Transcript BLI Presentation for Visits and Seminars Programme

Measuring and managing multidimensionality: insights
from How’s Life? and other OECD projects
Paul Schreyer,
Deputy Director of the Statistics Directorate
E-Frame Final Conference “GDP and Beyond: Measurement,
Policy Use and Moving Forward”
10-11 February 2014, Amsterdam
Background (1)
• OECD work on well-being started over 10
years ago
• OECD’s measurement of well-being:
•
•
•
•
•
Multi-dimensional
Focus on people and households
Focus on outcomes
Objective and subjective aspects
Both averages and inequalities
Background (2) the OECD well-being framework
Background (3) OECD work on well-being: main
products
How’s Life? Measuring well-being
A biannual report providing evidence on wellbeing (cross-country, over time)
The Better Life Index
An interactive web application to disseminate
and engage with people on what matters
most in life
• What have we learned from this process?
• And how can we make the link to policy?
Policy use of multi-dimensional frameworks and measures
1. Tool to inform policy debate (How’s Life?,
Better Life Index)
2. Framework for policy design (National
approaches)
3. Quantitative tool for policy analysis
(Inclusive Growth)
A tool to inform policy debate (ex 1): understanding
strengths and weaknesses
20% top performers
Canada
Netherlands
Greece
60% middle performers
20% bottom performers
Tool to inform policy debate (ex 2): assess the full
consequence of the Great Recession
GDP does not tell the whole story
United States
OECD Euro Area, 2007 = 100
Household disposable income
GDP
Household net disposable incme
104
102
102
100
100
98
98
96
96
94
94
92
92
90
2007
2008
2009
2010
2011
2012
90
2007
Source: OECD National Accounts Database
2008
2009
2010
GDP
2011
2012
Tool to inform policy debate (ex 3): crisis and
subjective well-being
Life satisfaction dropped as unemployment increased
United States
OECD Euro area (selected countries)
Life satisfaction
Long-term unemployment rate (right hand y-axis)
Life satisfaction
Long-term unemployment rate (right hand y-axis)
7.6
3
7.5
3
7
7.4
6
7.2
7.4
7.3
2
5
7.0
6.8
7.2
2
7.1
4
6.6
3
6.4
7.0
1
6.9
1
6.8
6.7
7.6
6.2
2
6.0
1
5.8
2007
2008
2009
2010
2011
2012
0
5.6
2007
2008
2009
2010
2011
Source: How’s Life? 2013
X-axis: Life Satisfaction =average score on a 0-10 scale ; source: OECD calculations on the World Gallup Poll
Y-axis: Long term unemployment rate= % of the labour force unemployed for one year or more; source: OECD Labour Force Statistics
2012
0
Tool to inform policy debate (ex 4): The crisis also
affected other aspects of life
Trust in governments declined
But new forms of solidarity emerged
Percentage of people reporting
to trust national government
OECD
JPN
55
Percentage of people reporting having helped
someone, 2007=100
OECD Euro area
USA
OECD
115
45
110
105
35
100
30
25
95
20
90
15
85
10
USA
120
50
40
OECD Euro area
2007
2008
2009
2010
2011
2012
80
2007
2008
Source: OECD calculations on Gallup World Poll
2009
2010
2011
2012
Lessons (1) Dashboard vs.composite index
• Much debate about pros and cons
– Ease of communication
– Weights, interpretation of composite
• We may need both
– For different audiences
– For different purposes:
• How do drivers of WB evolve? Dashboard
• How is WB jointly determined by drivers? Composite
• OECD:
– No weights (HiL)
– Self-selected weights (BLI)
– Estimated weights in Inclusive Growth (new)
•
Lessons (2) The ‘correlation’ argument
‘WB measures show enough correlation with GDP per
capita to simply concentrate on the latter’
• Only approximately true: much unexplained variance
• Incorrect for particular dimensions (GDP and obesity)
• Correlation says nothing about relationship GDP – WB: e.g.,
could higher levels of WB be achieved with different GDP?
• Loses a key policy message: WB should not be a ‘spin-off’
or collateral of growth but the primary policy target
Lessons (3) The ‘happiness confusion’
‘OECD shows that happiest people are in country X’
• distinction between measures of subjective and
objective WB gets lost – its all about ‘happiness’
• Relegation to ‘quality problem’: the ‘real issues’ are
elsewhere
• Even harder: getting across distinction between
different subjective measures of life evaluation (eg
cantril scale) and subjective experience measures
(affect)
Well-being as a framework for policy design (Ex 1): The
New Zealand Treasury Framework
• Policy tool developed for
front-line policy analysts
•A “manageable list of
the key issues that make
the most difference”
• Embed the concept of
living standards more
systematically and more
visibly in policy advice to
Ministers
Well-being as a framework for policy design (Ex. 2):
informing the budgetary process in Israel
Wellbeing indicators as part of
the strategy process
Wellbeing indicators as
analysis and measurement
tool
Vision and
overarching
goals
Analysis
Options
Emphasis
and focus for
the term of
office
Detailed
planning
and
allocation of
funds
Implement
ation
Measurement
and
evaluation
Well-being as a framework for policy design (Ex 3):
New UK vision
Lessons (4) Needed: a policy-integrated framework for
well-being
• From ‘accidental’ to systematic checking of
consequences of policies on multiple dimensions of wellbeing
• OECD proposes (E-Frame Handbook) a policy-integrated
framework that drives:
– Alignment of outcomes across government agencies and
processes
– Analysis of policy options and consequences
– Accountability of results (next slide)
Joining-up policy at all stages
Alignment
Planning
Evaluation and
review
Policy options identified
Analysis of costs and
benefits
Implementation and
delivery
Analysis
Accountability
Strategy
development
Identify policy goals
Lessons (5)
• Whole of government approach for credibility
and to go beyond institutional silos
• A common set of criteria for setting priorities
• Systematic evaluation but also ‘stories’ needed
how WB Framework has affected policy
design
Sendsteps question here
(”What do we need to do to make multidimensional measures to become a true reference
for policy makers?”)
Finally: WB as quantitative tool for policy appraisal
• Example: OECD work on Inclusive Growth
• Experimental composite measure of Living
Standards
• Sub-set of WB dimensions:
Income
Jobs
Health
• Adjusted for inequality
• Model to link living standards to policies
Overall measure: Living standards
De-composition of living standards of median households
1995-2007
Identifying determinants of components of living standards
(e.g. health)
Lessons (6) Quantitative policy appraisal
• Need to build up empirical evidence on
interaction between dimensions
• Tricky but crucial: estimating determinants of
health, jobs, HH income and their distribution
• Trade-off between capturing complexity and
quantification
• But much of the success of WB measures will
lie in our capacity to link to policies
THANK YOU!
www.oecd.org/howslife
www.oecd.org/measuringprogress
www.oecdbetterlifeindex.org