The Impact of Mega‐Catastrophes on Insurers: An Exposure‐Based Analysis of the U.S. Homeowners’ Insurance Market

Insurance is a key risk‐sharing mechanism that protects citizens and governments from the losses caused by natural catastrophes. Given the increase in the frequency and intensity of natural catastrophes over recent years, this article analyzes the performance effects of mega‐catastrophes for U.S. insurance firms using a measure of market expectations. Specifically, we analyze the share price losses of insurance firms in response to catastrophe events to ascertain whether mega‐catastrophes significantly damage the performance of insurers and whether different types of mega‐catastrophes have different impacts. The main message from our analysis is that the impact of mega‐catastrophes on insurers has not been too damaging. While the exact impact of catastrophes depends on the nature of the event and the degree of competition within the relevant insurance market (less competition allows insurers to recoup catastrophe losses through adjustments to premiums), our overall results suggest that U.S. insurance firms can adequately manage the risks and costs of mega‐catastrophes. From a public policy perspective, our results show that insurance provides a robust means of sharing catastrophe losses to help reduce the financial consequences of a catastrophe event.     

Sovereign Cat Bonds and Infrastructure Project Financing

We examine the opportunities for using catastrophe‐linked securities (or equivalent forms of nondebt contingent capital) to reduce the total costs of funding infrastructure projects in emerging economies. Our objective is to elaborate on methods to reduce the necessity for unanticipated (emergency) project funding immediately after a natural disaster. We also place the existing explanations of sovereign‐level contingent capital into a catastrophic risk management framework. In doing so, we address the following questions. (1) Why might catastrophe‐linked securities be useful to a sovereign nation, over and above their usefulness for insurers and reinsurers? (2) Why are such financial instruments ideally suited for protecting infrastructure projects in emerging economies, under third‐party sponsorship, from low‐probability, high‐consequence events that occur as a result of natural disasters? (3) How can the willingness to pay of a sovereign government in an emerging economy (or its external project sponsor), who values timely completion of infrastructure projects, for such instruments be calculated? To supplement our treatment of these questions, we use a multilayer spreadsheet‐based model (in Microsoft Excel format) to calculate the overall cost reductions possible through the judicious use of catastrophe‐based financial tools. We also report on numerical comparative statics on the value of contingent‐capital financing to avoid project disruption based on varying costs of capital, probability and consequences of disasters, the feasibility of strategies for mid‐stage project abandonment, and the timing of capital commitments to the infrastructure investment. We use these results to identify high‐priority applications of catastrophe‐linked securities so that maximal protection can be realized if the total number of catastrophe instruments is initially limited. The article concludes with potential extensions to our model and opportunities for future research.     

Insurability and Mitigation of Flood Losses in Private Households in Germany

In Germany, flood insurance is provided by private insurers as a supplement to building or contents insurance. This article presents the results of a survey of insurance companies with regard to eligibility conditions for flood insurance changes after August 2002, when a severe flood caused 1.8 billion euro of insured losses in the Elbe and the Danube catchment areas, and the general role of insurance in flood risk management in Germany. Besides insurance coverage, governmental funding and public donations played an important role in loss compensation after the August 2002 flood. Therefore, this article also analyzes flood loss compensation, risk awareness, and mitigation in insured and uninsured private households. Insured households received loss compensation earlier. They also showed slightly better risk awareness and mitigation strategies. Appropriate incentives should be combined with flood insurance in order to strengthen future private flood loss mitigation. However, there is some evidence that the surveyed insurance companies do little to encourage precautionary measures. To overcome this problem, flood hazards and mitigation strategies should be better communicated to both insurance companies and property owners.     

Market‐Implied Spread for Earthquake CAT Bonds: Financial Implications of Engineering Decisions

In the event of natural and man‐made disasters, owners of large‐scale infrastructure facilities (assets) need contingency plans to effectively restore the operations within the acceptable timescales. Traditionally, the insurance sector provides the coverage against potential losses. However, there are many problems associated with this traditional approach to risk transfer including counterparty risk and litigation. Recently, a number of innovative risk mitigation methods, termed alternative risk transfer (ART) methods, have been introduced to address these problems. One of the most important ART methods is catastrophe (CAT) bonds. The objective of this article is to develop an integrative model that links engineering design parameters with financial indicators including spread and bond rating. The developed framework is based on a four‐step structural loss model and transformed survival model to determine expected excess returns. We illustrate the framework for a seismically designed bridge using two unique CAT bond contracts. The results show a nonlinear relationship between engineering design parameters and market‐implied spread.     

