at protecting the communities in these countries and increasing resilience, particularly of those in the lowest socioeconomic strata.

Results for the GDP per capita analysis show robust, statistically significant effects in the short term with the three hurricane damage indexes modelling different specifications. The household analysis, on the other hand, despite data limitations, gives an insight into the household characteristics that contribute to dealing with hurricane windstorm risk better. The data for the household analysis, however, has important drawbacks, particularly in terms of time coverage, and is more difficult to handle for comparability purposes.

An interesting area for future research has to do with the long‐term cumulative effects of hurricanes. In the literature there is no consensus on whether there are long‐term impacts in the national economy as well than at the household level. A more detailed analysis on long‐term impact of hurricanes for Central America on the determinants of economic growth and social progress in the region could be valuable. Moreover, the challenge is also in quantifying the indirect effects of disasters. Estimating both direct and indirect economic effects of disasters is central to designing effective DRM policies to support the most vulnerable population in a more efficient way. The effects of adverse natural events impact upon a variety of human welfare indicators and these effects add up. Furthermore, a discussion regarding coping mechanisms would also be relevant. Understanding how households exposed to natural events make decisions, the context in which these decisions are made, and other behavioral elements, could help identify and better characterize their coping mechanisms, resilience levels, and mitigation strategies. Understanding this is paramount in designing effective risk managing strategies. Qualitative research plays an important role in this particular set of questions and could complement quantitative analysis, enriching the lessons learned along the way.

# 6. REFERENCES

Anttila‐Hughes, J. & Hsiang, S. (2014). Destruction, Disinvestment, and Death: Economic and Human Losses Following Environmental Disaster. Available at SSRN: <u>http://ssrn.com/abstract=2220501</u>

- Baez, J. & Santos, I. (2007). Children’s Vulnerability to Weather Shocks:  A Natural Disaster as a Natural Experiment. Retrieved from:

- http://citeseerx.ist.psu.edu/viewdoc/download;jsessionid=D3E4D0D9B5A87E66A235C91E269501 7D?doi=10.1.1.175.2774&rep=rep1&type=pdf

- Baez, J., Lucchetti, L., Genoni, M., & Salazar, M. (2015). Gone With the Storm: Rainfall Shocks and Household Well‐being in Guatemala. _Policy Research Working Papers_ , No. WPS7177, World Bank, Washington, DC.

- Bruno, G. S. F. (2005). Approximating the Bias of the LSDV Estimator for Dynamic Unbalanced Panel Data Models. _Economics Letters,_ 87: 361‐366.

- Bustelo, M. (2011). Bearing the Burden of Natural Disasters: Child Labor and Schooling in the Aftermath of the Tropical Storm Stan in Guatemala. (Doctoral dissertation).  Retrieved from the University of Illinois at Urbana‐Champaign.

- Carter, M., Little, P., Mogues, T., & Negatu, W. (2007). Poverty Traps and Natural Disasters in Ethiopia and Honduras. _World Development_ 35 (5), 835–856.

- CEPAL (2011). Resumen regional del impacto de la depresión tropical 12‐E en Centroamérica. Cuantificación de daños y pérdidas sufridos por los países de la región en el mes de octubre de

21