New Volcanic Futures

Measuring the distribution of impacts

Measuring the distribution of impacts of a potential volcanic disaster across household types with a dynamic CGE model

Previous assessments of the economic impacts exerted by natural disasters using CGE models have neglected the heterogeneity of impacts across households even within income or regional groups. Natural disasters impact households by raising the cost of commodities demanded, by changing their incomes, and by changing their investment behaviour in damaged assets. A complete analysis requires taking all effects into account. The impact from natural disasters is determined by heterogeneity in household spending patterns, heterogeneity in factor income patterns, and savings-investment behaviour across income groups. For example, for a given asset loss, a wealthy household might quickly recover, while a poor household might suffer major, long-lasting impacts. This research proposes a methodology to quantify disaster impacts more equitably by linking macroeconomic changes in production and employment to household-level impacts using a CGE model. The model will contribute to the literature by assessing the impacts of disasters on people’s consumption, considering asset losses and changes in income, among other factors. We will apply the model to a hypothetical volcanic eruption in Mount Taranaki, New Zealand, considering the differential impact of consumption loss on households of varying wealth. With this study we expect to identify if pre-existing socio-economic conditions play a significant role in the ability for particular economic classes to respond immediately to disasters and to cope with the aftermath. We expect this study to help policymakers to design policies to reduce social and economic vulnerabilities to natural disasters.

Timeframe for deliverables

Preliminary results from the CGE model will be available mid-late 2022 and a draft of the journal article by the end of the year.

Data

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  • .Damages to infrastructure developed by the University of Canterbury with RiskScape.
  • .Census data from Statistics NZ to distribute households spatially.
  • .Social Accounting Matrix (SAM) for the Taranaki region developed by M.E Research.

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