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

User Interface of the CatSim Model and Practical Guidelines

This user manual should help performing a CatSim analysis for a specific country. The policy applications of the CatSim tool can provide insights on the development and use of indicators of vulnerability, resilience, coping capacity and other concepts important for policy interventions with regard to disasters and other global-change phenomena. The CatSim tool relies on quantitative indicators. Risk is estimated making use of historical statistics and exposure; financial resilience is estimated with an index of observations on the financial preparedness of the government; financial vulnerability is a composite of the two and is measured in terms of the financing gap. Clearly financial vulnerability of the public sector presents only one aspect, albeit an import one, of vulnerability to natural hazards. Other indicators are necessary in order to complement this concept. Furthermore, participation and transparency in the design, estimation and use of vulnerability indicators is essential for their legitimacy. As there is a substantial degree of uncertainty in estimates of disasters risks and financial vulnerability, it is important that users have full participation in their design, estimation and use. CatSim has been created as a participatory, interactive tool for building capacity of policy makers by sensitizing them to the tradeoffs inherent in planning for disasters

Changes in fiscal risk against natural disasters due to Covid-19

The coronavirus pandemic caused serious social and economic impacts around the world. Governments implemented massive fiscal stimulus and protection packages to counteract these severe consequences which lead them into weak fiscal positions and elevated debt. This affects the fiscal risk to natural hazards governments are exposed to as well. To shed light on this issue we compare fiscal risk due to natural disaster events pre-Covid and for today to indicate the magnitude of change. This is done by applying the so-called CatSim model which combines natural disaster risk and corresponding losses a government is exposed to with financial resources it has available to finance them. While only indicative due to data limitations our results can be interpreted as a warning call to not underestimate disaster risks that can realize any moment and that will be much more difficult to be efficiently responded to compared to the pre-Covid era. Especially the poor are now in a significant weaker position than before. We suggest some possible ways forward how to enable a more integrated perspective and to track progress of fiscal risks over time

Assessing the Macroeconomic Impacts of Natural Disasters: Are There Any?

There is an ongoing debate on whether disasters cause significant macroeconomic impacts and are truly a potential impediment to economic development. This paper aims to assess whether and by what mechanisms disasters have the potential to cause significant GDP impacts. The analysis first studies the couterfactual versus the observed gross domestic product. Second, the analysis assesses disaster impact as a function of hazard, exposure of assets, and, importantly, vulnerability. In a medium-term analysis (up to 5 years after the disaster event), comparing counterfactual with observed gross domestic product, the authors find that natural disasters on average can lead to negative consequences. Although the negative effects may be small, they can become more pronounced depending mainly on the size of the shock. Furthermore, the authors test a large number of vulnerability predictors and find that greater aid and inflows of remittances reduce adverse macroeconomic consequences, and that direct losses appear most critical

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 -