household today might not necessarily be poor in the future and vice versa. Therefore, a household's current poverty status is not a good indicator of a country's poverty risk.<sup>8</sup> This vulnerability is influenced by the incidence of hazards present in a country. Vulnerability can be poverty-driven or risk-driven. Poverty-driven vulnerability refers to a high probability of falling back into poverty due to a low accumulation of productive assets, such as housing, human capital, or financial resources. Risk-driven vulnerability occurs whenever a household has a high chance of becoming poor due to high exposure to risks, such as falling victim to a crime or illness, or natural disasters. On the other hand, these risks can occur at the individual level, such as a personal illness or job loss, or at the community level, such as a regional economic downturn or epidemic. Depending on which is relatively more important, policy makers should adapt their risk-mitigation strategy and coping mechanisms.

**Several scholars have addressed the need to quantify vulnerability to poverty over the last decades in various countries, but there is currently no consensus on how to best measure vulnerability to poverty.** The empirical discussion about the estimation of vulnerability to poverty is not new and has a long history. In 2000, Pritchett et al. took a probabilistic view on vulnerability to poverty and calculated the overall vulnerability rate for Indonesia. They define a household to be vulnerable as soon as it has a 50-50 odd ratio or worse to fall into poverty. In 2002, a literature review by Kamanou and Morduch found that, while there is a large consensus on the need to measure vulnerability to poverty, there is no consensus on how to measure it. They introduce an empirical strategy that combines Monte Carlo and bootstrap statistical techniques and applies their measure to the case of Côte d'Ivoire. Related work by Celidoni (2013) compares the performance of several measures of individuals’ vulnerability to poverty. A more recent review by Gallardo (2017) shows that there is still no consensus on measuring vulnerability to poverty

**There are a number of studies applying different measures of vulnerability to poverty to a number of countries, but empirical applications are still relatively limited.** Several papers have further elaborated the measurement of vulnerability to poverty, but the number of empirical applications is still relatively low.<sup>9</sup> Recently, several scholars have made an effort to make the measurement of vulnerability to poverty more accessible to a broader range of development economists (Gao et al., 2020). In this line of research, a recent application by Skoufias et al. (2021) shows that vulnerability is 1.6 times higher than poverty in Ethiopia and is especially high in drought-prone lowlands.

**We tie in with the current line of research and apply a novel vulnerability measure developed by Gao et al. (2020) to the context of El Salvador.** This paper is the first to quantify an ex-ante measure of vulnerability to poverty in El Salvador. There is currently no overall estimation of vulnerability to poverty available for the country. Additionally, to the best of our knowledge, this paper is also the first to apply the tool developed by Gao et al. (2020) to an income-based welfare measure. It is crucial to characterize vulnerable in El Salvador, as the challenges created through natural and human hazards and climate change in El Salvador might reverse the positive trend in poverty experienced by the country in recent years.

**Evidence from other countries shows that natural and human hazards disproportionately affect poor people (Hallegatte, 2020), further fostering the case for studying vulnerability to poverty in these settings.** Poor people are often more exposed to natural hazards, more vulnerable to them (when exposed, they lose a more significant fraction of their assets), and have a lower socioeconomic resilience (a lower ability to cope with its impacts). This can create a vicious circle between poverty and disasters (Hallegatte, 2020). Therefore, disaster risk management can be part of a poverty reduction strategy and vice versa. Similarly, human hazards and poverty are intertwined. To give an example, crime may induce poverty traps under low levels of modernization and high levels of production (Mehlum et al., 2005). Poverty, on the other hand, can trigger crime (McCrea, 2019). Based on this evidence, it is crucial to understand the relationship between both and design adequate policies to address these.

> 8 Analyzing three waves of data from Nigeria, for example, shows that households are unlikely to remain in poverty over time. Only 7 percent of households were always below the poverty line while 35 percent were never below it. The rest of households reported a switching poverty status (Skoufias and Baez, 2021).

> 9 Further examples are studies by Chaudhuri et al. (2002), Chaudhuri (2003), Azam and Imai (2010), Imai et al. (2011), Dutta et al. (2011), Barrientos (2013), Klasen and Waibel (2015), Ward (2016).

6