Systemic and Extreme Risks:Ways Forward for a Joint Framework

Systemic risk is getting increasing attention in the science as well as popular press not to the least due to the growing complexity of the world as well as increasing data availability. The aim of this paper is to discuss selected topics in extreme and systemic risk modelling, measuring and management approaches.We find that from a purely quantitative modelling perspective, single and systemic risk assessment can be jointly performed via the concept of copulas and therefore can be embedded within an integrated framework without major difficulties. Consequently, we see single and systemic risks as not independent but indivisible which have to be assessed jointly. However, from a risk measure perspective we see some important differences as single risk measures focus on probability distributions while systemic risk measures focus on dependency measures. Hence, we call for ensembles of risk measures which should be a superior approach for studying single and systemic risks in complex networks as different events can cause systemic risk to realize (e.g. too big to fail, too interconnected to fail, keystone species etc.). From a risk management perspective, we conclude that the inclusion of human agents causes a fundamental difference in the management of systemic risks compared to other systems as their decisions are contingent and may cause unpredictable shifts due to mutual uncertainties that can evolve. Consequently, we argue for an iterative risk management approach similar to the call from climate change and adaptation science, for example discussed in the various IPCC reports. Last but not least, the idea of collective responsibility echoes the need to target risks that threaten whole societies. That such risks are reduced is foremost in the public interest and we therefore call for an institutional change that enables the effective handling of it in the future

Modelling Dependent Risk With Copulas: An Application On Flooding Using Agent-Based Modelling

In the present work we introduce a copula approach to model dependencies between risks in large scale networks and show how this could be used to avoid underestimation of extreme events. Furthermore, we apply the approach within an agent based model to determine the macroeconomic consequences due to flood events. We show that without a copula approach only average annual losses on the country level would be available. However, with the copula approach, which includes the estimation of basin scale loss distribution through catastrophe modelling, exposure estimation through Corine land cover mapping, assessment of appropriate copulas and parameter estimation, including a algorithm to couple coupled basins as well as an upscaling procedure to the country level, the whole risk spectrum can be, for the first time on this scale, estimated. The direct loss estimates from the copula approach, separated into different risk bearers, are used to build a damage scenario generator which gives the input for the agent based model. The agent based model in turn assesses the additional indirect losses due to the event which can be much larger than the direct losses alone

Modelling Macroeconomic Effects of Natural Disaster Risk: A Large Scale Agent Based Modelling Approach Using Copulas

We introduce a copula approach to model dependencies between risks and show how this could be used to avoid underestimation of extreme events in large-scale risk assessments. We apply the approach within an extensive agent based model to determine the macroeconomic consequences due to catastrophic events. The agent based approach is capable of modelling an entire national economy with all sectors, including households, firms and banks. It is based on an input-output model with 64 industries where all goods and services are produced endogenously. We show that without a copula approach only average annual losses on the country level would be available which limits analysis on long term effects. However, with the copula approach, which includes the estimation of basin scale loss distribution through catastrophe modelling, exposure estimation through Corine land cover mapping, assessment of appropriate copulas and parameter estimation, including an algorithm to couple coupled basins as well as an upscaling procedure to the country level, the whole risk spectrum can be estimated. The direct loss estimates from the copula approach, separated into different risk bearers, are used to build a damage scenario generator which gives the input for the agent based model. The agent based model in turn assesses the additional indirect losses due to the event which can be much larger than the direct losses alone. The agent based model is calibrated to the case of Austria at a scale 1: 10, e.g. with hundreds of thousands of agents and the agents are calibrated according to micro data, including business information, balance-sheets, and income statements. We show that there can be severe effects due to large scale natural disaster events through different transmission channels, even leading to systemic risks. This detailed information should be useful for determining risk management options on various scales

Evaluating Partnerships to Enhance Disaster Risk Management using Multi-Criteria Analysis: An Application at the Pan-European Level

Disaster risk is increasingly recognized as a major development challenge. Recent calls emphasize the need to proactively engage in disaster risk reduction, as well as to establish new partnerships between private and public sector entities in order to decrease current and future risks. Very often such potential partnerships have to meet different objectives reflecting on the priorities of stakeholders involved. Consequently, potential partnerships need to be assessed on multiple criteria to determine weakest links and greatest threats in collaboration. This paper takes a supranational multi-sector partnership perspective, and considers possible ways to enhance disaster risk management in the European Union by better coordination between the European Union Solidarity Fund, risk reduction efforts, and insurance mechanisms. Based on flood risk estimates we employ a risk-layer approach to determine set of options for new partnerships and test them in a high-level workshop via a novel cardinal ranking based multi-criteria approach. Whilst transformative changes receive good overall scores, we also find that the incorporation of risk into budget planning is an essential condition for successful partnerships

A methodological framework to operationalize Climate Risk Management: Managing sovereign climate-related extreme event risk in Austria

