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Explained Differences: The Human Capital Model
Spring 2010
Rosburg (ISU) Human Capital Model Spring 2010 1 / 57
Supply-Side Explanations
Differences in occupations and earnings can be from either demand-side(employer) or supply-side (employee) factors.
Supply-side factors:
Different tastes of potential/current employees
Different qualifications of potential/current employees (i.e. education,experience, training, etc.)
Such differences could cause certain groups (race, sex, etc.) to earn lessand concentrate in different occupations
Rosburg (ISU) Human Capital Model Spring 2010 2 / 57
Employee differences
Differences in tastes and qualifications may come from two sources:
Voluntary choices of employees
Societal Discrimination
Definition: Multitude of societal influences that cause specific groups(ex. women) to make decisions that adversely influence their status inthe labor market
Different than labor market discrimination
Rosburg (ISU) Human Capital Model Spring 2010 3 / 57
Human Capital
Human Capital (HK) - resources invested in an individual today in orderto increase his or her future productivity and earnings
Alternative definition: stock of marketable skill and knowledgeembodied in a worker that may be rented on the labor market
Stock: not used up at once but offers stream of services
Marketable: includes only the skills that are important in the labormarket
Embodied, rented: employer cannot access stock without paying theholder
Rosburg (ISU) Human Capital Model Spring 2010 4 / 57
Human Capital II
Examples: formal education, on-the-job training, job search methods,geographic migration, health
Similarities to physical capital (K):
Depreciation
Investment
Stock
Differences from physical capital (K):
Influenced more by non-pecuniary costs (ex: distaste for school)
More difficult to finance investment in human capital – no collateralto offer if loan not repaid
Rosburg (ISU) Human Capital Model Spring 2010 5 / 57
Education Differences
Gender Differences in HK - Education
Educational attainment differences are not large in US
Recall Goldin et al.’s (2006) article on reversal of college gender gap
Women less likely to drop out of high school
Gender differences in educational attainment by race
Whites: men and women nearly equalAsians: men have edgeBlacks and Hispanics: women have edge
Declining gender difference in educational attainment among youngercohorts
Rosburg (ISU) Human Capital Model Spring 2010 6 / 57
Education Differences
Gender Differences in HK - Education II
Differences in high school courses taken:
There has been considerable progress in reducing differences in HScourses
Higher proportion of men take AP exams in science and calculus andscore higher on average than women
Differences in college fields of specialization:
Differences in fields of specialization more substantial than differencesin high school courses
Index of segregation by college major:
1964: 51.41990: 29.4
Rosburg (ISU) Human Capital Model Spring 2010 7 / 57
Education Differences
Differences in HK - Education III
Blacks and Hispanics have lower educational attainment relative to whites
Difference smaller for blacks
Note: Even though men and women have similar educational attainment,gender differences in amount and type of education may impact earningsand occupational attainment
Rosburg (ISU) Human Capital Model Spring 2010 8 / 57
Educational Investment Model
Educational Investment Model (EIM)
Basics:
Individual makes decision whether to invest in formal education or not
Considers both pecuniary and non-pecuniary benefits and costs
Two types of pecuniary costs:
Direct costs - expenditures such as tuition, fees and booksIndirect costs - earnings foregone during time in school [opportunitycost]
Compare expected experience-earnings profiles associated witheach type of schooling
Definition: Annual earnings at each level of labor market experience
Rosburg (ISU) Human Capital Model Spring 2010 9 / 57
Educational Investment Model
Educational Investment Model (EIM) II
Evaluates incremental costs and benefits
Obtain additional education if net benefits (benefits - costs) areabove a given threshold
Threshold may vary by individualForgone interest if money had been invested in a bank insteadDelayed gratificationDecision can not be determined graphically
For simplicity, all graphs will exclude non-pecuniary costs or benefitsunless specified
On average, private rate of return to college education ranges from 5to 15 percent
Rosburg (ISU) Human Capital Model Spring 2010 10 / 57
Educational Investment Model Education
Experience-earnings profile by education level
College profile: ABCRHigh School profile: OEDR’
Rosburg (ISU) Human Capital Model Spring 2010 11 / 57
Educational Investment Model Education
Two views of education
1 Productivity Enhancing
Provides a variety of skills and knowledge that are potentially useful inthe job marketTeaches desirable behaviors (punctuality, following instructions,dependability, etc.)
