New Zealand is uniquely exposed to a wide range of natural hazards and with the growing influence of climate change, New Zealand’s exposure and vulnerability to natural hazards are likely to increase. Many of the impacts of these disruptions will be economic in nature and can be estimated.
However, traditional approaches often overlook the unique disruptive elements of natural hazards such as the out of equilibrium dynamics and the propagation of impacts along the economy’s supply chains. While both partial and general equilibrium analysis attempt to explain the behaviour of supply, demand, and prices, other economic methods such as network analysis enable the identification of other behaviors including supply chain vulnerabilities. Dynamic impacts and recovery across both space and time can also be estimated.
This is a natural progression to estimating the impacts of natural hazards due to the changing dynamics that natural hazards provide. The complex, dynamic nature of natural hazards is often overlooked when using temporally or spatially aggregated data or oversimplified economic methods leading to poor quantitative analysis of natural disaster impacts.
This approach can subsequently highlight criticalities, or the linkages in the economy where minor impacts can propagate into relatively large disruptions, providing important information as to where resilience can be built within the economic system.
Using an approach that intertwines ecology and economics, the research will incorporate standard (input-output) and emerging (network analysis) economic practices with business-level transaction data.
Both the direct and indirect impacts can be estimated by identifying the impacts on the linkages between economic sectors that are upstream or downstream in the supply chain of a disrupted good or service. Using this approach, the direct impact on the local area can be assessed as well as the indirect impacts which capture how the impacts ripple through to other sectors.
Allowing for significantly improved resolution by moving away from the annual averages typically used in economic impact assessments and towards smaller timesteps such as monthly data. In turn, this provides a significantly improved estimation of natural hazard disruptions and the recovery of businesses and industries following these disruptions. Hybrid approaches, bringing together IO analysis and the network approaches may also be explored.
Strengthening the quantitative analysis through the inclusion of a dynamic component to the value chains will allow for improved decision making at the macro level when developing disaster risk reduction strategies. Additionally, at a micro level, this approach will allow industries or specific businesses to test resilience-building strategies that could significantly reduce the impacts they may experience following a standalone hazard event of a series of cascading events.
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