Next, we explore whether there are differences in coping and adaptation mechanisms among poor and non-poor vulnerable households. To do this, we calculate the above household profiles, differentiating them by poor status.

In addition, we carried out a counterfactual exercise. In this exercise, we estimated the households' vulnerability in a scenario where all households face the lowest possible hazards and compare the estimated vulnerability rates with the actual vulnerability incidence. Thus, we set to all households the minimum hazard they can face, that is, the minimum number of events that occurred among districts and a value of very low damage (more details are presented in Appendix B).

# **3. Data and descriptive statistics**

The datasets for the analysis are the national Household Surveys of each country of the study from the SEDLAC database. This database provides harmonized information of coping and adaptation mechanisms at the household level and poverty status for different countries of the region. The analysis focuses on seven countries: Brazil, the Dominican Republic, Ecuador, El Salvador, Honduras, Mexico, and Peru. We use household survey data, pre-dating Covid19, from 2018 for Mexico and from 2019 for the rest of the countries. Except for Brazil survey, the surveys allow for the identification of the district where households reside. This enables the imputation of hazard and exposure aggregate data at the district level for each household. In the case of Brazil, the survey design led to impute at the state level. However, despite the imputation being carried out at the district level in most countries, the results need to be analyzed at the level of survey representation, which is at the state level.

To identify poor households, we utilize a monetary poverty measure assuming a poverty line of 6.85 dollars a day for the per capita total household income adjusted by 2017 PPP. The household poverty rate is 20% in Brazil, 15% in the Dominican Republic, 21% in Ecuador, 23% in El Salvador, 45% in Honduras, 26% in Mexico, and 26% in Peru (Table 1).

**Table 1.** Household poverty headcount ratio by country.

|Country|Brazil|Dominican<br>Rep.|Ecuador|El Salvador|Honduras|Mexico|Peru|
|---|---|---|---|---|---|---|---|
|_Poverty adjusted by P_|_PP 2017_|||||||
|Poor HH (6.85 U$S)|20%|15%|21%|23%|45%|26%|26%|
|Poor HH (3.65 U$S)|8%|2%|6%|5%|23%|7%|8%|
|Poor HH(2.15 U$S)|4%|1%|1%|1%|11%|2%|2%|

Note: Households are poor if their total income per capita falls below the a-day International Poverty Line (adjusted by 2017 PPP and CPI prices). Source: authors' calculations based on the SEDLAC database.

The selection and construction of variables of households' coping mechanisms, adaptation strategies, and socio-demographic characteristics are detailed in Appendix A. Here Table 2 provides basic information on all seven Latin American countries of coping and demographic variables ( and ) included in the model. Statistics suggest a low occupation protection among households and a lack of income diversification to deal with natural hazards. The level of informality is high; on average, in Ecuador and Peru, half of the household heads have an CC DD informal job. Moreover, in Ecuador, Honduras, and Peru, nearly one household in four reports 7