2 Screening device or signal
Education may be used to distinguish more productive applicants fromless productive applicants during hiring processIf employers believe education signals different productivity for peopleof different groups, unfavored group members need higher education toget same job (statistical discrimination)
Difficult to resolve but the reason doesn’t matter from individual’sperspective in EIM
Rosburg (ISU) Human Capital Model Spring 2010 12 / 57
Educational Investment Model Expected Work Life
EIM - Expected Work Life
Women may anticipate shorter, more disrupted work lives than men
Lowers incentive to make HK investments which:
1 Require sustained, high-level commitment to payoff2 Depreciate rapidly during interrupted periods
As young women anticipate longer and more continuous work lives, it willbe more profitable to increase investment in formal education
Rosburg (ISU) Human Capital Model Spring 2010 13 / 57
Educational Investment Model Expected Work Life
Discontinuous Worker
Return to college education without interruption: DRR’Return to college education with interruption: grey areasWork-force interruption reduces return to investment
Rosburg (ISU) Human Capital Model Spring 2010 14 / 57
Educational Investment Model Expected Work Life
EIM - Discontinuous Worker
Discontinuity of expected labor force participation may help explaingender differences in fields of specialization
Returning women have depreciation of skills AND face advancementof field during absence
May avoid fields with rapid technological progress
Note: Gender differences in college major is strongly related to thegender wage gap among college graduates
Expectations may affect which area of specialization a person chooseswhich leads to wage differences
Rosburg (ISU) Human Capital Model Spring 2010 15 / 57
Educational Investment Model Other Factors
Other factors - Educational Investment
Societal discrimination may cause differences in educationalattainment and fields of specialization
Need to consider non-pecuniary costs and benefits
Feedback effects: faced with discrimination in labor market, whichlowers returns to HK investment, individuals facing discrimination willhave less incentive to invest.
Socialization: process by which the influence of family, friends,teachers and media shapes an individual’s attitude and behavior
Rosburg (ISU) Human Capital Model Spring 2010 16 / 57
Educational Investment Model Other Factors
Socialization
Television and movies
Taught or influenced at early age to aspire and train forgender-appropriate jobs
Potential disapproval of family, teachers or friends is a non-pecuniarycost → lowers net value of investment
Example: Barbie and Ken
1 in 100,000 young women will have shape of Barbie1 in 50 young men will have shape of Ken
Some stores have separate toy aisles for ‘girls’ and ‘boys’ toys
Merchants argue they are responding to children’s preferencesPerpetuate traditional gender roles by limiting children’s visions
Rosburg (ISU) Human Capital Model Spring 2010 17 / 57
Educational Investment Model Other Factors
Gender-Appropriate Traits and Consequences
Female-dominated fields may be socialized to emphasize “feminine” traits:
subordinate, nurturing, emotional
Male-dominated fields may be stereotyped as requiring “masculine” traits:
dominance, competitiveness, rationality
Women may avoid male-dominated fields due to:
Non-pecuniary costs of acting in an “unfeminine” way
Perception that they are unequipped to act in an “unfeminine” way
Rosburg (ISU) Human Capital Model Spring 2010 18 / 57
Educational Investment Model Other Factors
Example - Women and Math Stereotype
Stereotype: Women have inferior math skills
Psychology study tested impact of stereotype on performance
Women may worry that difficulty during the test or poor performancecould be judged as proof of stereotype – extra pressure or stress
Participants were university men and women with equivalent mathbackgrounds and interests
Rosburg (ISU) Human Capital Model Spring 2010 19 / 57
Educational Investment Model Other Factors
Women and Math Stereotype Study - Results
First group: Gave participants either easy or difficult math test with onlyinformation about difficulty level
Women performed worse than men on the difficult test only
Second group: Gave the difficult test to all participants. Half of theparticipants were told the test had shown gender differences in past andother half were told it was a gender fair test.
Told gender fair → women performed equally well
Told gender differences → women scored lower
More evidence of “blanking-out” or “choking”
Rosburg (ISU) Human Capital Model Spring 2010 20 / 57
Educational Investment Model Other Factors
Women and Math Stereotype Study - Results II
Conclusion: If math skills can be judged negatively, even when controllingfor math interest and background, women’s performance is influenced bygender stereotypes when combined with stress and anxiety.
