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We provide a comprehensive analysis of the impact of probability weighting on optimal insurance demand in a unified framework. We identify decreasing relative overweighting as a new local condition on the probability weighting function that is useful for comparative static analysis. We discuss the effects of probability weighting on coinsurance, deductible choice, insurance demand for low-probability, high-impact risks versus high-probability, low-impact risks, and insurance demand in the presence of nonperformance risk. Probability weighting can make better or worse predictions than expected utility depending on the insurance demand problem at hand. [ABSTRACT FROM AUTHOR]

Index insurance offers an innovative risk management solution for uninsured agricultural weather risk. We investigate the theoretical relationship between prospect theory risk preferences and characteristics of index insurance. We pair these theoretical findings with data from a lab-in-the-field experiment in Kenya. Empirically, we find that insurance demand is decreasing in loss aversion, and the negative marginal effect of loss aversion on insurance demand increases with basis risk and the insurance premium. Our theoretical and empirical results combined illustrate the importance of considering both risk and loss aversion, as well as basis risk, in understanding index insurance decisions. [ABSTRACT FROM AUTHOR]

This paper investigates the benefits of incorporating diversification effects into the pricing process of insurance policies from two different business lines. The paper shows that, for the same risk reduction, insurers pricing policies jointly can have a competitive advantage over those pricing them separately. However, the choice of competitiveness constrains the underwriting flexibility of joint pricers. The paper goes a step further by modelling explicitly the relationship between premiums and the number of customers in each line. Using the total collected premiums as a criterion to compare the competing strategies, the paper provides conditions for the optimal pricing decision based on policyholders' sensitivity to price discounts. The results are illustrated for a portfolio of annuities and assurances. Further, using non-life data from the Brazilian insurance market, an empirical exploration shows that most pairs satisfy the condition for being priced jointly, even when pairwise correlations are high. [ABSTRACT FROM AUTHOR]

Uninsured risk impedes agricultural production, but traditional indemnity insurance is not a viable option for smallholder farmers due to market failures. Weather index insurance is often touted as an alternative risk management tool. Demand for weather index insurance, however, has been weak. One possible reason is basis risk, the mismatch between index insurance payouts and individual outcomes. We estimate the impact of two interventions on preferred coverage under a real index insurance product, as revealed through an auction: (a) a reduction in basis risk, and (b) an experiential game that teaches farmers how index insurance works, with an emphasis on basis risk. We show all farmers demonstrate strong sensitivity to basis risk. The experiential game modestly increased knowledge, and experiential game participants indicate higher levels of preferred insurance coverage. Although offering a lower basis risk insurance product and playing an experiential game both increase preferred coverage in isolation, there is no additional impact of doing both. We adapt a theoretical model of misattribution bias to demonstrate how reference‐dependent learning with loss aversion could lead to this unexpected result. [ABSTRACT FROM AUTHOR]

Agricultural insurance can be classified into two broad categories: Compulsory (government/public) and Voluntary (market/private) insurance. In practice, the vast majority of compulsory insurance is partially compulsory, where compulsory insurance provides only partial coverage, and it allows for supplemental voluntary purchases (mixed insurance). In this article, we use the Balloon Analogue Risk Task as the assessment of risk‐taking and insurance context to conduct an online experiment. The main objective is to compare compulsory, voluntary and mixed insurance in terms of adverse selection and moral hazard. We find adverse selection in purely voluntary insurance, but advantageous selection in mixed insurance. Moral hazard exists in all three types of insurance, but it is smaller in mixed insurance. Our ancillary results suggest that under the combined effects of significant moral hazard and "no adverse selection" in purely compulsory insurance make it the insurance type with the lowest social earnings. Overall there is no crowding‐out effect of the compulsory part on residual voluntary purchases in mixed insurance. [ABSTRACT FROM AUTHOR]

