Investments in Human Capital: Education and Training

1. 9 Investments in Human Capital: Education and Training

2. Chapter Outline • Human Capital Investments: The Basic Model • The Concept of Present Value • Modeling the Human Capital Investment Decision • The Demand for a College Education • Weighing the Costs and Benefits of College • Predictions of the Theory • Market Responses to Changes in College Attendance • Education, Earnings, and Post-Schooling Investments in Human Capital • Average Earnings and Educational Level • On-the-Job Training and the Concavity of Age/Earnings Profiles • The Fanning Out of Age/Earnings Profiles • Women and the Acquisition of Human Capital • Is Education a Good Investment? • Is Education a Good Investment for Individuals? • Is Education a Good Social Investment? • Is Public Sector Training a Good Social Investment?

3. Typically, investments involve initial costs or outlays of expenses with the hope and expectation to recoup/payoffs overtime. • Workers undertake three major kinds of labor market investments: • Education and training • Migration • Search for new jobs • Investment in knowledge and skills of workers takes place in three stages: • Early childhood human capital where such decisions are made by others – parents. • Acquisition of knowledge and skills as full-time student in high school, college, or vocational training program. • On-the-job training when in the labor force.

4. 9.1 Human Capital Investment: The Basic Model • Costs of acquiring or adding to human capital fall into three categories: • Out-of-pocket or direct expenses – tuition costs, expenditures on books, and other supplies. • Forgone earnings – salaries/income given up. • Psychic losses – occur because learning is often • difficult and tedious for some people. • Expected returns to education and training investments (human capital) are in the form of: • higher future earnings, • increased job satisfaction over one’s lifetime, and • a greater appreciation of nonmarket activities and interests.

5. 9.1Human Capital Investment: The Basic Model • The Concept of Present Value • Investment returns or expected future benefits are subject to delays, risks, and uncertainty, therefore, investment decisions are made by comparing the present value (PV = B0 = $100) of investment outlays with the expected future values/returns one year, two, three, or T-years later (FV = Bi , i = 1, 2, 3,….T ). The FV (= B1) of $100 at 5% interest rate a year from now is: • B1 = B0 + B0(r) = B0(1 + r) = 100(1.05) = 105 (9.1) • and solving for B0 (= PV) yields: • where r = market interest rate, and • (1 + r) = discount factor.

6. 9.1Human Capital Investment: The Basic Model • If the return is two years from now, the FV (= B2) is: • B2 = B1 + B1(r) = B1(1 + r) (9.3) • and substituting equation (9.1) into equation (9.3) yields: • B2 = B0(1+ r) + B0(1+ r)(r) = B0(1+ r)(1+ r) = B0(1+ r)2 (9.4) • Since B2 = B0(1 + r)2, therefore, solving for B0 (= PV) will yield: • The PV of a human capital investment yields return B1 in the 1st year, B2 in the 2nd year and so forth, and for T years, it is expressed as:

7. 9.1Human Capital Investment: The Basic Model • Modeling the Human Capital Investment Decision • People are assumed to maximize their utility, and they will take a lifetime perspective when making choices about education and training – they will compare near-term investment costs (C) with the PV of expected future benefits when making decisions. • Additional year of schooling is attractive or beneficial if PV > C • That is, if • Utility maximization requires that people continue to make additional human capital investments until the benefits of additional investment (MB) are equal to (or less than) the additional costs (MC) – that is, MB = MC.

8. Figure 9.1The Optimum Acquisition of Human Capital MC′ in Panel (a) is the marginal cost of those who find learning to be especially arduous hence they attach higher marginal psychic cost to the acquisition of human capital – they will acquire lower levels of human capital, hence HC′ < HC*. MB′′ in Panel (b) is the marginal benefit of those who expect smaller future benefits from additional human capital investments, therefore, they will acquire less human capital, thus HC′′ < HC*.

