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Eric M. Pondi Endengle, Seung Mo Choi, and Ms. Pritha Mitra
This paper assesses the impact of climate-related disasters on medium-term growth and analyzes key structural areas that could substantially improve disaster-resilience. Results show that (i) climaterelated disasters have a significant negative impact on medium-term growth, especially for sub-Saharan Africa; and (ii) a disaster’s intensity matters much more than its frequency, given the non-linear cumulative effects of disasters. In sub-Saharan Africa, electrification (facilitating irrigation) is found to be most effective for reducing damage from droughts while improved health care and education outcomes are critical for raising resilience to floods and storms. Better access to finance, telecommunications, and use of machines in agriculture also have a significant impact.
Eric M. Pondi Endengle, Seung Mo Choi, and Ms. Pritha Mitra

– Tables Annex III. Impact analysis with a different frequency proxy References FIGURES Figure 1: EMDEs: Model-based predicted growth and disaster proxies Figure 2: Reduction in impact of disasters on SSA’s medium-term growth if structural factors improve TABLES Table 1: Description of variables Table 2: Selected economies: Growth models with disaster Indicators (GMM) Table 3: Selected economies: Growth models with disaster indicators (Fixed effects) Table 4: b 2 estimates in model (5) Table 5 (A1): Baseline model with controls from Barro (2003

Eric M. Pondi Endengle, Seung Mo Choi, and Ms. Pritha Mitra

values being averages over the windows. Thus, the final panel has 12 five-year periods. However, the intensity and the frequency proxies are not aggregated the same way, as the aggregated intensity proxy aims at capturing the proportion of disruptive disasters while the aggregated frequency proxy gives the ratio between the disaster-related fatalities and the population. The control variables for the impact analysis are these of Loayza et al. (2012) , which proposes a growth model that includes disaster proxies. The control variables of Barro (2003) are applied in