Transcript The Human Capital Model of Differences in Occupations

The Human Capital Model
Human Capital
Individuals possess knowledge and
skills which affect their productivity.
The knowledge and skills are their
human capital.
Investments in Human Capital
There are many investments that individuals
and firms make that represent investments in
human capital.
These include education and job training.
Societal Discrimination Versus
Labor Market Discrimination
Societal discrimination (prelabor market discrimination) –
societal influences that cause individuals to make decisions that
adversely affect their status in the labor market
Example: Young women with an aptitude for math and science
do not enter those fields because they are socialized to believe
that those are men’s fields and women aren’t good at them.
Labor market discrimination – treating two individuals with equal
qualifications differently for reasons unrelated to their
productivity
Example: Employers do not hire or promote women in particular
types of jobs. Labor market discrimination lowers women’s
economic status directly when the employer refuses to hire or
promote them. It can also lower their status indirectly by
reducing their incentives to invest in themselves and to acquire
particular job qualifications.
Hispanics are more likely than Non-Hispanic Whites, Blacks,
and Asians to drop out of high school.
Blacks are more likely than the other groups to complete high
school, but go no further.
Asians are more likely to complete college than the other groups.
Non-Hispanic White, Black, and Hispanic women are more
likely to attend college and more likely to complete college than
their male counterparts.
Higher Education (2007-2008)
Percentage of Degrees Awarded to Women
First
Associate Bachelor’s Master’s Doctorates
Professional*
62.3
57.3
60.6
51.0
49.7
*First professional degrees are those awarded in post-college
professional training programs such as medicine, law, business,
dentistry, pharmacy, veterinary medicine, and theology.
Women receive more Associate’s, Bachelor’s, Master’s and
Doctorates, but slightly fewer first professional degrees.
http://nces.ed.gov/fastfacts/display.asp?id=72
While progress
has been made in
some fields,
women are still
much less likely
than men to major
in engineering,
computer and
information
sciences, and
economics.
Women are much
more likely than
men to major in
home economics,
health, and
education.
Experience-earnings profile
indicates the annual earnings at each age
or at each number of years of experience
experience-earnings profile
The experienceearnings profile
tends to rise
quickly with the
first few years of
experience and
then flatten out.
$
years
experience-earnings profile
$
college graduate
high school graduate
years
The experience-earnings
profile tends to be flatter
for the high school
graduate than for the
college graduate.
This is because college
graduates tend to receive
more on-the-job training
which increases their
productivity.
Decision to attend college
Consider an individual
who is considering
attending college. He
would not take a job while
going to school. He
would incur some direct
costs for tuition and
books. Upon completing
college he would take a
job. His experienceearnings profile would
look like this.
$
Earnings with college
Direct Costs
years
Decision to attend college
$
If he did not attend
college, his experienceearnings profile would
look like this.
Earnings without college
years
Decision to attend college
$
Earnings with college
If we combine the two
profiles, we can
examine his decision
by comparing the
present value of the
costs and benefits.
Earnings without college
Direct Costs
years
Decision to attend college
$
Earnings with college
Costs include both
direct and indirect costs
(foregone earnings).
Gross benefits
from college
Earnings without college
The benefits of college
include the higher
earnings.
Foregone
earnings
Direct Costs
years
Calculation of present value
T
PV =

n = 18
H
Yn
(Yn + Cn )
n - 18
(1 + r)
C
r = rate of discount
T = age at retirement
YnC = earnings at age n with a college education
YnH = earnings at age n with a high school degree
Cn = direct costs of college education at age n
If PV > 0, it pays to obtain the extra education
Implications of the model
It pays to invest in human capital when one is
young and there are more years to benefit.
How much investment is done depends on
how long the individual expects to be in the
labor force.
Investment in human capital is also influenced
by macroeconomic factors, such as the current
unemployment rate which influences the
probability of employment and therefore
foregone earnings.
Decision to attend college
Consider an individual
who expects to take
time out of the labor
force for child-rearing.
She expects to drop
out of the labor force in
year A and return in
year B.
$
Earnings with college
Earnings without college
Foregone
earnings
Direct Costs
A
B
years
Her skills become rusty
or maybe even
obsolete while she is
out of the labor force.
She needs to retool.
So when she returns to
the labor force, she is
on a lower earnings
curve.
$
Earnings after dropping
out of LF
Earnings without college
Foregone
earnings
Direct Costs
A
B
years
The benefits of the
higher earnings of
college relative to high
school are much
smaller than if she had
not dropped out of the
labor force.
$
Earnings after dropping
out of LF
Earnings
without
college
Gross benefits
from college
Foregone
earnings
Direct Costs
A
B
years
The gross benefits (GB) $
may not be sufficient to
compensate for the
direct costs and
foregone earnings.
