and sanitation, crowding,<sup>24</sup> subsistence capacity,<sup>25</sup> and precarious materials.<sup>26</sup> Therefore our estimates are not subject to bias from any unobservable determinant of poverty or income that is time varying but common across all households in Central America.

Our study period in this section involves only 13 years of analysis (2000‐2013). Given this shorter period –compared to the nearly 30 years for the per capita GDP analysis– we consider only three events: Hurricane Felix (2008) for Honduras, Hurricane Matthew (2011) for Guatemala and Honduras, and Hurricane Harvey (2012) for Honduras. The three hurricanes are part of SS scale 1, therefore we cannot evaluate the impact of major hurricanes. The other countries (Costa Rica, Panama, and El Salvador) did not have events within our study period and for the years where there is an available and comparable survey.<sup>27</sup> As discussed in the previous section, wind speed data was aggregated by year. When more than one event occurred in a calendar year in the same country, only the strongest event was taken into account. In this case, we also take into account the time when the household survey was conducted. This is key since household surveys usually record the income of the preceding month. We show two set of results: (i) linearly weighted by the difference between the event’s date and the survey’s date (divided by 12), and (ii) unweighted results (i.e., regardless of the number of months that have passed since the strongest event). The rationale for this is that the effect of a hurricane on household income (or poverty) might be underestimated if the interval is bigger. Noy (2009) discusses the importance of a weighting function to evaluate impacts on GDP since events observed earlier in the year may have higher impact on GDP than events that occur towards the end of the year.

# 4.3. Results

Table 5 presents the main results for this section using OLS. Standard errors are clustered at the regional level. Results are standardized in order to render all the indexes comparable. Column (1) – (4) show the non‐weighted results, while column (5) – (8) show the (linearly) weighted results. Weighted results are smaller than non‐weighted effects. All results include the control variables (maximum level of education, access to water and sanitation, crowding, subsistence capacity, and precarious materials).<sup>28</sup> Our results show that major hurricanes have substantial adverse impacts on both income and poverty. Based on the non‐weighted results, an increase of one standard deviation in the intensity (wind speed) of a hurricane leads to a decrease in total and labor income by 2 – 4 percent, while moderate and extreme poverty increases by 1 – 2 percentage points.

To illustrate these results, we will focus on Hurricane Matthew for Honduran Region 5.<sup>29</sup> According to these parameters, and taking MSWS as a measure of hurricane damage, Hurricane Matthew had a

> 24 The ratio of members of the household to the number of exclusive rooms occupied by the household.

> 25 Households are considered to have unsatisfied basic needs in subsistence capacity based on two conditions: (i) the ratio of members of the household to the employed members is higher than 3; and (ii) the household head has at most elementary school education.

> 26 Where the construction materials of the dwelling are of low quality.

> 27 Notice that Hurricane Beta discussed in the second section of the paper is not considered in the analysis because it was a tropical storm when hit Nicaragua.

> 28 Results shown in the paper exclude Panama because Panama’s observable household characteristics are not available. However results including Panama and without controlling for observable characteristics show similar qualitative results. Results available upon request.

> 29 Hurricane Matthew landed in Honduras in 2010 with an SS scale of 2 in the Socio‐Economic Region 5 with a Maximum Sustained Wind Speed of 97.92 mph and with and SS scale of 1 in the Socio‐Economic Region 2. Hurricane

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