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Does flood experience modify risk preferences? Evidence from an artefactual field experiment in Vietnam

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A Correction to this article was published on 21 January 2022

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Abstract

We conducted an artefactual field experiment in Vietnam to investigate whether and how experiencing a natural disaster affects individual attitudes toward risks. Using experimental and real household data, we show that households in villages affected by a flood in recent years exhibit more risk aversion, compared with individuals living in similar but unaffected villages. Interestingly, this result holds for the loss domain, but not the gain domain. In line with Prospect Theory, Vietnamese households distort probabilities. The distortion is related to aid received and social networks participation, but is unrelated to flood experience.

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Notes

  1. The question of whether preferences or only attitudes are changed also refers to the notion of conditional and unconditional preference stability. In our context, the environment of an individual is much changed after a disaster so that we cannot discuss unconditional stability. But we do attempt to identify more precisely some potential mediators of a change in choices.

  2. Other works combining experimental measures of risk preferences with real decisions include Azevedo et al. (2003), Brunette et al. (2017).

  3. See https://www.wri.org/resources/data-sets/aqueduct-global-flood-risk-country-rankings.

  4. In Tversky and Kahneman (1992), a loss aversion parameter is specified. The use of our simplified form has been dictated by empirical considerations. Our pilot experiment has indeed revealed that Vietnamese households had some difficulties manipulating lotteries involving both gains and losses, which are required for identifying loss aversion. Bruhin et al. (2010) also use a similar sign-dependent power function arguing that it is the best compromise between parsimony and goodness of fit in the context of PT.

  5. Tversky and Kahneman (1992) consider different probability weighting functions, one for the gain domain and the other for the loss domain. However, in most empirical applications they are the same (Abdellaoui et al. 2016).

  6. With our specification, the Arrow-Pratt absolute risk aversion coefficients for income y are \((1 - \alpha )/y\) in the gain domain and \((1 - \beta )/y\) in the loss domain, and are thus decreasing in y. The relative risk aversion coefficients are equal to \(1- \alpha\) and \(1 - \beta\) and are thus constant.

  7. Because we are primarily interested in the impact of flood experience on preferences, this asymmetry in the number of gambles should have a very limited impact on our analysis.

  8. An alternative approach would have been to estimate the risk preference parameter using maximum likelihood, following the approach proposed by Harrison and Rutström (2008). As a robustness check, we have estimated the three parameters (\(\alpha , \beta , \gamma\)) using this approach. Estimates are quite consistent with the individual-specific mid-point intervals obtained using the Tanaka et al. (2010) approach, and are available from authors upon request.

  9. As a robustness test we have also considered a dummy variable equal to 1 only if an individual selects the safest lottery in the gain domain. Econometric results are consistent with the ones reported in Table 5.

  10. Recall that with our specification the coefficient of absolute risk aversion are \((1-\alpha )/y\) in the gain domain and \((1-\beta )/y\) in the loss domain. They should thus be decreasing in income y, which is what we observe in our estimates.

  11. Interval regressions have also been estimated by including district-level fixed effects to account for regional heterogeneity. Results concerning the relationship between flood experience and risk preferences are qualitatively very similar to the ones presented in Table 6.

  12. The three other flood experiences (being injured, water elevation in house greater than 100 cm and being flooded more than 8 days per year) cannot be included due to high collinearity with reporting significant expenditures.

  13. In Table 8, flood experience is measured by the fact that a household has been flooded at least once in the last 5 years. Results for being evacuated or injured are available from the authors upon request.

  14. A tentative explanation is that formal aid tends to consists in fixed transfers (at least in a given range of flood severity) so that it covers well average losses but is not responsive to very large losses. This aspect of formal aid would be more salient to those households who experienced it.

References

  • Abdellaoui, M. 2000. Parameter-free elicitation of utility and probability weighting functions. Management Science 46 (11): 1385–1512.

    Google Scholar 

  • Abdellaoui, M., H. Bleichrodt, and O. L’Haridon. 2008. A tractable method to measure utility and loss aversion under prospect theory. Journal of Risk and Uncertainty 36 (3): 245–266.

