For Good Measure Read online

  Risk and resilience are other important aspects of complex systems. The repercussions of the financial crisis apart from the financial sphere have intensified interest in measuring the interactions of different sectors to quantify sustainability and systemic risk, as well as raising issues about accurate measurement of the value added by the financial sector. The G20 Data Gaps Initiative, which is working toward comprehensive measures of economic risk, is an important part of this analysis. Bringing different sectors together in the systems approach is a new idea, and substantial work will be required to make it operational, requiring inputs from across disciplines. An international task force would be important to move this agenda forward.

  Trust and Social Capital

  A key component of social capital is trust, the topic discussed by Yann Algan in Chapter 10 on the basis of the OECD’s definition of trust: “a person’s belief that another person or institution will act consistently with their expectations of positive behaviour.” Trust between individuals (inter-personal trust) and trust in institutions (institutional trust) are a key determinant of economic growth, social cohesion, and subjective well-being. Higher levels of inter-personal trust at the country level are associated with higher GDP per capita and lower income inequality (as measured by Gini coefficients). Having cooperative social relationships with others affects people’s health and happiness above and beyond the monetary gains derived from cooperation. Institutional trust is a key element of a resilient society and is critical for implementing effective policies, since public programs, regulations, and reforms depend on the cooperation and compliance of citizens. Trust is therefore a crucial component for policy reform and for the legitimacy and sustainability of any political system.

  Most of the research on the role of trust and cooperation draws on answers from survey questions. Survey data supply subjective information, which requires caution in use and interpretation. Issues include how individuals interpret the question they are asked, and whether there are systematic differences between groups in their interpretations that might be misread as differences in the underlying level of trust. Surveys are generally unable to disentangle the variety of social preferences that can be involved in inter-personal trust such as altruism, reciprocity, social desirability, and reputation. In some cases there is insufficient data coverage to fully analyze differences across people or countries, or over time.

  Experimental measures of trust are a promising tool for improving our grasp of these issues, especially when implemented in conjunction with surveys. Experimental measures ask participants to make decisions under uncertainty, with their degree of trust influencing their decision, allowing for a measure of trust that may be more reliable than responses to survey questions. There have been significant advances in experimental measures since 2009, including the development of online platforms that permit data collection based on representative samples at low cost. The relationship between lab-based experimental measures and field outcomes, however, has to be investigated more thoroughly if we are to rely on the experimental method to make inferences about the real world. In addition, identical experiments are generally not repeated in different countries, so it is difficult to understand if there is cross-country variation in the underlying mechanisms of trust.

  One solution is to combine surveys with experiments. Experiments carried out on representative samples could also shed light on the nature of social attitudes and on the extent of bilateral cooperation between individuals in the larger population.

  Both generalized trust and trust in institutions are higher among higher-income groups and among more highly educated people, and they are lower among unemployed people and single-person households with at least one dependent child. While these patterns hold true across the majority of OECD countries, it is important to study the drivers of trust in the context of countries’ specific circumstances so as to shed light on how policy-makers could develop such an important type of social capital. If trust plays a key role in explaining economic and social outcomes, it becomes urgent to identify the institutions and public policies needed for it to develop.

  Notes

  1. Similarly, those producing the data sets should document all assumptions clearly and thoroughly; make the data, programs, and results publicly available to allow for replicability whenever it applies; compare their methods and results with one another; and, eventually, agree on conventions and best practice when calculating inequality indicators from micro-data, secondary, and imputation-based sources.

  2. The DINA data are compiled based on tax records; as these records do not always allow combining information on individuals belonging to the same household, the national income data mentioned in the text are expressed on a “per adult” basis (with no adjustment for family size). This concept differs from the “per consumption unit” basis (with adjustment for family size) used for the income data discussed in Chapter 3.

  3. www.imf.org/external/np/seminars/eng/dgi/index.htm.

  References

  Anand, S., P. Segal and J.E. Stiglitz (eds.) (2010), Debates on the Measurement of Global Poverty, Oxford University Press, New York.

  Stiglitz, J.E., A. Sen, and J.-P. Fitoussi (2009), Report by the Commission on the Measurement of Economic and Social Progress, http://ec.europa.eu/eurostat/documents/118025/118123/Fitoussi+Commission+report.

  UNECE (2017), Guide on Measuring Human Capital, United Nations, New York, http://dx.doi.org/10.18356/c136-en.

  United Nations (2015), “Transforming our world: The 2030 agenda for sustainable development,” Resolution 70/1 of the UN General Assembly, www.un.org/ga/search/view_doc.asp?symbol=A/RES/70/1&Lang=E.

