  Reliable estimates of indirect economic losses arising from natural disasters
are currently out of scientific reach. To address this problem, we propose a
novel approach that combines a probabilistic physical damage catastrophe model
with a new generation of macroeconomic agent-based models (ABMs). The ABM moves
beyond the state of the art by exploiting large data sets from detailed
national accounts, census data, and business information, etc., to simulate
interactions of millions of agents representing \emph{each} natural person or
legal entity in a national economy. The catastrophe model introduces a copula
approach to assess flood losses, considering spatial dependencies of the flood
hazard. These loss estimates are used in a damage scenario generator that
provides input for the ABM, which then estimates indirect economic losses due
to the event. For the first time, we are able to link environmental and
economic processes in a computer simulation at this level of detail. We show
that moderate disasters induce comparably small but positive short- to
medium-term, and negative long-term economic impacts. Large-scale events,
however, trigger a pronounced negative economic response immediately after the
event and in the long term, while exhibiting a temporary short- to medium-term
economic boost. We identify winners and losers in different economic sectors,
including the fiscal consequences for the government. We quantify the critical
disaster size beyond which the resilience of an economy to rebuild reaches its
limits. Our results might be relevant for the management of the consequences of
systemic events due to climate change and other disasters.
