Predicting Insurance Demand from Risk Attitudes

Jaspersen, Johannes G.; Ragin, Marc A.; Sydnor, Justin R.

doi:10.2139/ssrn.3496484

Cited by 5 publications

(12 citation statements)

References 19 publications

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“…The difference can result from different preferences to UBI but could also be reflection of different willingness to getting insurance in general. For example Jaspersen et al (2022) found positive correlation between different measures of risk aversion (utility curvature, loss aversion, probability weighting) and insurance demand.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Factors determining usage-based insurance acceptance - Poland and Spain results

Forlicz¹,

Rólczyński²

2022

Journal of International Studies

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Usage-based insurance (UBI) is based on the idea that customers who are safer drivers should pay less for a policy than those who are less prudent. It is widely assumed that there is an incentive for insurers to use this technology, as it could make riskier drivers more likely to use non-telematics-based insurers. However, this hypothesis has not been verified empirically. In order to fill this research gap, a study (between December 2021 and March 2022) assessing the relationship between driving style and willingness to purchase a UBI-based policy and the relationship between risk propensity and willingness to purchase a UBI-based policy was conducted. The study, in the form of a questionnaire, was conducted in Poland and Spain. The samples consisted of 181 respondents in Poland and 51 in Spain. It was found that individual driving style was correlated with willingness to accept a UBI-based policy that included discounts and surcharges. It was also shown that propensity to risk influences willingness to purchase a UBI-based policy that offers discounts only to some extent. The study used suitable statistical measures and tests such as a chi-square test, U Mann-Whitney U test and a Kruskal-Wallis test. Results are significant for insurance companies that are going to introduce UBI. They allow shaping the product so that potential customers are interested in buying it, which, as research shows, may bring benefits to both insured and insurance companies.

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Section: Conclusion and Discussionmentioning

confidence: 99%

Factors determining usage-based insurance acceptance - Poland and Spain results

Forlicz¹,

Rólczyński²

2022

Journal of International Studies

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“…One could argue that such lottery decisions measure a preference for certainty instead of utility curvature. However, recent research on comparable lotteries shows no difference in behavior when certain payments are the safe option in multiple price lists rather than less risky lotteries (Jaspersen et al, 2022).…”

Section: Setting and Experimental Designmentioning

confidence: 98%

On the change of risk aversion in wealth: a field experiment in a closed economic system

Huber¹,

Jaspersen²,

Richter³

et al. 2022

Exp Econ

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How does risk aversion change in wealth? To answer this question, we implemented a field experiment in the form of a free-to-play mobile game. Players made lottery choices at various points in the game and at different levels of in-game wealth. Since the game was designed as a closed economic system, that is, wealth could not be transferred into or out of the game, only in-game wealth was relevant for players’ choices. Analyzing the choices of over 2000 players, we find evidence for decreasing absolute risk aversion and decreasing relative risk aversion. We also find evidence of an “always safe” heuristic in a subgroup of decisions and observe a tendency of players to act according to the “hot hand fallacy”. Our research design allows us to exclude inertia and lets us analyze lottery stakes of significant size relative to in-game wealth. Our results render implications for theoretical research, empirical studies, and for the optimal design of financial products.

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“…Willingness to pay for insurance then depends on the precise shape of both the distribution of losses and the weighting function (Baillon et al, 2022b). 5 See Jaspersen et al (2022) for alternatives. 6 This is because the weight placed on the probability of the loss rises, w p p ( ) > , while the weight attached to the prospect of paying the insurance premium is the same as that given under EU, w (1) = 1.…”

Section: The Variance Of Consumption With Insurancementioning

confidence: 99%

“…A prospect theory (PT) model of insurance in which the premium is perceived as a loss predicts that convex utility over losses will drive demand down (Wakker et al, 1997). Any motivation to insure would then have to come from the distorted transformation of loss probabilities into decision weights (Barseghyan et al, 2013; Jaspersen et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Do time preferences explain low health insurance take‐up?

Baillon

O’Donnell

Quimbo

et al. 2022

J of Risk & Insurance

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Low insurance take-up in low-income populations is not easily explained by the standard single-period expected utility model of insurance that overlooks the relevance of time preference when liquidity is constrained. We design field survey instruments to elicit quasi-hyperbolic time preferences, as well as prospect theory risk preferences, and use them to examine whether time preferences explain health insurance behavior of lowincome Filipinos. Consistent with theory, those with stronger parameterized time preference are less likely to insure and the partial association is most pronounced at low wealth where liquidity is most likely to be constrained. Among those with better understanding of insurance, lower take-up is also associated with present bias. We do not find that insurance is significantly associated with risk preferences.

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Predicting Insurance Demand from Risk Attitudes

Cited by 5 publications

References 19 publications

Factors determining usage-based insurance acceptance - Poland and Spain results

Factors determining usage-based insurance acceptance - Poland and Spain results

On the change of risk aversion in wealth: a field experiment in a closed economic system

Do time preferences explain low health insurance take‐up?

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