Behavioral bias and the demand for bicycle and flood insurance

Economic Experiments, Hypothetical Surveys and Market Data Studies of Insurance Demand Against Low‐probability/High‐impact Risks: A Systematic Review of Designs, Theoretical Insights and Determinants of Demand

“…Browne et al . () found that more policyholders purchase add‐on coverage to homeowner's policies for bicycle theft (HPLI event) insurance than for flood (LPHI event) insurance. Nevertheless, a market data study on violations of EUT in terms of aversion to mean‐preserving spreads is likely to suffer from the obvious problem that it is difficult to control for the expected value of insurance prospects.…”

“…Expected utility theory, first axiomized by von Neumann and Morgenstern (), is used as the benchmark for analysing behaviour under risk. Expected utility theory tends to perform well under medium to high‐probability/low‐impact (HPLI) risks; however, in the domain of LPHI risk the theory sometimes fails to give an adequate explanation of behaviour (Browne et al ., ).…”

Catastrophic risk: social influences on insurance decisions

“…By contrast, when probabilities are only learned by observation or experience, individuals may be prone to the underestimation of low probabilities (Hertwig et al 2004). In particular, a significant group of people may simply neglect small risks (Botzen and Bergh 2012), but at the same time, over-insure against high-probability low-cost risks (Browne et al 2015). …”

“…Using field data, Gallagher (2014) shows when a county is hit by a flood, residents in neighboring counties increase their insurance take-up. Friedl et al (2014) argue that the simultaneous over-insurance for high-probability low-cost risk and under-insurance for low-probability high-cost risks is due to social comparison and correlated losses: typical low-probability natural risks are highly correlated across people in a region or neighborhood (e.g., flood insurance as in Browne et al 2015) and typical highprobability risks are uncorrelated across people (e.g., bike theft as in Browne et al 2015). In the former case, social comparison does, therefore, not lead to the feelings of loss, because peers also lose, while in the latter case, the loss is felt more strongly.…”

“…We observe that the aforementioned results derive from a set of studies that each used specific empirical and experimental setups and that it is not clear in how far these findings generalize across different situations. Studies based on field data as in Gallagher (2014), Viscusi and Zeckhauser (2015) or Browne et al (2015) have high external validity for the type of catastrophic risk under investigation. However, they typically have less control over the underlying mechanisms.…”