Environmental and Resource Economics

, Volume 74, Issue 4, pp 1533–1562 | Cite as

Combining Risk Attitudes in a Lottery Game and Flood Risk Protection Decisions in a Discrete Choice Experiment

  • Markus GlattEmail author
  • Roy Brouwer
  • Ivana Logar


Decision-making about flood protection is surrounded by outcome uncertainty. In this paper we look at the influence of individual risk attitudes on flood protection decisions. To this end, we combine the results of a lottery game with the findings from a discrete choice experiment focusing on flood risk reduction measures. We find that the inclusion of non-linear probability weighting increases the explanatory power of the choice model. The result is however sensitive to behavioral assumptions about decisions under uncertainty, as well as whether the lottery was played in the loss or gain domain. Including risk attitudes in the probability weighted model decreases marginal willingness to pay for measures with a low to intermediate flood risk reduction capacity and increases marginal willingness to pay for measures with a very high flood risk reduction effect. This has important implications for the social acceptability of flood reduction measures under different baseline conditions.


Lottery game Choice experiment Flood risk Bayesian model averaging Risk attitudes 

JEL Classification

C11 C57 D81 Q54 



We thank Mehmet Kutluay for his valuable advice on the lottery game and the modeling approaches used in this study and Rosi Siber for helping us to link respondents’ addresses to current flood risk areas in Switzerland. This study is funded by the Swiss National Science Foundation (Grant No. 100018_156709).


