Introduction Although individuals' insurance decisions have attracted a great deal of theoretical interest from economists, except for Sherden (1984) applied studies related to motor insurance have been rather scarce. This is surprising, because other issues relating to car ownership--taxation, road usage, and the purchasing decision itself--have been extensively examined. Because motor insurance is a compulsory requirement in the United Kingdom under the Road Traffic Acts, it is of interest to examine this particular component of expenditure. It would be highly desirable to have access to microdata relating to expenditure on motor insurance and related products and to have detailed data on insurers. Data of this type are not available in sufficient quantities to enable one to conduct a thorough analysis. At the aggregate level, a longer time series of data can be utilized, and it is of interest to examine the interaction between demand and at this level of aggregation. For example, government regulation applies to the entire market, and so some knowledge of its workings is necessary for the successful implementation of specific economic policies. Forecasting is another area where an aggregate model might prove useful. Despite certain attractions (and the necessity) of working with aggregate data, there are drawbacks. Changes in the microstructure of a model are always ignored in studies using aggregate data. In this case, one feature not captured is the distinction between third-party and comprehensive coverage. An increase in the number of young drivers, for example, is likely to lead to more third-party coverage, a feature not represented in the aggregate model. Aggregate models are usually based on the underlying assumption of a representative agent whose decision problem is captured by a stylized mathematical model. At the empirical level, aggregation issues are typically discounted, and the model is estimated as if the microproperties carry over to the macroparameters. Although this may be unrealistic, data limitations often necessitate such an approach, which does, at least, give some structure and a theoretical basis to the analysis. This article argues that using a representative agent model derived from microeconomic theory to capture the side of the model is unrealistic, mainly because insurers base their pricing behavior on expectations and because firms are inherently heterogeneous. The approach adopted here is intended to be flexible enough for the data to determine the precise form of the supply side. More commonly used models of demand are considered, but only the broad implications of the theory are tested with the data. The empirical work uses the econometric concept of cointegration to analyze the time series properties of the data, leading to a parsimonious error correction model. The objective is to develop an empirical model in which the estimated parameters have desirable statistical properties. The approach is to consider appropriate theoretical models and then to specify empirical models that reflect the important implications of the theory. The U.K. Motor Insurance Market The Supply of Motor Insurance Motor insurance in the United Kingdom is provided mainly by large multiple line insurers and by syndicates of underwriters operating through the Lloyd's of London market. In 1983, for example, there were 315 companies licensed by the Department of Trade and Industry to provide motor insurance in the United Kingdom in addition to 43 Lloyd's syndicates (Department of Trade and Industry, 1984; Rowe and Pitman, 1985). Of the 315 companies, the top twenty (in terms of premium income) accounted for 91 percent of the U.K. motor insurance market in 1983, while the 43 Lloyd's syndicates accounted for 14 percent (British Insurance Association, 1983; Rowe and Pitman, 1985). Although market share is concentrated in the hands of a relatively small number of insurers, there is fierce premium rate competition. …
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