The OECD-hosted High-Level Group on the Measurement of Economic Performance and Social Progress (HLEG) was created in 2013 to pursue the work of the Commission on the Measurement of Economic Performance and Social Progress convened by former French President Nicolas Sarkozy in 2008, the so-called Stiglitz-Sen-Fitoussi Commission, whose final report was published in September 2009. This book contains a collection of chapters written by members of the HLEG on topics that were the focus of the Group’s work. A companion report, Beyond GDP: Measuring What Counts for Economic and Social Performance, presents the Chairs’ overview of the issues discussed by the HLEG over the past five years and sets out a number of recommendations on what needs to be done next.

Assessing the progress of society presents a range of challenges: conceptual challenges (e.g. the inevitable trade-off between trying to be comprehensive and the limits in people’s capacity to deal with too much information); technical challenges (e.g. how to combine information across micro-data sets dealing with different issues, how to integrate micro-data informing on inequalities with macro-economic accounts dealing with averages); and organisational (e.g. how to improve coordination among different data-collectors, how to balance international harmonisation and local accountability, how to improve timeliness of existing data). The High-Level Group on the Measurement of Economic Performance and Social Progress (HLEG), hosted by the OECD from 2013 to 2018, addressed some of these challenges, building on the report of the Stiglitz-Sen-Fitoussi Commission published in 2009. The aim remains the same – help to develop the means to describe progress and, in this way, to contribute to better policies. This book consists of a collection of authored chapters dealing with those issues that the HLEG felt deserved further attention and have thus been at the core of the Group’s deliberations over the past few years. A complementary report by the HLEG Chairs (J.E. Stiglitz, J.-P. Fitoussi and M. Durand, Beyond GDP: Measuring What Counts for Economic and Social Performance) provides a broader overview of the issues discussed by the Group.

This chapter provides a high-level overview of the themes discussed in more detail in the individual chapters of this report. For each issue addressed in this report, the chapter spells out the reasons for their importance, the measurement challenges they raise, and the steps that should be taken to improve statistics in these fields.

The report by the Stiglitz-Sen-Fitoussi Commission raised fundamental questions about GDP as a measure of economic performance and social progress. The Sustainable Development Goals (SDGs) process put in train by the UN system proposes a number of goals and targets going beyond GDP that apply universally, to developing and developed countries alike. This chapter takes stock of the SDG process in relation to the general movement towards a broader perspective on the measurement of economic performance and social progress. Three central themes emerge. First, the inevitable and enduring tension between the pull to broaden and expand indicators for assessing and monitoring economic and social progress in development on the one hand, and the imperative to keep a relatively small number of top-level indicators, in order to facilitate national discourse and policy-making, on the other. The SDG list of 17 goals and 169 targets is useful as a platform from which to choose and narrow down, but choose we must at the national level. Second, National Statistical Offices must be given the governance independence and the financial resources with which to provide the framework for a data-based dialogue on economic and social progress at the national level. Third, some aspects of the measurement of progress and development are global and beyond the sole remit of any one National Statistical Office. For these exercises, and as a conduit for providing support to National Statistical Offices, the international community needs to commit resources for the provision of this global public good.

This chapter addresses the challenges posed by measuring vertical inequalities in household income, consumption and wealth. It takes stock of international databases on economic inequality, highlighting the fact that they often display not only different levels of inequality but, for some countries, diverging trends as well. The chapter also discusses the challenges in measuring inequality because of under-coverage and under-reporting of top incomes (the “missing rich”) and approaches to correct for the problem. The shortcomings of typical welfare metrics used to measure economic inequality in international databases (disposable income and/or consumption expenditures) are also discussed, stressing the need of a more comprehensive metric, using an income variable that includes social transfers in-kind (especially for education and healthcare) and adds the effect of consumption taxes and subsidies. The chapter makes several recommendations to address the existing shortcomings in the measurement of income and wealth inequality.

This chapter discusses the importance of horizontal inequalities, i.e. inequalities in both the income and non-income dimensions among groups of people with shared characteristics; of intra-household inequality; and of gender inequalities in the distribution of wealth (the gender wealth gap). Measurement of horizontal inequalities raises the question of which group classification to adopt, whether to weight measures for each group by their population size in order to obtain an aggregate measure, and how to take into account intra-group distribution. The chapter then considers how estimates of overall inequality might be impacted by the neglect of intra-household inequality, highlighting the difference between household and individual welfare, and how to obtain better estimates of the gender wealth gap.

