For Good Measure

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  Figure 9.2. Shocks and Capacities

  Source: Manca, A.R., P. Benczur, and E. Giovannini (2017), “Building a scientific narrative towards a more resilient EU society—Part 1: A conceptual framework,” IRC Science for Policy Report, No. 106265, Publications Office of the European Union, Luxembourg, http://publications.jrc.ec.europa.eu/repository/bitstream/JRC106265/jrc106265_100417_resilience_scienceforpolicyreport.pdf.

  When the time of exposure is not too long and the intensity is not too large, the main characteristic of this ability is the absorptive capacity, which relates to stability and resistance, i.e., a situation where agents absorb the impact of shocks without changing their behavior. As the time of exposure or its intensity increases, and absorptive capacity is exceeded, adaptive capacity will start playing a role: agents adjust their expectations and aspirations when coping with deteriorating conditions. This requires flexibility, and involves incremental changes that are necessary to allow agents to continue functioning without major qualitative distress in response to disturbances. Agents try to mitigate potential damages and at best turn the adverse situation into an opportunity. Adaptation often takes place on multiple levels, as it is rarely related to a single specific stressor, but rather reflects a broad combination of many.

  Ultimately, as the disturbance becomes unbearable (both in terms of its intensity and persistence) and adaptation would lead to too large a change, transformative capacity is the way forward. This transformation can be both the outcome of a deliberate decision and action of agents, like a regime change through a democratic election process, or a change forced by environmental or socio-economic conditions. The main feature of transformative capacity is that it does not only include technical and technological changes, but also cultural changes, behavioral shifts, and institutional reforms. Transformative resilience can be defined as the means of learning from past events and engineering changes, ideally toward a better condition given current constraints. Such a shift of the status quo may nevertheless be difficult to achieve.6

  In real situations, different agents might experience the two dimensions differently. Moreover, disturbances seldom have a single channel of transmission; instead, they tend to originate from a chain of events and consequences and trigger multiplicative effects. This means that the three types of capacity often act simultaneously, at multiple levels (individuals, community, region, country, institutions) and with potentially different intensity at different levels. In other words, they are different perspectives of the same reality rather than opposing or competing components.

  In this context,7 a society is resilient if, when facing shocks or persistent structural changes, it keeps its ability to deliver individual and societal well-being in an inter-generationally fair way, i.e., ensuring current well-being without seriously compromising that of future generations. Absorptive and adaptive capacity means that, despite some initial inevitable losses after a shock, a resilient society tends to return to its original level of well-being and functionality, and potentially move to a better one. When the situation becomes unbearable and a transformation is necessary, the original level of well-being and functionality can no longer be sustained; however, these transformations should lead to a new, sustainable path, with acceptable levels of well-being.

  This approach establishes a close link between resilience and sustainability, the former being the means to achieve the latter in a dynamic sense. While sustainability in the capital approach is about the quantity and value of the stock of the capital available (which acts as a buffer), a resilience approach focuses on the qualitative side, which in turn depends on many aspects of a “system” (diversity, the flow of assets, inter-connectedness). One way to think of this complementarity is that sustainability is the long-term design phase, while resilience is about reactive capacity, i.e., about managing imbalances and acting to keep or restore sustainability.

  In the real world, where reaching a tipping point may determine “breaks” in some parts of the system, sustainability can become impossible because of nonlinearities: for example, political institutions can become unsustainable because of a prolonged recession and decline in people’s standards of living. In this case a “revolution” may happen, leading to the collapse (a deep transformation) of the socio-economic system or to deep conflicts (foreign war, civil war, etc.).

  Layers and Inter-dependences

  One of the main implications of this approach is that resilience needs to be analyzed in the context of sustainability by looking at the entire ecological-social-economic-political system. Such a general approach may have several “sectoral” applications: for example, focusing on resilience of the ecosystems for the benefit of our generation and of the generations to come should be at the center of any long-term policy, such as the 2030 Agenda, no matter which specific economic or social policies are concerned.

  In this perspective, the global system can be visualized as a “doughnut” with different layers: the economic, social, and environmental layers, with an indication of the planetary boundaries (and showing where these boundaries have already been crossed), as well as an area of safe and just space for humanity (Figure 9.3). Not only are systems embedded in one another, but there are layers within each of them.

  In this perspective, society consists of individuals, communities, regions, nation-states, supranational and international entities, and humankind at large. The resilience of individuals should be considered in the context of resilience of communities, which in turn are embedded in regions and nation-states, and so on. The concept of resilience goes hand in hand with the situation of a system being hit by disturbances. If the risk materializes, a system can be vulnerable or not, depending on the intensity of the shock and the properties of the system. A vulnerable system can recover with a contained social welfare loss or not.

  Figure 9.3. A Safe and Just Space for Humanity

  Source: Raworth, K. (2012), “A safe and just space for humanity. Can we live within the doughnut?,” Oxfam Discussion Paper, February, www.oxfam.org/sites/www.oxfam.org/f/dp-a-safe-and-just-space-for-humanity-130212-en.pdf; and Rockström, J. et al. (2009), “Planetary boundaries: Exploring the safe operating space for humanity,” Ecology and Society, Vol. 14(2), p. 32, www.ecologyandsociety.org/vol14/iss2/art32/.

