Chapter 9 Gender Gap in Earnings: Explanations

1. Chapter 9 Gender Gap in Earnings: Explanations • Two broad explanations: • Differences in skills: human capital (HK) differences • Differences in treatment in the labor market: discrimination • Both explanations rely a great deal on work by Gary Becker

2. Human Capital • What is human capital? • Skills that workers possess and that determine their labor productivity. • Workers are human capital. • 5 questions to ask about HK: • 1) Who produces HK? • 2) What are its benefits/costs? • 3) Is HK valuable? • 4. How make HK investment decision? • 5) Can sex differences in HK investment explain the earnings gap?

3. 3 Main Producers of Human Capital • 1) Families (thru investments of time, money, and resources); • 2) Education gained in schools (K – 12 and college); • 3) Skills acquired while working (via on-the-job training, or OJT). • General Training:  worker productivity at this firm as well as any other firm so worker will pay via reduced wages • Specific Training:  productivity at just this firm doing the training so firm has incentive to pay for the training.

4. Education as an Investment • Gary Becker: any activity with current cost and future increased productivity can be analyzed like an investment. • Is education a good investment? • Compare costs to benefits across the entire lifetime. • Costs include opportunity costs. • Overall: yes college education is “worth it” (even though college costs  faster than inflation).

5. Important Terms • Future Value: FV • Present Value: PV • Example if just two periods (t=2): • FVt = PV * (1+r)t • PVt = FV/[(1+r)t] • R = 6%; PV = $100; FV = $106. • Present value: more distant in time • the $ is received, the lower its current/present value. • FV must be discounted to get PV • If t big like a lifetime: • PV(B1,…,BT) = SUMT[Bt\(1+r)t] • Can sum costs in same way, although mostly incurred in early periods.

6. Further Details • Internal Rate of Return: • r* that makes present value of sum of all benefits equal to the PV of the sum of all costs. • In other words, r * solves the below expression: • SUMT[Bt\(1+r*)t] = SUMT[Ct\(1+r*)t] • HK investment rule compares r* to actual market r:  Yes make investment as long as r* > r.

7. Why Might There Be Gender Differences in HK? • Two ways that HK could differ: • 1) women may have less HK than men; • 2) women may have same amount of HK but different kinds: • a) invest in HK with high non-mkt return; • b) invest in HK that will  satisfaction in work and at home; • c) invest in HK with less potential for depreciation; • d) invest in less of specific HK.

8. Earnings Across a Lifetime • See Figure 9.1: • female average earnings for high school graduate and college graduate • See different pattern across lifetime. • Note that there is less wage growth across lifecycle if have intermittent work. • Why intermittent work causes flatter age/earnings profiles? • 1. Less OJT investment (due to less chance of return to investment). • 2. Less access to occupations with much specific OJT (so women stuck in secondary sector). • 3) HK depreciates during time out of LF  difficulty of mid-career re-entry

9. See Figure 9.2: • estimates of IRR for different lifecycle work patterns. • See lower if anticipate intermittent work; this might explain less HK investment if anticipate intermittent work.

10. Sex Differences in Human Capital • Two key components of HK are education and experience. • Education: See Figures 9.3 and 9.4 • Field of Study: • 1970: < 1 % of engineering degrees ; 10% of business; < 15% of physical sciences and < 15% computer sciences. • 2001: 18%; 50%; 40% 30% • And now more of advanced degrees. • Still, degrees associated with higher earnings disproportionately male.

11. Gender Differences in Workplace Experience • Overall, female work experience is growing as is their fulltime, year-round experience and continuous experience. But still lags behind that of men. • Here is where sex differences appear greatest: • Females have less tenure with same employer, • Females have less overall work experience, and more intermittent work..

12. Evidence on Impact of HK Differences on Earnings Gap • Run regressions to control for various HK characteristics (like education, OJT, experience). • Evidence suggests that about 30% to 50% of gap can be explained by differences in measurable HK. • Rest of gap? • Attributable to unmeasured HK differences, discrimination, individual choices (e.g., different preferences; anticipate discrimination).

13. Critiques of HK Explanation for Sex Gap • 1) Source of differences in HK investment: some due to pressures of society or anticipation of discrimination so not really a “choice.” • 2) Is “penalty” for intermittent work greater than that justified by productivity issues? • 3) Discrimination in access to HK: explained much of historical gap; not so important now except possibly for specific OJT. • 4) Are individuals really as forward-looking as economic model assumes? • 5) Feminist perspective: some pressures to maintain patriarchal structure.

14. Discrimination • Becker: Economics of Discrimination • 3 potential sources: • 1) employers: most important source of discrimination • 2) employees: who willing to work alongside? • 3) customers: who willing to buy from or sit next to?

15. Employer Discrimination • Set up discussion: • Males are majority group (M); • Females are minority group (F). • M employers discriminate against F employees. • Discrimination coefficient = d = monetary equivalent of the prejudice. If actual hourly wage = w, then this discriminating employer views the wage “he” must pay as w + d. • Example: w = $5; d = $1, so employer views wage as $6, which includes monetary component plus a disutility component.

16. Employer Discrimination (cont.) • Further details when d  0 and same for all firms: • Market will favor male employees. • F only get job if their wage (Wf+d)  Wm; otherwise only men hired. • But what if different employers have different d? • Employer with no prejudice has d = 0; d  for more discriminatory firms. • Then some employers will hire women. • These less discriminating employers have competitive advantage. • See Table 9.3.

17. Results of Discrimination • Result of discrimination: • In equilibrium, women earn less than they would earn in absence of discrimination. • LR: competition should  d to 0. • Firms hiring women have lower labor costs then firms hiring just men, so firms with women have higher profits. • Discrimination is inconsistent with profit-maximization. • So why doesn’t discrimination disappear? D  to 0 requires: • Enough potential firms with zero d. • Freedom of firm entry.

18. Professional Baseball as Example • Until 1947, every player in Major League Baseball was white: • All owners had such high d’s that zero African Americans were hired. • Also had discrimination on part of “customers” so more complicated. • Why persisted? • Industry lacked freedom of entry. • Negro Baseball League created. • In 1947, Major League Baseball race “color line” was broken: • Brooklyn Dodgers signed Jackie Robinson (BD exploited their low d). • Within 10 years—all teams integrated.

19. Alternative Source of Discrimination • Statistical Discrimination: Because cannot observe any individual’s true current productivity nor his/her future productivity, treat this person as if he/she were the average from a specific group (such as female). • Asymmetric information: worker knows his/her own productivity more than any potential employer. This is a form of market failure (I.e., results in inefficiency). • Car insurance rates differ by sex due to average differences in accident propensities.