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THE OECD INCLUSIVE GROWTH FRAMEWORK Paul Schreyer Deputy Director OECD Statistics Directorate OECD/ESCAP/ADB Regional Consultation on Inclusive Growth in Southeast Asia Bangkok, 9 June 2015
THE OECD INCLUSIVE GROWTH
FRAMEWORK
Paul Schreyer Deputy Director OECD Statistics Directorate OECD/ESCAP/ADB Regional Consultation on Inclusive Growth in Southeast Asia Bangkok, 9 June 2015
Ensure that growth goes hand-in hand with improvements in people’s living conditions
Policies need to target multiple objectives simultaneously, not just GDP
Need new metrics • Aspects beyond income
• Distribution
Need to revisit our models • Integrate multidimensionality and interactions
The issue
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• A 3-pronged approach:
– Which growth? -> Multidimensional
– Whose growth? -> Distributions
– What drivers? -> Policy relevance
Defining Inclusive Growth
Housing Income
Work-Life Balance Jobs
Education and skills
Social Connections Health
Civil Engagement and Governance
Environmental Quality
Personal Security
Subjective Well-being
Which growth? OECD How’s Life?
framework
• Measuring evolution of income, health, employment of particular parts of the population:
• Median households
• Bottom 10%
• Being able to assess the net effect of policies on these variables
• Drawing conclusions for governance, institutions and policy design
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Whose growth?
• For assessment of net effects of policies, we need common units
• Translate changes in health or jobs into income equivalents
• Econometric techniques, well-researched
• Life assessment = f(income, health, jobs)
• Valuation in money terms 1 year of life expectancy = 5% of income
1 point of unemployment = 2% of income
• Weights are conservative and standard and representative of peoples (implicit) preferences
• Measure of multi-dimensional living standards
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How do we measure?
Note: OECD calculations based on OECD National Accounts, Health and Income Distribution databases.
Average growth in MLS 1995 and 2012
-2
0
2
4
6
8
10
ITA
PR
T
USA
AU
T
DN
K
DEU
NLD BEL
SWE
FRA
CZE
CA
N
HU
N
NZL
AU
S
NO
R
FIN
CH
N r
ur
CH
N u
rb
CH
N
Inequality Unemployment Longevity Income Inclusive growth Economic growth
Average OECD MLS
%
USA – AUS: similar GDP/cap and real HH income growth But unemployment declines in AUS, life expectancy rises and inequality effects are small Growth in living standards AUS>USA
Time profiles of MDLS
$, PPP adjusted
Note: OECD calculations based on OECD National Accounts, Health and Income Distribution databases.
… and 2012 MLS levels
-25000
-15000
-5000
5000
15000
25000
35000
CH
N r
ur
CH
N
MEX
CH
L
HU
N
CH
N u
rb
EST
SVK
PO
L
GR
C
PR
T
CZE
ESP
SVN
KO
R
IRL
ITA
NZL
DN
K
FIN
GB
R
JPN
BEL
NLD
FRA
USA
SWE
DEU
CA
N
AU
T
AU
S
CH
E
NO
R
LUX
Inequality Unemployment Longevity Income Living standards
Living standard of the median household (OECD average)
USD per capita USA higher income levels than AUS But overcompensated by differences in LE and inequality
Quantifying policy transmission:
example GDP and household income
Long experience about policy effects on GDP per capita
But much less on HH income
GDP growth has trickled down less since the mid-1980s.
The gap may reflect differential impact of pro-growth policies on household disposable incomes
Different effects for different social groups along the
distribution of income.
Gains in GDP have not fully trickled down to
household incomes
(on average since the mid-1980s)
The elasticity of household disposable income to GDP per capita has been even lower at the bottom end of the distribution pointing to growing inequality.
0.5
0.55
0.6
0.65
0.7
0.75
0.8
0.85
0.9
0.95
1
-12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 11 12
Bottom to top-sensitive income standards
A. Household disposable incomes elasticities to GDP
Average income
Source: Causa, de Serres and Ruiz (2014)
Reforms can have a differential impact on wage
dispersion and employment
Effect of change on:
A pro-growth change in: Wage dispersion Employment
Overall earnings
inequality
Innovation and Technology
Technical progress (Higher MFP) + = +
Higher R&D intensity + = +
Globalisation
Deeper trade integration = = =
Higher FDI openness = = =
Education / Human capital
Higher share of skilled workers - + -
Product market competition
Lowering regulatory barriers to
entry
+ + =
Source: Going for Growth 2015, Chapter 2
Work ahead
• Further quantifying policy effects on health and jobs and computing net effects
• Health and Unemployment inequalities: monetisation allows combining with income inequalities
• Adding education -> ‘welfare return to education’ as opposed to income return to education
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