2. There have been many attempts to measure individual risk aversion by looking at individuals’ behavior with regard to risk—how much they are seemingly willing to pay to reduce the risks that they confront.
Conclusions
Since the Stiglitz, Sen, and Fitoussi (2009) report, a substantial amount of work has been carried out on measuring progress toward sustainable development, based on different models and approaches and in different geographical settings. However, further work is needed. Directions for future work include the following.
On the Capital Approach
Economic Capital
1. Distinguish between nominal wealth and the quantity of productive capital—data should be collected and displayed in such a way that the volume of productive capital is not obscured by revaluation effects. Also, the scope of nominal wealth and productive capital may be different and should be distinguished (for instance, nominal wealth includes net foreign financial assets, productive capital does not).
2. Use a balance sheet approach to help assess economic sustainability for all institutional sectors (e.g., banks, nonfinancial corporations, households) rather than for the government alone; and focus on both liabilities and as sets, recognizing that fire sales of assets in depressed financial markets will worsen net worth.
3. Improve fiscal modeling to incorporate demographic evolution and more generally engage in research on how much further to take simultaneity into account.
Human Capital
1. Increase efforts to understand and measure human capital stock and its formation process. In particular, skills (cognitive and noncognitive) and other components of human capital, and approaches to their measurement, need further discussion and analysis.
2. Develop satellite accounts for human capital using the cost approach together with more detailed nonmonetary indicators. In practice, satellite accounts for education and training should be a main building block. Coverage of nonformal education processes (e.g., on-the-job training) is important.
3. Pursue research on the income-based approach to provide more complete information, in particular on labor earnings from both market and nonmarket activity.
4. Increase efforts to understand and measure the noneconomic returns to human capital.
5. Rethink how the SNA treats public and private expenditures in human capital in view of capitalizing them.
6. Further explore the links between human capital and social capital.
Natural Capital
1. Improve measurement of environmental assets, including land and ecosystems (e.g., the extent and condition of different types, the services they provide).
2. Calculate and communicate at least annually how much carbon space is left before reaching potential “tipping points.”
3. National Statistical Offices should apply the SEEA, and produce timely estimates of “resource productivity” and the “circular economy.”
4. Improve the timeliness of indicators and accounts for natural capital applying the same now-casting techniques already used for economic variables like GDP.
On the Systems Approach
Stretching the Boundaries of Research
Interest in this complementary way of accounting for systems’ resilience is growing, as shown by initiatives taken in the context of the European Commission’s 7th Environmental Action Programme, or EAP (European Parliament and Council, 2013); the 2014 United Nations Development Programme (UNDP) framework; European Environment—State and Outlook 2015, also known as the SOER report (European Environment Agency, 2015); and the Joint Communication on “A Strategic Approach to Resilience in the EU’s External Action” (European Commission, 2017).
While the maturity of research in this field is not yet comparable with other fields of research included in this book, multi-disciplinary cooperation should be enhanced. A macro-prudential approach to sustainability policies needs to be underpinned with high-quality information, best fit for this purpose. In this regard, the two workshops on resilience organized by the HLEG can only be seen as starting points. While necessary and fruitful for the first collection of ideas and questions, they exemplified the difficulties to overcome “silo” mentalities and cultures of scientific disciplines and to merge expertise from all “camps” in one broader program.
The Stiglitz, Sen, and Fitoussi (2009) report has shown that it is possible to breach the boundaries and traditional ways of thinking and thereby achieve essential progress. Similar progress should be made in the field of resilience by inviting researchers to contribute to this major set of questions.
Recommendations
1. Improve measurement of resilience so as to better understand vulnerability and risk at each level and across all dimensions, while also examining the links and interactions between all levels, and the dynamic properties of the system. The international statistical community should establish a taskforce on the measurement of sustainability using the systems approach.
2. Further explore and document the complementarity of both the capital and the systems approaches, liaising theoretical considerations with empirical information.
3. Improve estimates and communication of risk and resilience to all stakeholders.
4. Involve various disciplines and assure horizontal cooperation to lay the basis of a special education path for sustainable development.
5. Introduce standardized terms and variables, which can serve as “ideal types” (in the sense of Max Weber), so that they fulfill expectations from both theoretical and empirical sides, thus helping to produce statistical metrics with high quality.
A New Impetus
The establishment of the 17 SDGs and 169 targets has given a new impetus to the development of common sustainable development indicators, and to the scientific work needed to underpin these indicators, so that progress toward sustainable development can be traced at global level, across countries and regions, in a reliable and timely manner. New measurement initiatives should take into account developments in statistical methodologies such as making use of big data or other approaches as proposed by the Global Conference on a Transformative Agenda for Official Statistics8 and in the report by the Independent Advisory Group to the UN Secretary-General (United Nations, 2014).
However, in a world of complex systems, sustainability cannot be measured in full: there are limits to the measurement, and only part of the knowledge is available. According to good democratic principles, both the knowledge available—monetary and physical indicators as well as models such as those for considering resilience of systems—and the areas where knowledge is missing should be communicated in a correct way to all stakeholders to show possibilities as well as limits for governance.
More investment is also needed to develop analytical models at global scale to evaluate future scenarios and the impact of alternative policies for sustainable development employing a systems approach. Transboundary effects of policies and the global interactions of economic, social, and environmental phenomena can only be addressed by analytical models. Development of these models will require better and more-timely data from the international statistical system. A more continuous and fruitful dialogue, at global scale, between scientists and statisticians has to be established as soon as possible.
Notes
1. As is the case in the recommendations of the Conference of European Statisticians (UNECE, 2014).
2. www.imf.org/en/News/Seminars/Conferences/DGI/global-conferences-on-dgi.
3. Previous definitions of human capital by the OECD differed in that they referred to economic well-being only. Social capital is considered in Chapter 10 of this book.
4. However, some of the strong assumptions of the lifetime income approach to calculating human capital are not very appealing. For example, “rates of return to schooling” typically capture only labor market returns, while they should ideally be extended to capture nonmonetary returns (such as the longer life expectancies of better-educated people, though there is debate over
causality in this relationship). However, capturing nonmonetary returns requires valuing them, which is frequently done using income. This is problematic, because such an approach might lead to the conclusion, with respect to life expectancy, that lives in poor countries are worth less than lives in rich countries, and by implication that the returns to human capital are lower. This approach is also less useful to explain future growth of GDP and productivity because the (real) service flows from that stock are themselves a function of the income streams expected in the future.
5. Adjusting the 3P + T framework of social protection (Devereux and Sabates-Wheeler (2004) to a broader resilience framework.
6. For example, the European Union faced a massive flow of migrants and refugees from 2015–16 onwards. This is likely to have a significant impact on the composition of European society in the coming decades. The ability of the EU to adapt to the new situation, and to transform itself through the integration of nonnative European citizens, will be key to avoiding a massive socio-economic crisis and instead build a strong cohesive society.
7. This interpretation of resilience draws on Manca, Benczur, and Giovannini (2017).
8. http://unstats.un.org/unsd/nationalaccount/workshops/2015/NewYork/lod.asp.
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