So she might decide not
to attend college.
Earnings after dropping
out of LF
Earnings
without
college
Gross benefits
from college
GB
Foregone
earnings
Direct Costs
A
B
years
Implications for occupational choice
A woman who anticipates spending time out of the
labor force might choose a field for which her skills
are less likely to become obsolete during her absence
from the labor force.
For example, she might choose to teach English or
History rather than entering a field where
technological change is an important factor.
Other factors that affect
career decisions
“Gender-appropriate” traits & competencies:
Women may be socialized to believe that
certain fields are appropriate only for men and
that only men are really good at them.
Other factors that affect
career decisions
Biased evaluations:
Studies have found that, among both male and
female college students, identical papers were
given higher ratings on such dimensions as
value, persuasiveness, profundity, writing
style, and competence when the respondent
believed the author to be male rather than
female.
Other factors that affect
career decisions
Discrimination by educational institutions American women were not admitted to higher
education until Oberlin College opened its doors to
women in 1837. Women did not gain entrance to
medical school until 1847, and it was not until 1915
that the American Medical Association accepted
women members.
Women continued in many cases to be discriminated
against in admissions and financial aid policies long
after they gained formal admittance.
Other factors that affect
career decisions
Subtle Barriers:
A lack of female role models and mentors
may also effect a woman’s choice of career.
Factors affecting women’s
increased educational attainment
• More opportunities are available to women since
the passage of the anti-discrimination laws of the
1960s.
• Changing social attitudes about the role of women.
• The passage and enforcement of Title IX in 1972
as an amendment to the Civil Rights Act of 1964.
• The birth control pill, which became more widely
available in the late 1960s and early 1970s.
Title IX
To remedy discrimination in educational institutions,
in 1972 Congress passed Title IX of the Educational
Amendments to the Civil Rights Act of 1964.
It prohibits discrimination on the basis of sex in any
educational program or activity receiving federal
financial assistance.
It covers admissions, financial aid, and access to
programs and activities, as well as employment of
teachers and other personnel.
Title IX
Title IX had a particularly dramatic impact on athletics.
Support and facilities for women athletes have greatly
increased since its passage.
When it was enacted in 1972, 50% of American boys
participated in school sports compared to only 4% of girls.
By the mid-1990s, 1/3 of high school girls participated in
school sports and almost half of college varsity players
were female.
In the 1976 Olympics, only one out seven athletes was
female. By the 2000 games, 42% of the athletes were
women, and for the first time women competed in the
same number of team sports as men.
On-the-job training
Two types:
• General training -- training that can be
used at any firm (for example, word
processing).
• Firm-specific training -- training that is
useful only to the firm where you are
currently working (for example, computer
software used only by your firm)
On-the-job training
On-the-job training entails costs.
Some costs are direct, such as expenses for
instructors or materials.
Other costs are indirect. The attention of the worker
and his or her coworkers or supervisor is diverted
from production activities to training. The resulting
decline in output represents an opportunity cost to
the firm of the training.
Who pays the costs of
on-the-job general training?
Since the worker can leave and take the skills to other
firms, the firm will not be willing to pay the costs of
general training. So the worker pays the costs. How?
The worker pays the costs by initially accepting a wage
below what could be obtained elsewhere without
training. The wage is the worker’s productivity net of
training costs.
As the worker becomes more skilled, his/her earnings
catch up and eventually exceed what she could have
earning without training. The amount by which
earnings exceed what could have been made without
training represents the benefits of the training.
General training
$
Earnings with training
Gross benefits
Costs
Earnings without
training
Experience
An individual will invest in
general training if the
benefits are sufficient to
compensate for the costs.
How do expectations of discontinuous LF
experience influence an individual’s
investment in general training?
$
Earnings with training
Earnings after dropping
out of LF
Gross
benefits
GB
Earnings
without
training
Costs
A
B
Experience
If an individual expects to
drop out of the labor force
at year A and return at year
B, the gross benefits (GB)
are reduced.
If they are not sufficient to
compensate for the costs,
the individual will not make
the investment.
Who pays the costs of firm-specific training?
If the worker were to be laid off, he/she would
be unable to reap the benefits of the firm-specific
training. So the worker would not be willing to
bear all the costs of the training.
If the worker were to quit, the firm would lose its
investment in the worker. So the firm would not
be willing to bear all the costs of the training
either.
So the worker and the firm share both the costs
and the benefits of the training.
How do the worker & the firm share the costs
& benefits of firm-specific training?
The worker pays part of the costs by initially accepting
a wage below what could be obtained elsewhere without
training.
The firm pays part by paying the worker more than the
worker’s productivity net of training costs.
Later, when the worker is more productive, the worker
earns benefits by receiving more than he/she would
have earned if he/she worked elsewhere without
training.