9. 9.2The Demand for a College Education • The demand for a college education varied over the years among males (men) and females (women). Weighing the Costs and Benefit of College • People attend college when they believe they will be better off by so doing. • College as a consumption good has consumption benefits that are unlikely to change much overtime. • A person considering college education has two streams of earnings (streams A and B) over his/her lifetime: • Stream A begins after high school (HS) at the age of 18 but does not rise very high. • Stream B has a negative income for the first four years owing to college costs and rises above stream A.

10. Figure 9.2Alternative Earnings Streams

11. 9.2The Demand for a College Education Predictions of the Theory Present-Orientedness – Present-oriented people are less likely to go to college than forward-looking people (other things equal). –present-oriented people tend to have higher rates of discount (r) and they impute smaller benefits to college education in comparison to future- looking people Age – Most college students will be young. – Young people have larger PV of total benefits than older workers because the younger workers would have longer labor market experience, therefore, T is greater for younger people than for older ones Costs – College attendance will decrease if costs of college rise –Human capital investments are more likely when costs are lower. Earnings Differentials – College attendance will increase if the gap widens between the earnings of college and HS graduates. – The demand for education is positively related to the increases in expected (but uncertain) lifetime earnings/benefits that a college education allows

12. Table 9.1

13. 9.2The Demand for a College Education Other Factors That Can Affect the Demand for a College Education after Controlling for Parental Influence • Uncertainty –even if individuals know the average earnings differentials between college and high school graduates, they must also assess their own probabilities of success in specific fields requiring a college education/degree. The presence of role models can help reduce the uncertainty that surrounds the estimates of future success in specific areas. –current returns to human capital may be an unreliable estimate of future returns, that is, returns observed currently may not persist into the future • Friends –friends could be important in human capital decisions (fit with the crowd) • Ethnic affiliation/origin –The importance attached to human capital investments varies across ethnic groups. • Neighborhoods in the human capital decisions of individuals – Human capital investments decisions in affluent neighborhoods will not be the same as those in poor-inner-city neighborhoods.

14. 9.3Education, Earnings, and Post-Schooling Investments in Human Capital • Four notable characteristics of the age/earnings profiles for • both male and female workers depicted in Figures 9.3 - 9.5: • Average Earnings and Educational Level • Average earnings of more educated full-time workers exceed those of less educated workers, that is, more education is associated/correlated with higher pay. • On-the-Job Training and the Concavity of Age/Earnings Profiles • Training Declines with Age • The age/earnings profiles typically rise steeply early on, then tend to flatten, that is, workers’ investments in OJT tend to be greatest when young and tend to fall gradually as they grow older.

15. Figure 9.3Money Earnings (Mean) for Full-Time, Year-Round Male Workers, 2011

16. Figure 9.4 Money Earnings (Mean) for Full-Time, Year-Round Female Workers, 2011

17. Figure 9.5Investment in On-the-Job Training over the Life Cycle Individual is assumed to have completed full-time schooling and enters the labor market at age A0 with earnings at Es. With no further training and no skills atrophy, earnings would remain at Es over the worker’s life cycle. If the worker chooses to invest in OJT, his/her future earnings potential will be enhanced as indicated by the (dashed) curve Ep in comparison to actual earnings (Ea) which lie below Ep. For those who invest in OJT, Ea starts below Es and approaches it at age A* (“overtaking age”) at which Ea and Es are equal, then thereafter, Ea rises above Es.

18. 9.3Education, Earnings, and Post-Schooling Investments in Human Capital • The Fanning Out of Age/Earnings Profiles • Earnings differences across workers with different educational • backgrounds tend to become more pronounced as they age. • Investments in human capital tend to be more likely when expected earnings differentials are greater and when people have the ability to learn more quickly or faster – which may shorten the training period. • Human capital theory suggests that workers who invested more in schooling will also invest more in post-schooling job training. • People with the ability to learn quickly select the ultimately high-paying jobs where much learning is required and thus put their abilities to greatest advantage.

