This study evaluates the socioeconomic risk that extreme El Niño event-related road damages present to Peru by combining an environmental modelling of events’ occurrences in the country with a quantitative modelling of their effects on its economy. The dynamic of occurrence of events is modelled as a stochastic process with a vector autoregressive representation based on historical climatic data, and simulated over a 10-year period with a non-parametric bootstrap procedure. The indirect consequences of events’ related road damages are addressed with a multiregional dynamic computable general equilibrium model through an increase in interregional transportation costs and, more originally, a negative externality effect on activities’ output, which is estimated beforehand using a firm database. We find that extreme El Niño events constitute a significant one-off disaster risk for the country, threatening shifts of − 2.8% in GDP and + 1.9% in poverty rates with an annual probability p = 1.4%. We further show that they also present a longer-term risk, leading to average annual deviations from normal trend by − 0.8% in GDP and + 0.4% in poverty rate with a probability p = 12.6% over a 10-year period. However, we finally show that Peru might reduce these socioeconomic risks associated with these non-frequent but recurrent climatic shocks in constructing more disaster-resilient road infrastructure.
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