Human capital

1
Human capital

• Its not what you own that counts its what you
  know. David Owens

2
Education expenditures and outcomes
Source KILM, International Labor Office, last
available year
3
Education expenditures and outcomes
Source KILM, International Labor Office, last
available year
4
Education expenditures and outcomes
Source KILM, International Labor Office, 2003
5
Education expenditures and outcomes
Source US Bureau of Labor Statistics, March 2005
6
Illustration of the Schooling Model Alternative
Earnings Streams
7
Present value of age-earnings profiles

• Let the present value of a payment of y next
  year be
• Hence, the present value of receiving y 2 years
  from now is
• The present value of y received t years from now
  is

8
Present value of age-earnings profiles

• The present value of the earnings stream if a
  worker gets only a high school education is
• The present value of the earnings stream if the
  worker gets a college diploma is
• Invest if

9
The Wage-Schooling Locus
The wage-schooling locus gives the salary that a
particular worker would earn if he completed a
particular level of schooling. If the worker
graduates from high school, he earns 20,000
annually. If he goes to college for 1 year, he
earns 23,000.
10
The Stopping Decision
The MRR schedule gives the marginal rate of
return to schooling, or the percentage increase
in earnings resulting from an additional year of
school. A worker maximizes the present value of
lifetime earnings by going to school until the
marginal rate of return to schooling equals the
rate of discount. A worker with discount rate r
goes to school for s years.
11
Schooling and Earnings When Workers Have
Different Rates of Discount
12
Schooling and Earnings When Workers Have
Different Abilities
Ace and Bob have the same discount rate (r) but
each worker faces a different wage-schooling
locus. Ace drops out of high school and Bob gets
a high school diploma. The wage differential
between Bob and Ace (or wHS - wDROP) arises both
because Bob goes to school for one more year and
because Bob is more able. As a result, this wage
differential does not tells us by how much Aces
earnings would increase if he were to complete
high school (or wACE - wDROP).
13
Estimating the Rate of Return to Schooling

• A typical study estimates a regression of the
  form
• Log(w) as other variables
• w is the wage rate
• s is the years of schooling
• a is the coefficient that estimates the rate of
  return to one added year of schooling

14
The omitted variables bias revisited
Instrumental variables

• Recall the model
• If we estimate this model without including
  relevant ability variable(s), we are likely to
  experience the omitted variable bias

15
The IQ test instrument e.g. Griliches and Mason
(1972)

• Correct model
• Use proxy for IQ
• Hence
• OLS is still biased due to the correlation of
  test 1 with the residual use 2SLS to resolve the
  problem. Results round 4-5 returns to education

16
The twin experiments e.g. Ashenfelter and
Krueger, AER, 1994

• Experiment Collect data on 1000 identical twins
  and compare the average difference in earnings
  between twins with university education and twins
  without
• Let YB,f and YHS, f be the respective earnings of
  a pair of twins with bachelor and high school
  degree, respectively.
• The baseline equation is

17
The twin experiments e.g. Ashenfelter and
Krueger, AER, 1994

• Ashenfelter and Krueger estimate
• Results returns to education about 7-10

18
Other experiments compulsory schooling laws

• Angrist and Krueger (1991) government policies
  generate instruments for comparison of earnings
  among equally able workers, RE estimates around
  7.5

19
School Quality and the Rate of Return to Schooling
Source David Card and Alan B. Krueger, Does
School Quality Matter? Returns to Education and
the Characteristics of Public Schools in the
United States, Journal of Political Economy 100
(February 1992), Tables 1 and 2. The data in the
graphs refer to the rate of return to school and
the school quality variables for the cohort of
persons born in 1920-1929.
20
School quality continued
Source KILM, International Labor Office, last
available year
21
Self-Selection Bias

• Workers may select themselves into jobs for which
  they are better suited
• Therefore, wage differentials may not be
  associated with education
• Then what is the point of investing in education?

22
An example from West Africa
Source 1-2-3 Surveys, DIAL/AFRISTAT
23
Post-School Human Capital Investments

• Three important properties of age-earnings
  profiles
• Highly educated workers earn more than less
  educated workers
• Earnings rise over time at a decreasing rate
• The age-earnings profiles of different education
  cohorts diverge over time (they fan outwards)
• Earnings increase faster for more educated workers

24
Age-Earnings Profiles
25
Age-Earnings Profiles
26
On-The-Job Training

• Most workers augment their human capital stock
  through on-the-job training (OJT) after
  completing education investments
• Two types of OJT
• General training that is useful at all firms
  once it is acquired
• Specific training that is useful only at the
  firm where it is acquired

27
The Acquisition of Human Capital Over the Life
Cycle
The marginal revenue of an efficiency unit of
human capital declines as the worker ages (so
that MR20, the marginal revenue of a unit
acquired at age 20, lies above MR30). At each
age, the worker equates the marginal revenue with
the marginal cost, so that more units are
acquired when the worker is younger.
28
The Age-Earnings Profile Implied by Human Capital
Theory
The age-earnings profile is upward-sloping and
concave. Older workers earn more because they
invest less in human capital and because they are
collecting the returns from earlier investments.
The rate of growth of earnings slows down over
time because workers accumulate less human
capital as they get older.
29
Age-Earnings profiles and OJT

• Human capital investments are more profitable the
  earlier they are taken
• The Mincer earnings function
• Log(w) as bt ct2 other variables
• The overtaking age is t and indicates the time
  when the worker slows down acquisition of human
  capital to collect the return on prior
  investments so as to overtake earnings of those
  that do not undertake similar investments

30
Educational Signaling
31
Educational Signaling
32
Educational Signaling an algebraic example

• Let the lifetime salary of a high-productivity
  worker be 300,000, and that of a
  low-productivity worker 200,000
• The yearly cost of education of a
  low-productivity worker is 25,001 and that of a
  high-productivity worker 20,000.
• The low productivity worker will not attend
  college if
• The high productivity worker gets education when
  

33
Signalling versus skill acquisition? E.g. Tyler,
Murnane and Willett, QJE 2000

• Observation/natural experiment The grade you
  need to pass the GED differs across states, even
  though the tests are equivalent
• Hypothesis If the score in the exam is an
  unbiased measure of ability and there is no
  signalling, individuals with and without the
  degree who got the same score will get the same
  wage. In contrast, if GED is a signal and
  employers dont know where the test was taken,
  these individuals will get different wages
• Results Individuals who obtained the same grade
  but received the degree earned about 10-19 more
  per year than those with similar grades that did
  not get the degree