Economics of Gender Chapter 9 Assist. Prof.Dr .Meltem INCE YENILMEZ

1. Economics of GenderChapter 9Assist.Prof.Dr.Meltem INCE YENILMEZ

2. The Gender Gap in Earnings: Explanations • Human Capital • Definitions • The Investment Decision • Empirical Evidence • Labor Market Discrimination • Other Explanations • Statistical Discrimination • Occupational Segregation

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

4. Producers of Human Capital • There are 3 main producers of Human Capital: 1) Families (through investments of time, money, and resources); 2) Schools (K–12 and college); 3) Firms (via on-the-job training).

5. 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 of a person • Costs include opportunity costs • Overall: Yes college education is “worth it” (even though college costs  faster than inflation).

6. Human Capital Investment Decisions • Compare these two “life strategies” 1) Finish high school and start working full time at age 18 to age 65. 2) After high school, go to college for four years, then work full time from age 22 to age 65. • What is being compared? • Direct costs: tuition (not housing). • Opportunity costs: foregone earnings.

7. The Two Strategies • Compare lifetime earnings for HS versus C: $ earnings: • HS: $1.5 million; • C: $2.5 million. • BUT need to know these two figures in present value terms. • HS: $540,000 • C: $880,000. • Present value: The more distant in time the money is received, the lower its current/present value. • FV = $106; PV = $100. • FV must be discounted to get PV.

8. Important Terms and Formulas • Terms: • Future Value: FV • Present Value: PV • Net Present Value: NPV • Internal rate of return: IRR • Formulas: FVt = PV * (1 + r)t PVt = FV/[(1 + r)t]

9. Making the Investment Decision • Left hand side is the PV of the benefits • Right hand side is the costs • Level of r that equates the PV to the costs is called the internal rate of return (IRR) • Compare IRR to market interest rate, if IRR is greater then college is a good investment

10. Investment in On-the-Job Training • OJT is like any other HC investment but now some of OJT investment costs (and benefits) will be shared between worker and employer • General OJT:  worker productivity at this firm as well as any other firm • Specific OJT:  productivity at just this firm where the training is occurring

11. Who Pays for Training? • General OJT: Worker can use this training to  productivity at many firms so employer won’t pay; worker must pay with reduced wages during training but then benefits with increased wages after training • Specific OJT: The training is specific to this firm; worker can’t “take it with him” so firm is willing to pay for it, but then reaps some of the benefits of the increased productivity post-training

12. Gender Differences in Human Capital • Human Capital explanations for earnings differences: 1) women may have less HC than men; 2) women may have same amount of HC but different kinds: • invest in HC with high non-market return; • invest in HC that will  satisfaction in work and at home; • invest in HC with less potential for depreciation; • invest in less of specific HC.

13. Labor Market Discrimination and Women’s Earnings • Becker: Economics of Discrimination Some people may have a taste for discrimination, subjective dislike • 3 potential sources of discrimination: • employers • employees • customers

14. Employer Discrimination • Assume: • 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*(1 + d). • Example: w = $5; d = $1, so employer views wage as $10, which includes monetary component plus a disutility component.

15. Employer Discrimination (continued) • Further details when d 0 and is the same for all firms: • Market will favor male employees • Females only get jobs if their wage (Wf+ d)  Wm; otherwise only men are 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 thus have a competitive advantage

16. Results of Discrimination • Results 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 than firms hiring only men, so firms with women in them have higher profits. • Discrimination is inconsistent with profit-maximization. • So why doesn’t discrimination disappear? Because d  to 0 requires: • Enough potential firms with zero d. • Freedom of firm entry.

17. Alternative Explanations for Gender Earnings Gap • Statistical Discrimination • Asymmetric information: The employee has more information than the employer about his/her own skills and commitment.

18. Explaining Occupational Segregation • Gender Roles and Occupational Choice • Innate preferences • Social cues as to what is acceptable for women • However, in order for women’s jobs to pay lower wages it must be true that: • The Occupational Crowding Hypothesis must hold

19. The Gender Gap in Earnings: Methods and Evidence • Sources: • Human capital: partially from different lifetime work experience • Discrimination: hard to measure • Quantitative Methods: • Regression Analysis and Oaxaca Decomposition (an extension of regression) • Audit Studies of Discrimination

20. The Statistical Analysis of the Gender Gap • Regression Equation: Y =  + 1YrsEduc + 2WorkExp + 3Race + 4Female +  Y = earnings = dependent variable 4 independent variables (Xs)  and s are regression coefficients 1 = effect of  education by one year on earnings, holding other Xs fixed μ =error term: the effect of unobserved factors on Y

21. Measured Versus Unmeasured Factors • The estimated coefficients pick up the effects of measured characteristics • The error term picks up the effect of unmeasured factors, which are often important • Discrimination: some researchers use this error term as an estimate of the role of discrimination but it can under-state or over-state discrimination • There are unobserved factors that legitimately affect wages, such as motivation, quality of training, etc.

22. Decomposition Mathematically • The first term on the right-hand side is the explained portion of the gender wage gap • The second term on the right-hand side is the unexplained portion of the gender wage gap • Is the unexplained portion discrimination?

23. Has the Gender Gap Become a Family Gap? • Family Gap: The impact of family responsibilities (children and marriage) on the earnings of men and women • Waldfogel has found that family factors have become more important determinants of wages than human capital factors in recent years

24. Gender Discrimination in Hiring • Sometimes discrimination takes place on the hiring side of a job—ex: Employers may be reluctant to hire women • An Audit Study can help us determine if there is discrimination in hiring and in initial wage offers • An audit study allows us to perform an economic “experiment”—testers are sent out in pairs with identical resumes • Several audit studies have detected discrimination in hiring

25. Specialized Studies of Women’s Earnings • The gender gap among college graduates • Discrimination on the basis of physical appearance • Wage differences between black and white women • Female executives and their compensation