Insurer Competition in Health Care Markets

The impact of insurer competition on welfare, negotiated provider prices, and premiums in the U.S. private health care industry is theoretically ambiguous. Reduced competition may increase the premiums charged by insurers and their payments made to hospitals. However, it may also strengthen insurers' bargaining leverage when negotiating with hospitals, thereby generating offsetting cost decreases. To understand and measure this trade‐off, we estimate a model of employer‐insurer and hospital‐insurer bargaining over premiums and reimbursements, household demand for insurance, and individual demand for hospitals using detailed California admissions, claims, and enrollment data. We simulate the removal of both large and small insurers from consumers' choice sets. Although consumer welfare decreases and premiums typically increase, we find that premiums can fall upon the removal of a small insurer if an employer imposes effective premium constraints through negotiations with the remaining insurers. We also document substantial heterogeneity in hospital price adjustments upon the removal of an insurer, with renegotiated price increases and decreases of as much as 10% across markets.     

Communicating Earthquake Preparedness: The Influence of Induced Mood,Perceived Risk,and Gain or Loss Frames on Homeowners’ Attitudes Toward General Precautionary Measures for Earthquakes

Despite global efforts to reduce seismic risk, actual preparedness levels remain universally low. Although earthquake‐resistant building design is the most efficient way to decrease potential losses, its application is not a legal requirement across all earthquake‐prone countries and even if, often not strictly enforced. Risk communication encouraging homeowners to take precautionary measures is therefore an important means to enhance a country's earthquake resilience. Our study illustrates that specific interactions of mood, perceived risk, and frame type significantly affect homeowners’ attitudes toward general precautionary measures for earthquakes. The interdependencies of the variables mood, risk information, and frame type were tested in an experimental 2 × 2 × 2 design (N = 156). Only in combination and not on their own, these variables effectively influence attitudes toward general precautionary measures for earthquakes. The control variables gender, “trait anxiety” index, and alteration of perceived risk adjust the effect. Overall, the group with the strongest attitudes toward general precautionary actions for earthquakes are homeowners with induced negative mood who process high‐risk information and gain‐framed messages. However, the conditions comprising induced negative mood, low‐risk information and loss‐frame and induced positive mood, low‐risk information and gain‐framed messages both also significantly influence homeowners’ attitudes toward general precautionary measures for earthquakes. These results mostly confirm previous findings in the field of health communication. For practitioners, our study emphasizes that carefully compiled communication measures are a powerful means to encourage precautionary attitudes among homeowners, especially for those with an elevated perceived risk.     

Catastrophe Risk Models for Evaluating Disaster Risk Reduction Investments in Developing Countries

Major natural disasters in recent years have had high human and economic costs, and triggered record high postdisaster relief from governments and international donors. Given the current economic situation worldwide, selecting the most effective disaster risk reduction (DRR) measures is critical. This is especially the case for low‐ and middle‐income countries, which have suffered disproportionally more economic and human losses from disasters. This article discusses a methodology that makes use of advanced probabilistic catastrophe models to estimate benefits of DRR measures. We apply such newly developed models to generate estimates for hurricane risk on residential structures on the island of St. Lucia, and earthquake risk on residential structures in Istanbul, Turkey, as two illustrative case studies. The costs and economic benefits for selected risk reduction measures are estimated taking account of hazard, exposure, and vulnerability. We conclude by emphasizing the advantages and challenges of catastrophe model‐based cost‐benefit analyses for DRR in developing countries.     

