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

Abstract

This paper provides a systematic review of the literature on 80 experimental, hypothetical survey and market data studies of insurance demand against low‐probability/high‐impact risks. The objective of the review is to extract lessons from these studies and to outline an agenda for future research. We contrast the results of experimental and survey studies to findings from market data. We focus on experimental design methods, insurance characteristics, as well as results about theories, heuristics, behavioural biases and explanatory variables. Lessons for policymakers are drawn which can facilitate disaster preparedness.

Behavioral Economics and Auto Insurance: The Role of Biases and Heuristics

“…anchoring effect. Robust evidence in the literature (Coe, Belbase, & Wu, 2016;Robinson & Botzen, 2019) argues that this effect can be relevant when purchasing insurance. Based on the experiment by Johnson et al (1993), it was asked how much respondents would be willing to pay for certain insurance coverage in two locations.…”

An experimental study of charity hazard: The effect of risky and ambiguous government compensation on flood insurance demand

“…Our experiment is a framed one (i.e., in the context of flood risk), therefore some context was warranted regarding the source of certain, risky and ambiguous government compensation. There are advantages to framing an insurance experiment in a specific context as summarized in a recent literature review by Robinson and Botzen (2019), such as external validity and in the absence of contextual framing individuals may make up their own. We tried to keep the source of certain, risky and ambiguous government compensation as neutral as possible, because offering more contextual richness (e.g., political factors and flooding experience), may have lead subjects to based their priors about government compensation more on contextual elements rather than the riskiness and ambiguity by and of itself.…”

“…According to Jaspersen (2016) and Robinson and Botzen (2019), we define a decision under risk as a situation where the probability of each possible outcome is known. If the probabilities are not known, and a distribution of probabilities over possible probabilities is not known either, the decision is considered one under ambiguity.…”

The Earthquake Insurance Protection Gap: A Tale of Two Countries

“…19. We direct the interested reader to Robinson and Wouter Botzen (2019), who provide a systematic review of 80 studies of insurance demand for low-probability, high-severity events.…”