# **1 Introduction**

The Sixth Assessment Report (AR6) of the Intergovernmental Panel on Climate Change (IPCC) highlights that climate risk arises from the convergence of climate hazards, vulnerability, and exposure. Following Cardona et al. (2012), hazard refers to the possible future occurrence of natural or human-induced physical events that may have adverse effects on vulnerable and exposed elements (White, 1973; UNDRO, 1980; Cardona, 1990; UNDHA, 1992; Birkmann, 2006). On the other hand, exposure refers to the inventory of elements in an area where hazard events may occur (Cardona, 1990; UNISDR, 2004, 2009). Lastly, vulnerability refers to the susceptibility, sensitivity, and lack of resilience or capacities that favor adverse effects on exposed elements such as human beings, their livelihoods, and assets when impacted by hazard events (UNDRO, 1980; Cardona, 1990). According to IPCC (2007), vulnerability is the degree to which a system is susceptible to, or unable to cope with, adverse effects of climate change, including climate variability and extremes. Vulnerability describes the likelihood of suffering adverse effects. It is associated with a set of conditions of people that derive from the historical and prevailing cultural, social, environmental, political, and economic contexts. Moreover, climate risk has the potential to drive people into poverty. For instance, Skoufias et al. (2023) find that in Ethiopia, households living in drought-prone lowlands have a significantly higher vulnerability to poverty than households in other ecological zones in the country. Similarly, Malawian households' exposure to droughts and excess rainfall shocks decreases their consumption and elevates their vulnerability to poverty (Baquie & Fuje, 2020). Climate risk can also have long-term impacts on wealth, spanning generations (Damania et al., 2017; Carrillo, 2020; Aguilar & Vicarelli, 2022; among others).

Over the last 50 years, the Latin America and the Caribbean region has had a rise in natural disasters and extreme weather events, as reported in the Emergency Events Database (EM-DAT) of the Université Catholique de Louvain, Belgium (Guha-Sapir et al., 2022). These events have resulted in fewer deaths over the years but higher damage costs, especially in the Caribbean islands when scaled by GDP. This study aims to provide a comprehensive analysis of the vulnerability to poverty in a climate risk framework. It seeks to estimate the number of people in the region who are at risk of being pushed into poverty due to climate disaster risk such as floods, droughts, or extreme temperature events.

In our analysis, we simplify the climate disaster risk by reducing dimensions and treating it as a type of covariate risk. We do this by using natural disasters that have occurred, extreme weather conditions that households have been exposed to, and natural hazard geographical indexes. We model the per capita household income and identify poor households within the vulnerability to poverty framework. The framework considers climate disaster risk, idiosyncratic risk, community factors, and specific household characteristics. The climate disaster risk is interpreted as an aggregate shock, while idiosyncratic risks are specific shocks to each household. Both risks are modeled through the shape of the per capita income distribution, estimating the expected variance. On the other hand, the expected mean income is estimated based on the household and community characteristics. It offers a more structural idea of the proportion of households already poverty-induced independent of the type of risk they face. This framework has been proposed by Chaudhuri (2002, 2003) and modeled by Gunther & Hartgen (2009) following Hox (2010) and used by Skoufias et al. (2023) for Ethiopia and Rud and Robayo-Abril (2023) for El Salvador.

However, our analysis differs and expands past studies in various ways. It explicitly considers climate disaster risk as an aggregate shock by exploiting natural disaster and extreme weather data. Doing so allows us to establish the proportion of households in different countries within the region that are likely to become poor due to structural characteristics (poverty-induced -PI) or due to the occurrence 3