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The contribution of higher education to economic growth

Craig HolmesHigher Education and the Economy seminar

25th November 2014

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Introduction

• “there is compelling evidence that …higher education is the most important phase of education for economic growth in developed countries.” (DES, 2004, pg. 58)

• How might it do this?

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Introduction

• “The capacity for systematic invention, the capacity readily to perceive and apply the results of scientific progress, and the capacity for leadership both in the fields of organisation and in the transmission and the sifting of ideas - such capacities, if they do not come solely from education at the higher stages, certainly derive in a large measure from the existence of a sufficient proportion of persons educated to this level and of institutions devoted to higher education and research (Robbins Report, p. 206)”

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Key terms and definitions

• National income = national output = national expenditure• Gross domestic product (GDP):

– Private consumption– Investment– Government expenditure– Trade balance

• GDP per capita = income per person• Real vs. nominal

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National income

19801982

19841986

19881990

19921994

19961998

20002002

20042006

20082010

0

5000

10000

15000

20000

25000

30000

35000

40000

45000

50000

AustraliaFranceGermanyHungaryJapanSwedenUnited KingdomUnited StatesBrazilChinaKorea

GDP,

$ co

nsta

nt P

PP

Source: World Bank

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Economic growth

1950 1960 1970 1980 1990 2000 2010 2020

-8

-6

-4

-2

0

2

4

6

8Real GDP growth

GDP growth, %

GDP per capita growth, %

Source: ONS

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Economic growth

19711973

19751977

19791981

19831985

19871989

19911993

19951997

19992001

20032005

20072009

2011

-6

-4

-2

0

2

4

6

8

United Kingdom

United States

Real

GDP

gro

wth

per

capi

ta, %

Source: World Bank

www.skope.ox.ac.uk

Economic growth

19711972

19731974

19751976

19771978

19791980

19811982

19831984

19851986

19871988

19891990

19911992

19931994

19951996

19971998

19992000

20012002

20032004

20052006

20072008

20092010

2011

-15

-10

-5

0

5

10

France Germany

Hungary Sweden

United States

Real

GDP

per

capi

ta g

row

th, %

Source: World Bank

www.skope.ox.ac.uk

Economic growth

19711973

19751977

19791981

19831985

19871989

19911993

19951997

19992001

20032005

20072009

2011

-10

-5

0

5

10

15

United States

Brazil

China

Korea

Real

GDP

per

capi

ta, %

Source: World Bank

www.skope.ox.ac.uk

Economic growth

1980 1985 1990 1995 2000 2005 2010

-6.00

-4.00

-2.00

0.00

2.00

4.00

6.00

8.00

10.00

WorldHigh incomeMiddle incomeLow income

Real

GDP

per

capi

ta g

row

th, %

Source: World Bank

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Seminar outline

1. Economic theory on education and growth2. Empirical analyses of education and growth

– Specific studies looking at higher education

3. Problems with evidence4. Implications for policy

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The production function

• Simple production function:

• Mankiw, Romer and Weil (1992):

– Diminishing returns to each factor of production – α, β and γ < 1– Constant returns to scale – α+β+γ = 1– H = hL– A = productivity, for a given set of production factors. Captures what

can’t be measured, including technological progress, resource shocks and the health of institutions

𝑌= 𝐴.𝐹(𝐾,𝐿,𝐻) 𝑌= 𝐴𝐾𝛼𝐿𝛽𝐻𝛾

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Output and productivity

Source: World Bank, Barro-Lee (2000)

4 5 6 7 8 9 10 11 12 136.0

6.5

7.0

7.5

8.0

8.5

9.0

9.5

10.0

10.5

11.0

AUSAUT BEL CAN

CZE

DNKFINFRA DEU

GRC

HUN

ISLIRL

ISRITA

JPN

KOR

NLD

NZL

NOR

POL

PRT

SVK

SVN

ESP

SWECHE

GBR

USA

DZA

ARG

BWABRA

BGR

CHL

CHN

COL

CRI

CUBDOM

ECUIRN

JAM

JOR

MYSMUS

MEX

PAN

PERROM

ZAF

THATUN

TUR

URY

VEN

Schooling years, 2000

ln G

DP, 2

000

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Output and productivity

Source: World Bank (2000)

0 5 10 15 20 25 30 35 40 456.0

6.5

7.0

7.5

8.0

8.5

9.0

9.5

10.0

10.5

11.0

AUSAUT BEL CAN

CZE

DNK

EST

FINFRADEU

GRC

HUN

ISLIRL

ISRITA

JPN

KOR

LUX

NLD

NZL

NOR

POL

PRT

SVK

SVN

ESP

SWECHE

GBR

USA

BGR

CRI

DOMLVA LTU

MUS

MEX

PAN

PERROM

LCATUR

% workforce with tertiary education, 2000

ln G

DP, 2

000

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Education and growth

1. Neoclassical growth model – Solow, 1956 (without human capital)– Mankiw, Romer and Weil, 1992 (with human capital)

2. Endogenous growth models– Spillovers from capital investment– Innovation

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Neoclassical growth model

• Economy reaches a steady state (k*):