  1. Allais M (1979) The so-called Allais paradox and rational decisions under uncertainty. In: Allais M, Hagen O (eds) Expected utility hypotheses and the Allais paradox. Theory and decision library (an international series in the philosophy and methodology of the social and behavioral sciences), vol 21. Springer, Dordrecht, pp 437–681Google Scholar
  2. Balcombe K, Fraser I (2015) Parametric preference functionals under risk in the gain domain: a Bayesian analysis. J Risk Uncertain 50(2):161–187. CrossRefGoogle Scholar
  3. Botzen WJW, van den Bergh JCJM (2012) Risk attitudes to low-probability climate change risks: WTP for flood insurance. J Econ Behav Organ 82(1):151–166. CrossRefGoogle Scholar
  4. Botzen WJW, Aerts JCJH, van den Bergh JCJM (2009) Willingness of homeowners to mitigate climate risk through insurance. Ecol Econ 68(8–9):2265–2277. CrossRefGoogle Scholar
  5. Brouwer R, Martín-Ortega J (2012) Modeling self-censoring of polluter pays protest votes in stated preference research to support resource damage estimations in environmental liability. Resour Energy Econ 34(1):151–166. CrossRefGoogle Scholar
  6. Brouwer R, Schaafsma M (2013) Modelling risk adaptation and mitigation behaviour under different climate change scenarios. Clim Change 117(1–2):11–29. CrossRefGoogle Scholar
  7. Brouwer R, Tinh BD, Tuan TH, Magnussen K, Navrud S (2014) Modeling demand for catastrophic flood risk insurance in coastal zones in Vietnam using choice experiments. Environ Dev Econ 19(02):228–249. CrossRefGoogle Scholar
  8. Bruhin A, Fehr-Duda H, Epper T (2010) Risk and rationality: uncovering heterogeneity in probability distortion. Econometrica 78(4):1375–1412. CrossRefGoogle Scholar
  9. de Palma A, Ben-Akiva M, Brownstone D, Holt C, Magnac T, McFadden D, Moffatt P, Picard N, Train K, Wakker P, Walker J (2008) Risk, uncertainty and discrete choice models. Mark Lett 19(3–4):269–285. CrossRefGoogle Scholar
  10. Denwood MJ (2016) runjags: an R package providing interface utilities, model templates, parallel computing methods and additional distributions for MCMC models in JAGS. J Stat Softw 71(9):1–25. CrossRefGoogle Scholar
  11. Etchart-Vincent N, L’Haridon O (2011) Monetary incentives in the loss domain and behavior toward risk: an experimental comparison of three reward schemes including real losses. J Risk Uncertain 42(1):61–83. CrossRefGoogle Scholar
  12. Ferber M (2013) Risky built near the water (Org: Riskant nahe am Wasser gebaut). Neue Zürcher Zeitung, 19 Jun 2013Google Scholar
  13. Glenk K, Colombo S (2013) Modelling outcome-related risk in choice experiments. Aust J Agric Resour Econ 57(4):559–578. CrossRefGoogle Scholar
  14. Goldstein WM, Einhorn HJ (1987) Expression theory and the preference reversal phenomena. Psychol Rev 94(2):236–254CrossRefGoogle Scholar
  15. Grothmann T, Reusswig F (2006) People at risk of flooding: why some residents take precautionary action while others do not. Nat Hazards 38(1–2):101–120. CrossRefGoogle Scholar
  16. Harrison GW, Humphrey SJ, Verschoor A (2010) Choices under uncertainty: evidence from Ethiopia, India and Uganda. Econ J 120(543):80–104. CrossRefGoogle Scholar
  17. Hausmann P, Kurz C, Rebuffoni G (2012) Floods in Switzerland-an underestimated risk. Swiss Reinsurance Company Ltd. Accessed 12 Sept 2018
  18. Johnston RJ, Boyle KJ, Adamowicz W, Bennett J, Brouwer R, Cameron TA, Hanemann WM, Hanley N, Ryan M, Scarpa R (2017) Contemporary guidance for stated preference studies. J Assoc Environ Resource Econom 4(2):319–405Google Scholar
  19. Kahneman D, Tversky A (1979) Prospect theory: an analysis of decision under risk. Econometrica 47(2):263–292CrossRefGoogle Scholar
  20. Koetse MJ, Brouwer R (2016) Reference dependence effects on WTA and WTP value functions and their disparity. Environ Resource Econ 65(4):723–745. CrossRefGoogle Scholar
  21. Kutluay M, Brouwer R, Tol RSJ (2017) Preference updating in public health risk valuation. In: Paper presented at the 23rd Annual Conference of the European Association of Environmental and Resource Economists (EAERE), Athens, 28 June–1 July 2017Google Scholar
  22. Maidl E, Buchecker M (2015) Raising risk preparedness by flood risk communication. Nat Hazards Earth Syst Sci 15(7):1577–1595. CrossRefGoogle Scholar
  23. McFadden D, Train K (2000) Mixed MNL models for discrete response. J Appl Econom 15(5):447–470CrossRefGoogle Scholar
  24. Petrolia DR, Landry CE, Coble KH (2013) Risk preferences, risk perceptions, and flood insurance. Land Econ 89(2):227–245. CrossRefGoogle Scholar
  25. Planat National Platform for Natural Hazards (2005) Protection against natural hazards in Switzerland—vision and strategy. PLANAT-Serial 1Google Scholar
  26. Prelec D (1998) The probability weighting function. Econometrica 66(3):497–527. CrossRefGoogle Scholar
  27. Quiggin J (1982) A theory of anticipated utility. J Econ Behav Organ 3(4):323–343. CrossRefGoogle Scholar
  28. R Core Team (2016) R: a language and environment for statistical computing. Accessed 12 Sept 2018
  29. Rabin M (2002) A perspective on psychology and economics. Eur Econ Rev 46(4–5):657–685. CrossRefGoogle Scholar
  30. Sarrias M, Daziano R (2017) Multinomial logit models with continuous and discrete individual heterogeneity in R: the gmnl package. J Stat Softw 79(2):1–46. CrossRefGoogle Scholar
  31. Siegrist M, Gutscher H (2006) Flooding risks: a comparison of lay people’s perceptions and expert’s assessments in Switzerland. Risk Anal 26(4):971–979. CrossRefGoogle Scholar
  32. Stott HP (2006) Cumulative prospect theory’s functional menagerie. J Risk Uncertain 32(2):101–130. CrossRefGoogle Scholar
  33. Swait J, Louviere J (1993) The role of the scale parameter in the estimation and comparison of multinomial logit models. J Mark Res 30(3):305–314CrossRefGoogle Scholar
  34. Swiss Academy of Sciences (2016) Spotlight on climate in Switzerland—basics, consequences and perspectives (in German). Swiss Academies Reports 11(5):216Google Scholar
  35. Tversky A, Kahneman D (1992) Advances in prospect-theory—cumulative representation of uncertainty. J Risk Uncertain 5(4):297–323. CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Eawag, Swiss Federal Institute of Aquatic Science and TechnologyDübendorfSwitzerland
  2. 2.Department of Economics and the Water InstituteUniversity of WaterlooWaterlooCanada
  3. 3.Department of Environmental EconomicsVrije Universiteit AmsterdamAmsterdamThe Netherlands

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