    Google Scholar 

  • Abdellaoui, M., H. Bleichrodt, O. L’Haridon, and D. van Dolder. 2016. Measuring loss aversion under ambiguity: A method to make prospect theory completely observable. Journal of Risk and Uncertainty 52 (1): 1–20.

    Google Scholar 

  • Ali Bchir, M. and M. Willinger (2013). Does the exposure to natural hazards affect risk and time preferences? Some insights from a field experiment in Peru. LAMETA working paper serie 2013. University of Montpellier, France.

  • Andersen, S., G.W. Harrison, M.I. Lau, and E.E. Rutström. 2008. Lost in state space: Are preferences stable? International Economic Review 49 (3): 1091–1112.

    Google Scholar 

  • Andrabi, T. and J. Das (2010). In aid we trust: Hearts and minds and the Pakistan earthquake of 2005. Policy Research Working Paper 5440, The World Bank.

  • Azevedo, C.D., J.A. Herriges, and C.L. Kling. 2003. Combining revealed and stated preferences: Consistency tests and their interpretations. American Journal of Agricultural Economics 85 (3): 525–537.

    Google Scholar 

  • Baucells, M., and A. Villasís. 2010. Stability of risk preferences and the reflection effect of prospect theory. Theory and Decision 68 (1): 193–211.

    Google Scholar 

  • Beaud, M., and M. Willinger. 2015. Are people risk vulnerable? Management Science 61 (3): 624–636.

    Google Scholar 

  • Becchetti, L., S. Castriota, and P. Conzo. 2017. Disaster, aid, and preferences: The long-run impact of the tsunami on giving in sri lanka. World Development 94 (C): 157–173.

    Google Scholar 

  • Binswanger, H.P. 1980. Attitudes toward risk: Experimental measurement in rural India. American Journal of Agricultural Economics 62 (3): 395–407.

    Google Scholar 

  • Booij, A.S., B. van Praag, and G. van de Kuilen. 2010. A parametric analysis of prospect theory’s functionals for the general population. Theory and Decision 68 (1–2): 115–148.

    Google Scholar 

  • Bruhin, A., H. Fehr-Duda, and T. Epper. 2010. Risk and rationality: Uncovering heterogeneity in probability distortion. Econometrica 78 (4): 1375–1412.

    Google Scholar 

  • Brunette, M., J. Foncel, and E.N. Kéré. 2017. Attitude towards risk and production decision: An empirical analysis on french private forest owners. Environmental Modeling and Assessment 22 (6): 563–576.

    Google Scholar 

  • Bubeck, P., W.J.W. Botzen, and J.C.J.H. Aerts. 2012. A review of risk perceptions and other factors that influence flood mitigation behavior. Risk Analysis 32 (9): 1481–1495.

    Google Scholar 

  • Callen, M. 2015. Catastrophes and time preference: Evidence from the Indian Ocean Earthquake. Journal of Economic Behavior & Organization 118: 199–214.

    Google Scholar 

  • Cameron, L., and M. Shah. 2015. Risk-taking behavior in the wake of natural disasters. Journal of Human Resources 50 (2): 484–515.

    Google Scholar 

  • Cassar, A., A. Healy, and C. von Kessler. 2017. Trust, risk, and time preferences after a natural disaster: Experimental evidence from Thailand. World Development 94: 90–105.

    Google Scholar 

  • Castillo, M., R. Petrie, and M. Torero. 2010. On the preferences of principals and agents. Economic Inquiry 48 (2): 266–273.

    Google Scholar 

  • Chuang, Y., and L. Schechter. 2015. Stability of experimental and survey measures of risk, time, and social preferences: A review and some new results. Journal of Development Economics 117: 151–170.

    Google Scholar 

  • Dang Nguyen, A. 2009. Household registration system and the well-beings of rural-to-urban migrants. Vietnam’s Socio-economic Development: A Social Science Review 59 (9): 75–80.

    Google Scholar 

  • Dave, C., C.C. Eckel, C.A. Johnson, and C. Rojas. 2010. Eliciting risk preferences: When is simple better? Journal of Risk & Uncertainty 41 (3): 219–243.

