THE EFFECT OF FIRM TRAITS ON LONG-TERM CARE INSURANCE PRICING

ABSTRACT Financing long-term care is an issue of concern to many Americans, yet private long-term care insurance product sales have experienced slow growth. Pricing problems may in part explain this phenomenon. This study provides the first empirical evidence on pricing in the long-term care insurance market and analyzes the relationship between insurer operating characteristics and premium. The results suggest that prices vary across firms due to size, organizational form, default risk, and tenure in the market, but not due to differences in distribution system. The evidence is also consistent with significant price differences due to contract design variables that control moral hazard and adverse selection. INTRODUCTION Financing long-term care has become an issue of increasing concern to many Americans. Long-term care includes a range of social and medical services needed by individuals unable to care for themselves due to physical or cognitive disability. Care may be provided in nursing homes, at home, in other residential facilities, or at adult day care centers for the elderly or disabled. People of all ages use long-term care, but the need is especially acute for the elderly (i.e., those over age 65). Private long-term care insurance is one solution to the financing issue. However, this product has experienced relatively slow growth in recent years, possibly because price and policy characteristics are not sufficiently appealing to generate strong sales. This study analyzes the relationship between insurer operating characteristics and the price of insurance. In particular, the importance of insurer organizational form, size, financial strength, distribution system, and tenure in the market is documented and analyzed. M oral hazard and adverse selection effects with respect to particular policy design features are also examined. This article begins with a review of the context in which long-term care insurance is sold. Next, the research methods used in the study are discussed, and the data set and the expected results are described. The empirical results are then reported, followed by a discussion of the major conclusions and implications of the study. THE LONG-TERM CARE INSURANCE MARKET Concern about long-term care financing has increased for several reasons. First, demographic trends show that the elderly are the fastest growing age group in the nation. Figure 1 depicts past and projected growth trends for the elderly to the year 2020. Kemper and Murtaugh (1991) estimate that 43 percent of the elderly will use nursing home care, that over half of those in nursing homes will stay for at least one year, and that 20 percent will remain five years or longer. The concern about paying for nursing home care will become more pronounced in the future, as the proportion of younger persons relative to older persons decreases, thereby making family care less feasible for many. Extended life expectancies, due to advances in medical science and increasingly healthy lifestyles, further increase the likelihood that long-term care outside of the family unit will be needed. Concern about long-term care financing arises not only from increasing utilization of services, but from the high cost of such services. Typical nursing home costs range from $35,000 to $65,000 or more per year, and costs are rising faster than inflation. Community-based residential care or home care is less expensive, but can still be prohibitive for middle- and-lower-income families. In 1995, national aggregate long-term care expenditures exceeded $100 billion annually, of which 44 percent was paid by Medicaid, 16 percent by Medicare, and 30 percent by individuals and their families. Private long-term care insurance represented only about 2 percent of benefit payments. [1] Reductions in state Medicaid funding are likely to have a significant impact on the financing of long-term care in the future, and another public sector solution to the problem of funding long-term care is unlikely, given efforts to control federal spending. …