Post on 15-Jan-2016
Chapter 6
Human Capital
Copyright © 2010 by The McGraw-Hill Companies, Inc. All rights reserved.
McGraw-Hill/Irwin
6-2
Introduction
• People bring into the labor market a unique set of abilities and acquired skills known as human capital.
• Workers add to their stock of human capital throughout their lives, especially via work experience and education.
6-3
Education: Stylized Facts
• Education is strongly correlated with:– Labor force participation rates– Unemployment rates– Earnings
6-4
台灣教育別失業率( 1978-2009)
教育別失業率
0
1
2
3
4
5
6
7
1978 19791980 19811982 19831984 1985 19861987 19881989 19901991 19921993 19941995 19961997 19981999 20002001 2002 20032004 20052006 20072008 2009
年度
%
國中及以下 ( )高中 職 專科 大學及以上
6-5
男女年齡別薪資 (2009)
男女年齡別薪資
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
50000
15~19歲
years
20~24歲
years
25~29歲
years
30~34歲
years
35~39歲
years
40~44歲
years
45~49歲
years
50~54歲
years
55~59歲
years
60~64歲
years
65 歲及以上
years & over
年齡
月薪資
男性月薪資 女性月薪資
6-6
Age-Earnings Profiles
Men
200500800
110014001700200023002600
18 25 32 39 46 53 60
Age
We
ek
ly E
arn
ing
s
Some college
College Graduates
High school graduatesHigh school dropouts
6-7
台灣 男性 不同教育程度 年齡別薪資 (2009)
男性不同教育程度年齡別薪資
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,000
15~19歲years
20~24歲years
25~29歲years
30~34歲years
35~39歲years
40~44歲years
45~49歲years
50~54歲years
55~59歲years
60~64歲years
65 歲及以 years & over 上
年齡別
月薪資
小學國中高中高職專科大學以上
6-8
Age-Earnings Profiles
Women
200400
600800
1000
12001400
18 25 32 39 46 53 60
Age
Wee
kly
Ear
ning
s
Some college
High school graduates
College Graduates
High school dropouts
6-9
台灣 女性 不同教育程度 年齡別薪資 (2009)
女性不同教育程度年齡別薪資
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
15~19歲years
20~24歲years
25~29歲years
30~34歲years
35~39歲years
40~44歲years
45~49歲years
50~54歲years
55~59歲years
60~64歲years
65 歲及以 years & over 上
年齡別
月薪資
國小國中高中高職專科大學
6-10
Present Value Calculations
• Present value allows comparison of dollar amounts spent and received in different time periods. (An idea from finance.)
• Present Value = PV = y/(1+r)t
– r is the per-period discount rate.– y is the future value.– t is the number of time periods.
6-11
Potential Earnings Streams Faced by a High School Graduate
18 6522Age
wCOL
wHS
-H
Dollars
Goes to College
Quits After High School
0
A person who quits school after getting her high school diploma can earn wHS from age 18 until retirement.
If she decides to go to college, she foregoes these earnings and incurs a cost of H dollars for 4 years and then earns wCOL until retirement.
6-12
The Schooling Model
• Real earnings (earnings adjusted for inflation).• Age-earnings profile:
the wage profile over a worker’s lifespan.
• The higher the discount rate, the less likely someone will invest in education (since they are less future oriented).
• The discount rate depends on:– the market rate of interest.– time preferences:
how a person feels about giving up today’s consumption in return for future rewards.
6-13
The Wage-Schooling Locus
• The salaries firms are willing to pay workers depends on the level of schooling.
• Properties of the wage-schooling locus.– The wage-schooling locus is upward sloping.– The wage-schooling locus is concave,
reflecting diminishing returns to schooling.
6-14
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. And so on.
0 13 14 1812
30,000
20,000
23,000
25,000
Years of Schooling
Dollars
6-15
Education and the Wage Gap
• Observed data on earnings and schooling does not allow us to estimate returns to schooling.
• In theory, a more able person gets more from an additional year of education.
• Ability bias: The extent to which unobserved ability differences exist affects estimates on returns to schooling, since the ability difference may be the true source of the wage differential.
6-16
The Schooling Decision
Years of Schooling
Rate of Discount
s*s
r
r
MRR
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.
