Estimating the welfare loss to households from natural disasters in developing countries: a contingent valuation study of flooding in Vietnam

摘要

Background: Natural disasters have severe impacts on the health and well-being of affected households. However, we find evidence that official damage cost assessments for floods and other natural disasters in Vietnam, where households have little or no insurance, clearly underestimate the total economic damage costs of these events as they do not include the welfare loss from mortality, morbidity and reduced well-being experienced by the households affected by the floods. This should send a message to the local communities and national authorities that higher investments in flood alleviation, reduction and adaptive measures can be justified since the social benefits of these measures in terms of avoided damage costs are higher than previously thought.Methods: We pioneer the use of the contingent valuation (CV) approach of willingness-to-contribute (WTC) labour to a flood prevention program, as a measure of the welfare loss experienced by household due to a flooding event. In a face-to-face household survey of 706 households in the Quang Nam province in Central Vietnam, we applied this approach together with reported direct physical damage in order to shed light of the welfare loss experienced by the households. We asked about households’ WTC labour and multiplied their WTC person-days of labour by an estimate for their opportunity cost of time in order to estimate the welfare loss to households from the 2007 floods.Results: The results showed that this contingent valuation (CV) approach of asking about willingness-to-pay in-kind avoided the main problems associated with applying CV in developing countries.Conclusion: Thus, the CV approach of WTC labour instead of money is promising in terms of capturing the total welfare loss of natural disasters to households, and promising in terms of further application in other developing countries and for other types of natural disasters.