Annette Hofmann

The objective of this paper is to pursue an intuitive idea: for a consumer who represents an “unfavorable” health risk but an “excellent risk” as a driver, a multi-peril policy could be associated with a reduced selection effort on the part of the insurer. If this intuition should be confirmed, it will serve to address the decade-long concern with risk selection both in the economic literature and on the part of policy makers. As an illustrative example, a two-peril model is developed in which consumers deploy effort in search of a policy offering them maximum coverage at the current market price while insurers deploy effort designed to stave off unfavorable risks. Two types of Nash equilibria are compared: one in which the insurer is confronted with high-risk and low-risk types, and another one where both types are a “better risk” with regard to a second peril. The difference in the insurer’s selection effort directed at high-risk and low-risk types is indeed shown to be lower in the latter case, resulting in a mitigation of adverse selection.

The consistently missing demand for catastrophe insurance and for coverage of other low-probability–high-consequence risks is often referred to as the catastrophe insurance puzzle. People show reluctance to insure low-probability–high-consequence events, even with some disastrous consequences, yet insure against small high-probability–low-consequence events. There has been no convincing explanation of this puzzle to this date. This article points out that the underlying rationale may be that individuals interpret insurance contracts with low payout probability as an investment with negative expected net present value. While premium payments start with the conclusion of the contract, usually there is only one loss payment in the near or far future. Using a simple annuity model with fixed annual premiums and expected indemnity payouts, it is found that even an individual characterized by the degree of risk aversion found in the literature is unlikely to purchase insurance with these characteristics. To alleviate this unfavorable insurance purchase syndrome, combining a low-probability with a high-probability loss insurance contract may be a way to incentivize individuals to purchase catastrophe risk coverage.

This paper challenges the question of existence and predictability of underwriting cycles in the U.S. property and casualty insurance industry. Using an approach in the frequency domain, we demonstrate the existence of a hidden periodic component in annual aggregated loss ratios. The data support an underwriting cycle length of 8–9 years. Going beyond previous research and studying almost 30 years of quarterly underwriting data, we can improve forecasting performance by (dis)connecting cycles and catastrophic events. Superior out-of-sample forecast results from models with intervention variables flagging the time point of catastrophic outbreaks is achieved in terms of mean squared/absolute forecast errors. We evaluate model confidence sets containing the most accurate model with a certain confidence level. The analysis suggests that reliable forecasts can be achieved net of the irregular major peaks in loss distributions that arise from natural catastrophes as well as unusual “black swan” events.

We study the relationship between risk managers’ dark triad personality traits (Machiavellianism, narcissism, and psychopathy) and their selective hedging activities. Using a primary survey of 412 professional risk managers, we find that managers with dark personality traits are more likely to engage in selective hedging than those without. This effect is particularly pronounced for older, male, and less experienced risk managers. The effect is also stronger in smaller firms, less centralized risk management departments, and family-owned firms.