These studies show the impact of major events in specific socioeconomic conditions. As there is an absence of regional studies focused at both macro and household levels, the contribution of this study is to provide a regional perspective to the negative impact of hurricane windstorm on a particular set of social and economic outcomes. This is relevant not only because a systematic regional perspective is currently absent in the existing literature, but also because the region shares many characteristics and a common approach to disaster and climate risk management.

The second section of this study investigates the interconnection between hazard and damage which determine the impacts found by empirical studies. In this section we discuss how windstorm hazard data are translated into damage indexes, and present three different ways of computing hurricane damage indexes. To characterize hurricane windstorm we draw on a model developed in the WBG Latin‐American and the Caribbean Disaster Risk Management (DRM) team by Pita et al. (2015) which employs a fully probabilistic hurricane windstorm model calibrated and adjusted for Central America. This model has been used to reproduce historical hurricanes windstorm characteristics with higher temporal and spatial resolution. This model allows a richer and more accurate characterization of the hurricane windstorm hazard than heretofore seen in the literature, improving the different damage indexes used and enabling better understanding of the implicit biases in the model.

Sections 3 and 4 of the study turn to the data, methodology, and results of the analysis at macro and micro (household analysis) levels, focusing on the strong negative impacts of major hurricanes in the short term on per capita GDP (gross domestic product) growth, income, and poverty. One standard deviation in the intensity of hurricane windstorm leads to a decrease in total per capita GDP growth of between 0.9 percent and 1.6 percent, and a decrease in total income and labor income by 3 percent; which in turn increases moderate and extreme poverty by 1.5 percentage points. These socioeconomic indicators are further informed by 3 indexes derived from hurricane damage modeling. Studying both the macro (per capita GDP growth) and the micro (household poverty and income among the variables) levels encompasses a more comprehensive level of analysis of impacts of hurricane windstorms, resulting in a more detailed and nuanced understanding of the negative economic implications of such events.

Finally, the concluding section draws all these angles together to provide a more comprehensive analysis, provides recommendations, and throws up research questions for the future.

# 2. FROM WINDSTORM HAZARD TO DAMAGE

Recent studies have focused on improving the modeling of the natural hazard in order to more explicitly address the impact of adverse natural events on socioeconomic indicators. For example, Hsiang and Jina (2014) and Strobl (2012) evaluate the hurricane windstorm hazard data using global hurricane models to generate gridded data sets with different levels of resolution (Hsiang and Jina at the global level and Strobl for the Caribbean basin). One of the main innovations of this paper is to use a fully probabilistic hurricane windstorm model developed by Pita el al. (2015) which has been validated and calibrated for the Central America region to generate hazard information with the temporal and spatial resolution needed for this study. The windstorm hazard data are used to calculate the damage indexes which are used as input in both the macro and micro models. As a result we substantially improve the understanding of how hurricane windstorm hazards could affect socioeconomic outcomes.

## 2.1. Modeling the Windstorm Hazard

Being complex, the dynamic atmospheric environment of windstorms is often oversimplified. This study uses an accurate and comprehensive model that generates high‐resolution surface‐level sustained wind 3