The rest of the paper is structured as follows: Section 2 reviews the macro-level evidence of adverse natural events, suggesting that low-income countries suffer disproportionately high damages from disasters. Section 3 investigates evidence at the household level, with a particular focus on the implications for welfare and human capital of poor households, and discusses the role of ex-ante behavior. Section 4 discusses how disaster damages can translate into long-term and indirect impacts on income and welfare and create poverty traps. Section 5 highlights the importance of not overlooking the detrimental impact from small but repeated disasters – particularly in the context of a changing climate. Section 6 briefly discusses policy options for building resilience, underscores the need for further research to fully understand the link between disasters and poverty, and concludes.

# **2. Macro impacts of disasters – The poor are hit the hardest**

## **2.1. Evidence at the country level**

Taking a closer look at the loss data of natural catastrophes of the past 30 years, it becomes apparent that low-income countries suffer disproportionately high damages from disasters, even though the incurred economic losses may appear small in absolute terms. On the contrary, high-income countries have incurred very high economic damages (in absolute terms) as a result of disasters. However, these costs are borne at the margin – i.e., high-income countries have the resources and capacity to recover from these events without significant long-term consequences (at least at the national level).

Evidently, natural catastrophes affect countries around the world, regardless of their level of economic development. Depending on geographical circumstances, developing and developed countries alike can be prone to experience frequent natural “loss events”– for instance, Bangladesh (floods), the USA (hurricanes), or Japan (earthquakes). However, the nature of experienced damages and losses varies significantly across countries. Generally, such variation can be attributed to differences in terms of hazard probability (i.e. the frequency of hazards varies across countries), exposure (for instance, some countries having larger population shares in at-risk areas than others), vulnerability (for instance, countries with poorly enforced building codes being likely to incur more casualties in an earthquake), and resilience (for example, some countries being able to reconstruct more quickly than others). Of these factors, exposure, vulnerability and resilience all depend strongly on a country’s level of income.

Based on the analysis by Wirtz (2013), the following breakdown of the structure of disaster related losses illustrates three key facts: (i) the vast majority of human fatalities are experienced by low-income countries; (ii) absolute economic losses are the highest in high-income countries; and (iii) economic losses relative to GDP are the highest in low-income countries – which has further implications, e.g., for the speed of recovery and reconstruction.

In order to distinguish between different income levels, it is useful to apply the World Bank country classifications according to income groups<sup>3</sup> : HIC: High-income countries (Per capita income US$ > 12,275); UMIC: Upper-middle-income countries (Per capita income US$ 3,976 – 12,275); LMIC: Lower-middle-income countries (Per capita income US$ 1,006 – 3,976); LIC: Low-income countries (Per capita income US$ < 1,006).

> 3 For coherence with the subsequently presented data, we use the World Bank’s 2011 country classification.

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