Flood Catastrophe Model for Designing Optimal Flood Insurance Program: Estimating Location‐Specific Premiums in the Netherlands

As flood risks grow worldwide, a well‐designed insurance program engaging various stakeholders becomes a vital instrument in flood risk management. The main challenge concerns the applicability of standard approaches for calculating insurance premiums of rare catastrophic losses. This article focuses on the design of a flood‐loss‐sharing program involving private insurance based on location‐specific exposures. The analysis is guided by a developed integrated catastrophe risk management (ICRM) model consisting of a GIS‐based flood model and a stochastic optimization procedure with respect to location‐specific risk exposures. To achieve the stability and robustness of the program towards floods with various recurrences, the ICRM uses stochastic optimization procedure, which relies on quantile‐related risk functions of a systemic insolvency involving overpayments and underpayments of the stakeholders. Two alternative ways of calculating insurance premiums are compared: the robust derived with the ICRM and the traditional average annual loss approach. The applicability of the proposed model is illustrated in a case study of a Rotterdam area outside the main flood protection system in the Netherlands. Our numerical experiments demonstrate essential advantages of the robust premiums, namely, that they: (1) guarantee the program's solvency under all relevant flood scenarios rather than one average event; (2) establish a tradeoff between the security of the program and the welfare of locations; and (3) decrease the need for other risk transfer and risk reduction measures.     

Cyber Security Risk Management: Public Policy Implications of Correlated Risk,Imperfect Ability to Prove Loss,and Observability of Self‐Protection

The correlated nature of security breach risks, the imperfect ability to prove loss from a breach to an insurer, and the inability of insurers and external agents to observe firms’ self‐protection efforts have posed significant challenges to cyber security risk management. Our analysis finds that a firm invests less than the social optimal levels in self‐protection and in insurance when risks are correlated and the ability to prove loss is imperfect. We find that the appropriate social intervention policy to induce a firm to invest at socially optimal levels depends on whether insurers can verify a firm's self‐protection levels. If self‐protection of a firm is observable to an insurer so that it can design a contract that is contingent on the self‐protection level, then self‐protection and insurance behave as complements. In this case, a social planner can induce a firm to choose the socially optimal self‐protection and insurance levels by offering a subsidy on self‐protection. We also find that providing a subsidy on insurance does not provide a similar inducement to a firm. If self‐protection of a firm is not observable to an insurer, then self‐protection and insurance behave as substitutes. In this case, a social planner should tax the insurance premium to achieve socially optimal results. The results of our analysis hold regardless of whether the insurance market is perfectly competitive or not, implying that solely reforming the currently imperfect insurance market is insufficient to achieve the efficient outcome in cyber security risk management.     

Heston模型下保险公司和再保险公司的投资与再保险博弈

在同时考虑保险公司和再保险公司利益的前提下,研究了保险公司和再保险公司之间的投资与再保险博弈问题。假设保险公司面临的赔付过程由带漂移的布朗运动描述。保险公司可以向再保险公司购买比例再保险,两公司均可以投资于一种无风险资产和一种价格过程服从Heston模型的风险资产,并以加权终端财富的期望效用最大化为目标,利用动态规划原理建立相应的HJB方程并求解,分别得到了保险公司与再保险公司的均衡投资与再保险策略的解析表达,并利用均衡保险市场上再保险合同的供需关系分析了保险产品的定价问题。最后通过数值实例分析了各模型参数对均衡策略的影响。     

An Adaptive Regional Input-Output Model and its Application to the Assessment of the Economic Cost of Katrina

This article proposes a new modeling framework to investigate the consequences of natural disasters and the following reconstruction phase. Based on input-output tables, its originalities are (1) the taking into account of sector production capacities and of both forward and backward propagations within the economic system; and (2) the introduction of adaptive behaviors. The model is used to simulate the response of the economy of Louisiana to the landfall of Katrina. The model is found consistent with available data, and provides two important insights. First, economic processes exacerbate direct losses, and total costs are estimated at $149 billion, for direct losses equal to $107 billion. When exploring the impacts of other possible disasters, it is found that total losses due to a disaster affecting Louisiana increase nonlinearly with respect to direct losses when the latter exceed $50 billion. When direct losses exceed $200 billion, for instance, total losses are twice as large as direct losses. For risk management, therefore, direct losses are insufficient measures of disaster consequences. Second, positive and negative backward propagation mechanisms are essential for the assessment of disaster consequences, and the taking into account of production capacities is necessary to avoid overestimating the positive effects of reconstruction. A systematic sensitivity analysis shows that, among all parameters, the overproduction capacity in the construction sector and the adaptation characteristic time are the most important.     