Capital stock per worker, k

Investment in k = saving rate * output

Replacement capital = k *(population growth + depreciation rate)

k0 k0 + new investment

Required replacement capital

new investment

Saving and investment

k*

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Neoclassical growth model

• Short run growth is driven by accumulation• Long run growth at the steady state

– Capital stock increases until investment = depreciation– Long run growth = technical progress

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Neoclassical growth model

• Mankiw, Romer and Weil (1992):– Both human and physical capital are accumulated– Human capital:

• requires investment (share of national output diverted into education and training)

• depreciates (skills lost if underused, or become obsolete following technical progress, or people retire)

– Diminishing returns to investment There is a steady state level of both k and h.

– Once reached, long run growth depends on A.

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Endogenous growth• Lucas (1988):

– Human capital produces spillovers (onto other workers) that raise overall productivity.

– If spillovers are large enough, diminishing returns to scale become constant returns i.e. double the capital stock double output per worker

– Simplify as a broad measure of capital:

– No steady state𝑦= 𝐴𝑘

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Human capital and growth

Broad capital stock per worker, k

Investment in k = saving rate * output

Replacement capital = k *(population growth + depreciation rate)

Saving and investment

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Human capital and growth

• Physical capital can accumulate without bound.• What about human capital?

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Human capital and growth

• Human capital in Lucas’ model is non-rival:– Investment (time spent studying) builds upon existing

human capital – Can be used by everyone, including later generations– Is this a satisfactory assumption for investment in HE?

• Rival vs. non-rival human capital– Skills– Knowledge

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Empirical studies

• Model options:– Neoclassical / conditional steady state models (e.g. Mankiw, Romer

and Weil, 1992) saving rates for human capital and physical capital and initial income (all per capita)

– Growth accounting growth rate of human capital stock (increase in average years of education) and growth rate of physical capital stock but not initial income

– Endogenous growth absolute increase in human capital stock (initial average years of education) and (possibly) initial income

– Quality vs. quantity measures (e.g. Hanuschek and Woessmann, 2007) – average performance on international tests (e.g. PISA 2006)

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Empirical studies

• What evidence supports policy claims • By the time of the Dearing Report in 1997:

– One cross country analysis (Gemmell, 1996, looking at 1960-1985)– “However the cross-section evidence for higher education remains

limited…the robustness of these results is uncertain” (Gemmell, 1997, paragraph 3.19)

• By the time 2006 and 2011 reforms:– Supporting evidence from Gemmell (1996) or literature reviews which

relied on it.

• Results that follow taken from Holmes (2013) which tests all the above model specifications

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Results 1: steady state

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Results 2: growth accounting

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Results 3: endogenous growth

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Results 4: extensions

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Problems with growth studies

• Krueger and Lindahl (2001) find numerous problems with macro growth studies:– Errors in education data– Controlling for capital– Assumptions about returns being constant across time– Causality– Other omitted variables

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Problems with growth studies

• Robustness:

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Comparison with other studies

• Aghion et al. (2009) – increases in patenting in the US can be attributed to exogenous

increases in spending on four-year degree courses at research intensive universities, and subsequently economic growth.

• Vandenbussche et al. (2006) – link between five-year growth rates and higher education, once

distance from the technological frontier is controlled for– Measure of variable: share of labour market with a tertiary education

degree

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Comparison with other studies

• BIS (2013)– 15 country, EUKLEMS data, 1982-2005– Finds a 0.2-0.5pp increase in productivity for a 1pp increase in the

employment share of graduates– Possible problems:

• Education is only captured by graduate employment share (as with Vandenbussche, 2006)

• Model mixes levels (human capital) with flows (investment)• Causality is overstated (for above reasons, plus reverse causation)

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Discussion

• How does this week’s material fit in / conflict with what you have studied so far?

• What are the policy implications?

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The expansion of HE in the UK

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The expansion of HE in the UK

• The occupational composition has changed in favour of graduates, but not enough

• Labour Force Survey, 1995-2008, 3 digit occupations:

Undergraduates and post-graduates

Higher (sub degree)

qualifications ApprenticeshipsLower

qualifications

Occupational composition 2.9% 1.1% -1.1% -2.8%

Residual 5.6% -1.0% -5.0% -5.5%

Total change 8.5% 0.1% -6.1% -8.3%

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The expansion of HE in the UK

• The big questions for “high skills vision” are:1. Do non-graduate jobs get upgraded when more graduates

are available?2. Does graduate expansion facilitate increases in demand for

skills?

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Job upgrading

0.000 0.050 0.100 0.150 0.200 0.250 0.300 0.350 0.400

-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

High initial relative graduate influenceLow initial relative graduate influence

Increase in graduate share, 2004-2011

Chan

ge in

rela

tive

grad

uate

influ

ence

Media associate professionals IT technicians Corporate managers

Public service professionals

Sales associate professionals

Managers in agriculture and forestry

Health associate professionals

Therapists

Legal professionals

Research professionals