Flood insurance demand and probability weighting: The influences of regret, worry, locus of control and the threshold of concern heuristic

Peter John Robinson*, W. J.Wouter Botzen

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

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Low-lying densely populated areas can be susceptible to flooding due to extreme river discharges. Insurance may be used to spread flood risk and reduce potential material damages. However, homeowners often purchase insufficient amounts of insurance against natural hazard risks like flooding, which may be due to the way they process probabilities. A common finding from (Cumulative) Prospect Theory is that individuals over-weight low probabilities and under-weight moderate to high probabilities in making decisions under risk. However, very low probabilities typical of flood risks are either significantly over-weighted or neglected altogether. This study aims to examine factors related to flood insurance demand regarding emotions specific to risk, like immediate and anticipated emotions, the threshold level of concern as well as personality traits, like locus of control. In addition, we compare results under real experiment incentives to hypothetical ones with high loss outcomes. Based on data collected from 1041 homeowners in the Netherlands, we find that: an internal locus of control and anticipated regret about potentially uninsured flood losses is related to higher flood insurance demand. The use of the threshold of concern model is related to more probability under-weighting/less probability over-weighting when probabilities of flooding are low. Several policies are suggested to overcome psychological factors related to low demand for flood insurance to improve future flood preparations.

Original languageEnglish
Article number100144
Pages (from-to)1-19
Number of pages19
JournalWater Resources and Economics
Early online date24 Apr 2019
Publication statusPublished - Apr 2020


  • Cumulative prospect theory
  • Flood insurance demand
  • Hypothetical bias
  • Risk preferences

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