Equilibria in Health Exchanges: Adverse Selection versus Reclassification Risk

This paper studies regulated health insurance markets known as exchanges, motivated by the increasingly important role they play in both public and private insurance provision. We develop a framework that combines data on health outcomes and insurance plan choices for a population of insured individuals with a model of a competitive insurance exchange to predict outcomes under different exchange designs. We apply this framework to examine the effects of regulations that govern insurers' ability to use health status information in pricing. We investigate the welfare implications of these regulations with an emphasis on two potential sources of inefficiency: (i) adverse selection and (ii) premium reclassification risk. We find substantial adverse selection leading to full unraveling of our simulated exchange, even when age can be priced. While the welfare cost of adverse selection is substantial when health status cannot be priced, that of reclassification risk is five times larger when insurers can price based on some health status information. We investigate several extensions including (i) contract design regulation, (ii) self‐insurance through saving and borrowing, and (iii) insurer risk adjustment transfers.     

Multidimensional Approach for Tsunami Vulnerability Assessment: Framing the Territorial Impacts in Two Municipalities in Portugal

This study presents a new multidimensional methodology for tsunami vulnerability assessment that combines the morphological, structural, social, and tax component of vulnerability. This new approach can be distinguished from previous methodologies that focused primarily on the evaluation of potentially affected buildings and did not use tsunami numerical modeling. The methodology was applied to the Figueira da Foz and Vila do Bispo municipalities in Portugal. For each area, the potential tsunami‐inundated areas were calculated considering the 1755 Lisbon tsunami, which is the greatest disaster caused by natural hazards that ever occurred in Portugal. Furthermore, the four components of the vulnerability were calculated to obtain a composite vulnerability index. This methodology enables us to differentiate the two areas in their vulnerability, highlighting the characteristics of the territory components. This methodology can be a starting point for the creation of a local assessment framework at the municipal scale related to tsunami risk. In addition, the methodology is an important support for the different local stakeholders.     

Risk Perception and Disaster Preparedness in Immigrants and Canadian‐Born Adults: Analysis of a National Survey on Similarities and Differences

Research has documented that immigrants tend to experience more negative consequences from natural disasters compared to native‐born individuals, although research on how immigrants perceive and respond to natural disaster risks is sparse. We investigated how risk perception and disaster preparedness for natural disasters in immigrants compared to Canadian‐born individuals as justifications for culturally‐adapted risk communication and management. To this end, we analyzed the ratings on natural disaster risk perception beliefs and preparedness behaviors from a nationally representative survey (N = 1,089). Factor analyses revealed three underlying psychological dimensions of risk perception: external responsibility for disaster management, self‐preparedness responsibility, and illusiveness of preparedness. Although immigrants and Canadian‐born individuals shared the three‐factor structure, there were differences in the salience of five risk perception beliefs. Despite these differences, immigrants and Canadian‐born individuals were similar in the level of risk perception dimensions and disaster preparedness. Regression analyses revealed self‐preparedness responsibility and external responsibility for disaster management positively predicted disaster preparedness whereas illusiveness of preparedness negatively predicted disaster preparedness in both groups. Our results showed that immigrants’ risk perception and disaster preparedness were comparable to their Canadian‐born counterparts. That is, immigrant status did not necessarily yield differences in risk perception and disaster preparedness. These social groups may benefit from a risk communication and management strategy that addresses these risk perception dimensions to increase disaster preparedness. Given the diversity of the immigrant population, the model remains to be tested by further population segmentation.     

Shadow Insurance

Life insurers use reinsurance to move liabilities from regulated and rated companies that sell policies to shadow reinsurers, which are less regulated and unrated off‐balance‐sheet entities within the same insurance group. U.S. life insurance and annuity liabilities ceded to shadow reinsurers grew from $11 billion in 2002 to $364 billion in 2012. Life insurers using shadow insurance, which capture half of the market share, ceded 25 cents of every dollar insured to shadow reinsurers in 2012, up from 2 cents in 2002. By relaxing capital requirements, shadow insurance could reduce the marginal cost of issuing policies and thereby improve retail market efficiency. However, shadow insurance could also reduce risk‐based capital and increase expected loss for the industry. We model and quantify these effects based on publicly available data and plausible assumptions.     

