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Economics of Human Capital
Lecture 3
Education
Ian Walker
Lancaster University Management [email protected]
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Last week
• Returns to education – Ability bias
– Twins
– IV methods – Matching
• See
– Card chapter in Handbook of Labour Economics – Ashenfelter et al meta-analysis
– Goldin and Katz NBER WP
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Overview of this lecture
• Wider effects of education – Clear that beneficial effects go beyond
earnings
• Inequality – Changes in D and S
– Other factors
• Signalling• Education and growth
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Non-pecuniary effects
• Oreopolous JEP 2012
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Some facts about returns
over time• Returns to education in the U.S. fell
during the 1970s
– when there was a very sharp increase inthe supply of educated workers.
• Returns to education then began a
sharp rise in 80s – Rise slowed in the 1990s
• Race between technology and
education 8
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Some facts
• This conclusion is robust to manysensible ways of measuring educationreturns
– In a standard OLS Mincer wage equation,return to year of education rose from about7.5% in 1980 to 10% in 1990.
– Large increase in wage differentialbetween college and HS grads
– And between HS graduates and HS
dropouts 9
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Some facts
• Also an increase in the estimated returnto “experience” (for younger cohorts).
– Note: 'returns to experience' typically
estimated x-section data, so this patternprobably has no meaningful predictivepower for lifecycle earnings.
• Many other economies experienced arise in earnings differentials in1980s
– but only in the UK was the rise as
pronounced as in the U.S. 10
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Some facts
• Very large increases: US and UK – And Germany
– recent work by Dustmann, et al using
Germany social security records
• Modest increases: Australia, Canada,Japan, Spain, and Sweden
• No noticeable changes: France andItaly
• Modest falls: Netherlands 11
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Some facts
• After the 1990s, rise in overall inequality inthe US gave way to a 'polarization‘
– wage inequality rising in the upper-half of the
wage distribution – but attenuating or even declining in the lower
half.
• Some share of the rise in overall inequality isdue to a rise in 'residual' inequality
– That is, the inequality remaining after partiallingout the estimated contribution of observables
(such as education and experience). 12
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Theory of skill premia
• Demand and supply – Competitive market
• Two types of workers (L, H), imperfect subs
• CES
• Wages equal marginal products so
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Theory of skill premia
• Expansion in education (rise in H/L) reducesreturns to education
• But large expansion in H/L has occurred in
most countries since 1945• Yet ω has risen in most countries
• Something must be happening to AH/AL to
counteract the rise in H/L …. • Labour saving technical progress
– AH rising faster than AL 16
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Katz and Murphy
• KM estimate
where γ2 is 1/σ
• That is, they assume that AH/AL can becaptured by a time trend
• KM uses CPS 63-87 (25 obs) and find
• So σ=1/0.71=1.4
• See also Katz and Goldin’s “race” book 17
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Other evidence
• Blau and Kahn JPE 1996 – found that labour market institutions (unions and
wage centralization) are much better predictorsof cross-country wage inequality than are supplyand demand indices
• They find little evidence that D and S explainany of the cross-country differences in the
relative earnings of the less-skilled
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Other evidence
• Leuven, Oosterbeek and van Ophem, EJ 2004 use IALS data rather tha education
– Weak link between IALS scores and schooling
• Estimate relative wages of skill j acrosscountries as a fn of relative D and Sdifferences
• They find β<0 and support D and S story
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Human Capital and GrowthMacro evidence
• Aggregating a Mincer HCEF to the economylevel we get
• Differencing removes technologicaldifferences that are part of the error termterms to give
• so the S coeff shows how returns havechanged over time, while the S coefficient
gives the (social) rate of return in j at time t .22
ln jt jt jt jt w r S e
ln j j jt jt j jt w r S r S e
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Evidence
• O’Neill (JPE 1995)
– (social) return rising
• The idea that growth rates should converge
is in a feature of many macro-studies – those below their steady-state growth rate
should catch up with those above.
