A windstorm hazard model is used to simulate maximum sustained wind speeds,<sup>16</sup> which is a proxy for potential damage from hurricanes, experienced by the affected areas at a resolution of 1 square kilometer. It is capable of producing a fully exogenous measure of hurricane intensity and its potential destructive power at a fine-grained geographical level. The resulting wind speed data are then merged with nightlight data.

Recent studies have focused on improving natural hazard modeling to more explicitly address the impact of adverse natural events on socioeconomic indicators. For example, Hsiang and Jina (2014) and Strobl (2012) evaluate hurricane windstorm hazard data using global hurricane models to generate a gridded data set with different levels of resolution. One of the main innovations in this paper is its use of the fully probabilistic hurricane windstorm model developed by Strobl (2012), which we have validated and calibrated for the Caribbean region to generate hazard information with the temporal and spatial resolution needed for this study. We use windstorm hazard data to calculate the damage indexes, which we then use as inputs in both the macro and micro models. As a result, the paper substantially improves the understanding of how hurricane windstorm hazards could affect socioeconomic outcomes.

# **2.3.Mangrove forest data**

Mangroves are commonly found along sheltered coastlines in the tropics and subtropics, where they fulfill important socioeconomic and environmental functions, from providing a large variety of wood and nonwood forest products to protecting the coast against the effect of wind, waves, and water currents, and conserving coral reefs, sea-grass beds, and endangered animals for biological diversity (FAO 2007). Together, coastal mangroves, coral reefs, and seagrass beds act as a natural barrier from the high wave energy and strong coastal currents that are typical of the Caribbean environment (Menéndez et al. 2020).

Although Caribbean mangroves have sustained human activity since pre-Columbian times (Sanoja 1992), climate-forcing factors, such as extreme winds caused by tropical storms, and anthropogenic factors like deforestation and urbanization have severely impacted mangroves in the region. In fact, anthropogenically-driven increases in atmospheric carbon dioxide concentration and regional sea level are expected to have a huge impact on mangroves (Ellison and Farnsworth 1996). Unfortunately, the demands on mangrove forests are more intensive and pervasive and include converting them to other uses such as agricultural production and urbanizing their uplands. This lack of concern for these ecosystems has led to the loss of mangroves, changed the conditions that regulate their functioning, and caused the overexploitation of dependent fisheries and other forest products (Lugo 2002).

The literature on mangrove forests is extensive and many case studies describe their extent and losses over time; yet, comprehensive global information on the status and trends in mangrove extent is lacking. The first attempt to estimate total mangrove area worldwide was undertaken as a part of the FAO and United Nations Environment Programme’s _Tropical Forest Resources Assessment_ in 1980, which estimated the world mangrove total area at 15.6 million hectares. More recent estimates range from 12 to 20 million hectares (FAO 2007).

For this study, we used two mangrove distribution sources:

- Mangrove data from the _World Atlas of Mangroves_ (Spalding, Blasco and Field 1997): the first collection of harmonized maps from 1960 to 1996, which estimates a total mangrove extent of 18.1 million hectares in 112 countries and territories (including small island nations).

> 16 We thank Eric Strobl for sharing the model results.

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