  Resilience of systems should also be seen as inter-dependent with the people within those systems, as one might think of micro-, meso-, and macro-economies. While at a macro-level, a country’s economy might be resilient to economic shocks, not all groups of people within the country might be resilient. So the analysis of macro-measures, such as GDP, might be misleading in the analysis of resilience if not accompanied with other socio-economic indicators and by in-depth analysis of vulnerable groups.

  Improved measurement should be produced at each layer in order to understand their vulnerability and risks, but the links and interactions between all levels also need to be examined. The systems approach allows us to create different scenarios and estimate and demonstrate the related effects (similarly to stress tests). The challenge consists in increasing our capacities to distinguish between dangerous situations and sustainable pathways in an uncertain context. This approach could also help to generate a baseline against which to estimate the cost of different types of shocks and the risks associated with them, as well as estimates of investments to be made to make the systems more resilient.

  While recognizing the limits of scenarios and forecasting, model results are important inputs in the design and implementation of policies and programs for reducing risk and increasing resilience. These results could provide a framework for a public discourse about choices that have to be made as society moves toward sustainability, choices which might include trade-offs between the “now” and “tomorrow” as well as between the “here” and “elsewhere” dimensions of sustainability.

  A practical example of a systems approach is given in Figure 9.4, which describes the impact of changes in water quantity and quality on different
system layers.

  From an overall perspective, a starting point to understand how shocks spread among the different segments of the whole system, and where to intervene, is provided by the materially closed Earth system (Figure 9.5). Its three main ingredients are the inputs (the four types of capital stocks), the outputs (well-being and its determinants), and the engine (the overall “assembly” system) that translates inputs into outcomes and outputs. The final results of a system are ultimately determined by the outcomes—i.e., societal and individual well-being—while shocks typically affect the inputs (capital stocks), and then the effects interact in the assembly system. In some cases, the engine might be in distress, and is the place where most of the policy interventions should occur.

  Figure 9.4. The Vulnerability to Variations in Water Availability and Quality

  Source: Sosa-Rodríguez, F.S. (2016), “An alternative framework for analyzing the vulnerability of socio-ecological systems,” Realidad, Datos y Espacio. Revista Internacional de Estadística y Geografia, Vol. 7(1), INEGI.

  With respect to measurement, this approach implies that we should concentrate on three aspects:

  1. Resilience of assets, to be measured in the context of the capital approach.

  2. Resilience of the engine, referring to eco- and social system services and to institutions, production processes, and their complex interactions. Measurement here is highly problematic, since it refers to the power of institutions to shape the production process, in a broad sense.

  3. Resilience of outcomes/output, in terms of investment, consumption of goods and services, well-being, and negative externalities such as pollution, social marginalization, or poverty.

  Figure 9.5. Ingredients of Resilience in the Materially Closed Earth System

  Source: Manca, A.R., P. Benczur, and E. Giovannini (2017), “Building a scientific narrative towards a more resilient EU society—Part 1: A conceptual framework,” JRC Science for Policy Report, No. 106265, Publications Office of the European Union, Luxembourg, http://publications.jrc.ec.europa.eu/repository/bitstream/JRC106265/jrc106265_100417_resilience_scienceforpolicyreport.pdf, based on Costanza, R. et al. (1997), “The value of the world’s ecosystem services and natural capital,” Nature, Vol. 387, pp. 253–260.

  Metrics for Resilience, Risks, and Uncertainties

  A macro-prudential, system-wide approach in the sense described above does not yet exist either in policy or in statistical terms. Even in the SNA, and its extensions by the SEEA, a classical aggregation concept is used, rooted in the inventory and valuation of single capital goods. Nevertheless, it is possible to broadly outline the main conceptual components and procedural steps that would be necessary to explore and develop in detail a complementary way of accounting for a system’s dynamics and resilience:

  • Scope and dimensions: Available knowledge in various scientific disciplines should be used to evaluate and quantify risks, i.e., threats for the resilience and the sustainability of economic, social, and environmental systems. Priority should be given to the risks that are most relevant for sustainability, e.g., those that are pushing systems close to planetary boundaries, as defined by the scientific community. While micro-level accounting tends to undervalue natural and social capital, macro-level accounting can capture systemic interactions between environment, society, and economy.

  • Quantification: Geographical Information Systems (GIS), accounting methods, and indicator systems (e.g., dashboards) should be combined to achieve the best possible and most far-reaching condensed presentation of the major risks (current, emerging).

  • Aggregation, valuation: The actual price system does not work well with complex and/or systemic risks. Actuarial expertise (scientists or practitioners) that is used to estimate “premiums” necessary to ensure the major risks could provide valuable inputs for this exercise.