    Google Scholar 

  • De Martino, B., C.F. Camerer, and R. Adolphs. 2010. Amygdala damage eliminates monetary loss aversion. Proceedings of the National Academy of Sciences 107 (8): 3788–3792.

    Google Scholar 

  • Dionne, G., and L. Eeckhoudt. 1985. Self-insurance, self-protection and increased risk aversion. Economics Letters 17 (1–2): 39–42.

    Google Scholar 

  • Dohmen, T., A. Falk, D. Huffman, and U. Sunde. 2012. The intergenerational transmission of risk and trust attitudes. Review of Economic Studies 79 (2): 645–677.

    Google Scholar 

  • Dohmen, T., A. Falk, D. Huffman, U. Sunde, J. Schupp, and G.G. Wagner. 2011. Individual risk attitudes: Measurement, determinants, and behavioral consequences. Journal of the European Economic Association 9 (3): 522–550.

    Google Scholar 

  • Eckel, C.C., M.A. El-Gamal, and R.K. Wilson. 2009. Risk loving after the storm: A Bayesian-network study of Hurricane Katrina evacuees. Journal of Economic Behavior & Organization 69 (2): 110–124.

    Google Scholar 

  • Eckel, C.C., and P.J. Grossman. 2002. Sex differences and statistical stereotyping in attitudes toward financial risk. Evolution and Human Behavior 23 (4): 281–295.

    Google Scholar 

  • Eckel, C.C., and P.J. Grossman. 2008. Forecasting risk attitudes: An experimental study using actual and forecast gamble choices. Journal of Economic Behavior & Organization 68 (1): 1–7.

    Google Scholar 

  • Eeckhoudt, L., C. Gollier, and H. Schlesinger. 1996. Changes in background risk and risk-taking behavior. Econometrica 64 (3): 683–89.

    Google Scholar 

  • Ehrlich, I., and G.S. Becker. 1972. Market insurance, self-insurance, and self-protection. Journal of Political Economy 80 (4): 623–648.

    Google Scholar 

  • Engle-Warnick, J., J. Escobal, and S. Laszlo. 2009. How do additional alternatives affect individual choice under uncertainty? Canadian Journal of Economics 42 (1): 113–140.

    Google Scholar 

  • Gollier, C., and J.W. Pratt. 1996. Risk vulnerability and the tempering effect of background risk. Econometrica 64 (5): 1109–1123.

    Google Scholar 

  • Gonzalez, R., and G. Wu. 1999. On the shape of the probability weighting function. Cognitive Psychology 38 (1): 129–166.

    Google Scholar 

  • Harrison, G.W., and E.E. Rutström. 2008. Risk aversion in the laboratory. Research in Experimental Economics 12: 41–196.

    Google Scholar 

  • Hirabayashi, Y., R. Mahendran, S. Koirala, L.K.D. Yamazaki, S. Watanabe, H. Kim, and S. Kanaee. 2013. Global flood risk under climate change. Nature Climate Change 3: 816–821.

    Google Scholar 

  • Ho, M.-C., D. Shaw, S. Lin, and Y.-C. Chiu. 2008. How do disaster characteristics influence risk perception? Risk Analysis 28 (3): 635–643.

    Google Scholar 

  • Hopland, A.O., E. Matsen, and B. Strom. 2016. Income and choice under risk. Journal of Behavioral and Experimental Finance 12: 55–64.

    Google Scholar 

  • Kahneman, D., and A. Tversky. 1979. Prospect theory: An analysis of decision under risk. Econometrica 47 (2): 263–291.

    Google Scholar 

  • Kimball, M.S. 1993. Standard risk aversion. Econometrica 61 (3): 589–611.

    Google Scholar 

  • Knuth, D., D. Kehl, L. Hulse, and S. Schmidt. 2014. Risk perception, experience, and objective risk: A cross-national study with European emergency survivors. Risk Analysis 34 (7): 1286–1298.