  United Nations et al. (2014), System of Environmental-Economic Accounting 2012—Experimental Ecosystem Accounting, https://unstats.un.org/unsd/envaccounting/seeaRev/eea_final_en.pdf.

  2.

  Sustainable Development Goals and the Measurement of Economic and Social Progress

  Ravi Kanbur, Ebrahim Patel, and Joseph E. Stiglitz

  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 toward 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.

  Ravi Kanbur is T.H. Lee Professor of World Affairs, International Professor of Applied Economics and Management, and Professor of Economics at Cornell University; Ebrahim Patel is Minister of Economic Development in South Africa; and Joseph E. Stiglitz is University Professor at Columbia University. This chapter draws on the outcomes of an HLEG workshop on “Measurement of Well-Being and Development in Africa,” sponsored by the Government of South Africa, the Japanese International Cooperation Agency, Columbia University, and Cornell University, and held in Durban, South Africa, on Nove
mber 12–14, 2015. The authors wish to thank those who participated in this workshop for their contributions. The section titled “The Rationale of Goal Setting” draws on the section “Conceptual Foundations of the MDG Process” in Bourguignon et al. (2010). The opinions expressed and arguments employed in the contributions below are those of the authors and do not necessarily reflect the official views of the OECD or of the governments of its member countries.

  Introduction

  The report by the Stiglitz-Sen-Fitoussi Commission raised fundamental questions about GDP as a measure of economic performance and social progress (Stiglitz, Sen, and Fitoussi, 2009, 2010). The critique included GDP’s neglect of (1) nonmarket and social transactions; (2) stocks and flows of physical, natural, and human capital; and (3) broad distributional issues. It also highlighted that GDP has many shortcomings even as a measure of market production. The OECD-hosted High-Level Expert Group on the Measurement of Economic and Social Progress (HLEG) has been working on developing further the recommendations of the report by the Stiglitz-Sen-Fitoussi Commission. This chapter focuses, in particular, on the suitability of GDP, and alternatives to it, for developing countries. At the same time, the SDG process has been put in train by the UN system and has proposed a number of goals and targets as successors to the Millennium Development Goals (MDGs) after 2015, the MDG target date. It is thus becoming increasingly clear that the international community views progress in broader terms than just an increase in GDP. All of this links to, and feeds into, ongoing processes in developing countries to develop robust indicators of human, social, and economic development.

  This chapter takes stock of the SDG process in relation to the general movement toward a broader perspective on the measurement of economic performance and social progress. We begin with a brief history of the MDGs and their transformation into the SDGs. Then, we consider the rationale for global targeting of the type found in the MDGs and SDGs in terms of their potential for setting norms. After that, we translate this global norm setting into the national context and take up, in particular, the “dashboard versus single index” question, as well as the question of how large a dashboard should be. We follow up with implications for statistics and statistical processes within countries. Next, we address the question of global level monitoring, beyond a primarily national perspective, before sharing our concluding thoughts.

  MDGs and SDGs: A Brief History

  The push to take a broad perspective on well-being, and especially in the measurement of development progress, goes back at least as far as the basic needs indicators and physical quality-of-life indexes in the 1970s. Both of these reflected the dissatisfaction with standard GDP as a measure of well-being. Basic needs went further than income and included access to food, water, shelter, clothing, sanitation, education, and health care. Richard Jolly (1976) spoke of the “enthronement of basic needs.” In 1980, Morris (1980) proposed his Physical Quality of Life Index (PQLI) by taking a simple average of measures of literacy, infant mortality, and life expectancy. And in the 1980s Amartya Sen developed his capability theory, which broadened the basis of social evaluation beyond income to “functionings and capabilities,” defined as aspects of what human beings could be and do, whether they are in good health and can perform paid work in safe conditions (see, for example, Sen, 1985).

  Agencies like the World Bank still gave primacy to national income per capita as a measure of development, but this began to change during the 1980s. The 1990 World Development Report (World Bank, 1990) was on poverty. It introduced the famous “dollar a day” poverty line, and the iconic figure of “one billion people around the world” who “live below one dollar a day.” But the move toward broader perspectives was given a big push by the launch of the Human Development Index (HDI) in UNDP’s first Human Development Report in 1990 (UNDP, 1990). This index was a simple average of per capita income and measures of literacy and longevity. Although criticized for various technical reasons at the time of its release (Kanbur, 1990), the HDI proved to be enormously useful in (1) shifting attention to other development outcomes beyond income, such as health and education; and (2) setting up a competition between countries on their HDI rank. The HDI has been modified and improved over the years to take account of the criticisms, incorporating, in particular, concerns about inequality. But the core index still elicits great attention when it is published, and leads to national and international press coverage comparing different countries, which in turn can be used by civil society as a lever to pressure their governments in areas like health and education.