19. 9.3 Education, Earnings, and Post-Schooling Investments in Human Capital • Women and the Acquisition of Human Capital • The traditional/historical role of women in childrearing and household production contributed to their shorter expected work life and the skills atrophy when they drop-out of the labor force as well as their reduced labor force attachment. • Earnings of women who work full-time year-round are lower than those of men of equivalent age and education. • Women’s earning within each group identified in Figure 9.4 rise less • steeply with age. • Women and Job Training • Women receive less OJT than men because employers expect women workers to have shorter work lives due to drop out. • Women and Formal Schooling • There have been dramatic changes in the level of formal education received by • women in recent years, which no doubt reflect the increased returns to human • capital investments and increased labor force attachment and longer expected • work lives.

20. Table 9.2 On the average, women are less likely than men to be in the labor force and, if employed, they are less likely to work full-time. Women employed full-time averaged fewer hours of work per week than men in each of the occupations shown.

21. Figure 9.6The Increased Concavity of Women’s Age/Earnings Profiles The age/earnings profiles of women reveal that the earnings for both high school and college graduates have become steeper for women in their 20s and 30s, especially among those with college education. This faster earnings growth among women at early stages of their careers suggests that they may be receiving more OJT than they did two decades ago.

22. Table 9.3 • Women’s expected labor force attachment has grown so fast that investing in bachelor’s and master’s degrees has become more attractive over the last four decades.

23. 9.4 Is Education a Good Investment? • The question of whether more education would be a good investment is one that concerns both individuals and government policymakers. • Individuals must decide whether the increase in the monetary and psychic income is enough to justify the costs of additional education. • Government must decide if the expected social benefits of enhanced productivity outweigh the opportunity costs of investing more of the scarce social resources in the educational sector. Is Education a Good Investment for Individuals? • Is there evidence that investment in a college education, which involves monetary costs of at least $25,000 per year, pays off for the typical students?

24. 9.4 Is Education a Good Investment? • Many studies reported the estimate rates of return that fall • into the range of 5 – 12 percent, but there are problems • with these conventional estimates due to: • Ability Bias • Conventional estimates may overstate the gain an individual could obtain by investing in education because they do not distinguish between the contribution that (innate)abilitymakes to higher earnings and the contribution made by schooling. • Results of studies of identical twins with the same genes suggest that ability bias in the conventional estimates may not be very large. • Returns for Whom? • People who seek more schooling may have lower psychic costs of learning, or lower discount rates, than those who do not make the investment – returns to schooling for those who do invest may be very different than the returns facing those who chose not to invest.

25. 9.4Is Education a Good Investment? Is Education a Good Social Investment? • The issue of education as a social investment is not unique to the United States, it is in fact a worldwide issue because of three related developments, which may undermine the productivity of America’s future workforce relative to workers elsewhere: • Product markets have become more global, thus increasing the elasticity of both product and labor demand. • The growing availability of high-technology capital has created new products and production systems that may require workers to have greater cognitive skills and to be more adaptable, efficient learners. • American elementary and secondary school students have scored relatively poorly on achievement tests in mathematics and science.

26. Table 9.4 • The poor performance of American elementary and secondary students on achievement tests raises some pertinent policy questions: • Are we devoting enough resources to educating our current and future workforce? • Should the resources we devote to education be reallocated in some way? • Should we demand more of students in elementary and secondary schools?

27. 9.4Is Education a Good Investment? • The Social Cost • Among some of the highly industrialized countries, the United • States devotes relatively more resources (over a tenth of its • gross domestic product) to education, from elementary schools • to universities. • The relatively poor performance of American students on • achievement tests has led to questions about whether we are • devoting too many or too few resources to education. • The Social Benefit • If an individual’s productivity increases because of more schooling, then that increases society’s stock of capital. • Education has positive externalities so that the social benefits • are larger than the private benefits.