    Google Scholar 

  • Levin, I.P., and S.S. Hart. 2003. Risk preferences in young children: Early evidence of individual differences in reaction to potential gains and losses. Journal of Behavioral Decision Making 16 (5): 397–413.

    Google Scholar 

  • Levin, I.P., G. Xue, J.A. Weller, M. Reimann, M. Lauriola, and A. Bechara. 2012. A neuropsychological approach to understanding risk-taking for potential gains and losses. Frontiers in Neuroscience 6: 15.

    Google Scholar 

  • Li, J.-Z., S. Li, and H. Liu. 2011. How has the Wenchuan earthquake influenced people’s intertemporal choices? Journal of Applied Social Psychology 41 (11): 2739–2752.

    Google Scholar 

  • Li, J.-Z., S. Li, W.-Z. Wang, L.-L. Rao, and H. Liu. 2011. Are people always more risk averse after disasters? Surveys after a heavy snow-hit and a major earthquake in China in 2008. Applied Cognitive Psychology 25 (1): 104–111.

    Google Scholar 

  • Liu, E.M. 2013. Time to change what to sow: Risk preferences and technology adoption decisions of cotton farmers in China. Review of Economics and Statistics 95 (4): 1386–1403.

    Google Scholar 

  • Loewenstein, G.F., E.U. Weber, C.K. Hsee, and N. Welch. 2001. Risk as feelings. Psychological Bulletin 127 (2): 267–286.

    Google Scholar 

  • Mai, C.V., M.J. Stive, and P.H. VanGelder. 2009. Coastal protection strategies for the red river delta. Journal of Coastal Research 25 (1): 105–116.

    Google Scholar 

  • Nguyen-Hoang, P., and J. McPeak. 2010. Leaving or staying: Inter-provincial migration in vietnam. Asia and Pacific Migration Journal 19 (4): 473–500.

    Google Scholar 

  • Page, L., D.A. Savage, and B. Torgler. 2014. Variation in risk seeking behaviour following large losses: A natural experiment. European Economic Review 71: 121–131.

    Google Scholar 

  • Pilarczyk, K.W., and N.S. Nuoi. 2005. Experience and practices on flood control in Vietnam. Water International 30 (1): 114–122.

    Google Scholar 

  • Quiggin, J. 2003. Background risk in generalized expected utility theory. Economic Theory 22 (3): 607–611.

    Google Scholar 

  • Reynaud, A., C. Aubert, and M.-H. Nguyen. 2013. Living with floods: Protective behaviours and risk perception of Vietnamese households. Geneva Papers on Risk and Insurance Issues and Practice 38: 547–579.

    Google Scholar 

  • Reynaud, A., and M.-H. Nguyen. 2016. Valuing flood risk reductions. Environmental Modeling & Assessment 21 (5): 603–617.

    Google Scholar 

  • Reynaud, A., M.-H. Nguyen, and C. Aubert. 2018. Is there a demand for flood insurance in Vietnam? Results from a choice experiment. Environmental Economics and Policy Studies 20 (3): 593–617.

    Google Scholar 

  • Said, F., U. Afzal, and G. Turner. 2015. Risk taking and risk learning after a rare event: Evidence from a field experiment in Pakistan. Journal of Economic Behavior & Organization 118: 167–183.

    Google Scholar 

  • Samphantharak, K. and S. Chantarat (2015). The effects of natural disasters on households’ preferences and behaviours: Evidence from thai farmers during and after the 2011 mega flood. Disaster Risks, Social Preferences, and Policy Effects: Field Experiments in Selected ASEAN and East Asian Coutries, 57–84.

  • Schoemaker, P. 1990. Are risk-attitudes related across domains and response modes? Management Science 36 (12): 1451–1463.

    Google Scholar 

  • Scott, J.C., G.E. Matt, K.M. Wrocklage, C. Crnich, J. Jordan, S.M. Southwick, J.H. Krystal, and B.C. Schweinsburg. 2015. A quantitative meta-analysis of neurocognitive functioning in posttraumatic stress disorder. Psychological Bulletin 141 (1): 105.

