by Geena Kim, University of Pennsylvania
The high cost of providing long-term care for the elderly has prompted proposals to make private long-term care insurance (LTCI) more affordable. One proposal is to provide tax credits for LTCI purchase. Despite the importance of measuring the potential effect of different levels of tax subsidies on the demand for LTCI, a quantitative assessment does not yet exist.
This dissertation will fill that gap by developing and estimating a stochastic dynamic model of the decision by elderly single (widowed, divorced or never-married) women to purchase private long-term care insurance. The model also incorporates related decisions about Medicaid enrollment, nursing home utilization and asset holdings. The parameters of the model are estimated using data from the Health and Retirement Study for the years 1998 to 2004.
The Health and Retirement Study data provide a rich source of variables, including longitudinal information on the purchase of long-term care insurance, the premium associated with the purchase, the value of household assets, Medicaid enrollment, health outcomes and nursing home utilization. The reported data on LTCI premiums, which have not been exploited before, provide an important source of variation for identifying the effect of tax subsidies on the demand for LTCI.
The dynamic programming decision model is solved numerically and the structural parameters of the model are estimated by the method of simulated maximum likelihood. By recovering the parameters of the model, it is possible to perform counterfactual policy experiments such as providing a LTCI tax subsidy or changing Medicaid eligibility requirements so as to examine Medicaid crowd-out effects. Those experiments will inform policy makers not only about the effect of alternative policies on the purchase of LTCI by elderly single women, but also about the effect of such policies on their health and welfare.