But underestimation of the welfare impact can also arise from the disregarding of the distributional impacts of disasters. For instance, it seems rather intuitive to think that the impacts of disasters on the livelihoods of poor and marginalized people are more substantial, first because of their higher exposure to physical risks, but also because of the reliance of their livelihood strategy on fewer and more vulnerable assets. While the impact of the disaster can be disastrous for such people, the repercussion on GDP can be invisible, especially if the very poor own close to nothing.

Thus, to more precisely examine the impacts of a disaster at the micro level, it is important to examine who is affected and how they are affected. Below we first examine how asset losses are distributed among the population, and then how asset losses translate into welfare losses.

# **3.1. Asset losses differ depending on who is exposed**

Before examining how asset losses translate into total losses, it is imperative to assess how asset losses at the microeconomic level are determined and distributed. Asset losses are a function of the hazard, exposure and vulnerability. While a hazard is not determined by socio-economic characteristics, exposure and vulnerability are.

One major determinant of asset losses is poverty status. First, poor people may be more exposed to natural disasters due to the role of formal and informal land markets: if natural risks are included in land price valuation (or desirability), poor households should be more likely to live in risky areas where land is cheaper (Fay, 2005). This explains why slums are typically located in floodplains or in areas at risk of mudslides, and why poor people are approximately 70% more likely to be exposed to disasters in cities such as Mumbai (see more in Section 0) (Patankar, 2015). But this may not always be the case. Risky locations may attract richer people: coastal cities are often highly exposed to flood risk, but they host households that are generally richer than those from rural and inland regions, due to sunny weather and amenities. For instance, (Carter et al., 2007) find that Hurricane Mitch in Honduras in 1998 affected only 22% of households in the poorest quintile, as opposed to 68% in the richest quintile. (Hallegatte et al., 2016) proposes a review of case studies of post-disaster contexts examining exposure of poor and nonpoor people, see Figure 5 **, panel a.** While the evidence on poverty exposure to disasters is scale- and context- dependent, it is generally well observed that when hit, poor people lose more in relative terms. This “vulnerability bias” is due to poor people having lower quality assets of which a larger portion in material form and thus more vulnerable to disasters. For instance, while (Carter et al., 2007) find that poor people did not have a higher exposure to Hurricane Mitch, they were nonetheless more vulnerable in relative terms: poor people had lost 31% of their assets while the rich only 8%. (Hallegatte et al., 2016) proposes a review of case studies of postdisaster contexts examining the vulnerability of poor and non-poor people, see Figure 5 **, panel b.** 12