    Google Scholar 

  • Shin, L.M., S.L. Rauch, and R.K. Pitman. 2006. Amygdala, medial prefrontal cortex, and hippocampal function in ptsd. Annals of the New York Academy of Sciences 1071 (1): 67–79.

    Google Scholar 

  • SwissRe, 2012. World insurance in 2011—non-life ready for take-off. Sigma 3: 1–40.

    Google Scholar 

  • Tanaka, T., C. Camerer, and Q. Nguyen. 2010. Risk and time preferences: Linking experimental and household survey data from vietnam. American Economic Review 100 (1): 557–571.

    Google Scholar 

  • Townsend, R.M. 1994. Risk and insurance in village India. Econometrica 62 (3): 539–591.

    Google Scholar 

  • Tversky, A., and D. Kahneman. 1992. Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and Uncertainty 5 (4): 297–323.

    Google Scholar 

  • von Gaudecker, H.-M., A. van Soest, and E. Wengstrom. 2011. Heterogeneity in risky choice behavior in a broad population. American Economic Review 101 (2): 664–694.

    Google Scholar 

  • Voors, M.J., E.E. Nillesen, P. Verwimp, E.H. Bulte, R. Lensink, and D.P. Van Soest. 2012. Violent conflict and behavior: A field experiment in Burundi. American Economic Review 102 (2): 941–964.

    Google Scholar 

  • Weber, E. U. and J. S. Ancker (2010). Risk perceptions and risk attitudes in the United States and Europe. The Reality of Precaution: Comparing Approaches to Risk Regulation in the United States and Europe. J. B. Wiener, M. D. Rogers, P. H. Sand, and J. K. Hammitt (eds). Ch. 18, Taylor and Francis.

  • Weller, J.A., I.P. Levin, B. Shiv, and A. Bechara. 2007. Neural correlates of adaptive decision making for risky gains and losses. Psychological Science 18 (11): 958–964.

    Google Scholar 

  • WorldBank (2005). Natural disaster hotspots: A global risk analysis. Disaster Risk Management Series No. 5, Hazard Management Unit, The World Bank.

  • WorldBank (2010). Weathering the Storm: Options for Disaster Risk Financing in Vietnam. The World Bank.

  • Yesuf, M., and R.A. Bluffstone. 2009. Poverty, risk aversion, and path dependence in low-income countries: Experimental evidence from Ethiopia. American Journal of Agricultural Economics 91 (4): 1022–1037.

    Google Scholar 

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Acknowledgements

We thank Mr. Nhung Nguyen from the Vietnamese Ministry of Agriculture and Rural Development for his patience when explaining flood protection in Vietnam. We also thank Thanh Duy Nguyen for his very efficient assistance during the field work and Maht Hung Nguyen for his work during the survey. The field survey would not have been possible without the support of the VanXuan University of Technology at Cua Lo. This research is funded by Vietnam National Foundation for Science and Technology Development (NAFOSTED) under grant number 502.01-2016.18. We acknowledge the support from the ANR under grant ANR-17-EUR-0010 (Investissements d’Avenir program) for traveling and conferences. Conflict of Interest: The authors declare that they have no conflict of interest.

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  1. Toulouse School of Economics, INRA, University of Toulouse Capitole, Toulouse, France

    Arnaud Reynaud

  2. University of Economics and Law Ho Chi Minh City and Vietnam Center of Research in Economics, Management and Environment (VCREME), Ho Chi Minh City, Vietnam

    Arnaud Reynaud

  3. University of Bordeaux, GREThA, and Toulouse School of Economics, Bordeaux, France

    Cécile Aubert

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  1. Arnaud Reynaud
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The original online version of this article was revised to add a second affiliation to Arnaud Reynaud and to change the acknowledgments (“We acknowledge the support from the ANR under grant ANR-17-EUR-0010 (Investissements d’Avenir program) for traveling and conferences”).

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Reynaud, A., Aubert, C. Does flood experience modify risk preferences? Evidence from an artefactual field experiment in Vietnam. Geneva Risk Insur Rev 45, 36–74 (2020). https://doi.org/10.1057/s10713-019-00044-w

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