Daron Acemoglu and David Autor NBER 17820, 2012

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What does human capital do? A review of Goldon and Katz’s The Race between Education

and Technology

Daron Acemoglu and David AutorNBER 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 wideninequality 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 itseducational 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 outputK=Stock of physical capitalX=Stock of human capitalA=Technology (residual)

Assumption:(1) CRS in K and X(2) No technological or human capital externalities in production

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Growth model

R=Rent of capital and RK/Y=0.3w=wX/Y=0.7

gXYXwgK

YRKgAgY X

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Canonical Model with two skill groups

L= Low skill labourH=High skill labour

Production function for the whole economy:

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

ssss

ss /1/1

]))(1()([ /1

HALAY HL

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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

ssss

ss /1/1

]))(1()([ /1

HALAY HL

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Canonical Model with two skill groups

..after some differating steps we ends with

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

LtHtttconst ln111tanln 10 s

gs

sgs

s

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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 constantpace, so changes in inequality must beexplained by the pace of the increase inthe 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 skill-biased 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-hypothesisMincerian wage equation

• Wit is weekly earnings for individual i observed in year t, Xit is a set of controls which include nine educational dummies, experience, regions

ittitXit 'ln

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Residualul inequality measureswhite males 1963-97 in the US

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Sweden Residual wage differnces90/10, 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.