This chapter discusses what is meant by inequality of opportunity (i.e. “ex ante inequality”), in the sense of how different circumstances involuntarily inherited or faced by individuals could affect their economic achievements later in life. This concept is also taken to include how fair the procedures are. The chapter presents the theoretical principles that can be used for measuring inequality of opportunity. Practical issues of measurement are illustrated through examples and stylised facts from the applied literature on inequality of opportunity and, in particular, on inter-generational economic mobility. The chapter summarises the nature of the data needed to monitor the observable dimensions of inequality of opportunity and makes recommendations on the statistics that should be regularly produced for effectively monitoring them.

This chapter summarises concepts, methods, and goals of the WID.world project, the World Inequality Database, along with some first results from this source. WID.world builds on the experience of the World Top Incomes Database (WTID) to construct time-series on the concentration of income at the very top of the distribution in more than 30 countries, to include wealth distribution and developing as well as developed countries. The ultimate goal of WID.world is to provide annual estimates of the distribution of income and wealth using concepts consistent with macro-economic accounts, i.e. to construct distributional national accounts (DINA). WID.world also aims to produce synthetic micro-files providing online information on income and wealth (i.e. individual level data that do not result from direct observation but rather through estimates that reproduce the observed distribution of the underlying data). The long-run aim of the WID.world project is to release income and wealth synthetic DINA micro-files for all countries on an annual basis.

This chapter evaluates progress in measuring subjective well-being since the 2009 Stiglitz-Sen-Fitoussi Report. It summarises approaches based on evaluative measures, experiential well-being and eudaimonia (the extent to which a person believes that his or her life has meaning and purpose). It notes a tremendous uptake of subjective well-being measures by national statistical offices since 2009, and the growth in research on subjective well-being in the scientific literature. The chapter takes stock of what we have learned from global analyses of social and economic progress “Beyond GDP” since 2009, including through the UN World Happiness Report, the US National Academy of Science Report on Measuring Subjective Well-Being, the OECD “How’s Life?” series and its Better Life Initiative. It also describes progress in acquiring new knowledge about subjective well-being and progress in applying this to policy. The chapter identifies some of the key issues that will need to be addressed to gain a more complete understanding of subjective well-being, including causality and data collection.

This chapter examines what we know about economic security and what we still must learn. It defines economic security as vulnerability to economic loss, and treats “economic” as a description of the consequences (such as income loss) rather than the causes of insecurity. The chapter presents a series of recommendations for researchers and statistical agencies that would permit better measurement and analysis of economic security, both as a fundamental feature of economic life and as a major influence on subjective well-being and economic behaviour. It synthesises state-of-the-art theory and evidence regarding economic security and then lays out a small number of relatively well-developed measures. Based on this review and on the best available data, the chapter provides some preliminary evidence about the evolution of economic security in developed economies. The chapter then describes some of the continuing shortcomings of existing statistics in this field, and suggests ways to improve them.

This chapter outlines the principles of the capital approach and of the systems approach to measuring sustainable development. In the capital approach, human, social, natural, and economic capital are considered separately, with indicators presented on their stocks and how they change over time. While significant progress has been achieved in operationalising this approach to sustainability, this approach, argue the authors, implicitly assumes the independence of these stocks, and do not easily lend itself to considering interactions between different parts of the systems that underpin human well-being and functioning ecosystems. The chapter considers how the systems approach should be taken forward to move from theoretical considerations to empirical applications. It explains the key notions underpinning the systems approach, including risk, vulnerability and resilience, arguing that sustainability remains the ultimate objective. The chapter proposes a measurement agenda, suggesting steps to improve consideration of economic, human, and natural capital in the capital approach; and to improve the measurement of resilience and other aspects of the systems approach.

This chapter discusses the role of trust for social progress and people’s well-being. It reviews the different definitions and types of trust, including rational trust, moral trust and social preferences, as well as the state of existing statistics on trust. The chapter argues in favour of the definition of trust provided by the OECD Guidelines on Measuring Trust as “a person’s belief that another person or institution will act consistently with their expectations of positive behaviour”. It looks at why trust matters for the well-being of people and the country where they live, and assesses the available evidence on its role in supporting social and economic relations. It analyses trust between individuals (inter-personal trust) and trust in institutions (institutional trust) as determinants of economic growth, social cohesion and well-being, as a crucial component for policy reform and for the legitimacy and sustainability of any political system. Finally, the chapter stresses the importance of integrating survey measures of trust into the routine data collection activities of National Statistical Offices, and of implementing quasi-experimental measures of trust and other social norms based on representative samples of the population as a complement to traditional survey questions.