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-beingA biannual report providing evidence on

well-being (cross-country, over time)

The Better Life IndexAn 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

weaknesses20% top performers 60% middle performers 20% bottom performers

Canada

Netherlands

Greece

Tool to inform policy debate (ex 2): assess the full consequence of the Great Recession

GDP does not tell the whole story

Source: OECD National Accounts Database

2007 2008 2009 2010 2011 201290

92

94

96

98

100

102

104

United States

Household disposable income GDP

2007 2008 2009 2010 2011 201290

92

94

96

98

100

102

Household net disposable incme GDP

OECD Euro Area, 2007 = 100

Tool to inform policy debate (ex 3): crisis and subjective well-being

Life satisfaction dropped as unemployment increased

Source: How’s Life? 2013X-axis: Life Satisfaction =average score on a 0-10 scale ; source: OECD calculations on the World Gallup PollY-axis: Long term unemployment rate= % of the labour force unemployed for one year or more; source: OECD Labour Force Statistics

2007 2008 2009 2010 2011 20126.7

6.8

6.9

7.0

7.1

7.2

7.3

7.4

7.5

7.6

0

1

2

3

United States

Life satisfactionLong-term unemployment rate (right hand y-axis)

2007 2008 2009 2010 2011 20125.6

5.8

6.0

6.2

6.4

6.6

6.8

7.0

7.2

7.4

7.6

0

1

2

3

4

5

6

7

OECD Euro area (selected countries)

Life satisfactionLong-term unemployment rate (right hand y-axis)

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

2007 2008 2009 2010 2011 201210

15

20

25

30

35

40

45

50

55

OECD OECD Euro areaJPN USA

Percentage of people reporting to trust national government

2007 2008 2009 2010 2011 201280

85

90

95

100

105

110

115

120

OECD OECD Euro area USA

Percentage of people reporting having helped someone, 2007=100

Source: OECD calculations on Gallup World Poll

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

Vision and overarching

goalsOptions

Measurement and

evaluationImplemen

tationAnalysis

Detailed planning

and allocation of funds

Emphasis and focus

for the term of office

Wellbeing indicators as analysis and measurement

tool

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 well-being

• 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

Strategy developmentIdentify policy goals

PlanningPolicy options identifiedAnalysis of costs and benefits

Implementation and delivery

Evaluation and review

Acco

unta

bilit

yAnalysis

Alignment

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 multi-dimensional 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/measuringprogresswww.oecdbetterlifeindex.org