  • Scenarios: These might be used to show the dynamic evolution of sustainability over time. A good example is old-age pensions. A society may confront a large stock of pension entitlements for only one cohort, obligations that will be costly to meet for some years but then the system stabilizes. A policy action might be needed to deal with short-term problems, but possibly a different one from that implied by a large stock of pension obligations toward all future cohorts. Inter-generational accounting models, which typically focus only on government finances, could be used to show that large fiscal deficits in the future could be met by higher taxes or though other ways of shifting the burden to households, in particular when households have low debt and high assets; private debt is already co-analyzed with government debt in the context of the EU Micro-Imbalances Procedure (MIP).

  • Communication: It is important to integrate all societal stakeholders (science, civil society, business, policy) from the very early stages in generating knowledge of this kind. New metrics generated using this procedure should in particular facilitate a democratic dialogue. As a consequence, the processes of measurement and political discourse should be seen as mutually dependent and influencing each other. In this sense, new metrics, generated through new measurement processes, should be tailored and fit for specific purposes in the policy cycles.

  VULNERABILITY, POVERTY, AND RESILIENCE

  This chapter has argued that it is important to assess the risk properties of the economic system—i.e., its exposure to risk, its vulnerability, and its resilience. Changes in economic policy can have significant effects on “risk performance”: increasing exposure to risk; making the economic system more vulnerable; reducing the capacity of individuals or other entities in the system to cope with risks; or making the system as a whole (or the units within it) less resilient. Some reforms may simultaneously improve average economic performance but reduce risk-performance. It is important not only to know when this is happening, but also to quantitatively assess the effects. If GDP growth increases but resilience decreases, we would want to know this. In some circumstances, a country might want some measure of resilience in its dashboard of key indicators.

  While this is an area in which so far there has been limited progress—and it is an important arena for future research—some promising approaches include the following:

  Vulnerability and poverty. When individuals move out of poverty, we would hope that that move is permanent. In reality, many of those who escape poverty often fall back into it again. Even those who have never been poor have a chance of falling into poverty. The threat of falling into poverty can loom large in the life of a person and other family members—it can be a source of anxiety that our national income statistics never pick up. One simple measure of vulnerability is the share of people who are not poor at any one date but may experience at least one year of poverty in the next five years (UNDP, 2014).

  Resilience to economic phenomena. Vulnerability is a measure of the possibility of downward mobility. Resilience, by contrast, is a measure of “recovery,” i.e., how quickly (if ever) a family or an economy that experiences a negative shock recovers. There can, of course, be many measures of resilience: how fast it takes for a family that winds up in poverty to move out of poverty; or how fast on average it takes for an economy that experiences a negative shock to return to its pre-crisis level, or to the level that it could have attained in the absence of a crisis. At each level, it is important to know the determinants of resilience, i.e., what makes some families or economies more resilient than others. In the light of the systems approach, it is also important to look at resilience from a broad societal perspective, beyond simple income or output measures.

  A striking aspect of the 2008/2009 crisis was that different countries experienced shocks of different magnitudes; by and large, the recovery has also been slower than for previous economic downturns, which is understandable given the magnitude of the shock. In the beginning, some commentators had expected a “V-shaped recovery,” with the economy quickly bouncing back; others thought, however, that the economy was less resilient, and that the recovery would be “U shaped.”
The latter perspective proved right, and in the following years the debate was about how long the flat bottom of the U would last. These experiences highlight that an economy can be resilient with respect to small shocks, and not with respect to big shocks.

  Money-equivalent measures. This chapter has described the economy as a dynamic sub-system, connected to social and environmental sub-systems. In assessing changes in the economic system, we can measure its overall risk performance in a way similar to the Atkinson and Stiglitz measures for inequality and to the Arrow and Pratt measures for risk: how much society would be willing to pay to avoid the systemic risk that it confronts. Such a measure would compound the risk properties of the system as a whole and the aversion to risk of society.1

  The chapter has described the properties of systems that affect the size of systemic risks. For instance, better automatic stabilizers could make the economic system more resilient—it would more quickly recover from an adverse shock. Thus, for a given degree of risk aversion, a more resilient economic system—one that recovers more quickly from an adverse shock—would presumably lower the systemic money-equivalence of the risk. This measure could provide guidance on the value that should be assigned to the risk aspects of various economic reforms.2 For example, a move from a defined benefit to a defined contribution pension scheme could weaken automatic stabilizers since individuals are more exposed to business-cycle risks; in this situation, such a measure might provide some guidance as to how much “better” in some other way the defined contribution system has to be compared with the defined benefit to offset the loss in systemic stability.

  1. The discussions of inequality and of risk highlighted the importance of money-equivalent measures. These measures ask how much a person would be willing to pay to avoid some risk, or society to avoid inequality. But in economics, we typically think of matters at the margin—how much we are willing to pay to get rid of a small amount of risk or inequality. In evaluating a new policy, we may ask what is the incremental value of the reduction in risk or inequality compared with the status quo baseline. Stiglitz has described such a marginal measure for income inequality (Stiglitz, 2015b).

 

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