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We take a simple time-series approach to modeling and forecasting daily average temperature in U.S. cities, and we inquire systematically as to whether it may prove useful from the vantage point of participants in the weather derivatives market. The answer is, perhaps surprisingly, yes. Time-series modeling reveals conditional mean dynamics, and crucially, strong conditional variance dynamics, in daily average temperature, and it reveals sharp differences between the distribution of temperature and the distribution of temperature surprises. As we argue, it also holds promise for producing the long-horizon predictive densities crucial for pricing weather derivatives, so that additional inquiry into time-series weather forecasting methods will likely prove useful in weather derivatives contexts.
Our article integrates the manager’s care in the literature on auditor’s liability. With unobservable efforts, we face a double moral hazard setting. It is well-known that efficient liability rules without punitive damages do not exist under these circumstances. However, we show that the problem can be solved through strict liability, contingent auditing fees, and fair insurance contracts. Neither punitive damages nor deductibles above the damages are required.
During the last IAIS Global Seminar in June 2017, IAIS disclosed the agenda for a gradual shift in the systemic risk assessment methodology from the current Entity Based Approach (EBA) to a new Activity Based Approach(ABA). The EBA, which was developed in the aftermath of the 2008/2009 financial crisis, defines a list of Global Systemically Important Insurers (G-SIIs) based on a pre-defined set of criteria related to the size of the institution. These G-SIIs are subject to additional regulatory requirements since their distress or disorderly failure would potentially cause significant disruption to the global financial system and economic activity. Even if size is still a needed element of a systemic risk assessment, the strong emphasis put on the too-big-to-fail approach in insurance, i.e. EBA, might be partially missing the underlying nature of systemic risk in insurance. Not only certain activities, including insurance activities such as life or non-life lines of business, but also common exposures or certain managerial practices such as leverage or funding structures, tend to contribute to systemic risk of insurers but are not covered by the current EBA (Berdin and Sottocornola, 2015). Therefore, we very much welcome the general development of the systemic risk assessment methodology, even if several important questions still need to be answered.
Investors and insurance policyholders are often confronted with complex products and providers' opaque organisational structures. At the same time, the possibility that their claims will not be honoured often poses an existential risk. Financial regulation therefore aims at putting in place a financial services framework that will safeguard market processes whilst also protecting consumers. However, benefits of regulation are accompanied by certain risks, as can be exemplified with the case of insurance regulation.
When markets are incomplete, social security can partially insure against idiosyncratic and aggregate risks. We incorporate both risks into an analytically tractable model with two overlapping generations and demonstrate that they interact over the life-cycle. The interactions appear even though the two risks are orthogonal and they amplify the welfare consequences of introducing social security. On the one hand, the interactions increase the welfare benefits from insurance. On the other hand, they can in- or decrease the welfare costs from crowding out of capital formation. This ambiguous effect on crowding out means that the net effect of these two channels is positive, hence the interactions of risks increase the total welfare benefits of social security.
When markets are incomplete, social security can partially insure against idiosyncratic and aggregate risks. We incorporate both risks into an analytically tractable model with two overlapping generations. We derive the equilibrium dynamics in closed form and show that joint presence of both risks leads to over-proportional risk exposure for households. This implies that the whole benefit from insurance through social security is greater than the sum of the benefits from insurance against each of the two risks in isolation. We measure this through interaction effects which appear even though the two risks are orthogonal by construction. While the interactions unambiguously increase the welfare benefits from insurance, they can in- or decrease the welfare costs from crowding out of capital formation. The net effect depends on the relative strengths of the opposing forces.
We study optimal investment in self-protection of insured individuals when they face interdependencies in the form of potential contamination from others. If individuals cannot coordinate their actions, then the positive externality of investing in self-protection implies that, in equilibrium, individuals underinvest in self-protection. Limiting insurance coverage through deductibles or selling “at-fault” insurance can partially internalize this externality and thereby improve individual and social welfare. JEL Classification: C72, D62, D80
We compute the optimal dynamic asset allocation policy for a retiree with Epstein-Zin utility. The retiree can decide how much he consumes and how much he invests in stocks, bonds, and annuities. Pricing the annuities we account for asymmetric mortality beliefs and administration expenses. We show that the retiree does not purchase annuities only once but rather several times during retirement (gradual annuitization). We analyze the case in which the retiree is restricted to buy annuities only once and has to perform a (complete or partial) switching strategy. This restriction reduces both the utility and the demand for annuities.
Mutual insurance companies and stock insurance companies are different forms of organized risk sharing: policyholders and owners are two distinct groups in a stock insurer, while they are one and the same in a mutual. This distinction is relevant to raising capital, selling policies, and sharing risk in the presence of financial distress. Up-front capital is necessary for a stock insurer to offer insurance at a fair premium, but not for a mutual. In the presence of an owner-manager conflict, holding capital is costly. Free-rider and commitment problems limit the degree of capitalization that a stock insurer can obtain. The mutual form, by tying sales of policies to the provision of capital, can overcome these problems at the potential cost of less diversified owners.
Mutual insurance companies and stock insurance companies are different forms of organized risk sharing: policyholders and owners are two distinct groups in a stock insurer, while they are one and the same in a mutual. This distinction is relevant to raising capital, selling policies, and sharing risk in the presence of financial distress. Up-front capital is necessary for a stock insurer to offer insurance at a fair premium, but not for a mutual. In the presence of an ownermanager conflict, holding capital is costly. Free-rider and commitment problems limit the degree of capitalization that a stock insurer can obtain. The mutual form, by tying sales of policies to the provision of capital, can overcome these problems at the potential cost of less diversified owners. JEL Classification: G22, G32