vulnerability curves), these damage ratios are estimates at 5–15% for residential properties, 15–35% for commercial properties, and 10–30% for industrial properties. In the absence of data on infrastructure, a constant ratio of infrastructure to non‐infrastructure losses is introduced. Based on previous events in various world cities, this ratio is taken at 40% (i.e., where there is $1 of non‐infrastructure losses, there is $0.40 of infrastructure losses).

From this, the analysis can then provide an estimate of the direct economic losses that corresponds to various probability of occurrence, expressed in terms of return periods. For instance, the losses due to the 50‐yr return period flood are estimated between $210 and $570 million.

To complete this analysis with information on how these losses are distributed in the population and especially on the poorest, a survey was conducted with informal dwellers affected by the 2005 floods. It was found that the aggregated losses they suffered from are about $250 million (for total losses due to the 2005 flood of about $2 billion), but the relative impact on their savings and consumption was extremely large, with average capital losses of the same order of magnitude than their average total savings (in other terms, their savings were totally wiped out by the event).

For instance, hurricanes in 1806 and 1807 participated in the shift that occurred at la Réunion – a French island in the Indian Ocean – from coffee to sugar cane production. Indeed, it takes about 5 years for a coffee plant to start producing usable fruits. When the hurricanes hit, the need to start producing again as soon as possible drove farmers to plant sugar cane, an annual crop that can be harvested in a year. Moreover, coffee production was then considered more vulnerable to wind damages than sugar cane. But sugar cane production also has a different economic vulnerability to other stresses such as changes in food markets, consumer tastes, and agricultural subsidies. Therefore, it is difficult to assess whether the shift from coffee to sugar cane should be considered as a cost of the hurricanes (if sugar cane eventually reveals less profitable than coffee) or as a benefit (if sugar cane is more profitable than coffee). The final outcome depends on many other factors that can hardly be predicted at the time of the disaster.

This baseline issue – very common in economics – is not easy to deal with, and different scholars have used different techniques. (Coffman and Noy, 2011) use two nearby islands to assess the impact of hurricane Iniki. Since the hurricane affected only one island, the other can be used as a “control”, i.e. as a proxy for the economic condition of the affected island if it had been spared. But such convenient control is not always available, making it necessary to construct the counterfactual, for instance using modelling tools (DuPont and Noy, 2012).

# **2.2 Output losses and their drivers**

Damages to assets make them unable to produce: a damaged factory cannot build cars, a damaged road cannot be used, and a damaged house cannot be inhabited. The first step in an assessment of output losses is to estimate how much output is lost because of these direct asset losses.

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