In this paper, we consider an optimal insurance problem from the perspective of a risk-averse individual who faces an insurable risk as well as some background risk and wants to maximise the expected utility of his/her final wealth. To reduce ex post moral hazard, we follow Huberman et al. (Bell J. Econ. 14:415–426 1983) to assume that alternative insurance contracts satisfy the principle of indemnity and the no-sabotage condition. When the insurance premium is calculated by the expected value premium principle, a necessary and sufficient condition for the optimality of an insurance contract is established under a general dependence structure between insurable and background risks. By virtue of this condition, some qualitative properties of optimal contracts are developed, a scheme is provided to improve any suboptimal insurance strategy, and optimal insurance forms are derived explicitly for some dependence structures of interest. These forms are not always piecewise linear. [ABSTRACT FROM AUTHOR]

Forests are often threatened by storms; and such a threat is likely to rise due to climate change. Using private forest insurance as a vehicle to fund resilience and adaptation emerge as a policy recommendation. Hence the forest owners would have the possibility to consider insurance when defining their forest management practices. In this context, we analyze the impact of the forest owner's insurance decision on forest management under storm risk. We extend the Faustmann optimal rotation model under risk, first, considering the forest owner's risk preferences, and second, integrating the decision of insurance. With this analytical model, we show that as the insurance coverage increases, the rotation length increases independently of the forest owner's risk aversion. In addition, we identify some cases where it may be optimal for the forest owner to not adopt insurance contract. Finally, we prove that a public transfer, reducing the insurance premium, may encourage the forest owner to insure. [ABSTRACT FROM AUTHOR]

Building on the work by Volkman-Wise Journal of Risk and Uncertainty, 51, 267–290 (2015) and Dumm et al. (The Geneva Risk and Insurance Review, 42, 117–139 (2017), we examine behavioral aspects of risk through the representative heuristic's impact on catastrophe-related probability assessment and insurance demand of Florida homeowners. The representative heuristic models individuals as underweighting prior probabilities and overweighting posterior probabilities, thereby overweighting the probability of a loss from a disaster after a disaster occurs. Using data for homeowners' insurance purchases through Florida's residual market over a time period (2003-2008) that includes a sub-period of many losses (2004-2005) and sub-period of few catastrophic losses (2003, 2006-2008), we find increases in demand at the individual policyholder level for coverage following losses. Also consistent with the representative heuristic, we find that the effect attenuates as the losses fade from memory. That is, the effect of losses on demand is much higher for more recent losses. We also are able to parameterize the representative heuristic model showing that individual policy holders overweight the probability of another catastrophic event occurring by nearly 50%, after one has occurred. [ABSTRACT FROM AUTHOR]

We define a premium principle under the continuous cumulative prospect theory which extends the equivalent utility principle. In prospect theory, risk attitude and loss aversion are shaped via a value function, whereas a transformation of objective probabilities, which is commonly referred as probability weighting, models probabilistic risk perception. In cumulative prospect theory, probabilities of individual outcomes are replaced by decision weights, which are differences in transformed, through the weighting function, counter-cumulative probabilities of gains and cumulative probabilities of losses, with outcomes ordered from worst to best. Empirical evidence suggests a typical inverse-S shaped function: decision makers tend to overweight small probabilities, and underweight medium and high probabilities; moreover, the probability weighting function is initially concave and then convex. We study some properties of the behavioral premium principle. We also assume an alternative framing of the outcomes; then, we discuss several applications to the pricing of insurance contracts, considering different value functions and probability weighting functions proposed in the literature, and an alternative mental accounting. Finally, we focus on the shape of the probability weighting function. [ABSTRACT FROM AUTHOR]

This article provides an overview of flood risk management in the United States, focusing on the National Flood Insurance Program and the Community Ratings System (CRS), which is designed to promote flood hazard mitigation. We review the empirical literature that examines market penetration and demand for flood insurance, as well as factors that influence community participation in CRS. Combining data from separate (but similar) surveys conducted in Dare County, North Carolina in 1998 and 2008, we examine trends in flood insurance holdings and explore the extensive (binary participation) and intensive (coverage level) margins using regression analysis. We explore trends in CRS mitigation activities in Dare County and discuss potential difficulties in analyzing these data. Finally, we highlight avenues for future research. [ABSTRACT FROM AUTHOR]