28. 9.4Is Education a Good Investment? The Signaling Model • Apart from observing certain indicators (age, experience, education, and personal characteristics) that are correlated to productivity, employers cannot determine the actual productivity of any applicant during the interviewing and hiring process, therefore, they rely on the formal education that workers acquire. • Some see the educational system as a means of findingoutwho is productive, not of enhancing worker productivity. • Employers use education as a signaling device, which enables them to sort workers into different levels or categories of productivity rather than assume that all workers/applicants are “average.”

29. Figure 9.7The Benefits to Workers of Educational Signaling An Illustration of Signaling Employers use education to classify workers with less than e* years of education as lower-productivity workers that should be rejected or prevented from any job paying a wage above 1. Those workers with at least e* or more years of education beyond high school are considered to be the higher-productivity workers who can obtain a wage of 2. Note that if education is a signaling device which yields a wage of 2, all workers would want to acquire the signal of e* if it were costless for them to do so.

30. Figure 9.8The Lifetime Benefits and Costs of Educational Signaling PVE1 and PVE2 are the sums of the discounted lifetime earnings of workers who earn wage of 1 and wage of 2, respectively. Each year of education costs C for those with lower productivity (lower cognitive ability or distaste for learning) and C/2 for those with greater productivity. Workers choose the level of schooling at which PVE1 – C and PVE2 – C/2will be maximized. For lower productivity workers, the choice would beA0 withzero years of schooling beyond high school because acquiring e* yields BD (< A0). Higher productivity workers with cost of C/2 would find it profitable to acquire e* years beyond high school because BF (>A0) exceeds other schooling choices.

31. Figure 9.9Requiring a Greater Signal May Have Costs without Benefits Some Cautions About Signaling If those with costs along C have higher costs only because of lower family wealth, and that they may be no less productive on the job than those along line C/2, then using e* as signaling would fail. Even when using e* as a useful way to predict future productivity, there is an optimumsignal beyond which society would not find desirable to go. If employers now require e* years of schooling beyond HS for their entry level jobs paying wage of 2, and if they raised their hiring standards to e′ years, then those with costs along C would still find it in their best interests to remain at zero years and retain A0 since A0 > B′D′. Those with costs along C/2 would still find it profitable to invest in the newly required signal of e′ years because B′F′ still exceeds other schooling choices (since B′F′ > A0).

32. 9.4Is Education a Good Investment? If 50 years ago being a high school graduate signaled above- average intelligence and work discipline, why incur the enormous costs of expanding college attendance only to find out that now these qualities are signaled by having a bachelor’s degree? Signaling or Human Capital? • Direct evidence of the role schooling (signaling or human capital) plays in society is difficult to obtain because of the different views. • Advocates of the signaling hypothesis argue that what is learned in school is proportional to the time spent there and that an added bonus, which is the rate of return, just for a diploma is proof of the signaling hypothesis. • Advocates who are of the view that schooling enhances human capital argue that those who graduate after four years of college have more than four times what the freshman dropout learned.

33. 9.4Is Education a Good Investment? • Proponents of the signaling and human capital theory of education can agree that people of higher cognitive ability are likely to be more productive; where they disagree is whether better schools (by improving cognitive skills) can enhance worker productivity. School Quality • Advocates of the signaling viewpoint cite studies that emphasize the difficulty of showing the relationship between schooling expenditures and student performance on tests of cognitiveskills. • Advocates of the human capital view cite studies that support the relationship between earnings and school quality – students attending higher-quality schools have higher subsequent earnings. • Arguable Possibilities: – Better quality schools enhance productivity by enhancing creative skills or promoting better work habits. – Better schools give students better information about their own interests and abilities, thus helping them to make more successful career choices.

