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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