•
– where W* is the steady state level of GDP pc
• Then the macro growth equation wouldbecome
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*
1 j jt j jW W W u
1 , 1 ...... j jt j t jW W rS e
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Tests
• Many unconvincing attempts• See Brown and Sessions paper
– in G Johnes and J Johnes, Intl Handbook of
Education Economics• For example, compare returns to self
employed with returns to employed
– But self-employed are self-selected – Unclear if IV available
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Tests
• One idea –signalling says
that relat ive educationmatters
–HC saysabsoluteeducation
matters 25
• Chevalier, Harmon,Walker and ZhuEconomic Journal
2004
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Better idea
• A more direct test would be to show thata ‘signal’ has a positive effect onwages even when acquiring that signal
has no impact on productivity.• Tyler et al QJE 2000 natural experiment
• Does GED raise earnings?
– GED is a post-school test that is supposedto be equivalent to getting a high schooldiploma
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TMW strategy
• GED costs $50 and takes 20 hours• GED holders earn less than HS graduates
– But more than HS dropouts
• Selection issue – GED holders, compared to dropouts, have:
• More S, better cognitive skills, better educated parents
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Method
• GED pass level differs by state!• But if GED score is a good measure of
a person’s ability/productivity, then
people with same‘ability
’ (i.e. 40 − 44)
are given a GED in Texas but not in NY.
• This quasi-experiment effectively
randomly assigns the GED ‘signal’ topeople with the same GED scoresacross different U.S. states.
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Result• What does the signalling model predict
in this case? – People with GED scores of 40 − 44 will earn
more if they get the GED certificate than not
• But Human Capital model implies thatsince ability is comparable among these
groups, wages will be also• MTW found 20% effect after 5 years
– Note: MTW method assumes that employers
think that a NY GED is not perceived as betterthan a Texas GED29
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Aggregation
• Signalling depends on relative education• So if education levels rose generally
– Signalling model would show no rise in incomes
• HC depends on absolute level of education
• So if education levels rise generally
– HC model would show rise in incomes
• So how do income levels change aseducation levels rise on average?
– Aggregate HC earnings function30
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Human Capital and GrowthMacro evidence
• Aggregating a Mincer HCEF to the economylevel we get
• Differencing removes technologicaldifferences that are part of the error termterms to give
• so the S coeff shows how returns havechanged over time, while the ΔS coefficient
gives the (social) rate of return in j at time t .31
ln jt jt jt jt w r S e
lnw j = r jS jt + r jt S j + u jt
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Evidence
• O’Neill (JPE 1995) and Lindahl and Krueger(JEL 2001)
– (social) return rising
• The idea that growth rates should convergeis in a feature of many macro-studies
– those below their steady-state growth rateshould catch up with those above.
– where W* is the steady state level of GDP pc
• Then the macro growth equation wouldbecome 32
*1 j jt j j
W W W u
1 , 1 ......t t
W W rS e
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Externalities
• Several studies examine the effects ofschooling of one group on another group’sincomes
• Most convincing work exploits migration• Iranzo and Peri (2009)
– variation in the push-driven immigration of highlyeducated workers
– They find that an increase in college education(but not an increase in high school education)had significant positive productivity externalities.
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Externalities
• Peri et al . (NORFACE Migration DiscussionPaper 2013, and IZA WP 2013)
– exploit the exogenous variation in the stock offoreign-born “STEM” workers induced by visa
policy changes• 1% increase in the foreign-STEM share of a US city’s
total employment in the US increases wages for nativegraduates by 4-6%
• Small positive effects on native employment
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Endogenous growth
• Endogenous growth models with R&D – Romer (NBER WP 1989, NBER WP2000)
• growth rate partly depends on the level of human
capital.• Policy that incentivizes innovative activity,
such as R&D tax credits
– Needs to also encourage a more STEM workers• Goolsbee (AER 1998)
– government R&D spending raises wages ofscientists
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Next week
• Intergenerational transmission
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