Similar results found for:
African-Americans and Latinos in intellectual situations
Elderly in memory testing
White men in sports
Rosburg (ISU) Human Capital Model Spring 2010 21 / 57
Educational Investment Model Other Factors
Discrimination by Educational Institutions
Overt discrimination against women (and other minorities) in collegeadmission and professional school in not-so-distant past
Occurred at highly respected institutions (ex: Princeton, Yale)
Allowed access to classes and certain facilities but minorities weresometimes limited to separate colleges
‘Opening of doors’ does not mean it has been opened as wide
Minorities held to higher standardsOvert or informal quotasDifferent course requirements
Rosburg (ISU) Human Capital Model Spring 2010 22 / 57
Educational Investment Model Other Factors
Subtle Barriers to Women
Overt barriers are beginning to decline but subtle barriers remain a problem
Male dominance in field may discourage young women from attempting toenter
Lack of role models (lack mentor-protege system)
Lack successful strategies or plan for combining work and family roles
Forced pioneers – more difficult than well-established path
Exclusion from informal networks (i.e. study groups and discussions)
Rosburg (ISU) Human Capital Model Spring 2010 23 / 57
Educational Investment Model Other Factors
Subtle Barriers to Women II
Informal contact between teachers and students and among studentsprovide:
Support
Encouragement
Access to information
Lack of informal contact raises non-pecuniary cost
May result in feedback effects (lower incentive to invest)
Problem: Quantitative evidence difficult to gather
Rosburg (ISU) Human Capital Model Spring 2010 24 / 57
Educational Investment Model On-the-Job Training
On-the-Job Training
Similar to investment in education, human capital theory suggests thatweaker attachment to labor force of women who follow “traditional”gender roles lowers their incentive to acquire on-the-job training
Two types of on-the-job training:
1 General training: increases productivity in all firms
2 Firm-specific training: increases productivity only at firm whichprovides training
Note: Usually a mixture of both but will assume separate for simplicity
Rosburg (ISU) Human Capital Model Spring 2010 25 / 57
Educational Investment Model On-the-Job Training
General Training
Employer will not pay any costs since collects no return - employeecan abandon job at any point and use skills from general training atnew job
Employee bears all costs and reaps all return
During training, employee transfers attention from daily production totraining
Decline in output is opportunity cost to firm of trainingEmployee will initially accept wage below what could get elsewhere dueto expected future benefits from training
Rosburg (ISU) Human Capital Model Spring 2010 26 / 57
Educational Investment Model On-the-Job Training
Experience-Earnings Profile for General Training
No training: UU’
General training: GG’
Rosburg (ISU) Human Capital Model Spring 2010 27 / 57
Educational Investment Model On-the-Job Training
Firm-Specific Training
Benefits from training are firm-specific – if employee leaves, trainingwill not be beneficial at new job
Employee will not bear all costs since ability to reap returns dependson continued employment at firm
Employer will not bear all costs since employee would have noincentive to remain at firm unless you provide them with a financialincentive
Share costs and returns
Employer has incentive to retain workerEmployee develops a relatively permanent attachment
Rosburg (ISU) Human Capital Model Spring 2010 28 / 57
Educational Investment Model On-the-Job Training
Experience-Earnings profile for Firm-Specific Training
Employee return to firm-specific training: GG’
Employer return to firm-specific training: SS’
Benefits and costs noted in diagram
Rosburg (ISU) Human Capital Model Spring 2010 29 / 57
Educational Investment Model On-the-Job Training
Experience and Earnings
HK theory: earnings increase with experience since work productivity isaugmented by on-the-job training
Critics are not sure if this causes higher earnings
Rise in earnings may be result of widespread use of seniorityarrangements
Rosburg (ISU) Human Capital Model Spring 2010 30 / 57
Educational Investment Model On-the-Job Training
Experience and Earnings - Alternative Argument
Alternative explanation: upward-sloping earnings profiles rewardsexperience which raises productivity through the motivation to gainbenefits of tenure (retirement, higher earnings)
Higher productivity NOT due to training
Productivity does NOT rise with experience
Focus is on tenure
Empirical evidence mixed
Again, the reason doesn’t matter from the individual’s perspective
Rosburg (ISU) Human Capital Model Spring 2010 31 / 57
Educational Investment Model On-the-Job Training
Gender Differences in Training Investment
Gross return to on-the-job training depends on number of years overwhich the return is earned
Workforce interruption lowers earning profiles due to depreciation ofskills
Next graph illustrates consequences on the incentive to invest infirm-specific training of shorter and more discontinuous labor forceparticipation [i.e. women following ‘traditional’ path]
