OBJECTIVE: This article examines the factors related to an individual's decision to purchase a given amount of long-term care insurance coverage. DATA SOURCE AND STUDY SETTING: Primary data analyses were conducted on an estimation sample of 6,545 individuals who had purchased long-term care (LTC) insurance policies in late 1990 and early 1991, and 1,248 individuals who had been approached by agents but chose not to buy such insurance. Companies contributing the two samples represented 45 percent of total sales during the study year. STUDY DESIGN: A two-stage logit-OLS (ordinary least squares) choice-based sampling model was used to examine the relationship between the expected value of purchased coverage and explanatory variables that included: demographic traits, attitudes, risk premium, nursing home bed supply, and Medicaid program configurations. DATA COLLECTION: Mail surveys were used to collect information about individuals' reasons for purchase, attitudes about long-term care, and demographic characteristics. Through an identification code, information on the policy designs chosen by these individuals was linked to each of the returned mail surveys. The response rate to the survey was about 60 percent. PRINCIPAL FINDINGS: The model explains about 47 percent of the variance in the dependent variable-expected value of policy coverage. Important variables negatively associated with the dependent variable include advancing age, being married, and having less than a college education. Variables positively related include being male, having more income, and having increasing expected LTC costs. Medicaid program configuration also influences the level of benefits purchased: state reimbursement rates and the presence of comprehensive estate recovery programs are both positively related to the expected value of purchased benefits. Finally, as the difference between the premium charged and the actuarially fair premium increases, individuals buy less coverage. CONCLUSIONS: An important finding with implications for policymakers is that changes in Medicaid policy affect the decisions of consumers regarding the acquisition of private LTC policies as well as the level of protection chosen. This is particularly important to states interested in pursuing public-private partnerships in long-term care financing.
OBJECTIVE: This article examines the factors related to an individual's decision to purchase a given amount of long-term care insurance coverage. DATA SOURCE AND STUDY SETTING: Primary data analyses were conducted on an estimation sample of 6,545 individuals who had purchased long-term care (LTC) insurance policies in late 1990 and early 1991, and 1,248 individuals who had been approached by agents but chose not to buy such insurance. Companies contributing the two samples represented 45 percent of total sales during the study year. STUDY DESIGN: A two-stage logit-OLS (ordinary least squares) choice-based sampling model was used to examine the relationship between the expected value of purchased coverage and explanatory variables that included: demographic traits, attitudes, risk premium, nursing home bed supply, and Medicaid program configurations. DATA COLLECTION: Mail surveys were used to collect information about individuals' reasons for purchase, attitudes about long-term care, and demographic characteristics. Through an identification code, information on the policy designs chosen by these individuals was linked to each of the returned mail surveys. The response rate to the survey was about 60 percent. PRINCIPAL FINDINGS: The model explains about 47 percent of the variance in the dependent variable-expected value of policy coverage. Important variables negatively associated with the dependent variable include advancing age, being married, and having less than a college education. Variables positively related include being male, having more income, and having increasing expected LTC costs. Medicaid program configuration also influences the level of benefits purchased: state reimbursement rates and the presence of comprehensive estate recovery programs are both positively related to the expected value of purchased benefits. Finally, as the difference between the premium charged and the actuarially fair premium increases, individuals buy less coverage. CONCLUSIONS: An important finding with implications for policymakers is that changes in Medicaid policy affect the decisions of consumers regarding the acquisition of private LTC policies as well as the level of protection chosen. This is particularly important to states interested in pursuing public-private partnerships in long-term care financing.