Table 7 Heterogeneous Impacts of Hurricanes on Poverty and Income by Male/Female

|||Male‐headed<br>|households<br>||<br>|Female‐heade<br>|d households<br>||
|---|---|---|---|---|---|---|---|---|
||||||||||
||<br>Income|<br>Income|<br>Poverty|Poverty|<br>Income|<br>Income|<br>Poverty|Poverty|
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|
|MSWS|‐0.0234***|‐0.0454***|0.0183***|0.0204***|‐0.0321***|‐0.0380***|0.0161***|0.0181***|
|Standard Error|(0.0003)|(0.0003)|(0.0001)|(0.0001)|(0.0002)|(0.0002)|(0.00001)|(0.00001)|
|R‐squared|0.399|0.453|0.211|0.277|0.448|0.478|0.272|0.330|
|IDH|‐0.0249***|‐0.0500***|0.0227***|0.0233***|‐0.0402***|‐0.0461***|0.0203***|0.0236***|
|Standard Error|(0.0004)|(0.0003)|(0.0001)|(0.0001)|(0.0002)|(0.0002)|(0.00001)|(0.00001)|
|R‐squared|0.399|0.453|0.212|0.277|0.448|0.478|0.272|0.330|
|WEI|‐0.0164***|‐0.0308***|0.0121***|0.0145***|‐0.0178***|‐0.0217***|0.00963***|0.0111***|
|Standard Error|(0.0003)|(0.0003)|(0.0001)|(0.0001)|(0.0002)|(0.0002)|(0.00001)|(0.00001)|
|R‐squared|0.398|0.452|0.211|0.277|0.448|0.478|0.271|0.329|

*** p<0.01, ** p<0.05, * p<0.1. Standard errors clustered at the sub‐regional level.

# 5. CONCLUSION

Although Central America’s recent good economic performance has enabled a sustained reduction of poverty, a large percentage of its population is still battling poverty and extremely vulnerable to natural disasters. This means that gains are threatened and could be wiped out in the aftermath of a major disaster. A better understanding of the impacts and potential coping mechanisms is valuable input to inform poverty reduction strategies and policies taking into consideration disaster and climate risk management considerations.

Overall, the methodology of this study improves our understanding on how we model impacts and economic outcomes in Central America, providing a systematic approach to quantifying the effects of disasters on poverty and other well‐being indicators in the region. The comparative approach, in terms of hurricane damage indexes, provides a better understanding of how windstorm could impact economic and social outcomes.

One of the key innovations of this study has to do with the use of an accurate and comprehensive model that generates high‐resolution, surface‐level, sustained wind speed data of historic hurricanes and tropical storms in Central America proposed by Pita el al. (2015). The windstorm model was calibrated and validated for Central America, enabling a more accurate spatial specification and precise inland measures of wind speed. The three hurricane damage indexes (MSWS – unweighted wind speed, IHD – population‐ weighted index, and WEI – area‐weighted index) showcase different aspects of hurricane damage, however all three indexes provide similar conclusions in terms of the negative impacts in GDP per capita, income, and poverty. Results vary slightly across each index but are not statistically different.

The GDP per capita and household analysis complement each other. While data for GDP per capita have been of better quality and statistical significance, they underestimate the effects of hurricane windstorm on the most vulnerable population. GDP per capita does not begin to capture the impact on well‐being resulting from these natural hazard events. It requires the combined insight from both sets of analyses to contribute to improve the design of programs and policies, which could then be aimed more effectively 20