This paper investigates the capital and portfolio risk decisions of property-liability insurance firms. A theoretical model based on option pricing theory is developed which predicts a positive relationship between insurer capital and risk, as firms balance these two factors to achieve their desired overall insolvency risk. The implications of the model are then tested empirically using a simultaneous equations methodology. The results support the predictions of the model. They also provide evidence that managerial incentives play a role in determining capital and risk in insurance markets. The findings have significant implications for insurance solvency regulation.

This paper examines the relationship between mergers and acquisitions, efficiency, and scale economies in the US life insurance industry. We estimate cost and revenue efficiency over the period 1988–1995 using data envelopment analysis (DEA). The Malmquist methodology is used to measure changes in efficiency over time. We find that acquired firms achieve greater efficiency gains than firms that have not been involved in mergers or acquisitions. Firms operating with non-decreasing returns to scale (NDRS) and financially vulnerable firms are more likely to be acquisition targets. Overall, mergers and acquisitions in the life insurance industry have had a beneficial effect on efficiency.

Insurance guaranty funds have been adopted in all states to compensate policyholders for losses resulting from insurance company insolvencies. The guaranty funds charge flat premium rates, usually a percentage of premiums. Flat premiums can induce insurers to adopt high-risk strategies, a problem that can be avoided through the use of risk-based premiums. This article develops risk-based premium formulas for three cases: a) an ongoing insurer with stochastic assets and liabilities, b) an ongoing insurer also subject to jumps in liabilities (catastrophes), and c) a policy cohort, where claims eventually run off to zero. Premium estimates are provided and compared with actual guaranty fund assessment rates.

ABSTRACT Insurance guaranty funds have been adopted in all states to compensate policyholders for losses resulting from insurance company insolvencies. The guaranty funds charge flat premium rates, usually a percentage of premiums. Flat premiums can induce insurers to adopt high‐risk strategies, a problem that can be avoided through the use of risk‐based premiums. This article develops risk‐based premium formulas for three cases: a) an ongoing insurer with stochastic assets and liabilities, b) an ongoing insurer also subject to jumps in liabilities (catastrophes), and c) a policy cohort, where claims eventually run off to zero. Premium estimates are provided and compared with actual guaranty fund assessment rates.

This paper analyzes the productivity and efficiency effects of mergers and acquisitions (M&As) in the US property-liability insurance industry during the period 1994–2003 using data envelopment analysis (DEA) and Malmquist productivity indices. We seek to determine whether M&As are value-enhancing, value-neutral, or value-reducing. The analysis examines efficiency and productivity change for acquirers, acquisition targets, and non-M&A firms. We also examine the firm characteristics associated with becoming an acquirer or target through probit analysis. The results provide evidence that M&As in property-liability insurance were value-enhancing. Acquiring firms achieved more revenue efficiency gains than non-acquiring firms, and target firms experienced greater cost and allocative efficiency growth than non-targets. Factors other than efficiency enhancement are important factors in property-liability insurer M&As. Financially vulnerable insurers are significantly more likely to become acquisition targets, consistent with corporate control theory, and we also find evidence that M&As are motivated to achieve diversification. However, there is no evidence that scale economies played an important role in the insurance M&A wave.

This paper develops a model of price determination in insurance markets. Insurance is provided by firms that are subject to default risk. Demand for insurance is inversely related to insurer default risk and is imperfectly price elastic because of information asymmetries and private information in insurance markets. The model predicts that the price of insurance, measured by the ratio of premiums to discounted losses, is inversely related to insurer default risk and that insurers have optimal capital structures. Price may increase or decrease following a loss shock that depletes the insurer's capital, depending on factors such as the effect of the shock on the price elasticity of demand. Empirical tests using firm-level data support the hypothesis that the price of insurance is inversely related to insurer default risk and provide evidence that prices declined in response to the loss shocks of the mid-1980s.Journal of Economic LiteratureClassification Numbers: G22, G32, G33.

We provide evidence on the validity of the it conglomeration hypothesis versus the strategic focus hypothesis for financial institutions using data on U.S. insurance companies. We distinguish between the hypotheses using profit scope economies, which measure the relative efficiency of joint versus specialized production, taking both costs and revenues into account. The results suggest that the conglomeration hypothesis dominates for some types of financial service providers and the strategic focus hypothesis dominates for other types. This may explain the empirical puzzle of why joint producers and specialists both appear to be competitively viable in the long run. Journal of Economic Literature Classification Numbers: G22, G28, G34, L23, L89.

This paper presents a theoretical and empirical analysis of the capacity of the US property–liability insurance industry to finance catastrophic property losses in the 100 billion range. In our theoretical analysis, we show that the sufficient condition for capacity maximization, given a level of total resources in the industry, is for all insurers to hold a net of reinsurance underwriting portfolio which is perfectly correlated with aggregate industry losses. This result leads to a natural definition of industry capacity as the amount of industry resources that are deliverable conditional on an industry loss of a given size. Estimating capacity using insurer financial statement data, we find that the industry could adequately fund a 100 billion event. However, such an event would cause numerous insolvencies and severely destabilize insurance markets.