Progressive increase in educational levels of the population 1940: 60% Elementary Educated, 5% college educated 2004: 7% elementary educated, 25% college educated

Money Earnings (Mean) for Full-Time, Year-Round Male Workers, 2003 Lifetime Sum of College vs High School Earnings $593,000

Money Earnings (Mean) for Full-Time, Year- Round Female Workers, 2003 Lifetime Sum of College vs High School Earnings $415,000

Does this Mean College Pays for Itself?

College Enrollment and College Wage Premium Based on Ehrenberg and Smith. 2006: Table 9.1, p. 286

College Enrollment and College Wage Premium Based on Ehrenberg and Smith. 2006: Table 9.1, p point increase in wage premium raise male enrollment by 1 point 3 point increase in wage premium raise female enrollment by 1 point

Male Profile Female Profile

Stylized Facts Regarding Age Earnings Profiles 1)All profiles flatten with age Most rapid wage growth early in career 2)Earnings increase with education 3)Earnings gap between education groups widens with age 4)Male female comparisons 1)Female earnings lower than male earnings 2)Female wage profiles flatter than men Note: These are synthetic cohorts—longitudinal data may differ especially for women

Factors affecting returns to college in the Human Capital Model H t = Earnings from High School Education in year t S t = Earnings from College Education in year t C t = College Tuition in year t r = Rate of time preference T = Time Span

Factors affecting returns to college in the Human Capital Model PV S = PV C = Present Value of College Costs PV S = Present Value of College Salary

H t => decreases incentive to invest S t => increases incentive to invest C t => decreases incentive to invest r => decreases incentive to invest T => increases incentive to invest NPV = Factors affecting returns to college in the Human Capital Model NPV: Net Present Value

Internal rate of return: the interest rate that sets NPV = 0 Measure of the returns to college NPV = Factors affecting returns to college in the Human Capital Model

How does human capital investment model explain the pattern of age earnings profiles? 1)All profiles flatten with age Most rapid wage growth early in career Role of T in human capital investment As age increases, incentive to invest falls

How does human capital investment model explain the pattern of age earnings profiles? 2)Earnings increase with education S>H required for investment

How does human capital investment model explain the pattern of age earnings profiles? 3)Earnings gap between education groups widens with age More educated get more firm-provided training Sorting on r: More educated have lower r?

How does human capital investment model explain the pattern of age earnings profiles? 4) Male female comparisons 1)Female earnings lower than male earnings Discrimination? Role of discontinuous labor supply Human capital decay affects occupational choice Absence decreases wages

Source: Anne Preston (2004) Leaving Science: Occupational Exit from Scientific Careers

How does human capital investment model explain the pattern of age earnings profiles? 2)Male female comparisons 2) Female wage profiles flatter than men Role of marital status in age earnings profiles

How does human capital investment model explain the pattern of age earnings profiles? 2)Male female comparisons 2)Female wage profiles flatter than men How have these changed over time

Women's Age/Earnings Profiles Getting Steeper

Occupational/Educational Choices getting more similar between men and women

How high do returns have to be for college to break even? NPV = = 0 at breakeven C = $5,000/year H = 20,000/year for 44 years r = 0.10 PV College cost = $79,250 Breakeven S – H = $8,104 over 40 years Total: $324,000 C = $15,000/year H = 20,000/year for 44 years r = 0.10 PV College cost = $110,950 Breakeven S – H = $11,346 over 40 years Total: $453,830

Diminishing returns to schooling Why?

Diminishing returns to schooling Why? Opportunity cost Direct cost Marginal Product of time invested in schooling

Computing returns to schooling ln(W) = β 0 + β 1 ED + β 2 EXP + β 3 EXP^2 + γZ + ε β 1 is a measure of the percentage returns to an additional year of schooling Log Earnings Function

Alternative estimates of the returns to schooling as summarized in David Card, Handbook of Labor Economics Vol. 3A Card, Card, 1999 Men0.106 Women0.110 Conneely and Uusitalo, Ashenfelter and Zimmerman, – 0.109

If individuals get returns to schooling, why should the public subsidize it?

Externalities: Benefits go to individuals other than the one receiving schooling =>Individuals will underinvest relative to social optimum Liquidity constraints: individuals cannot borrow against future expected returns =>Poor will underinvest

Iowa State University Revenue by Source, FY2005

Revenues rose by 13.7% compared to 12.3% for inflation Iowa State University Revenue by Source, FY2001 and FY2005 (Thousands of dollars) 1 Iowa State Center, Residence System, University Bookstore, Athletic Department. 2Ames Laboratory. 3Sales of educational activities and equipment, investment income

Source: What D'Ya Know? Lifetime Learning in Pursuit of the American Dream 2004 Annual Report—Federal Reserve Bank of Dallas Higher Proportion Educated means higher per capita income, faster growth Correlation or causation?

45 o line: male = female >0: Rural Male ed > Female ed >0: Urban Male ed > Female ed Higher enrollment Quad 1: Males Quad 2: Urban male, Rural Females Quad 3: Females Quad 4: Rural Males, Urban Females III IIIIV Male and Female Enrollment Rates, Ages 15-17, 70 Developing countries

If individuals get returns to schooling, why should the public subsidize it? Are externalities bigger for women? Fertility Health