Should the government provide insurance for catastrophes?

This paper evaluates the need for a government role in insuring natural and man-made catastrophes in the United States. Although insurance markets have been stressed by major natural catastrophes, such as Hurricane Katrina, government involvement in the market for natural catastrophe insurance should be minimized to avoid crowding-out more efficient private market solutions, such as catastrophe bonds. Instead, government should facilitate the development of the private market by reducing regulatory barriers. The National Flood Insurance Program has failed to cover most property owners exposed to floods and is facing severe financial difficulties. The program needs to be drastically revised or replaced by private market alternatives, such as federal "make available" requirements with a federal reinsurance backstop. A federal role may be appropriate to insure against mega-terrorist events. However, any program should be minimally intrusive and carry a positive premium to avoid crowding-out private market alternatives.Insurance, Government

An Asian Option to the Valuation of Insurance Futures Contracts

While insurers have a variety of instruments readily available to hedge the risk of assets and interest rate sensitive liabilities, until recently reinsurance was the only mechanism for hedging underwriting risk. The insurance futures contracts introduced in December 1992 by the Chicago Board of Trade (CBOT) offer insurers an alternative to reinsurance as a hedging device for under-writing risk. These instruments have the usual features of liquidity, anonymity, and low transaction costs that characterize futures contracts. Unlike reinsurance, hedging through futures has the advantage of reversibility since any position may be closed before the maturity of the futures contract if the overall exposure of the insurer has diminished. Reversing a reinsurance transaction exposes the insurer to relatively high transactions costs as well as additional charges to protect the reinsurer against adverse selection. Because futures contracts are based on losses incurred by a pool of a least 10 insurance companies selected by the Insurance Services Officer, the potential for adverse selection and the accompanying administrative costs are greatly diminished relative to a reinsurance contract. Unlike most futures contracts traded on the CBOT, insurance futures are based on an accumulation of insurance loss payments over a period of time rather than the price of a commodity or asset at the end of a period of time. The classical relationships between the spot price and the futures price do not hold. The fact that the futures price at maturity will reflect a sum of claim payments entails a structural similarity between this contract and an Asian option, for which the underlying asset is an average, i.e., a sum of spot prices (up to a multiplicative constant). Thus, it would be incorrect to price these instruments using standard futures pricing techniques. Geman and Yor (1992, 1993) investigate the exact solution of this problem. The authors apply the Geman-Yor approach to the valuation of the insurance catastrophe futures contracts offered by the CBOT. In their model, the state variable is assumed to be a geometric Brownian motion - the claims process. The payoff on the insurance futures contract is determined by the accumulation or integral of the state variable. The authors believe there is a significant systematic component to insurance losses, especially those involving catastrophes. Insurers should be able to reduce risk by trading futures contracts. In their view the primary reason for limited trading of insurance futures is the lack of information on the loss index. There is very little information to support parameter estimation or to assist traders in forming expectations. In the authors' view, the CBOT's current offerings are unlikely to be successful unless the information problem is solved.

Comparison of Frontier Efficiency Methods: An Application to the U.S. Life Insurance Industry

The objective of this paper is to provide new information on the performance of efficiency estimation methods by applying a wide range of econometric and mathematical programming techniques to a sample of U.S. life insurers. Average efficiencies differ significantly across methods. The efficiency rankings are well-preserved among the econometric methods; but the rankings are less consistent between the econometric and mathematical programming methods and between the data envelopment analysis and free disposal hull techniques. Thus, the choice of estimation method can have a significant effect on the conclusions of an efficiency study. Most of the insurers in the sample display either increasing or decreasing returns to scale, and stock and mutual insurers are found to be equally efficient after controlling for firm size. Key words: Efficiency estimation, stochastic frontiers, data envelopment analysis, free disposal hull, life insurance industry, organizational form.

