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 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.

This paper provides new information on the effects of organizational structure on efficiency by analyzing Spanish stock and mutual insurers over the period 1989–1997. We test the efficient structure hypothesis, which predicts that the market will sort organizational forms into market segments where they have comparative advantages, and the expense preference hypothesis, which predicts that mutuals will be less efficient than stocks. Technical, cost, and revenue frontiers are estimated using data envelopment analysis. The results indicate that stocks and mutuals are operating on separate production, cost, and revenue frontiers and thus represent distinct technologies. In cost and revenue efficiency, stocks of all sizes dominate mutuals in the production of stock output vectors, and smaller mutuals dominate stocks in the production of mutual output vectors. Larger mutuals are neither dominated by nor dominant over stocks in the cost and revenue comparisons. Thus, large mutuals appear to be vulnerable to competition from stock insurers in Spain. Overall, the results are consistent with the efficient structure hypothesis but are generally not consistent with the expense preference hypothesis.

This paper conducts an event study analysis of the impact of operational loss events on the market values of banks and insurance companies, using the OpVar database. We focus on financial institutions because of the increased market and regulatory scrutiny of operational losses in these industries. The analysis covers all publicly reported banking and insurance operational risk events affecting publicly traded US institutions from 1978 to 2003 that caused operational losses of at least $10 million – a total of 403 bank events and 89 insurance company events. The results reveal a strong, statistically significant negative stock price reaction to announcements of operational loss events. On average, the market value response is larger for insurers than for banks. Moreover, the market value loss significantly exceeds the amount of the operational loss reported, implying that such losses convey adverse implications about future cash flows. Losses are proportionately larger for institutions with higher Tobin’s Q ratios, implying that operational loss events are more costly in market value terms for firms with strong growth prospects.