What does human capital do? A
review of Goldon and Katz’s The
Race between Education and
Technology
Daron Acemoglu and David Autor
NBER 17820, 2012
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Thomas Picketty
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G&K conclusion 1
U.S leadership in education has economic,
political and social roots that are related to
specific characteristics of the American society
at the turn iof the 20th century (114 years ago)
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G&K conclusion 2
Human capital is a central determinant of
economic growth, both in general and in the
specific case of economic growth in the US
during the 20th century
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G&K conclusion 3 (a)
Investments in human capital can play a major
equalizing role. Under the Tinbergian
assumption that technology is skill-biased,
technological progress will necessarily widen
inequality among skill groups unless it is
countered by increases in the supply of human
capital.
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G&K conclusion 3 (b)
The steady accumulation of human capital has
thus been the main equalizer in the U.S. labor
market. The rise in inequality over the last three
or so decades, in turn, can be understood as the
consequence of a slowing rate of accumulation
of human capital, which has not kept pace with
skill-biased technological change.
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G&K conclusion 4
The United States has, to a signi.cant degree,
lost its educational leadership because its
educational institutions have become decadent.
This problem can be redressed throughreform
and re-investment.
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Canonical Model
G&K analysis is based on the so called Canonical
Model (Tinbergen 1973, Becker 1973?):
Technological progress raisesthe demand for
skill, and human capital investsment slake that
demand.
When demand moves outward faster than does
the supply of human capital, inequality nrises,
and vise versa when supply outpaces demand.
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Jan Tinbergen
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Gary Becker
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General Model
Y=F(K, X, A)
Y=Aggregate output
K=Stock of physical capital
X=Stock of human capital
A=Technology (residual)
Assumption:
(1) CRS in K and X
(2) No technological or human capital externalities
in production
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Growth model
RK
wX X
gY  gA 
gK 
gX
Y
Y
R=Rent of capital and RK/Y=0.3
w=wX/Y=0.7
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Canonical Model with two skill groups
L= Low skill labour
H=High skill labour
Production function for the whole economy:
s 1 / s
Y  [ ( AL L)
 (1   )( AH H )
s 1 / s
]
s 1 / s
Where s=elasticity of substitution between L and H, AL and
AH are factor augmenting technology terms, and Q is a
distribution parameter that determines the relative
importance of low skilled lbaour in the production function
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Acemoglu/Author vs G&K
AA: The growing wage differences are driven by
the technology (”GPT”)
GK: The growing wage differences are driven by
the educational system
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Canonical Model with two skill groups
Assuming that factor markets are competitive,
unskilled and skilled wages. WL and WH are
given by their marginal productivity, and can be
obtained by deriving
s 1/ s
Y  [ ( AL L)
 (1   )( AH H )
s 1 / s
s 1 / s
]
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Canonical Model with two skill groups
..after some differating steps we ends with
s 1
s 1
1  Ht 
lnt  cons tan t 
g0 
g 1t  ln 
s
s
s  Lt 
Whete g is calender time.
Implication: When H/L grows faster than the rate of
skill-biased technical change (s-1)g1, the skill
premium fall; when the supply growth falls short of
this rate, the premium increases
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Rate of return on human capital
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Problem: overpredicting
the last 15 years
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Why: Increased heterogeneity within
the different skill groups
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Problem with the general model?
Steady steady demand hypothesis versus
- Accelaration hypothesis
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Steady demand hypothesis (a)
Demand for skills increases at a constant
pace, so changes in inequality must be
explained by the pace of the increase in
the supply of skills.
According to this hypothesis, inequality (returns to
skills) was relatively stable before the 1970s,
because the rate of skill accumulation in the U.S.
economy was as rapid as the constant pace of skillbiased technical change
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Steady demand hypothesis (b)
The recent increase in inequality is then
explained, not by a major technological change,
but by a decline in the growth rate of the supply
of skills.
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Accelaration hypothesis
According to an alternative hypothesis,
acceleration hypothesis, the trend shift from
lower to higher wage dispersion in the U.S. in
the 1970s in the U.S. and many other OECD
countries in the 1980s, is explained by tempo
changes in technological development.
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Accelaration hypothesis
According to an alternative hypothesis, acceleration
hypothesis, the trend shift from lower to higher
wage dispersion in the U.S. in the 1970s in the U.S.
and many other OECD countries in the 1980s,,
explained by tempo changes in technological
development.
Supporters of this hypothesis believe that
information technology's rapid growth has created
a shortage of skilled labor. ICT has increased the
premium on education, skills and expertise.
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Literature background
• The second machine
age (Brynjolfson and
McAhee, 2013)
• The third industrial
revolution (Caselli 1999)
• General Purpose
technologies (Javanovic
and Rosseau 2005)
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Javanovic and Rousseau 2005
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Accelaration hypothesis
If the so-called residual wage difference, which
is the wage differences between seemingly
equally qualified individuals, increases it would
be interpreted as if the education system might
quantitatively, but not qualitatively, responds to
the increased demand for knowledge.
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Accelaration hypothesis
Alternatively, the new technology requires far
more of the workforce than merely formal
knowledge or ability to perform well-defined
tasks. This can include the initiative,
responsibility, curiosity, creativity,
innovativeness and ability to work together in
different configurations.
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Accelaration hypothesis
The development of residual differences shows
on companies' willingness to pay extra for such a
capability.
For the U.S. economy the difference in residual
wage increases in parallel with the growing
wage differentials in total and a steadily growing
share of people with higher education
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A kind of test of the A-hypothesis
Mincerian wage equation
lnit  X  t   it
'
it
• Wit is weekly earnings for individual i
observed in year t, Xit is a set of controls
which include nine educational dummies,
experience, regions
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Residualul inequality measures
white males 1963-97 in the US
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Sweden Residual wage differnces
90/10, 90/50 and 50/10 percentile
Increaced spread in wages within both high wage levels and low wages levels;
controlled for education, age, tenure, industry
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Conclusion
The paper finds that G&K’s model does a god
job in explaining return on H over a long-time
period.
Problem most recent period (IT-revolution?)
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Conclusion
• A&A argues that allowing for a richer set of
interactions between skills and technologies in
accomplishing job tasks both auguments and
refines the predictions of G&K’s approach –
and they suggest an ev en more important
role for H in economic growth than indicates
in the original model.
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