Productivity and Technical Efficiency in the Italian Insurance Industry

The purpose of this paper is to partially fill the gap in the existing literature by conducting an analysis of technical efficiency and productivity growth in the Italian insurance industry. The analysis makes use of a detailed data base on Italian life and non-life insurance companies over the period 1985-1993, provided by the Associazione Nazaionale fra le Impress Assicurazioni, the association of insurance companies. The authors measure technical efficiency, changes in technical efficiency over time, and technical changes over time for a sample of Italian insurers, and use the results to test hypotheses regarding industrial organization and to analyze trends associated with structural developments in the market. Data development analysis (DEA) is used to estimate product frontiers for each year of the sample. A production frontier gives the minimum inputs required to produce any given output vector. An important reason for conducting the analysis presented is to provide benchmark statistics to facilitate comparisons of efficiency and productivity under the new European regulatory regime when data on more recent periods become available. In addition, the production frontier results are used to test hypotheses about two major issues in industrial organization - the coexistence of alternative product distribution systems, and organizational forms in an industry. The results indicated that technical efficiency in the Italian insurance industry ranged from 70 to 78 percent during the sample period. There was almost no efficiency change over the sample period. However, productivity declined significantly over the sample period, with a cumulative decline of about 25 percent. The decline was attributable almost exclusively to technological regress, implying that insurers needed more inputs to produce their outputs at the end of the sample period that they did at the beginning. Although improvement in both technical efficiency and technical change appear to be needed, the main problem at present appears to be the adverse shift in the production frontier. Although the sources of the technical regress characterizing the Italian industry are not entirely clear, this phenomenon has been observed in at least one other financial services industry that experienced deregulation and growth in new products and distribution systems - the Spanish savings banks. In a dynamically changing environment, many insurers may be adopting new approaches to producing their outputs. This provides more opportunities for firms to make mistakes in the choice of technology, perhaps leading to excessive consumption of inputs even by "best practice" firms. An increase in the complexity of insurance products and markets could have a similar effect. As firms become more experienced at operating in the new environment and the initial false-starts in the adoption of new technology have been corrected, the productivity of the Italian insurance industry can be expected to improve. The increase in competition resulting from deregulation should reinforce this process, as firms that fail to improve are likely to be penalized the by the market.

Analyzing Firm Performance in the Insurance Industry Using Frontier Efficiency Methods

In this introductory chapter to an upcoming book, the authors discuss the two principal types of efficiency frontier methodologies - the econometric (parametric) approach and the mathematical programming (non-parametric) approach. Frontier efficiency methodologies are discussed as useful in a variety of contexts: they can be used for testing economic hypotheses; providing guidance to regulators and policymakers; comparimg economic performance across countries; and informing management of the effects of procedures and strategies adapted by the firm. The econometric approach requires the specification of a production, cost, revenue, or profit function as well as assumptions about error terms. But this methodology is vulnerable to errors in the specification of the functional form or error term. The mathematical programming or linear programming approach avoids this type of error and measures any departure from the frontier as a relative inefficiency. Because each of these methods has advantages and disadvantages, it is recommended to estimate efficiency using more than one method. An important step in efficiency analysis is the definition of inputs and outputs and their prices. Insurer inputs can be classified into three principal groups: labor, business services and materials, and capital. Three principal approaches have been used to measure outputs in the financial services sector: the asset or intermediation approach, the user-cost approach, and the value-added approach. The asset approach treats firms as pure financial intermediaries and would be inappropriate for insurers because they provide other services. The user-cost method determines whether a financial product is an input or output based on its net contribution to the revenues of the firm. This method requires precise data on products, revenues and opportunity costs which are difficult to estimate in insurance. The value-added approach is judged the most appropriate method for studying insurance efficiency. it considers all asset and liability categories to have some output characteristics rather than distinguishing inputs from outputs. In order to measure efficiency in the insurance industry in which outputs are mostly intangible, measurable services must be defined. The three principal services provided by insurance companies are risk pooling and risk-bearing, "real" financial services relating to insured losses, and intermediation. The authors discuss how these services can be measured as outputs in value-added analysis. They then summarize existing efficiency literature.

The Basis Risk of Catastrophic-Loss Index Securities

This paper analyzes the basis risk of catastrophic-loss (CAT) index derivatives, which securitize losses from catastrophic events such as hurricanes and earthquakes. We analyze the hedging effectiveness of these instruments for 255 insurers writing 93 percent of the insured residential property values in Florida, the state most severely affected by exposure to hurricanes. County-level losses are simulated for each insurer using a sophisticated model developed by Applied Insurance Research. We analyze basis risk by measuring the effectiveness of hedge portfolios, consisting of a short position each insurer's own catastrophic losses and a long position in CAT-index call spreads, in reducing insurer loss volatility, value-at-risk, and expected losses above specified thresholds. Two types of loss indices are used -- a statewide index based on insurance losses in four quadrants of the state. The principal finding is that firms in the three largest Florida market-share quartiles can hedge almost as effectively using the intra-state index contracts as they can using contracts that settle on their own losses. Hedging with the statewide contracts is effective only for insurers with the largest market shares and for smaller insurers that are highly diversified throughout the state. The results also support the agency-theoretic hypotheses that mutual insurers are more diversified than stocks and that unaffiliated single firms are more diversified than insurers that are members of groups.

