Scale Efficiency in a Dynamic Model of Canadian Insurance Companies

Abstract

INTRODUCTION The purpose of this research is to investigate scale efficiency in the Canadian Insurance Industry. This is an important issue for the industry, itself, and the government agency charged with the responsibilities of monitoring and regulating insurance companies, i.e., the Office of The Superintendent of Financial Institutions. Its obligations include, in addition to setting rules and conventions that cover a company's day to day operations, the responsibility of approving mergers or any other major change in the structure of ownership in the industry. Since social benefits like lower costs and lower policy premiums that could potentially arise from merger activity are determined, largely, by the scale efficiency of the firms involved, the knowledge of firm-specific scale elasticities is central to the successful implementation of policies that affect the industrial organization of the industry. The Canadian Life Insurance Industry has been the subject of a number of studies. Bernstein and Geehan (1988) provide an overview of the institutional arrangements and a description of how the industry actually functions. Similar material as well as a summary of recent developments including the implications of the 1992 Insurance Companies Act is discussed by Armstrong (1994). Issues of scale and scope have also received considerable attention starting with papers by Halpern and Mathewson (1975), Geehan (1977), Kellner and Mathewson (1983) and most recently by Bernstein (1992). Most of these studies take a similar approach to the problem by assuming that firms are competitive and maximize profits. Details vary depending on the type of data employed but, with the exception of Bernstein, researchers agree that the industry is characterized by constant returns to scale with the possibility of some limited scope economies.(1) Both Kellner and Mathewson and Bernstein utilize data on federally chartered insurance companies. Unlike most studies of the insurance industry, the database employed here allows the researcher to use the number of policies issued by line of insurance as the measure of the line's output. The measurement of output is, in fact, a contentious issue. A number of output definitions have been proposed. Some of the early literature used premium revenue. In spite of the limitations mentioned by Doherty (1981, 391), this and related measures continue to be used. See, for example, Grace and Timme (1990) and Fields and Murphy (1989) who use commission dollars. Yuengert (1993), in response to the use of reserves as a measure of output, recommends additions-to-reserves as a better representative of the flow of new business. Cummins and Zi (1996), following Doherty, advocate incurred benefit payments as the appropriate measure of output along with additions-to-reserves. All of these measures are value measures of output. On the other hand, the measure used in this study is a pure quantity measure. While that may be preferable in principle, there may be problems associated with the heterogeneity generated by differing policy sizes. Consequently, it is not clear at present which measures are most appropriate. In terms of econometric methodology, however, there are improvements that could be made. Even when there are good measures of output available the estimation procedures currently in use do not treat outputs as endogenous variables. This is a serious deficiency because it leaves the firm's most important observable decision unexplained.(2) Furthermore, assuming that factor prices are the same for all firms regardless of geographical location is an unsatisfactory way of dealing with an unobservable variable in a country like Canada in which large regional disparities exist. Finally, none of the Canadian studies exploit panel methods to obtain more efficient parameter estimates or to control for unobservable fixed effects even when there are time-series of cross-sections available. …