Topic 3. Investments in Human
Capital
Introduction
•Modeling investment decisions requires developing a
framework that incorporate a lifetime perspective.
•Workers undertake three major kinds of labor market
investments: education and training, migration, and
search for new jobs.
• Economists call them Human Capital: a set of skills
that can be rented out to employees. A stock concept.
• Society’s total wealth is a combination of human and
non-human capital.
• 60 percent of estimated national wealth was derived
from investments in human capital.
• Three stages of investments: a. early childhood
determined by parents, community; b. as students in
high school, college or vocational training; c on the
job training, night school, formal training.
• We want to explain why people faced with what
appears to be the same environments make different
choices.
• We will see that individuals’ decisions about
investing in human capital are affected by innated
ability, their aspirations and expectations about the
future, and access to financial resources.
Basic model: human capital
investments
•
•
Like any other investment, an investment
in hc entails costs with expected benefits
accrued in the future.
Costs of this investments are
1. Out of pocket or direct expenses: tuition,
books, etc.
2. Foregone earning
3. Psychic losses
• For education and training, expected returns are
in the form of higher future earnings, increased
job satisfaction over their lifetime, and a
greater appreciation of nonmarket activities.
• We need to discount this stream of benefits.
• Assuming a utility maximization consumer
• For investment in additional schooling, we
compare if sum over B/ (1+r) > C
• If r is known, we can just compare this
equation.
• Or we can find IRR, the largest r that make this
project profitable. In other words, if IRR >
interest rate, we will invest.
• Optimum acquisition of human capital
baht
mc’
mc
mb
hc
Demand for a college education
• Facts
Alternative earning streams
age
cost
Predictions of the theory
• Present-oriented people are less likely to go
to college than the forward-looking one
• Most college students will be young
• College attendance will drop if costs rise
• College attendance will rise if earning gap
widens, other things equal.
Prediction1:present-orientedness
• Describe people who do not weight future events
very heavily = who has a very high discount rate
• Using the present-value method to calculate
investment returns, imputed benefits will be smaller
• Using the IRR, require the larger IRR .
• Thus, these people are less likely to attend college.
• Evidence: we don’t have discount rate of these
people, but indirect evidence b/w edu and health.
• We found that positive correlation b/w health and
education. Health-concerned persons are forwardlooking.
Prediction2: age
• The young have a larger present value of
total benefits than the older, because of
longer time remaining for work.
Prediction3 costs
• Invesment more when costs are lower.
• If foregone earning or tuition cost fall, ceteris
paribus, we expect a rise in college enrolments.
• For older people, costs of college atttendance are
high.
• Students with lower achievement or higher
discount rate are more likely to be the margin, thus
are most responsive to cost considerations.
Prediction 4:earning differentials
• Demand for education is pos. related to increases
in lifetime earning. (expected)
• Since expected earning, and occupational choice
are uncertain, we can guess (decide) by looking at
the avg returns.
• Male enrolments in 80s declined
• Women enrolments rise throughout decades
• For individual, edu choices and occupational
choices of friends and acquaintances affect
investment decisions. (why)
Postschooling investment in HC
• Why training at work are needed?
• Skill mismatched, technological change, job
promotions.
• Two types of training: general and specific
• Examples of training.
Money
earning
for fulltime
male
workers
1999
Figure 9.4
Money
Earnings
(Mean), for
Full-Time,
Year-Round
Female
Workers, 1999
These figures reveal 4
characteristics
• 1. Avg earning of full-time workers rise with level
of education
• 2. Concave shape, rise rapidly early
• 3. Earning differences are greater over time.
• 4. Age/earning profiles of men tend to be more
concave and to fan out more than those for
women.
• Can we use HC theory to explain these empirical
regularities?
1. Average earnings rises with
education:
As implied by our investment model
otherwise they did not have incentives
to invest in education
2. Concavity and on-the-job
training
• 2 in 3 of wage growth occurred in the first ten
years.
• We can explain the early sharp rise in earning
profiles and then slower in terms of OJT
• OJT: learning by doing, formal training, informal
training with more experienced workers
• OJT reduces productivity of trainees during
learning.
• Training costs are either shared by workers and
the employer for specific training, whereas borne
mostly by employees for general training.
• Generally, training reduces wage during the
learning period, and then rise with enhanced
productivity afterwards.
• As with other forms of hc investment, we
will invest in OJT more at young and less as
we grow older.
• In other words, hc investment decline with
age.
Figure 9.5
Investment in
On-the-Job
Training over the
Life Cycle
• In figure 9.5, Es is earning after schooling
without further training
• Ep is the potential earning from OJT
• Ea is the actual earning
• Gap between Ep and Ea is the actual cost of
OJT.
• As they age, the gap is lessen, so investment
incentive declines with ages.
3. Earning gap becomes more
pronounced as they age
• Remind. We tend to invest more when the
expected earning differentials are greater; or when
investment costs are lower; or when you have
more time to recoup benefits; or you have a lower
discount rate; or you can learn quickly, shorten
training time, or lower psychic losses.
• Thus, this implies that workers who invested more
in schooling will invest also more in postschooling
training.
4. Men’s earnings profile more
concave than those for women
• Length of work life are different historically.
• Women, in average, have fewer hours of works
per week than men do.
• Expected work life for women is shorter due to the
role of women in child-rearing and household
production.
• This role makes women to drop out of the labor
market during their childbearing year, reducing
women’s work experience
• This may cause employer to avoid hiring
women for jobs requiring much OJT;
women probably know this too. In all,
women have less incentives to enter these
occupations.
• So the cause of the flatten earning profile
for women can come from the less OJT of
women
Is Education a good Investment?
• For individuals, most studies show that returns are
close to other types of investment.
• However, there are some biases in estimating returns to
education.
• Upward bias: not partial out effect of ability
• Downward bias: some benefits are not captured; not
include employee benefits.
• Selection bias: conventionally, we compare the earning
from college graduates and high school graduates. If in
fact, in the absence of college education, your earning
would have been less (cause you don’t like it),
therefore ror is underestimated. In the opposite, the ror
for high school graduate is overestimated.
Is education a good social
investment?
• Are we putting enough resources to
educating our current and future
workforces?
• Should the resources for education be
reallocated in some way?
• Should we demand more of students in
elementary or secondary schools?
• How education and productivity are related
• What is the socially optimal level of
schooling? Society should invest until
marginal social rate of return equals the
marginal ror on other forms of investment.
• For LDCs, rors for secondary and higher
educations appear to be higher than in
developed countries.
• Two hypotheses: education enhances worker
productivity vs. education is a means of finding
out who is productive. (it is just a signal for
productivity)
• Since worker’s productivity cannot be observed
even long after employed, edu attainment as a
hiring standard can increase firms’ profits even if
education does not enhance productivity.
Figure 9.7
The Benefits to
Workers of
Educational
Signaling
Figure 9.8
The Lifetime Benefits and Costs of Educational Signaling
• For less productive worker, they will choose
e=0, where gap bw benefit and costs are
maximized: A0 > BD.
• For productive worker, choosing e* will
give him BF which is > A0.
Signaling or Human capital
• Agree: people with higher cognitive skill are
likely to be more productive
• Disagree: better schools can enhance worker
productivity by improving cognitive skills.
• Pro for signaling believes there is no strong
relationship betweens school expenditures and
student performance.
• Pro for hc view believes that students attending
higher-quality schools have higher subsequent
earning, ceteris paribus.