Executive Summary
The High-Level Expert Group on the Measurement of Economic Performance and Social Progress (HLEG) builds on the analyses and recommendations of the 2009 Commission on the Measurement of Economic Performance and Social Progress (the “Stiglitz-Sen-Fitoussi” Commission, SSF) in highlighting the role of well-being metrics in policy and encouraging a more active dialogue between economic theory and statistical practice. The report makes explicit the often-implicit assumptions hidden in statistical practices and their real-world consequences. Its central message is that what we measure affects what we do. If we measure the wrong thing, we will do the wrong thing. If we don’t measure something, it becomes neglected, as if the problem didn’t exist.
There is no simple way of representing every aspect of well-being in a single number in the way GDP describes market economic output. This has led to GDP being used as a proxy for both economic welfare (i.e. people’s command over commodities), and general welfare (which also depends on people’s attributes and non-market activities). GDP was not designed for this task. We need to move “Beyond GDP” when assessing a country’s health, and complement GDP with a broader dashboard of indicators that would reflect the distribution of well-being in society and its sustainability across its social, economic and environmental dimensions. The challenge is to make the dashboard small enough to be easily comprehensible, but large enough to summarise what we care about the most.
The 2008 crisis and its aftermath illustrate why a change in perspective is needed. The GDP loss that followed the crisis was not the temporary one-off event predicted by conventional macro-economic models. Its effects have lasted over time, suggesting that the crisis caused the permanent loss of significant amounts of capital; not just machines and structures, but also “hidden capital”, in the form of lower on-the-job training, permanents scars on youths entering the labour market during a recession, and lower trust in an economic system “rigged” to benefit a few.
Different metrics, including better measures of people’s economic insecurity, could have shown that the consequences of the recession were much deeper than GDP statistics indicated, and governments might have responded more strongly to mitigate the negative impacts of the crisis. If, based on GDP, the economy is perceived to be well on the road to recovery, as many governments believed in 2010, one would not take the strong policy measures needed to support people’s living conditions suggested by metrics that inform on whether most of the population still feels in recession. Nor would one take measures to bolster the safety net and social protection in the absence of metrics on the extent of people’s economic insecurity.
These failings in the policy responses to the crisis were compounded by overly focusing on the consequences of public spending in raising government’s liabilities, when this spending could take the form of investment increasing the assets in governments’ and countries’ balance sheets. The same follows when measures of unemployment do not reflect the full extent of a country’s “unused” labour resources. The “Beyond GDP” agenda is sometimes characterised as “anti-growth”, but this is not the case: the use of a dashboard of indicators reflecting what we value as a society would have led, most likely, to stronger GDP growth than that actually achieved by most countries after 2008.
This book also looks at progress in implementing the recommendations of SSF since 2009, identifying areas that require increased focus by statistical agencies, researchers and policy-makers. The UN Sustainable Development Goals, agreed by the international community in 2015, clearly go far “Beyond GDP”, but their 169 policy targets and more than 200 indicators for “global monitoring” are too many to guide policies. Countries will have to identify their priorities within the broader UN agenda, and upgrade their statistical capacities which, even in developed countries, are insufficient to monitor whether the agreed commitments are being met. The international community should invest in upgrading the statistical capacity of developing countries, especially in areas where country data are needed to assess global phenomena, such as climate change or the world distribution of income.
Inequality in income and wealth has today a central role in policy discussions in ways it did not in 2009. But important progress is still needed in a range of areas, such as measuring what happens at both ends of the income distribution, integrating different data sources, and measuring the joint distribution of income, consumption and wealth at the individual level. When looking at inequality, it is also important to look at differences between groups (“horizontal inequalities”), at inequalities within households and the way resources are shared and managed, which are especially important in the case of wealth. We should also look beyond inequalities in outcomes to inequality of opportunity. Inequality of opportunity is even more unacceptable than inequality of outcomes, but the operational distinction between the two is fuzzy, as we don’t observe all circumstances that shape people’s outcomes and are independent of their efforts. It is also important to pursue efforts to integrate information on economic inequalities within national accounts, to provide metrics of how GDP growth is shared in as timely a fashion as output statistics.
The book also highlights metrics that still lack a solid foundation within official statistics. Subjective well-being measures are critical to assess the non-monetary costs and benefits of public programmes and policies. While much progress has been achieved since 2009 in embedding these measures in large-sample official surveys, such efforts should be maintained to shed light on the many measurement and research issues that are still open. Economic insecurity is a “new” field where much more effort is needed to develop metrics of the shocks affecting people, and of the buffers available to them. The 2008 crisis reduced not just people’s economic security but also their trust, because of the widespread perception of the unfairness in the manner in which the crisis was handled. The loss of trust (both in others and in institutions) is a long-lasting legacy of the crisis, whose effects are contributing to the political upheavals we are witnessing around the world. Finally, the measurement of sustainability in its environmental, economic and social dimensions, and of the resilience of systems to shocks, are priorities for research and statistical practice, requiring the contributions of different disciplines and approaches.
The book provides 12 recommendations for further work in all these areas, which complement those in the Stiglitz, Sen and Fitoussi (2009) report.
While different measures are clearly needed, alone they are not enough. What also matters is to anchor these indicators in the policy process, in ways that survive the vagaries of electoral cycles. This book draws on country-experiences to show how well-being indicators are being used in the different stages in the policy cycle, from identifying priorities for action, to assessing the advantages and disadvantages of different strategies to achieve a given policy goal, to help allocate the resources needed to implement the selected strategy, to monitor interventions in real time as they are implemented, and to audit the results achieved by policies and programmes to help decide how to change them in the future. Steps taken by several countries in this direction are described in this book. While these experiences are recent, they hold the promise of delivering policies that, by going beyond traditional silos, are more effective in achieving their goals and that could help in restoring people’s trust that public policies can deliver what we all care about: an equitable and sustainable society.