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Valuing Flood Risk Reductions

Abstract

A choice experiment is used to estimate how Vietnamese households value a flood risk reduction. The empirical analysis is conducted on a sample of households located in the Nghe An Province, one of the provinces which is the most affected by floods in Vietnam. The results reveal that there is a high level of heterogeneity in preferences across households. We compute the willingness to pay (WTP) for a flood risk reduction, and we identify how it relates to different attributes of flood management policies (reduction of economic losses, reduction of human losses, political level in charge of implementing the flood management policy). In particular, the marginal WTP for reducing the flood fatality rate, which can be interpreted as the value of statistical life (VSL), varies from 2 517 million VND (approximately 120,818 USD) to 3 590 million VND (approximately 172,323 USD) depending on the model considered. The VSL represents between 77 and 111 times the annual household average income in our sample, a result in line with previous estimates in similar countries.

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Fig. 1

Notes

  1. 1.

    For a country at high flood risk such as the Netherlands, flood defense expenses were in 2005 approximately equal to 1.3 billion euro, representing around 0.25 % of the country-level GDP [27].

  2. 2.

    This is also the case for studies assessing the WTP for a catastrophic flood risk insurance such as the recent work conducted in Vietnam by [7].

  3. 3.

    The multi-sectoral objectives of the flood policy in Vietnam are summarized in the national strategy for natural disaster prevention, response and mitigation to 2020 which states that the main goals of flood management policy are to “mobilize resources to effectively implement disaster prevention, response and mitigation from now up to 2020 in order to minimize the losses of human life and properties, the damage of natural resources and cultural heritages, and the degradation of environment, contributing significantly to ensure the country sustainable development, national defense and security.”

  4. 4.

    Largest dikes (category 1) are managed at the state level by the CCFSC, whereas smaller dikes (categories 2 and 3) are operated at provincial, district, or village level. Province CFSCs are, according to the Law, required to store necessary materials for dyke protection such as bags of sand, rock stones, or bamboo trunks. Broadcasting of flood-related information (warnings, evacuation, etc.) is processed by commune CFSCs which usually manage the system of loudspeakers.

  5. 5.

    Revealed preference methods have also been used by scholars, but mainly in the context of developed countries [1, 10, 16, 19, 23].

  6. 6.

    While agriculture’s share of GDP has fallen significantly over the years and now accounts for about 20 %, the primary sector still employs more than half of the labor force.

  7. 7.

    Intentionally, we did not use the term probability which may have been difficult to understand for some of the households we have interviewed. See the Supplementary Material available online.

  8. 8.

    Damage to home has been also used by [4] in the context of flood insurance valuation in Netherlands.

  9. 9.

    The fatality rate due to floods has also been used by [36] in the Japanese context.

  10. 10.

    Largest dikes (category 1) are managed at the state level by the CCFSC whereas smaller dikes (categories 2 and 3) are operated at provincial, district or village level. Province CFSCs are, according to the Law, required to store necessary materials for dyke protection such as bags of sand, rock stones, or bamboo trunks. Broadcasting of flood-related information (warnings, evacuation, etc.) is processed by commune CFSCs which usually manage the system of loudspeakers.

  11. 11.

    The official conversion rate is 1 USD for 20 833 VND on May 14th 2013.

  12. 12.

    The last section, not discussed here, is a CE for assessing the WTP for a flood insurance, see [26].

  13. 13.

    Due to missing answers, flood costs have been computed on a sub-sample of 407 households.

  14. 14.

    Since respondent characteristics do not vary over the repeated choices of a respondent, they have to be interacted with the ASC or at least with one of the five attributes of flood risk reduction programs.

  15. 15.

    See Appendix for the definition of each variable.

  16. 16.

    We have in fact four modalities for this variable namely “more floods,” “less floods,” “the same number of floods,” and “I don’t know if there will be more or less floods.”

  17. 17.

    In addition to the socio-economic variables presented in Table 4, we have considered some other potential determinants including household’ age, number of children, professional occupation, housing characteristics, risk, and time preferences. These variables were never significant.

  18. 18.

    Estimates of the main parameters of interest considering log-normal distributions are quite similar.

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Acknowledgments

The authors would like to thank Mr. Nhung Nguyen from the Vietnamese Ministry of Agriculture and Rural Development for his patience when explaining the organization of flood protection in Vietnam and in the Nghe An Province. We thank Thanh Duy Nguyen for his very efficient assistance during the field work and we are also grateful to Christoph Rheinberger and Henrik Andersson for very useful comments on a preliminary version of the choice experiment survey. This paper has also benefitted from very useful comments at the Cost-Benefit Analysis workshop of the Toulouse School of Economics (TSE) and at the fifth Vietnam Economist Annual Meeting (VEAM) in Hanoi. The usual disclaimer applies. Financial support from the Nghe An province in Vietnam is recognized as part of the VIETFLOOD project.

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Correspondence to Arnaud Reynaud.

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Appendix: Definition of Variables

Appendix: Definition of Variables

Table 7 Name and definition of variables used in the CE

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Reynaud, A., Nguyen, MH. Valuing Flood Risk Reductions. Environ Model Assess 21, 603–617 (2016). https://doi.org/10.1007/s10666-016-9500-z

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Keywords

  • Choice experiment
  • Environmental valuation
  • Flood risk
  • Value of statistical life
  • Vietnam