Wave-like global economic ripple response to Hurricane Sandy

Abstract

Tropical cyclones range among the costliest disasters on Earth. Their economic repercussions along the supply and trade network also affect remote economies that are not directly affected. We here simulate possible global repercussions on consumption for the example case of Hurricane Sandy in the US (2012) using the shock-propagation model Acclimate. The modeled shock yields a global three-phase ripple: an initial production demand reduction and associated consumption price decrease, followed by a supply shortage with increasing prices, and finally a recovery phase. Regions with strong trade relations to the US experience strong magnitudes of the ripple. A dominating demand reduction or supply shortage leads to overall consumption gains or losses of a region, respectively. While finding these repercussions in historic data is challenging due to strong volatility of economic interactions, numerical models like ours can help to identify them by approaching the problem from an exploratory angle, isolating the effect of interest. For this, our model simulates the economic interactions of over 7000 regional economic sectors, interlinked through about 1.8 million trade relations. Under global warming, the wave-like structures of the economic response to major hurricanes like the one simulated here are likely to intensify and potentially overlap with other weather extremes.

Economic losses from hurricanes cannot be nationally offset under unabated warming

“…We generate counterfactuals for an additional increase in global warming of up to 4 • C after 2017. These counterfactuals are based on a conceptualization [30] of the original (i.e. unscaled) Hurricane Harvey, modelled as a decrease in productive capacity (the direct economic shock).…”

“…Note that this shock only models short-term business interruption and does not cover reconstruction efforts or externalities on, e.g. the transport sector (see supplement A: methods and [30] for details). The original scenario is then projected to future climate (scaled or counterfactual scenarios).…”

Climate Impact Storylines for Assessing Socio-Economic Responses to Remote Events

“…Rationale of the storyline Major tropical cyclones (TCs) making landfall -besides causing devastating local damages and economic losses (direct impact) -can result in macro-economic trade shocks and ripples through trade loss propagation (indirect impact) (Lenzen et al, 2019). Earlier work on the New York/New Jersey landfall of hurricane Sandy (2012) analyzed the potential indirect impact on global (final) consumption, showing that both downstream and upstream interactions can result in losses or gains of consumption in other parts of the world that are not directly affected (Middelanis et al, 2021). The storyline concentrates on the shock propagation in the trade network induced by the direct effects from the landfall of TC Harvey (2017) and its global indirect economic repercussions, including impacts onto the European economy.…”

“…Harvey disrupted the globally important and strong economy of Texas and Louisiana, which is situated in a main Atlantic TC landfall area, identified as our climate hotspot. The impact transmission was expressed by modelled distributed production declines and subsequent price anomalies in a time window of up to one year in the aftermath of the TC landfall, and downstream and upstream interactions resulting in losses or gains of consumption and production in other parts of the world that are not directly affected, including Europe (Middelanis et al, 2021), which define the socioeconomic impacts. Similar to the EUSF storyline climate perturbations are applied by changing the rainfall intensity of the TC, motivated by the attribution of climate warming as one of the drivers of unprecedented precipitation volumes (Van Oldenborgh et al, 2017).…”

“…Alternative baseline characteristics of technology, GDP or distribution of trade volume over actors can be expected to modulate the transfer of direct to indirect impacts. For example, the previous work on TC Sandy (Middelanis et al, 2021) suggests a non-linear impact on consumption losses or gains as a function of the magnitude of the actor's baseline trade volume to the directly affected actors, giving unequal relative impacts for larger and smaller regions. The comparison of counterfactuals is using various metrics (including trade volume) to isolate the climate change impact on time-varying regional and sectoral shock impacts.…”