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McCarran-Ferguson and liability insurance

With so many trial lawyers claiming that they're innocent for recent increases in insurance rates, and that the rates actually reflect problems with the insurance industry that can be solved only by ending their antitrust exemption, and so many policymakers apparently listening, it's worth revisiting this 1992 Regulation article by Wharton Professor Patricia M. Danzon:

In fact, it is highly likely that repeal would actually reduce competition, increase the cost of insurance, and reduce the availability for some high-risk coverages, because the threat of antitrust litigation would make insurers unwilling to engage in efficiency-enhancing cooperative activities.

Insurers are in the business of assuming risk. Collective activities that increase information or spread risk among insurers tend to reduce the price of insurance. Collective action is most important for loss forecasting and pricing accuracy. The fair or competitive price of an insurance policy is equal to the present value of expected losses (including claim adjustment or litigation expense), discounted to reflect expected investment income and adjusted for taxes and a normal return on capital. Forecasting expected losses on a pool of policies is relatively simple for stable lines of insurance such as life insurance, where losses across policyholders are uncorrelated and trends over time are stable. For any pool of risks, the predictive accuracy achieved with a given number of policies is lower, the larger the variance of the underlying loss distribution, the higher the correlation between losses for individual policyholders in the pool, and the less certain the estimates of the parameters of the underlying loss distribution.

All of the factors that tend to undermine predictive accuracy for insurers apply more to liability insurance lines than to life insurance and are most severe for general liability, because general liability losses are highly dependent on the trends in tort law. The fact that both the frequency of claims and the size of awards against policyholders are influenced by trends in tort law induces a positive correlation of outcomes for individual risks in the pool. Differences in judicial rulings across jurisdictions and changes over time mean that the parameters of the underlying loss distribution cannot be estimated with precision.

Unpredictability is greater, the longer the duration of the liability. The so-called long tail of liability is more extreme for general liability than for other lines because in most states the statute of limitations for product liability does not begin to run until the discovery of the injury giving rise to the complaint, which may be many years after the insurance policy was written. The average lag between pricing the policy and paying out on claims is around five years for general liability and may be as long as twenty years or more for coverage of long-lived capital equipment and products that may be linked to cancers with very long gestation periods.

In addition to the uncertainty created by a long exposure period during which rules of tort law may undergo dramatic change, general liability is characterized by a huge range in possible losses for any policyholder. Although most policyholders will have no claims in a particular policy year, there is a small chance of a multimillion dollar loss in the event of a severe personal injury with a large pain and suffering award, multiplied manyfold if there are multiple claims from the same product line. Interstate differences in tort regimes and the potential for forum-shopping by plaintiffs exacerbate the uncertainty.

Those characteristics of the underlying loss distribution--high variance, high correlation, and imprecise parameter estimates because of dependence on tort regimes that differ across states and over time--mean that the experience of any single insurer typically gives a very imprecise estimate of expected losses for a given class of insureds in a single state. Precision in loss forecasts can be increased by pooling the loss data of multiple insurers, provided that the losses reflect similar policy provisions. Because the losses for a particular policy year are paid out over many years, the accuracy of loss forecasts requires tracking and analyzing payout patterns (loss development) and trends over time in the underlying loss distribution. Thus, as long as the underlying tort system remains unpredictable, loss forecasts for liability insurance will remain imprecise and there will be gains from using common policy forms and pooling loss experience, including estimation of loss development and trends over a period of years.

Improving precision of loss forecasts is not simply of concern to owners of insurance equity. Insurer risks that are not readily diversifiable must in the long run be reflected in higher prices or reduced coverage availability for policyholders. In the short run shocks to insurer capital that result when realized losses greatly exceed anticipated losses, as occurred in the mid-1980s, lead to shocks in the price and availability of coverage. Imprecision in insurer loss forecasts also contributes to the rate of insurer insolvencies, the costs of which are ultimately borne by policyholders, unsatisfied claimants, or solvent insurers that are assessed to cover payouts through state guaranty funds.



Rafael Mangual
Project Manager,
Legal Policy

Katherine Lazarski
Manhattan Institute


Published by the Manhattan Institute

The Manhattan Insitute's Center for Legal Policy.