The Value of Long-Term Care Insurance to Married and Single Persons

描述(申请人提供)：尽管一些个人和家庭在长期护理上花费了非常大的金额，但美国的长期护理保险(LTCI)市场并不发达。这个项目的总体目标是找出原因。这项研究是在生命周期支出模型的背景下进行的，该模型涵盖了与健康相关的部分，如自掏腰包的医疗保健支出、养老院的长期护理和长期护理投资。将采用两种互补的建模方法：第一种是基于对初始条件的经验估计，考虑家庭的所有财务资源以及按婚姻状况、性别和教育分层的相关转换率(支出、健康、死亡率、长期护理状况)，构建丰富的模拟模型。这些估计被用来模拟一个人在死前耗尽财富的风险，无论有没有LTCI。LTCI将耗尽财富的风险降低到某个定义水平以下的人口比例，将提供对LTCI的额外需求的估计，在一个市场中，参与者的理性行为是为了最大化他们的福利。第二种建模方法将构建和估计已婚和单身人士的动态规划模型。这两个模型都将被用来模拟不同长期护理保险政策的影响，包括类别法案的规定。这项研究结合了来自健康和退休研究的数据，包括其补充研究、消费和活动邮件调查的详细支出数据，以及新收集的关于消费者偏好的数据，以更好地了解购买LTCI的行为或信息障碍(例如，关于进入养老院的概率的错误信息)。它还包括分析个人关于医疗补助规则和私人保险的信息如何与个人关于自己需要长期护理的可能性的私人信息相互作用，以影响人们购买LTCI的决定。这些结果与对保险特征如何影响细分人群市场渗透率的估计相结合，以设计更符合不同细分市场需求的保险套餐，潜在地提高接受率。 与公共卫生相关：随着寿命的延长和痴呆症发病率的增加，对长期护理的需求将会增加。这项研究显示了人口中的哪些群体将从购买长期护理保险中受益最大，考虑到他们的健康和经济资源。它建议改进政策设计，增加LTCI的使用率，增加人们在不能再独立生活时获得所需帮助的机会，并降低与长期护理相关的财务风险。

DESCRIPTION (provided by applicant): Despite the very large amounts spent by some individuals and households on long-term care, the market for long-term care insurance (LTCI) in the United States is not well developed. The overall goal of this project is to find the reasons why. The research is framed in the context of life-cycle models of spending that cover such health-related components as out-of-pocket spending on health care, long-term care in nursing homes, and LTCI. Two complementary modeling approaches will be employed: the first constructs a rich simulation model based on empirical estimates of initial conditions, taking into account all financial resources of the household and relevant transition rates (spending, health, mortality, long-term care status) stratified by marital status, sex and education. These estimates are used to simulate a person's risk of exhausting wealth before death, with and without LTCI. The fraction of the population for whom the risk of exhausting wealth is reduced by LTCI below some defined level would provide an estimate of the additional demand for LTCI in a market in which the participants behaved rationally to maximize their welfare. The second modeling approach will construct and estimate a dynamic programming model for married and single persons. Both models will be used to simulate the effects of different long-term care insurance policies, including the provisions of the CLASS Act. The research combines data from the Health and Retirement Study, including the detailed spending data from its supplemental study, the Consumption and Activities Mails survey, with newly collected data on consumer preferences to better understand behavioral or informational barriers (e.g., misinformation about the probabilities of nursing-home entry) to the purchase of LTCI. It also includes analyses of how individuals' information about Medicaid rules and private insurance interacts with individuals' private information about their own likelihood of needing long-term care to influence people's decisions to purchase LTCI. These results are combined with estimates of how insurance characteristics affect market penetration across subpopulations to design insurance packages that are better matched to the needs of different market segments, potentially increasing take-up rates. PUBLIC HEALTH RELEVANCE: Increasing longevity accompanied with increased rates of dementia will drive up the need for long-term care. This research shows which groups in the population would benefit most from purchasing long-term care insurance, taking into account their health and their financial resources. It suggests improved policy designs that would increase take up of LTCI, increasing the chances that people will get the help they need when they can no longer live independently and reducing the financial risk related to long-term care.