Women in traditional gender roles find it less profitable to make largeinvestments in training than career-oriented men or women
Rosburg (ISU) Human Capital Model Spring 2010 32 / 57
Educational Investment Model On-the-Job Training
Discontinuous Worker and Firm-Specific Training
Rosburg (ISU) Human Capital Model Spring 2010 33 / 57
Educational Investment Model On-the-Job Training
Discontinuous Worker and Firm-Specific Training II
If exit, may not be able to get old job back
Firm-specific skills useless (return to profile without training)
Returns to investment wiped out
Unless guaranteed reemployment, employee faces risk of losing returns
HK theory suggests that workers who anticipate workforce interruptions oflong or uncertain duration will avoid jobs where firm-specific training isimportant (ex: ‘traditional’ wife)
Rosburg (ISU) Human Capital Model Spring 2010 34 / 57
Educational Investment Model On-the-Job Training
Expected Work Tenure and Training
Empirical evidence supports prediction that women receive less on-the-jobtraining
As labor force attachment and career-orientation increase → profitabilityof investment increases
Most important factor for firm-specific training is attachment to firm
Yet, differences in training are not fully explained by factors emphasized inthe HK model → discrimination has a role
Rosburg (ISU) Human Capital Model Spring 2010 35 / 57
Educational Investment Model On-the-Job Training
Occupations and Earnings - Gender DifferencesBased on the HK model, women fulfilling ‘traditional’ roles are expectedto:
Select occupations requiring less investment in education andon-the-job training
Employers may also be reluctant to hire women in these jobs(statistical discrimination)
Seek jobs where depreciation of earnings for time spent out of laborforce is minimal
Choose occupations with higher earnings now rather than in future
Avoid jobs where pay is highly dependent on experienceMay cause occupational segregation
Search less for best available job
Rosburg (ISU) Human Capital Model Spring 2010 36 / 57
Educational Investment Model On-the-Job Training
Gender Differences in Occupations and Training
Earnings profiles in male jobs: MM’Earnings profiles in female jobs: FF’
Rosburg (ISU) Human Capital Model Spring 2010 37 / 57
Educational Investment Model On-the-Job Training
Additional Supply-side Factors
Traditional gender roles (i.e. women as secondary earner)
Housework time may reduce available effort for work
Women are more likely to quit for family-related reasons
Non-market responsibilities
Availability of maternity leave mitigates this effect
Priority of husband’s career:
“Tied mover” - forced to relocate when not advantageous“Tied stayer” - forced to forgo good opportunities elsewhere
Rosburg (ISU) Human Capital Model Spring 2010 38 / 57
Educational Investment Model On-the-Job Training
Assessment of Human Capital Model
Most studies find HK important in explaining the gender pay gap
Other important factors: tenure, work interruptions, and timing of pastwork experience
Young women who expected to be working at 35 have experience-wageprofiles that start lower but have a steeper slope compared to women whodo not plan to be working at 35.
Expected to not work at 35: took higher paying jobs with lowerexpected wage growth
HK theory as the explanation for gender differences in occupations hasmixed results
Rosburg (ISU) Human Capital Model Spring 2010 39 / 57
Educational Investment Model On-the-Job Training
Evidence for the HK Model
A substantial portion of the pay difference is accounted for bydifferent skill requirements between male and female jobs
Married women have lower penalties for reentering the labor force infemale-dominated rather than male-dominated jobs
Women with limited expected future labor force participation selectoccupations with lower job skill requirements
Rosburg (ISU) Human Capital Model Spring 2010 40 / 57
Educational Investment Model On-the-Job Training
Evidence against HK model
In the diagram for women’s and men’s occupations and training,there was a crossover point in the experience-earnings profile → nocrossover point in the data
Returns to education are not higher for women in male-dominatedjobs versus female-dominated jobs
Earnings of women in female-dominated jobs do not depreciate lessthan in male-dominated jobs
Women with discontinuous work history were no more likely to be infemale-dominated occupations than women continuously employed
Overall: Labor force commitment and participation ingender-dominated jobs are not as closely associated as the HKexplanation for segregation suggests
Rosburg (ISU) Human Capital Model Spring 2010 41 / 57
Empirical Evidence
EMPIRICAL EVIDENCE
Rosburg (ISU) Human Capital Model Spring 2010 42 / 57
Empirical Evidence
2003 Distribution of Educational Attainment (25-64)1
Larger differences in investment in education across races thanbetween males and females
1Source: Blau, Ferber, Winkler. 2006. The Economics of Women, Men and Work.5th Edition.
Rosburg (ISU) Human Capital Model Spring 2010 43 / 57
Empirical Evidence
Ratio of College Graduate Rates at 35 by Birth Year2
Increase during Great DepressionOther significant events: GI Bill, WWII, Korea, Vietnam
2Source: Goldin, Katz and Kuziemko. 2006. “Homecoming of American Women.”Journal of Economic Perspectives.