This article analyzes the existence of moral hazard in prevented planting (PP) in the United States. The PP provision is defined as the "failure to plant an insured crop by the final planting date due to adverse events." If the farmer decides not to plant a crop, the farmer receives a PP indemnity. Late planting (LP) is an option for farmers to plant a crop while maintaining crop insurance after the final planting date. Crop insurance may alter farmers' behavior in selecting PP or LP and could increase the likelihood of PP claims even though farmers can choose LP. This study finds evidence that a farmer with higher insurance coverage tends to choose PP more often (ex‐post moral hazard). Spatial panel models attest to the existence of the ex‐post moral hazard in PP empirically. Empirical results show that the PP ratio has a positive relationship with insurance coverage in the case of corn production. [ABSTRACT FROM AUTHOR]

Risk and uncertainty are critical to human decision-making. Yet our understanding of the underlying traits that present the foundation of decision-making remains limited. The work develops a causal model of the antecedents of consumers’ purchase behavior in the context of unit-linked life insurance products. Our experimental approach (n = 929) builds on the risk as analysis and risk as feeling perspective, which entails huge theoretical and practical contributions. Risk avoidance and uncertainty avoidance are identified to strongly influence the product perceptions. We complement our findings by investigating the conditions that favor the influence of both traits by investigating moderating effects. [ABSTRACT FROM AUTHOR]

The replicating portfolio (RP) approach to the calculation of capital for life insurance portfolios is an industry standard. The RP is obtained from projecting the terminal loss of discounted asset-liability cash flows on a set of factors generated by a family of financial instruments that can be efficiently simulated. We provide the mathematical foundations and a novel dynamic and path-dependent RP approach for real-world and risk-neutral sampling. We show that our RP approach yields asymptotically consistent capital estimators if the chaotic representation property holds. We illustrate the tractability of the RP approach by three numerical examples. [ABSTRACT FROM AUTHOR]

In this paper we provide an axiomatic foundation to Orlicz risk measures in terms of properties of their acceptance sets, by exploiting their natural correspondence with shortfall risk Föllmer and Schied (Stochastic finance. De Gruyter, Berlin, 2011), thus paralleling the characterization in Weber (Math Financ 16:419–442, 2006). From a financial point of view, Orlicz risk measures assess the stochastic nature of returns, in contrast to the common use of risk measures to assess the stochastic nature of a position’s monetary value. The correspondence with shortfall risk leads to several robustified versions of Orlicz risk measures, and of their optimized translation invariant extensions (Rockafellar and Uryasev in J Risk 2:21–42, 2000, Goovaerts et al. in Insur Math Econ 34:505–516, 2004), arising from an ambiguity averse approach as in Gilboa and Schmeidler (J Math Econ 18:141–153, 1989), Maccheroni et al. (Econometrica 74:1447–1498, 2006), Chateauneuf and Faro (J Math Econ 45:535–558, 2010), or from a multiplicity of Young functions. We study the properties of these robust Orlicz risk measures, derive their dual representations, and provide some examples and applications. [ABSTRACT FROM AUTHOR]

With recent research suggesting a behavioral explanation for changes in demand for insurance (e.g., Volkman-Wise (2015)), we study homeowners' demand for windstorm insurance in the wake of losses. In particular, we examine the representative heuristic's impact on the demand for homeowners' insurance, which provides coverage for windstorm losses, in Florida (U.S.). Under this paradigm, individuals underweight prior probabilities and overweight posterior probabilities. This results in an over (under)-weighting of the probability of a loss from a disaster in the event (absence) of a disaster. Using data for new homeowners' insurance, purchases in Florida's residual market between 2005 and 2007 (a period of high hurricane activity), we find, subsequent to losses, the demand for coverage limits and the number of policies sold both increase. Further, we find that this effect attenuates as the losses become further away in time. That is, more recent losses have a stronger effect on demand. This attenuation of the demand is also consistent with the representative heuristic. [ABSTRACT FROM AUTHOR]

