pro. Tech/ Sales/ Admin Service Precision Prod. Oper. Fabric. Farm Forst Fish Female %38.88%15.45%2.15%7.51%1.03% <HS %20.71%40.32%4.48%25.50%3.00% HS %47.46%21.60%3.12%11.75%1.25% <CL %50.18%13.73%1.88%4.30%0.78% CL %23.35%3.49%0.71%1.03%0.48% White %39.51%13.98%2.04%6.82%1.17% <HS %22.16%37.77%4.60%25.54%3.58% HS %49.65%19.44%2.97%10.64%1.43% <CL %50.12%12.86%1.81%3.81%0.90% CL %22.76%3.26%0.61%0.95%0.54% Black %36.32%24.65%2.23%10.79%0.25% <HS %16.30%53.73%3.45%20.86%1.10% HS %36.37%33.62%3.02%17.21%0.27% <CL %50.45%18.01%1.82%6.64%0.10% CL %24.85%4.31%0.83%1.06%0.08%

Conclusions As compared to the 1970’s, at the end of the XX Century, American women have achieved parity in education attainments A white male college graduate is more likely to achieve managerial or professional status than the black male counterpart

Conclusions (continuation) A black male with less than a high school degree is more likely to be an operator or fabricator than the white male counterpart A white male with a high school degree is nearly twice as likely to be in managerial or professional status than the black counterpart

Conclusions (continuation) A white female with a high school degree is more likely to be in a technical/sales/administrative job than the black female counterpart. Black female college graduate is about as likely as her white counterpart to be in a managerial or professional job

Income Thus it appears that gender, race and education have an impact on the type of jobs and that has an impact on the wages Recall from an earlier handout the following table

HOUSEHOLD DATA ANNUAL AVERAGES ANNUAL AVERAGES 39. Median weekly earnings of full-time wage and salary workers by detailed occupation and sex (Numbers in thousands) 2005 Both sexes Men Women Occupation Number Median Number Median Number Median of weekly of weekly of weekly workers earnings workers earnings workers earnings Total, 16 years and over ,560 $651 58,406 $722 45,154 $585 Management, professional, and related occupations , ,311 1,113 18, Management, business, and financial operations occupations , ,195 1,167 6, Professional and related occupations , ,116 1,058 11, Service occupations , , , Sales and office occupations , , , Sales and related occupations , , , Office and administrative support occupations , , , Natural resources, construction, and maintenance occupations , , Farming, fishing, and forestry occupations Construction and extraction occupations , , Installation, maintenance, and repair occupations , , Production, transportation, and material moving occupations , , , Production occupations , , , Transportation and material moving occupations , ,

Marital Status Since financing Human Capital is so expensive and uncertain The marital status of the individual may have some barring on the investment

Women Have not Always faired as well Early in the XX Century women were not even allowed to obtain Professional degrees Very few went beyond high school

Percentage of Degrees Awarded to Women by Level, to Years Percent AssociateBachelorsMaster’sDoctor’s1 st Professional n.a n.a n.a

Table 287

Associate’s Degrees Earned by Race/Ethnicity Race or Ethnicity YEAR Number/Percent 410,174455,102635,912 White Black Hispanic Asian American Indian Non-Resident Alien

Bachelor’s Degrees Earned by Race/Ethnicity Race or Ethnicity YEAR Number/Percent 934,8001,051,3441,348,503 White Black Hispanic Asian American Indian Non-Resident Alien

Master’s Degrees Earned by Race/Ethnicity Race or Ethnicity YEAR Number/Percent 294,183324,301512,645 White Black Hispanic Asian American Indian Non-Resident Alien

Doctor’s Degrees Earned by Race/Ethnicity Race or Ethnicity YEAR Number/Percent 32,83938,37146,024 White Black Hispanic Asian American Indian Non-Resident Alien

But What is The Degree for? Are women selecting specific fields or are they searching for all fields Is there any fields that they avoid and what are the requirements

Percentage of Women obtain a Bachelor’s Degree tbl 288 Discipline Agricultural and Special Resources Architecture and related Programs Biological vs. Life Science Business Administration Computer and Information Services Education Engineering English and English Literature Foreign Languages Health Home Economics Mathematics Physical science and science technology Psychology Economics History Sociology

Relating Education and Wages The Following 3 Tables Show Median and Mean Income based on Level of Education by Gender