Information Asymmetries and Adverse Selection in the Market for Individual Medical Expense Insurance

Abstract

Introduction Both theoretical and empirical studies have found that adverse selection in an insurance market reduces consumption of insurance by low risk insureds. The theoretical works of Akerlof (1970), Rothschild and Stiglitz (1976), Miyazaki (1977), and Wilson (1977) describe separating equilibria, where high risks purchase a policy with higher coverage than the policy that is purchased by low risks. Miyazaki extends the separating model to allow cross-policy subsidization, resulting in a wealth transfer from low risks to high risks. In addition to a separating equilibrium, Wilson describes a pooling model where high and low risks purchase the same policy so that low risks actually subsidize the insurance purchases of high risks. The empirical evidence generally supports the predictions of these theoretical models. Beliveau (1981) found that adverse selection leads to reduced insurance consumption by low risks in the life insurance market, and Dahlby (1983) and Puelz (1990) found similar results in the automobile insurance market. Browne and Doerpinghaus (1993) found evidence of adverse selection in the market for private supplemental medical insurance for the elderly. In another study, Browne (1992a) found that low risk individuals had less complete coverage in the individual medical insurance market than in the group market, where adverse selection is believed to be less problematic. Additionally, Browne found evidence that low risks subsidize the insurance consumption of high risks in the individual medical insurance market. His results could be explained by the presence of adverse selection or by low risks receiving more coverage in the group market than they would choose if they were purchasing insurance on their own in the individual market. His study does not address whether Miyazaki's separating model or Wilson's pooling model better characterizes the individual medical insurance market. This study extends empirical investigation of the individual medical insurance market and directly tests whether there is reduced consumption of insurance by low risks, whether a separating or pooling model best characterizes the market, and whether cross-subsidization from low to high risks occurs. The Data, the Model and Hypotheses The Data and Potential Tests The data used in the study are from the National Medical Care Expenditure Survey (NMCES) conducted during 1977 and 1978.(1) Only families for which the primary insured had nongroup, individually purchased medical expense insurance and for which complete insurance policy data are available are included for analysis. The data contain extensive demographic information on those insured, including age, sex, marital status, income, and geographic location. In addition, the data contain information on any activity limitations that the insured may have as well as a measure of self-reported health status.(2) In the study, insureds are classified as being low risk if the self-reported health status of family members is excellent, good, or fair, and they are classified as high risk if the self-reported health status of any family member is poor.(3) The health status data were collected ex ante in the first of the five rounds of interviews conducted during the two-year period covered by the study so that health status information does not reflect the insured's revised expectations based on actual claims history during the covered period.(4) Using the demographic data, the activity limitation variable, and the self-reported health status variable allows for not only a test of risk-induced insurance purchase but isolation of the component of risk (self-reported health status) about which insurers are by definition asymmetrically informed.(5) Demographic and health status information from the sample are summarized in Table 1. TABULAR DATA OMITTED Detailed data on the policies purchased by individuals (such as policy premiums, deductible amounts, out-of-pocket maximum limits, and policy coverage limits) allow for measurement of the completeness of coverage provided by each insurance policy. …