We study behavioral patterns of insurance demand for low-probability large-loss events (catastrophic losses). Individual patterns of belief formation and risk attitude that were suggested in the behavioral decisions literature emerge robustly in the current set of insurance choices. However, social comparison effects are less robust. We do not find any evidence for peer effects (through social-loss aversion or imitation) on insurance take-up. In contrast, we find support for the prediction that people underweight others' relevant information in their own decision making. [ABSTRACT FROM AUTHOR]

In reliability theory projects are usually evaluated in terms of their riskiness, and often decision under risk is intended as the one-shot-type binary choice of accepting or not accepting the risk. In this paper we elaborate on the concept of risk acceptance, and propose a theoretical framework based on network theory. In doing this, we deal with system reliability, where the interconnections among the random quantities involved in the decision process are explicitly taken into account. Furthermore, we explore the conditions to be satisfied for risk-acceptance criteria to be consistent with the axiomatization of standard expected utility theory within the network framework. In accordance with existing literature, we show that a risk evaluation criterion can be meaningful even if it is not consistent with the standard axiomatization of expected utility, once this is suitably reinterpreted in the light of networks. Finally, we provide some illustrative examples. [ABSTRACT FROM AUTHOR]

The aim of this paper is to investigate the optimal insurance demand of a risk-averse agent who is faced with background uncertainty. The preferences of the agent are represented by two-moment, mean-standard deviation utility functions. By the comparative statics, we find that under the assumption of decreasing absolute risk aversion (DARA), the changes of background uncertainty have effects on optimal insurance demand. [ABSTRACT FROM AUTHOR]

We derive dual characterizations of two notions of weak time consistency for concave valuations, which are convex risk measures under a positive sign convention. Combined with a suitable risk aversion property, these notions are shown to amount to three simple rules for not necessarily minimal representations, describing precisely which features of a valuation determine its unique consistent update. A compatibility result shows that for a time-indexed sequence of valuations, it is sufficient to verify these rules only pairwise with respect to the initial valuation, or in discrete time, only stepwise. We conclude by describing classes of consistently risk averse dynamic valuations with prescribed static properties per time step. This gives rise to a new formalism for recursive valuation. [ABSTRACT FROM AUTHOR]

The representative heuristic causes individuals to underweight prior probabilities and overweight posterior probabilities. We examine the effect of the representative heuristic on the demand for insurance and participation in mitigation activities. Pre-disaster, the representative heuristic leads to lower demand for insurance, even for a subsidized policy; indeed zero coverage may be optimal for a subsidized policy. After a disaster occurs, the heuristic causes individuals to demand more insurance than those not subject to the heuristic, even if policies are unfairly priced. We depict the subsidization needed prior to a disaster to induce individuals to purchase insurance and show the level of unfair pricing that can be tolerated post-disaster. Similarly, the heuristic causes individuals to have a lower willingness to pay for mitigation activities pre-disaster, relative to an individual not subject to the heuristic. Post-disaster the heuristic causes willingness to pay for mitigation to be higher. [ABSTRACT FROM AUTHOR]

Index insurance – in which payments are based on an index correlated with, but not identical to, individual losses – has been faced with an unexpectedly low uptake, despite its promise as a tool for poverty alleviation. This paper offers new insights into the behavioral impediments to the uptake of index insurance. We start from the observation that an index insurance contract appears to the farmer as a compound lottery, with uncertainty about individual production outcomes, as well as about the validity of the index as a reflection of individual losses. Adopting the smooth model of ambiguity aversion to this insurance problem, we show that in theory this compound lottery structure per se will dampen the demand for index insurance. Using framed field experiments with cotton farmers in Southern Mali, we elicited the coefficients of risk aversion and compound-risk aversion. The experimental results find that almost 60% of farmers are compound-risk averse, and that the distribution of compound-risk aversion is such that it would nearly cut in half the potential demand for the standard index insurance contracts. Our results highlight the importance of designing contracts with minimal basis risk under compound-risk aversion. Such a reduction in basis risk would not only enhance the value and productivity impacts of index insurance, but would also assure that the contracts are purchased and have their anticipated impacts. [ABSTRACT FROM AUTHOR]