6-17
Schooling and Earnings When Workers Have Different Rates of
Discount
Years of Schooling
Years of Schooling
Rate of Interest
1212 1111
rBO
rAL
MRR
Dollars
wDROP PAL
PBO
wHS
6-18
Schooling and Earnings When Workers Have Different Abilities
Years of Schooling
Years of Schooling
Rate of Interest
1211
r
MRRACE
MRRBOB
Dollars
1211
wHS
wACE
PACE
wDROP
Z
Bob
Ace
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 (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 Ace’s earnings would increase if he were to complete high school (wACE - wDROP).
6-19
Estimating the Rate of Return to Schooling
• A typical empirical study estimates a regression of the form:
Log(w) = a·s + other variables
– w is the wage rate– s is the years of schooling– a is the coefficient that estimates the rate of return
to an additional year of schooling
6-20
Some Evidence
• In studies of twins, presumably holding ability constant, valid estimates of rate of return to schooling can be estimated.– Estimates range from 3% to 15% annual return to
a year of education.
• Generally, the rate of return to schooling is higher for workers who were born in states with well-funded education systems.
6-21
School Quality and the Rate of Return to Schooling
2
3
4
5
6
7
8
15 20 25 30 35 40
Pupil/teacher ratio
Rat
e of
ret
urn
to s
choo
ling
2
3
4
5
6
7
8
0.5 0.75 1 1.25 1.5 1.75 2
Relative teacher wage
Rat
e of
ret
urn
to s
choo
ling
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.
6-22
Do Workers Maximize Lifetime Earnings?
• The schooling model assumes that workers select their level of education to maximize the present value of lifetime earnings.
– once a choice is made, we cannot observe the earnings associated with the non-choice.
• Workers may select themselves into jobs for which they are better suited.
• Self-Selection Bias
6-23
Schooling as a Signal
• Education reveals a level of attainment which signals a worker’s qualifications or innate ability to potential employers.
• Information that is used to allocate workers in the labor market is called a signal.
• There could be a “separating equilibrium.”– Low-productivity workers choose not to obtain X
years of education, voluntarily signaling their low productivity.
– High-productivity workers choose to get at least X years of schooling and separate themselves from the pack.
6-24
Education as a Signal
Workers get paid $200,000 if they get less than y years of college, and $300,000 if they get at least y years. Low-productivity workers find it expensive to invest in college, and will not get y years. High-productivity workers do obtain y years. As a result, the worker’s education signals if he is a low-productivity or a high-productivity worker.
300,000
250,001 y
20,000 y
0
Dollars
Years of Schooling
Costs
Slope = 25,000
300,000
200,000
0
Dollars
Years of Schooling
Costs
Slope = 20,000
(a) Low-Productivity Workers
y y
(b) High-Productivity Workers
200,000
6-25
Implications of Schooling as a Signal
• Education is more than a signal, it alters the stock of human capital.
• Social return to schooling (percentage increase in national income) is likely to be positive even if a particular worker’s human capital is not increased.
6-26
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.
6-27
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.
6-28
Implications
• Firms only provide general training if they do not pay the costs.
• In order for the firm to willingly pay some of the costs of specific training, the firm must share in the returns to specific training. Engaging in specific training eliminates the possibility of the worker separating from the job in the post-training period.
6-29
The Acquisition of Human Capital Over the Life Cycle
MC
MR20
MR30
Dollars
0 Q30 Q20
Efficiency Units
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.
6-30
Age-Earnings Profiles and OJT
• Human capital investments are more profitable the earlier they are taken.
• The Mincer earnings function:
Log(w) = a·s + b·t – c·t2 + other variables.
6-31
The Age-Earnings Profile Implied by Human Capital Theory
Dollars
Age-Earnings Profile
Age
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.
6-32
Policy Application: Evaluating Government Training Programs
• Aimed at exposing disadvantaged and low-income workers to training programs.
• $4 billion of federal spending per year.
• Studies of the return to these human capital investments are unclear, largely because of self-selection bias.
6-33
Social Experiments
• National Supported Worker Demonstration (NSW).– Results of the NSW suggest a 10% return to
investments in human capital for workers treated under the program.