Rosburg (ISU) Human Capital Model Spring 2010 44 / 57
Empirical Evidence
Education by Race3
High school gap convergingCollege gap seems to be widening
3Source: Lang. 2007. Poverty and Discrimination. Princeton University Press.Rosburg (ISU) Human Capital Model Spring 2010 45 / 57
Empirical Evidence
Male Mean Earnings by Education in 2003
Limited to full-time, year-round MALE workers
Lifetime difference between college and HS earnings: $593,000
Rosburg (ISU) Human Capital Model Spring 2010 46 / 57
Empirical Evidence
Female Mean Earnings by Education in 2003
Limited to full-time, year-round FEMALE workers
Lifetime difference between college and HS earnings: $415,000
Rosburg (ISU) Human Capital Model Spring 2010 47 / 57
Empirical Evidence
Earnings by education
Given the high lifetime benefits of college ($593,000 for men and $415,000for women), does this imply that college pays for itself on average?
Recall: minimum returns to invest (threshold) varies by individual
Will depend on how much they discount future earnings
Rosburg (ISU) Human Capital Model Spring 2010 48 / 57
Present Value
PRESENT VALUE
Rosburg (ISU) Human Capital Model Spring 2010 49 / 57
Present Value
Present Value of HK Investment
Investment in human capital provides benefits for many years (stock)
Make decision today based on expected payoffs in the future → need tocalculate present value
Present value: today’s value of a future payment or series of futurepayments discounted to reflect the time value of money
Rosburg (ISU) Human Capital Model Spring 2010 50 / 57
Present Value
Present Value of HK
Since investment in HK typically provides benefits for many years and thevalue typically changes annually, we cannot use a standard form forpresent value.
Present value of the full set of benefits is calculated by dividing each year’sbenefit by (1 + r)T where r is the individual’s time preference (i.e. discountrate) and T is the number of years in the future the benefit will be received
Let:
Ht = Earnings from High School Education in year t
Et = Earnings from College Education in year t
Ct = College tuition and costs in year t
Rosburg (ISU) Human Capital Model Spring 2010 51 / 57
Present Value
Present Value of HK II
PVE = Present Value of Earnings with a College Degree
PVE =E5
(1 + r)5+
E6
(1 + r)6+
E7
(1 + r)7+ . . . +
ET
(1 + r)T
PVC = Present Value of College Costs (including opportunity costs)
PVC =H1 + C1
(1 + r)+
H2 + C2
(1 + r)2+
H3 + C3
(1 + r)3+
H4 + C4
(1 + r)4+
H5
(1 + r)5. . .+
HT
(1 + r)T
Rosburg (ISU) Human Capital Model Spring 2010 52 / 57
Present Value
Net Present Value
Net present value (NPV) is the difference between the present value ofbenefits (salary) less the present value of costs (direct and indirect)
NPV = −H1 + C1
(1 + r)− H2 + C2
(1 + r)2− H3 + C3
(1 + r)3− H4 + C4
(1 + r)4+
E5 − H5
(1 + r)5+ . . . +
ET − HT
(1 + r)T
Incentive to invest:
Increasing in: Et , T
Decreasing in: Ht , Ct , r
Rosburg (ISU) Human Capital Model Spring 2010 53 / 57
Present Value
Net Present Value
Investment Decision:
NPV > 0→ Go to college
NPV < 0→ Don’t go to college
NPV = 0→ Indifferent
There exists some r̄ such that NPV = 0
r̄ is the individual’s internal rate of return
Rosburg (ISU) Human Capital Model Spring 2010 54 / 57
Present Value
Example 1: Returns Necessary for College to Breakeven
Case 1:
C = $5,000/year
H = $20,000/year for 44 years
r = 0.10→ PV College cost = $79,250
For breakeven [NPV = 0] need
PV of earnings with a college degree to equal $79,250 or, equivalently
E - H = $8,104 for 40 years (or E = $28,104)
Lifetime gains of a college degree relative to a high school degreeneeds to be: $324,000
Given earlier statistics, the mean returns for men and women would beenough to incentivize investment for both men and women on average
Rosburg (ISU) Human Capital Model Spring 2010 55 / 57
Present Value
Example 2: Returns Necessary for College to Breakeven
Case 2:
C = $15,000/year
H = $20,000/year for 44 years
r = 0.10→ PV College cost = $110,950
For breakeven (NPV = 0) need:
PV of earnings with a college degree to equal $110,950 or,equivalently
E - H = $11,346 for 40 years (or E = $31,346)
Lifetime gains need to be: $453,830
Given earlier statistics, mean returns for men would be enough toincentivize investment in college but not for women
Rosburg (ISU) Human Capital Model Spring 2010 56 / 57
Present Value
Readings for Next Section:
Newspaper Articles Handout
Case Evidence - Women
Blau and Kahn (2000)
Blau and Kahn (2006)
Rosburg (ISU) Human Capital Model Spring 2010 57 / 57
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