Explained Differences: The Human Capital Model

Transcription

1 Explained Differences: The Human Capital Model Spring 2010 Rosburg (ISU) Human Capital Model Spring / 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 less and concentrate in different occupations Rosburg (ISU) Human Capital Model Spring / 57

2 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 in the labor market Different than labor market discrimination Rosburg (ISU) Human Capital Model Spring / 57 Human Capital Human Capital (HK) - resources invested in an individual today in order to increase his or her future productivity and earnings Alternative definition: stock of marketable skill and knowledge embodied 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 labor market Embodied, rented: employer cannot access stock without paying the holder Rosburg (ISU) Human Capital Model Spring / 57

3 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 collateral to offer if loan not repaid Rosburg (ISU) Human Capital Model Spring / 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 equal Asians: men have edge Blacks and Hispanics: women have edge Declining gender difference in educational attainment among younger cohorts Rosburg (ISU) Human Capital Model Spring / 57

4 Education Differences Gender Differences in HK - Education II Differences in high school courses taken: There has been considerable progress in reducing differences in HS courses Higher proportion of men take AP exams in science and calculus and score higher on average than women Differences in college fields of specialization: Differences in fields of specialization more substantial than differences in high school courses Index of segregation by college major: 1964: : 29.4 Rosburg (ISU) Human Capital Model Spring / 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 earnings and occupational attainment Rosburg (ISU) Human Capital Model Spring / 57

5 (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 books Indirect costs - earnings foregone during time in school [opportunity cost] Compare expected experience-earnings profiles associated with each type of schooling Definition: Annual earnings at each level of labor market experience Rosburg (ISU) Human Capital Model Spring / 57 (EIM) II Evaluates incremental costs and benefits Obtain additional education if net benefits (benefits - costs) are above a given threshold Threshold may vary by individual Forgone interest if money had been invested in a bank instead Delayed gratification Decision can not be determined graphically For simplicity, all graphs will exclude non-pecuniary costs or benefits unless specified On average, private rate of return to college education ranges from 5 to 15 percent Rosburg (ISU) Human Capital Model Spring / 57

6 Education Experience-earnings profile by education level College profile: ABCR High School profile: OEDR Rosburg (ISU) Human Capital Model Spring / 57 Education Two views of education 1 Productivity Enhancing Provides a variety of skills and knowledge that are potentially useful in the job market Teaches desirable behaviors (punctuality, following instructions, dependability, etc.) 2 Screening device or signal Education may be used to distinguish more productive applicants from less productive applicants during hiring process If employers believe education signals different productivity for people of different groups, unfavored group members need higher education to get same job (statistical discrimination) Difficult to resolve but the reason doesn t matter from individual s perspective in EIM Rosburg (ISU) Human Capital Model Spring / 57

7 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 payoff 2 Depreciate rapidly during interrupted periods As young women anticipate longer and more continuous work lives, it will be more profitable to increase investment in formal education Rosburg (ISU) Human Capital Model Spring / 57 Expected Work Life Discontinuous Worker Return to college education without interruption: DRR Return to college education with interruption: grey areas Work-force interruption reduces return to investment Rosburg (ISU) Human Capital Model Spring / 57

8 Expected Work Life EIM - Discontinuous Worker Discontinuity of expected labor force participation may help explain gender differences in fields of specialization Returning women have depreciation of skills AND face advancement of field during absence May avoid fields with rapid technological progress Note: Gender differences in college major is strongly related to the gender wage gap among college graduates Expectations may affect which area of specialization a person chooses which leads to wage differences Rosburg (ISU) Human Capital Model Spring / 57 Other Factors Other factors - Educational Investment Societal discrimination may cause differences in educational attainment and fields of specialization Need to consider non-pecuniary costs and benefits Feedback effects: faced with discrimination in labor market, which lowers returns to HK investment, individuals facing discrimination will have 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 / 57

9 Other Factors Socialization Television and movies Taught or influenced at early age to aspire and train for gender-appropriate jobs Potential disapproval of family, teachers or friends is a non-pecuniary cost lowers net value of investment Example: Barbie and Ken 1 in 100,000 young women will have shape of Barbie 1 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 preferences Perpetuate traditional gender roles by limiting children s visions Rosburg (ISU) Human Capital Model Spring / 57 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 / 57