  The move toward multi-dimensional evaluation continued with a series of United Nations conferences throughout the 1980s and 1990s that emphasized gender, children, environment, food, and so on. This move was combined with the normsetting potential of the HDI and culminated in the MDGs, which derived from the Millennium Declaration, proclaimed by over 150 world leaders at the Millennium Summit in September 2000. The MDGs set out eight goals, and targets within each goal, to be achieved by 2015. The eight goals were (1) eradicate extreme poverty and hunger; (2) achieve universal primary education; (3) promote gender equality and empower women; (4) reduce child mortality; (5) improve maternal health; 6) combat HIV/AIDS, malaria, and other diseases; 7) ensure environmental sustainability; and 8) create a global partnership for development. Specific targets were put forward under each goal, including, for example, the iconic target 1A: “Halve, between 1990 and 2015, the proportion of people whose income is less than $1.25 a day.”

  As 2015 approached, progress was gauged relative to these targets. Perhaps not surprisingly, United Nations Secretary General Ban Ki-moon proclaimed success and attributed it to the MDGs:

  The MDGs helped to lift more than one billion people out of extreme poverty, to make inroads against hunger, to enable more girls to attend school than ever before and to protect our planet. They generated new and innovative partnerships, galvanized public opinion and showed the immense value of setting ambitious goals. By putting people and their immediate needs at the forefront, the MDGs reshaped decision-making in developed and developing countries alike. (United Nations, 2015a, p. 3)

  Whatever the truth of the causal link (considered in the next section), the scope of the goals was bound to be broadened when considering what to do after 2015, as interested parties brought to the fore key elements they considered were left out of the MDGs. In September 2015, the United Nations General Assembly adopted Resolution 70/1, entitled “Transforming Our World: the 2030 Agenda for Sustainable Development,” which stated:

  The new Agenda builds on the Millennium Development Goals and seeks to complete what they did not achieve, particularly in reaching the most vulnerable.… In its scope, however, the framework we are announcing today goes far beyond the Millennium Development Goals. Alongside continuing development priorities such as poverty eradication, health, education and food security and nutrition, it sets out a wide range of economic, social and environmental objectives. It also promises more peaceful and inclusive societies.… We are announcing today 17 Sustainable Development Goals with 169 associated targets which are integrated and indivisible. Never before have world leaders pledged common action and endeavour across such a broad and universal policy agenda. (United Nations, 2015b)

  These seventeen goals are now under the following headings: (1) no poverty; (2) no hunger; (3) good health and well-being; (4) quality education; (5) gender equality; (6) clean water and sanitation; (7) affordable and clean energy; (8) decent work and economic growth; (9) industry innovation and infrastructure; (10) reduced inequalities; (11) sustainable cities and communities; (12) responsible consumption and production; (13) climate action; (14) life below water; (15) life on land; (16) peace, justice, and strong institutions; and (17) partnership. Compared to the eight MDGs listed above, the SDGs represent some constants (e.g., poverty) and some bundling together (e.g., child mortality and maternal health) but mainly unbundling (e.g., poverty and hunger are separated out) and the addition
of new dimensions (i.e., a full range of environmental goals, as well as goals on inequalities, on peace, on urbanization, on employment, etc.).

  The politics and pressures that led to an expansion of the scope of the eight MDGs to 17 SDGs (with its associated 169 targets and 232 indicators for these targets) are clear. Each constituency argued for its own particular goal to be represented in the overall list. Thus, for example, Doyle and Stiglitz (2014) argued, with success, for inequality reduction to be an explicit goal. Climate change was introduced as a separate goal but so, for example, was the goal to “conserve and sustainably use the oceans, seas and marine resources for sustainable development.” The urban constituency got its goal, to “make cities and human settlements inclusive, safe, resilient and sustainable,” and so on. The fact that everyone wanted the focal point of their concern (e.g., rule of law, inequality, urban issues, etc.) to be included in the list of SDGs is testimony to at least the belief in the power of these goals. Advocates believed that inclusion increased the chance of progress in their area of concern. But is 17 goals and 169 targets just too much, as some have argued? The answer to this depends on the objective of the exercise, i.e., the “goal” of goal-setting.