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Chapter 7: Causes of Earnings Differences

Chapter 7: Causes of Earnings Differences. Year 2002: FT employed females earned 77.5% of FT employed males. Female wage growth more than twice inflation; Male wage growth less than inflation. Sources of differences: 1) Human capital 2) Occupation 3) Discrimination.

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Chapter 7: Causes of Earnings Differences

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  1. Chapter 7: Causes of Earnings Differences • Year 2002: • FT employed females earned 77.5% of FT employed males. • Female wage growth more than twice inflation; • Male wage growth less than inflation. • Sources of differences: • 1) Human capital • 2) Occupation • 3) Discrimination

  2. Data on Earnings Differences • See Table1: • 1999 data by sex and race/ethnicity. • See Figure 1: • shows time trend in sex earnings ratio. • See Figure 2: • Age-earnings profiles for college grad and HS grad.

  3. 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?

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

  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. • Costs include opportunity costs. • Overall: yes college education is “worth it” (even though college costs  faster than inflation).

  6. HK Investment Decision • Compare two “life strategies”: • 1) Finish high school and start working FT at age 18 to age 65. • 2) After h.s., go to college for four years, then work FT from age 22 to age 65. • * 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: more distant in time the $ is received, the lower its current/present value. • FV = $106; PV = $100. • FV must be discounted to get PV.

  8. Important Terms • 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] See Table 2. • Extensions: • NPV is value in current period of sum of all future periods. • IRR = interest rate for which NPV = 0

  9. Exercise • Modify the verbal comparison of the two life strategies to reflect the following two trends. In your answer, include a discussion of how the costs and benefits (and so the comparison between the two options) have changed. • 1) more earned income during college years. • 2) more years to finish college.

  10. On-the-Job Training (OJT) • OJT like any other HK 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 doing the training.

  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 wage after training. • Specific OJT: the training is specific to this firm; worker can’t “take it with him” so firm willing to pay for it, but then reaps some of the benefits of the increased productivity post-training.

  12. Intermittent Work and Women’s Earnings • See Supplemental Figure 7.10: • Shows age/earnings profiles for men and women (college grads and just HS). • Three things to note: • 1) For both education levels, male earnings  female earnings • 2) Note proximity of female college grad to male HS! • 3) Male earnings profiles steeper: more  earnings w/age.

  13. Why Differences in Age/Earnings Profiles? • Three reasons: • 1. Women’s intermittent work. • 2. Different occupations. • 3. Role of discrimination. • 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

  14. Exercise • 1. Under what conditions would a firm find it profitable to pay for workers to attend school to obtain MBA degrees? • 2. Why would an employer be reluctant to hire worker for job with much specific OJT if person had high probability of leaving firm after short time? How does this help to explain flatter age-earnings profiles for women?

  15. HK Explanation for Gender Earnings Gap • Moe Chapter 9 by Jacobsen. • Focuses on 3 issues: • 1) Expanded definition of HK. • 2) Sex differences in amount and type of HK (& origins). • 3) Role of HK differences in sex earnings differences. • Definition of HK: • 1) Numerous factors that contribute to work productivity, including physical fitness and health. • 2) Very much like physical K, including potential for depreciation.

  16. Sex Differences in Human Capital • HK explanations for earnings differences: • 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.

  17. Any Observed Differences in HK Investment? • In developing countries: • Yes some evidence of gap in formal education and literacy but seems to be  over time. • In developed countries: • Formal schooling rates comparable across sex. • Yes observe difference by field: • Men more likely to major in fields with higher returns (engineering, computer science) than women (education). • Women receive about 40% of doctoral degrees but fewer in high paid fields • E.g. economics: 77% to men.

  18. HK Investment On the Job • Here is where sex differences appear greatest: • Females have less tenure with same employer, • Females have less overall work experience, and more intermittent work; • Less worktime HK.

  19. 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).

  20. 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.

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