Weathering storms in Central America: The impact of hurricanes on poverty and the economy
Countries are facing increasingly frequent negative impacts from adverse natural events. Central America, a region prone and vulnerable to disasters, is a clear example. Just from 1992 to 2011, Central America was hit by nearly 70 hurricanes with an average of 8 events per year, hindering sustainable economic growth.
Between 2005 and 2014, due to natural disasters, the region had a nominal cumulative loss of around US$5.8 billion, and witnessed more than 3,410 deaths and hundreds of thousands of displaced people. More recently, in October 2011, Tropical Depression 12-E hit the coasts of El Salvador and Guatemala with damages amounting to nearly US$1 billion.
In two recent studies, we evaluated the causal impacts of hurricane windstorms on poverty and income as well as economic activity measured using night lights at the regional and country level. In both cases, we applied a fully probabilistic windstorm model developed in-house, and calibrated and adjusted it for Central America. The first study (on poverty) used yearly information at the household level (for income and poverty measures) as well as the national level (GDP per capita). Due to the limited comparable household data between the countries, we decided to follow up with the second study (on economic activity) using granular data at the highest spatial resolution available (i.e., 1 km2) to understand more deeply the (monthly) impact over time.
Between 2005 and 2014, due to natural disasters, the region had a nominal cumulative loss of around US$5.8 billion, and witnessed more than 3,410 deaths and hundreds of thousands of displaced people. More recently, in October 2011, Tropical Depression 12-E hit the coasts of El Salvador and Guatemala with damages amounting to nearly US$1 billion.
In two recent studies, we evaluated the causal impacts of hurricane windstorms on poverty and income as well as economic activity measured using night lights at the regional and country level. In both cases, we applied a fully probabilistic windstorm model developed in-house, and calibrated and adjusted it for Central America. The first study (on poverty) used yearly information at the household level (for income and poverty measures) as well as the national level (GDP per capita). Due to the limited comparable household data between the countries, we decided to follow up with the second study (on economic activity) using granular data at the highest spatial resolution available (i.e., 1 km2) to understand more deeply the (monthly) impact over time.
Our results are striking:
