The above discussion first highlights that exposure and asset vulnerability differ based on poverty status, with poor people being more impacted in relative terms from a disaster. Further, we highlight the importance coping capacity and social protection, when examining the impact on welfare. This highlights the potential for DRM investments to help people manage risks, long-term impacts on welfare and prevent potential for poverty traps dynamics to occur after a disaster further degrading poor households’ welfare.

# **4. Slower development in the absence of DRM investments**

The take-away from **Sections 2 and 3** is that at the macro and micro levels, asset losses do not tell the whole story, and while the impact of a disaster might not be extensive at the macro level, without DRM investments, welfare losses can still be substantial for parts of the population, especially poor people. While this ex-post, loss-centric focus is certainly important, it ignores the ex-ante impacts.

In risky environments, evidence suggests that without the proper tools to manage natural risk, risk-averse households and other economic actors tend to spread risk over a large array of lower risk activities, thereby reducing returns to assets and investments. For example, smallholders plant low-return, low-risk crops (Cole et al., 2013), and infrastructure services may not be well provided in risky areas (Benson, 2002). Such phenomenon can be self-sustaining as evidence suggests that after a disaster, economic actors may change behaviors and become more risk averse, with less risks taken in other domains, for example in innovation and entrepreneurship (Cameron and Shah, 2015).

In this section, we examine first the benefits of taking “natural” risks when these risks are well managed. Then we highlight the existence of suppressed economic potential in risky areas, an issue that could be partly addressed with DRM investments.

## **4.1. Development and the exposure to natural hazards**

Economic losses from natural disasters have been growing as fast or faster than economic growth in many countries (Neumayer and Barthel, 2011; Nordhaus, 2010; Pielke et al., 2008). This evolution can be explained by growth – richer countries have more assets potentially damaged, but also by increasing risktaking behaviors with an increasing share of assets located in at-risk areas (Field et al., 2012; Neumayer and Barthel, 2011; Schmidt et al., 2009). For instance, the fact that hurricane losses are increasing more rapidly than GDP in the US is explained by migration toward hurricane-prone areas (Pielke et al., 2008). Globally, between 1970 and 2010, the population grew by 87%, but the population living in floodplains increased by 114% and in cyclone prone coastlines by 192%. The share of GDP globally exposed to tropical cyclones increased from 3.6% to 4.3% over the same period (UNISDR, 2011).

Many scholars have looked at reasons why individuals may over-invest in risky locations and take excessive risks in terms of flood or storm exposure. (Kunreuther, 1978; Thaler and Sunstein, 2009; Tversky and Kahneman, 1974) investigate behavioral biases in how people perceive and react to risks. (Burby et al., 1991; Laffont, 1995; Michel-Kerjan, 2008) study moral hazard issues linked to post-disaster support and ill-designed insurance schemes.

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