Despite considerable uncertainties regarding the exact contribution of anthropogenic climate change to disaster risk, rising losses from extreme events have highlighted the need to comprehensively address climate-related risk. This requires linking climate adaptation to disaster risk management (DRM), leading to what has been broadly referred to as climate risk management (CRM). While this concept has received attention in debate, important gaps remain in terms of operationalizing it with applicable methods and tools for specific risks and decision-contexts. By developing and applying a methodological approach to CRM in the decision context of sovereign risk (flooding) in Austria we test the usefulness of CRM, and based on these insights, inform applications in other decision contexts. Our methodological approach builds on multiple lines of evidence and methods. These comprise of a broad stakeholder engagement process, empirical analysis of public budgets, and risk-focused economic modelling. We find that a CRM framework is able to inform instrumental as well as reflexive and participatory debate in practice. Due to the complex interaction of social-ecological systems with climate risks, and taking into account the likelihood of future contingent climate-related fiscal liabilities increasing substantially as a result of socioeconomic developments and climate change, we identify the need for advanced learning processes and iterative updates of CRM management plans. We suggest that strategies comprising a portfolio of policy measures to reduce and manage climate-related risks are particularly effective if they tailor individual instruments to the specific requirements of different risk layers. (authors' abstract

Assessing current and future impacts of climate-related extreme events. The case of Bangladesh

Extreme events and options for managing these risks are receiving increasing attention in research and policy. In order to cost these extremes, a standard approach is to use Integrated Assessment Models with global or regional resolution and represent risk using add-on damage functions that are based on observed impacts and contingent on gradual temperature increase. Such assessments generally find that economic development and population growth are likely to be the major drivers of natural disaster risk in the future; yet, little is said about changes in vulnerability, generally considered a key component of risk. As well, risk is represented by an estimate of average observed impacts using the statistical expectation. Explicitly accounting for vulnerability and using a fuller risk-analytical framework embedded in a simpler economic model, we study the case of Bangladesh, the most flood prone country in the world, in order to critically examine the contribution of all drivers to risk. Specifically, we assess projected changes in riverine flood risk in Bangladesh up to the year 2050 and attempt to quantitatively assess the relative importance of climate change versus socio-economic change in current and future disaster risk. We find that, while flood frequency and intensity, based on regional climate downscaling, are expected to increase, vulnerability, based on observed behaviour in real events over the last 30 years, can be expected to decrease. Also, changes in vulnerability and hazard are roughly of similar magnitudes, while uncertainties are large. Overall, we interpret our findings to corroborate the need for taking a more risk-based approach when assessing extreme events impacts and adaptation - cognizant of the large associated uncertainties and methodological challenges -

Mainstreaming of climate extreme risk into fiscal and budgetary planning: application of stochastic debt and disaster fund analysis in Austria

While ageing-related costs are perceived as the major drivers of fiscal pressure in the EU, concerns over climate-related public expenditures have received comparatively little attention in securing the EU’s long-term fiscal sustainability. Using the Shared Socioeconomic Pathways (SSPs) scenarios as bridging concept for linking the assessment of public cost of demography- and climate-related expenditures, this study proposes a climate risk mainstreaming methodology. We apply a stochastic debt model and assess the potential flood risk in Austria to the public debt and the national disaster fund. Our results indicate that public debt under no fiscal consolidation is estimated to increase from the current level of 84.5% relative to GDP in 2015 to 92.1% in 2030, with macroeconomic variability adding further risk to the country’s baseline public debt trajectory. The study finds that the estimated public contingent liability due to expected flood risk is small relative to the size of economy. The existing earmarked disaster risk reduction (DRR) funding will likely reduce the risk of frequent-and-low impact floods, yet the current budgetary arrangement may be insufficient to deal with rising risk of extreme floods in the future. This prompts the need for further discussions regarding potential reforms of the disaster fund. As many EU member states are in the early stages of designing climate change policy strategies, the proposed method can support the mainstreaming of climate-related concerns into longer-term fiscal and budgetary planning

Changing risks of simultaneous global breadbasket failure

The risk of extreme climatic conditions leading to unusually low global agricultural production is exacerbated if more than one global ‘breadbasket’ is subject to climatic extremes at the same time. Such shocks can pose a risk to the global food system amplifying threats to global food security and have the potential to trigger other systemic risks. So far, while the possibility of climatic extremes hitting more than one breadbasket has been postulated little is known about the actual risk. Here we present quantitative risk estimates of simultaneous breadbasket failures due to climatic extremes and show how risk has changed over time. We combine region-specific data on agricultural production with spatial statistics of climatic extremes to quantify the changing risk of low production for the major food producing regions (‘breadbaskets’) in the world. We find evidence that there is increasing risk of simultaneous failure of wheat, maize and soybean crops, across the breadbaskets analyzed. For rice, risks of simultaneous adverse climate conditions have decreased in the breadbaskets analyzed in this study in the recent past mostly owing to solar radiation changes favoring rice growth. Depending on the correlation structure between the breadbaskets, spatial dependence between climatic extremes globally can mitigate or aggravate the risks for the global food production. Our analysis can provide the basis for more efficient allocation of resources to contingency plans and/or strategic crop reserves that would enhance the resilience of the global food system