The firm receives benefits by paying less than the
worker’s productivity with training.
Firm-specific training
$ Firm’s benefit
Productivity with training
Wage with training
Worker’s benefit
Worker’s cost
Wage without training
Firm’s cost
Experience
Implications of firm-specific training
• The worker has invested in the firm and the
firm has invested in the worker.
• Workers with firm-specific training are less
likely to quit and less likely to be laid off
than workers with no training or only
general training.
• Employers will be concerned with the
employment stability of a worker hired with
such training in mind.
More implications
of firm-specific training
A firm will be less willing to invest in a worker if it is
uncertain that it will reap sufficient benefits of the
training. Thus, if a firm thinks that a worker may drop
out of the labor force, it is less likely to train that worker.
If a worker expects a discontinuous labor force
experience, the benefits of specific training will be
reduced. Furthermore, if the worker is uncertain that she
will be able to get back her old job with the higher wages
from training, the benefits are reduced even further.
Consequently, a worker who expects a discontinuous
labor force experience will be less likely to invest in
firm-specific training.
In a study that examined job turnover, it was found
that women’s higher probability of leaving the labor
force can explain some of the gender training
difference. However, a major portion remains
unexplained after this and other determinants of
training are taken into account. This suggests that
differences in the amount of training men and
women acquire may not be fully explained by
factors emphasized in the human capital model and
that discrimination may play a role.
Human capital theory & occupations
Given that women spend less time in the
labor market and have discontinuous
working careers, they will choose an
occupation with the following characteristics:
• Less investment in on-the-job training.
• Requires no firm-specific training.
• Depreciation of skills from time spent out of
market is minimal.
Human capital theory & earnings
Human capital theory also explains the
differences in earnings. For men and women
with the same level of formal education, you
will observe a higher earnings profile for
males because they undertake substantial onthe-job training in comparison to women.
Other supply-side factors
Women are more likely to quit their jobs for
family-related reasons, and this negatively effects
their subsequent earnings.
This gender difference in the pattern of quits is
concentrated among workers with a high school
education or less. Little gender difference in this
respect is found among those who have attended
college. The work force attachment of collegeeducated women may be more nearly equal to their
male counterparts.
Other supply-side factors
The presence of children has been found to have a
negative effect on women’s wages.
Women with children earn less than women without
children, even after adjusting for experience.
One explanation for this finding is that in the past the
birth or adoption of a child often resulted in women
severing their tie to the firm and losing returns to
firm-specific training. The availability of maternity
leave significantly reduces this negative effect
because it enables women to take a short amount of
time out but maintain their attachment to the firm.
Other supply-side factors
Married men earn more than single men, whether or not
children are present.
This could partly reflect a selection of men with higher
earning potential into marriage or discrimination in
favor of married men by employers.
Evidence indicates that higher productivity is also an
important factor. This may reflect greater motivation or
commitment of married men to their jobs given some
adherence to traditional gender roles in the family.
Other supply-side factors
Women may be “tied movers” or tied stayers.”
The husband’s career often has priority over the
wife’s career.
So the family may move when the husband’s career
would benefit but the wife’s career is worse off.
Also, the family may stay where it is because the
husband’s career is better off there, despite the fact
that the wife’s career would benefit by moving.
Other supply-side factors
If women give greater priority than men to family
concerns, they may restrict the amount of daily
commuting they are willing to do, their hours and
work schedules, or their availability for workrelated travel. Such constraints could adversely
affect their occupational choices and reduce their
earnings relative to men’s.
Other supply-side factors
If women anticipate a shorter work life than men,
they may invest less time in searching out the best
possible job and, as a consequence, receive lower
earnings.
Evidence supporting
human capital theory
• Lower pay for predominately female jobs is accounted for
by differing skill requirements in predominately male and
female jobs.
• Married women have lower penalties on reentering the
labor market in female rather than male occupations.
• Women who expect to have limited time in the labor
market select occupations with lower job skills.
• With the increase in the educational attainment of women
and the increase in labor force attachment, one would
expect to see an increase in the slope of the age/earnings
profile for women. Indeed, we do.
While human capital factors are important in
explaining gender differences in labor market
outcomes, the human capital model does not
fully explain them.
Some of those differences may be due to labor
market discrimination.
Findings that are not explained
by human capital theory
• During the early years in the labor market, women should
earn more than men with the same education, since men
are investing more in on-the-job training. Instead, within
educational categories, men generally earn more than
women at every age.
• Both women who are committed to the labor market and
those who are not have age/earnings profiles that are lower
than comparable men.
• The returns to experience are no greater for women in
predominately male jobs than for women in predominately
female jobs.
• The earnings of women in predominately female jobs do
not depreciate less than that of women in predominately
male jobs when there is discontinuous employment.