CORPORATE RISK MANAGEMENT: A MODEL AND ITS APPLICATION

A problem faced by any corporate risk manager, once he has decided what set of properties will be insured, is to choose among the policies offered by potential insurers. This choice usually involves negotiating with insurers over the exact premium and deductible amounts which will characterize the coverage. In this paper, the problem is modeled in terms of expected utility of different forms of coverage. The model enables a risk manager to select among available terms of coverage and, more significantly, provides guidelines for him in negotiating with the insurers to obtain the best possible terms. As an illustration, an application using real data is described.     

An agent-based model for evaluating reforms of the National Flood Insurance Program: A benchmarked model applied to Jamaica Bay,NYC

Coastal flood risk is expected to increase as a result of climate change effects, such as sea level rise, and socioeconomic growth. To support policymakers in making adaptation decisions, accurate flood risk assessments that account for the influence of complex adaptation processes on the developments of risks are essential. In this study, we integrate the dynamic adaptive behavior of homeowners within a flood risk modeling framework. Focusing on building-level adaptation and flood insurance, the agent-based model (DYNAMO) is benchmarked with empirical data for New York City, USA. The model simulates the National Flood Insurance Program (NFIP) and frequently proposed reforms to evaluate their effectiveness. The model is applied to a case study of Jamaica Bay, NY. Our results indicate that risk-based premiums can improve insurance penetration rates and the affordability of insurance compared to the baseline NFIP market structure. While a premium discount for disaster risk reduction incentivizes more homeowners to invest in dry-floodproofing measures, it does not significantly improve affordability. A low interest rate loan for financing risk-mitigation investments improves the uptake and affordability of dry-floodproofing measures. The benchmark and sensitivity analyses demonstrate how the behavioral component of our model matches empirical data and provides insights into the underlying theories and choices that autonomous agents make.     

A Decision Framework for Managing Risk to Airports from Terrorist Attack

This article presents an asset‐level security risk management framework to assist stakeholders of critical assets with allocating limited budgets for enhancing their safety and security against terrorist attack. The proposed framework models the security system of an asset, considers various threat scenarios, and models the sequential decision framework of attackers during the attack. Its novel contributions are the introduction of the notion of partial neutralization of attackers by defenders, estimation of total loss from successful, partially successful, and unsuccessful actions of attackers at various stages of an attack, and inclusion of the effects of these losses on the choices made by terrorists at various stages of the attack. The application of the proposed method is demonstrated in an example dealing with security risk management of a U.S. commercial airport, in which a set of plausible threat scenarios and risk mitigation options are considered. It is found that a combination of providing blast‐resistant cargo containers and a video surveillance system on the airport perimeter fence is the best option based on minimum expected life‐cycle cost considering a 10‐year service period.     

Comparing the Economic Impact of Natural Disasters Generated by Different Input–Output Models: An Application to the 2007 Chehalis River Flood (WA)

Due to the concentration of assets in disaster‐prone zones, changes in risk landscape and in the intensity of natural events, property losses have increased considerably in recent decades. While measuring these stock damages is common practice in the literature, the assessment of economic ripple effects due to business interruption is still limited and available estimates tend to vary significantly across models. This article focuses on the most popular single‐region input–output models for disaster impact evaluation. It starts with the traditional Leontief model and then compares its assumptions and results with more complex methodologies (rebalancing algorithms, the sequential interindustry model, the dynamic inoperability input–output model, and its inventory counterpart). While the estimated losses vary across models, all the figures are based on the same event, the 2007 Chehalis River flood that impacted three rural counties in Washington State. Given that the large majority of floods take place in rural areas, this article gives the practitioner a thorough review of how future events can be assessed and guidance on model selection.     

Planning for disasters

Although in Great Britain the risk of large scale natural disasters is less than in some other countries, there is an increasing risk of the type of catastrophe bred by the complexities of modern industry and by political unrest. The author makes no apology for quoting the Belfast experience at some length.While individual rescue services show a high level of efficiency there appears to be a need to improve the overall co-ordination of the community's response to disaster. Techniques of communication are often inadequate. The importance of rehearsal requires to be stressed.There may be a case for establishing a national committee to review the country's readiness and to give direction and advice.