Enterprise Recovery Following Natural Disasters

By S. D. Mel, David J. McKenzie, Christopher Woodruff. 2010

189 citations recorded by the source corpus.

Using data from surveys of enterprises in Sri Lanka after the December 2004 tsunami, the authors undertake the first microeconomic study of the recovery of the private firms in a developing country following a major natural disaster. Disaster recovery in low-income countries is characterized by the prevalence of relief aid rather than of insurance payments; the data show this distinction has important consequences. The data indicate that aid provided directly to households correlates reasonably well with reported losses of household assets, but is uncorrelated with reported losses of business assets. Business recovery is found to be slower than commonly assumed, with disaster-affected enterprises lagging behind unaffected comparable firms more than three years after the disaster. Using data from random cash grants provided by the project, the paper shows that direct aid is more important in the recovery of enterprises operating in the retail sector than for those operating in the manufacturing and service sectors.

Subfields: Economics and Econometrics, Sociology and Political Science, Soil Science

View Paper: https://www.semanticscholar.org/paper/e7a0d357a15281642f02e4e6763bb1f0b68d8ccf

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Citations in the corpus

Unmasking the Impact of COVID-19 on Businesses : Firm Level Evidence from across the World (2020, background): “In Sri Lanka, cash grants helped micro-firms survive the crisis and accelerated their recovery following the 2004 Tsunami (De Mel et al., 2012).”
Generating Employment in Poor and Fragile States: Evidence from Labor Market and Entrepreneurship Programs (2015, background): “However, a year later all these gains 51Evans and Popova (2014) 52de Mel et al. (2012a) 53See Gertler et al. (2012) for Mexico and Macours et al. (2013) for Nicaragua.”
Dynamic Inputs and Resource (Mis)Allocation (2014, background): “7 For micro-based studies that consider the effect of each, see Collard-Wexler ð2013Þ on demand shocks; De Mel, McKenzie, and Woodruff ð2012Þ on natural disasters; Fisher-Vanden, Mansur, and Wang ð2012Þ on infrastructure; Fisman and Svensson ð2007Þ on corruption; De Loecker et al. ð2012Þ on…”