10 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 performance could be judged as proof of stereotype extra pressure or stress Participants were university men and women with equivalent math backgrounds and interests Rosburg (ISU) Human Capital Model Spring / 57 Other Factors Women and Math Stereotype Study - Results First group: Gave participants either easy or difficult math test with only information about difficulty level Women performed worse than men on the difficult test only Second group: Gave the difficult test to all participants. Half of the participants were told the test had shown gender differences in past and other 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 / 57

11 Other Factors Women and Math Stereotype Study - Results II Conclusion: If math skills can be judged negatively, even when controlling for math interest and background, women s performance is influenced by gender 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 / 57 Other Factors Discrimination by Educational Institutions Overt discrimination against women (and other minorities) in college admission 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 were sometimes limited to separate colleges Opening of doors does not mean it has been opened as wide Minorities held to higher standards Overt or informal quotas Different course requirements Rosburg (ISU) Human Capital Model Spring / 57

12 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 to enter 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 / 57 Other Factors Subtle Barriers to Women II Informal contact between teachers and students and among students provide: 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 / 57

13 Similar to investment in education, human capital theory suggests that weaker 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 which provides training Note: Usually a mixture of both but will assume separate for simplicity Rosburg (ISU) Human Capital Model Spring / 57 General Training Employer will not pay any costs since collects no return - employee can abandon job at any point and use skills from general training at new job Employee bears all costs and reaps all return During training, employee transfers attention from daily production to training Decline in output is opportunity cost to firm of training Employee will initially accept wage below what could get elsewhere due to expected future benefits from training Rosburg (ISU) Human Capital Model Spring / 57

14 Experience-Earnings Profile for General Training No training: UU General training: GG Rosburg (ISU) Human Capital Model Spring / 57 Firm-Specific Training Benefits from training are firm-specific if employee leaves, training will not be beneficial at new job Employee will not bear all costs since ability to reap returns depends on continued employment at firm Employer will not bear all costs since employee would have no incentive to remain at firm unless you provide them with a financial incentive Share costs and returns Employer has incentive to retain worker Employee develops a relatively permanent attachment Rosburg (ISU) Human Capital Model Spring / 57

15 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 / 57 Experience and Earnings HK theory: earnings increase with experience since work productivity is augmented by on-the-job training Critics are not sure if this causes higher earnings Rise in earnings may be result of widespread use of seniority arrangements Rosburg (ISU) Human Capital Model Spring / 57

16 Experience and Earnings - Alternative Argument Alternative explanation: upward-sloping earnings profiles rewards experience which raises productivity through the motivation to gain benefits 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 / 57 Gender Differences in Training Investment Gross return to on-the-job training depends on number of years over which the return is earned Workforce interruption lowers earning profiles due to depreciation of skills Next graph illustrates consequences on the incentive to invest in firm-specific training of shorter and more discontinuous labor force participation [i.e. women following traditional path] Women in traditional gender roles find it less profitable to make large investments in training than career-oriented men or women Rosburg (ISU) Human Capital Model Spring / 57

17 Discontinuous Worker and Firm-Specific Training Rosburg (ISU) Human Capital Model Spring / 57 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 of long or uncertain duration will avoid jobs where firm-specific training is important (ex: traditional wife) Rosburg (ISU) Human Capital Model Spring / 57

18 Expected Work Tenure and Training Empirical evidence supports prediction that women receive less on-the-job training As labor force attachment and career-orientation increase profitability of investment increases Most important factor for firm-specific training is attachment to firm Yet, differences in training are not fully explained by factors emphasized in the HK model discrimination has a role Rosburg (ISU) Human Capital Model Spring / 57 Occupations and Earnings - Gender Differences Based on the HK model, women fulfilling traditional roles are expected to: Select occupations requiring less investment in education and on-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 labor force is minimal Choose occupations with higher earnings now rather than in future Avoid jobs where pay is highly dependent on experience May cause occupational segregation Search less for best available job Rosburg (ISU) Human Capital Model Spring / 57

19 Gender Differences in Occupations and Training Earnings profiles in male jobs: MM Earnings profiles in female jobs: FF Rosburg (ISU) Human Capital Model Spring / 57 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 / 57

