MacroMode

The need to proactively redistribute the growth in asset exposure and to plan for disaster events is becoming increasingly prominent in the discussion on disaster risk management and climate change. The paradigm shift toward demand for a more proactive and risk-based approach can be partially attributed to disaster risk being increasingly recognized as a major challenge to economic growth and overall societal well-being in both developing and developed world regions.

However, especially in highly developed countries, a recent shift in the disaster risk management perspective can be observed with respect to direct and indirect losses. Indirect losses are the flow-on effects of direct losses, such as transport disruptions or business interruptions and it has been shown that they are significant and can be even larger than the direct losses. This is particularly the case for industrialized countries, as they are characterized by a high degree of specialization and strong inter-sectoral linkages. Hence, the economy-wide view is becoming more important, which includes indirect losses emerging from these economy-wide linkages (capturing the total losses of direct and indirect effects). For example, the extreme flood events in 2002 in Austria caused production losses of about 200 million Euro alone (total costs were estimated to be 3.1 billion Euro). To tackle these indirect risks, the government is often seen, at least implicitly, as responsible for keeping indirect losses as low as possible and/or to re-distribute them.

Given this shift to an economy-wide view, a significant shift from a risk management perspective also needs to be undertaken, namely, to ask how indirect losses due to natural hazard risks can be decreased within a highly interlinked and complex system such as the economy of a country like Austria. This question has so far not been addressed and thus is the main objective of the MacroMode project. To meet this objective, an integrated modelling approach is needed which should cover (i) cutting-edge direct flood risk modelling at high sectoral and spatial resolutions, (ii) economy-wide modelling that incorporates non-linear linkages across agents and sectors, as well as (iii) different time-horizons. Only when such an integrated approach is available can potential new and robust instruments be designed for the reduction of indirect risks due to natural disasters and these instruments be evaluated from a country-level perspective.

This requires new approaches to be developed, tested, and compared to other more conventional ones. Hence, another objective in MacroMode is to shed light on fundamental model uncertainties to provide more robust results. This is done by systematically comparing three highly detailed macro-economic modelling approaches for economic consequences of flood events, namely, Input-Output models, Computable General Equilibrium models and Agent-Based models. This is crucial as the model choice itself might determine or bias results. However, there is currently no systematic analysis of whether model results differ significantly across model types when applied for economy-wide risk assessments.

Such model assumptions, scenarios and results will need to be presented and discussed with key decision-makers and stakeholders. This is done an iterative manner to make sure that results and identified risk management options are policy relevant and can be used for determining strategies to decrease the risk of large scale indirect losses and systemic risks due to flood events for today and in the future. Hence, the third objective relates to the first two objectives and should guarantee that the results obtained are indeed a useful basis for climate action in Austria. Together with key decision-makers and stakeholders, MacroMode will develop policy-compatible ways forward on how to tackle current and future indirect risks due to flood events in Austria.