Deregulation, Consolidation, and Efficiency: Evidence From the Spanish Insurance Industry

This paper provides new information on the effects of deregulation and consolidation in financial services markets by analyzing the Spanish insurance industry. The sample period 1989-1998 spans the introduction of the European Union’s Third Generation Insurance Directives, which deregulated the EU insurance market. Deregulation has led to dramatic changes in the Spanish insurance market; the number of firms declined by 35 percent and average firm size increased by 275 percent. We analyze the causes and effects of consolidation using modern frontier efficiency analysis to estimate cost, technical, and allocative efficiency, as well as using Malmquist analysis to measure total factor productivity change. The results show that many small, inefficient, and financially under-performing firms were eliminated from the market due to insolvency or liquidation and that acquirers in the mergers and acquisitions market prefer relatively efficient target firms. As a result, the market experienced significant growth in total factor productivity over the sample period. Consolidation reduced the number of firms operating with increasing returns to scale but also increased the number operating with decreasing returns to scale. Hence, many large firms should focus on improving efficiency rather than on further growth.

The structure, conduct, and regulation of the property-liability insurance industry

Insurance industry

nsolvency Experience, Risk-Based Capital, and Prompt Corrective Action in Property-Liability Insurance

In December 1992, the National Association of Insurance Commissioners (NAIC) adopted a life-health insurer risk-based capital (RBC) formula and model law that became effective with the 1993 annual statement filed in March 1994. In principle, well-designed RBC requirements can help achieve an efficient reduction in the expected costs of insolvencies. They can provide incentives for insurers to operate safely in cases where market incentives are weak due to government mandated guarantees of insurer obligations or asymmetries regarding solvency between insurers and buyers. RBC requirements also may facilitate or encourage prompt corrective action by solvency regulators by helping regulators to identify weak insurers and giving regulators legal authority to intervene when capital falls below specified levels. RBC requirements may force regulators to act in amore timely manner when confronted with external pressure to delay action. However, RBC capital requirements have a number ofpotential limitations. Unavoidable imperfections in any meaningful RBC system will likely distort some insurer decisions in undesirable and unintended ways. RBC requirements by themselves will do little or nothing to help regulators determine when an insurer s reported capital (surplus) is overstated due to understatement of liabilities or overstatement of assets. A well-designed RBC system should minimize costs associated with misclassification of insurers. The system should be able to identify a high proportion of troubled companies early enough to permit regulators to take prompt corrective action and should identify as troubled only a minimal proportion of financially sound insurers. This study analyzes data on solvent and insolvent property-liability insurers to determine whether modifications in the NAIC s RBC formula can improve its ability to predict firms that subsequently fail without substantially increasing the proportion of surviving insurers that are incorrectly predicted to fail. It uses logistic regression models to investigate whether changes in the weight for the major components in the RBC formula and incorporation of information on company size and organizational form improve the tradeoff between Type I error rates (the percentage of insurers that later failed that are incorrectly predicted not to fail) and the Type II error rates (the percentage of surviving insurers that are incorrectly predicted to fail). The data analyzed were for 1989-91 for firms that subsequently failed and for firms that survived through the first nine months of 1993. The authors make four main conclusions. First, less than half of the companies that later failed had RBC ratios within the proposed ranges for regulatory and company action. Second, total and component RBC ratios generally are significantly different for failed and surviving firms based on univariate tests. Third, estimation of multiple logistic regression models of insolvency risk indicated that allowing the weights of the RBC component to vary and including firm size and organizational form variables generally produce a material improvement in the tradeoff between sample Type I and Type II error rates. And, fourth,the RBC models are noticeably less successful in predicting large firm insolvencies than in predicting smaller insolvencies. Regarding the estimated weights in the logistic regression models, a major conclusion is the reserve component of the NAIC risk-based capital formula, which accounts for half of industry risk-based capital, has virtually no predictive power in any of the tests conducted. Given the high costs associated with large failures and the inferior performance of the models in predicting large insolvencies, a higher payoff in terms of reduced insolvency costs is likely to be achieved by developing models that perform better for large firms.