34. 9.4Is Education a Good Investment? Does the Debate Matter? • The fact is that schooling investments offer individuals monetary rates of return that are comparable to those received from other forms on investment. • The fact that employers continue to emphasize (and pay for) educational requirements in the establishment of hiring standard suggests one of two things: • Either more education does enhance worker productivity or • It is a less expensive screening tool than any other that firms could use. • The fact that employers are willing to pay a high price for an educated workforce seems to suggest that education produces social benefits.

35. 9.4Is Education a Good Investment? Is Public Sector Training a Good Social Investment? • Evaluating the benefits of different (voluntary and mandatory) government programs such as the Jobs Corp requires comparing the costs per worker/trainee with an estimate of PV of the benefits measured in terms of the increase in wages made possible after the successful completion of the training program(s). • Many studies have analyzed the benefits of these programs by comparing what would be earned in the absence of the training programs. • studies found that per-student, the direct costs of these training programs have been in the range of $4,500 to $9,100, but they also had opportunity costs in the form of forgone output • studies also found that adult women are the only group among the disadvantaged that clearly benefit from these training programs.

36. 9A A “Cobweb” Model of Labor Market Adjustment

37. Boom-and-bust cycles for highly technical workers occur in the labor market due to the failure of supply to respond immediately to changes in labor market conditions. • 9A.1An Example of “Cobweb” Adjustments • When the demand for certain fields/professions (e.g. MD, CPA, CNA) increases, the supply may be slow to adjust because it takes a long time for people/workers to be certified in those fields/professions. • In the immediate market period (at the moment) supply will appear to be perfectly inelastic until more people decide to enter into those fields/professions and supply their services.

38. With the initial D0 and S, equilibrium wage and employment will be W0 and N0. An increase in the demand for engineers shifts D0 to D1, and because it takes a long time to become an engineer, the number of engineers available at the moment is N0 (i.e. the elasticity of labor supply is zero in the immediate market period). The currently available engineers N0 can obtain a wage of W1, which is above the new long-run equilibrium wage of W*. It will take a while before equilibrium employment is establish at N*. Figure 9A.1 The Labor Market for Engineers

39. Figure 9A.2 The Labor Market for Engineers: A Cobweb Model With the shift in demand from D0 to D1, the number of engineers currently at N0 can obtain a wage of W1. If people are myopic in forming their expectations, they will assume W1 to be the new equilibrium, therefore, N1 people will enter the engineering field/school. When they (N1) all graduate, there will be surplus engineers at W1. With supply fixed at N1, the fall in wage to W2 will cause students and workers to shift out of the engineering field, and N2 will be the number of engineers after full adjustment in a few years. With ND>NS at W2, wage rises to W3, and the process as described above continues until the long-run is reached at N* and W*.

40. Given the “cobweb” adjustment of wages in the labor market, how workers form expectations about future wages (prices) is important in understanding many labor market issues. 9A.2Adaptive Expectations • The Adaptive Expectations Hypothesis/Theory (AEH) asserts that people form their expectations of the future (or predict the future) based on current and past life experiences. • If in the labor market wage expectations are formed adaptively, this means that future expected wages will be equal to the weighted average of current and past wages. • Forecasting future wages in the labor market using AEH (based on backward-looking forecasting) may lead workers to first overpredict and then underpredict the equilibrium wage – workers are extremely shortsighted and make errors in predictions. • overprediction of the wage may overshoot the equilibrium wage • underprediction of the wage may undershoot the equilibrium wage

41. 9A.3Rational Expectations • The Rational Expectations Hypothesis/Theory (REH) asserts that an individual will use all available information in forming their expectations about future economic variables such as wages and prices. • REH assumes that workers (implicitly assumed to be economists or statisticians) will not be fooled into overpredicting or underpredicting future wage levels as indicated by the “cobweb” model. • REH assumes that if there are errors in expectations, they would be random errors not based on the available information or theory. • The important lesson from the cobweb model and the application of REH is that adjustments in certain technical fields will be slow and wages in those markets may over-adjust or under-adjust, therefore, governmental predictions and market interventions should be based on rational expectations.