20 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 past work experience Young women who expected to be working at 35 have experience-wage profiles that start lower but have a steeper slope compared to women who do not plan to be working at 35. Expected to not work at 35: took higher paying jobs with lower expected wage growth HK theory as the explanation for gender differences in occupations has mixed results Rosburg (ISU) Human Capital Model Spring / 57 Evidence for the HK Model A substantial portion of the pay difference is accounted for by different skill requirements between male and female jobs Married women have lower penalties for reentering the labor force in female-dominated rather than male-dominated jobs Women with limited expected future labor force participation select occupations with lower job skill requirements Rosburg (ISU) Human Capital Model Spring / 57

21 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 no crossover point in the data Returns to education are not higher for women in male-dominated jobs versus female-dominated jobs Earnings of women in female-dominated jobs do not depreciate less than in male-dominated jobs Women with discontinuous work history were no more likely to be in female-dominated occupations than women continuously employed Overall: Labor force commitment and participation in gender-dominated jobs are not as closely associated as the HK explanation for segregation suggests Rosburg (ISU) Human Capital Model Spring / 57 Empirical Evidence EMPIRICAL EVIDENCE Rosburg (ISU) Human Capital Model Spring / 57

22 Empirical Evidence 2003 Distribution of Educational Attainment (25-64) 1 Larger differences in investment in education across races than between males and females 1 Source: Blau, Ferber, Winkler The Economics of Women, Men and Work. 5th Edition. Rosburg (ISU) Human Capital Model Spring / 57 Empirical Evidence Ratio of College Graduate Rates at 35 by Birth Year 2 Increase during Great Depression Other significant events: GI Bill, WWII, Korea, Vietnam 2 Source: Goldin, Katz and Kuziemko Homecoming of American Women. Journal of Economic Perspectives. Rosburg (ISU) Human Capital Model Spring / 57

23 Empirical Evidence Education by Race 3 High school gap converging College gap seems to be widening 3 Source: Lang Poverty and Discrimination. Princeton University Press. Rosburg (ISU) Human Capital Model Spring / 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 / 57

24 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 / 57 Earnings by education Empirical Evidence Given the high lifetime benefits of college ($593,000 for men and $415,000 for 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 / 57

25 Present Value PRESENT VALUE Rosburg (ISU) Human Capital Model Spring / 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 to calculate present value Present value: today s value of a future payment or series of future payments discounted to reflect the time value of money Rosburg (ISU) Human Capital Model Spring / 57

26 Present Value Present Value of HK Since investment in HK typically provides benefits for many years and the value typically changes annually, we cannot use a standard form for present value. Present value of the full set of benefits is calculated by dividing each year s benefit by (1 + r) T where r is the individual s time preference (i.e. discount rate) and T is the number of years in the future the benefit will be received Let: H t = Earnings from High School Education in year t E t = Earnings from College Education in year t C t = College tuition and costs in year t Rosburg (ISU) Human Capital Model Spring / 57 Present Value of HK II Present Value PV E = Present Value of Earnings with a College Degree PV E = E 5 (1 + r) 5 + E 6 (1 + r) 6 + E 7 (1 + r) E T (1 + r) T PV C = Present Value of College Costs (including opportunity costs) PV C = H 1 + C 1 (1 + r) + H 2 + C 2 (1 + r) 2 + H 3 + C 3 (1 + r) 3 + H 4 + C 4 (1 + r) 4 + H 5 (1 + r) H T (1 + r) T Rosburg (ISU) Human Capital Model Spring / 57

27 Present Value Net Present Value Net present value (NPV) is the difference between the present value of benefits (salary) less the present value of costs (direct and indirect) NPV = H 1 + C 1 (1 + r) H 2 + C 2 (1 + r) 2 H 3 + C 3 (1 + r) 3 H 4 + C 4 (1 + r) 4 + E 5 H 5 (1 + r) E T H T (1 + r) T Incentive to invest: Increasing in: E t, T Decreasing in: H t, C t, r Rosburg (ISU) Human Capital Model Spring / 57 Net Present Value Present Value Investment Decision: NPV > 0 Go to college NPV < 0 Don t go to college NPV = 0 Indifferent There exists some r such that NPV = 0 r is the individual s internal rate of return Rosburg (ISU) Human Capital Model Spring / 57

28 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 degree needs to be: $324,000 Given earlier statistics, the mean returns for men and women would be enough to incentivize investment for both men and women on average Rosburg (ISU) Human Capital Model Spring / 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 to incentivize investment in college but not for women Rosburg (ISU) Human Capital Model Spring / 57

29 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 / 57