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

长期护理保险对已婚和单身人士的价值

• 批准号: 8892953
• 负责人: MICHAEL D HURD
• 金额: $ 47.41万
• 依托单位: RAND CORPORATION
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-30 至 2018-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8892953
• 关键词: Accounting; Address; Affect; Age; Behavioral; Benchmarking; Cessation of life; Characteristics; Consumer Preferences; Consumption; Data; Data Collection; Data Sources; Dementia; Disabled Persons; Discipline of Nursing; Economics; Evaluation; Event; Future; Goals; Health; Health Services; Healthcare; Heterogeneity; Home environment; Household; Individual; Insurance; Intervention; Interview; Investigation; Lead; Life; Life Cycle Stages; Link; Location; Long-Term Care; Long-Term Care Insurance; Longevity; Marital Status; Marketing; Medicaid; Medicare; Misinformation; Modeling; Nursing Homes; Participant; Penetration; Persons; Policies; Population; Preparation; Price; Probability; Quantitative Evaluations; Records; Research; Resources; Retirement; Risk; Secure; Sex Education; Side; Social Welfare; Specific qualifier value; Spouses; Structural Models; Surveys; Time; Uncertainty; United States; Unmarried person; Variant; base; cost; design; exhaust; health data; improved; models and simulation; mortality; programs; trend

ABSTRACT 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.

摘要 尽管一些个人和家庭在长期护理上花费了大量资金，但 美国长期护理保险(LTCI)市场不发达。这个项目的总体目标是 项目就是要找出原因。这项研究是在支出的生命周期模型的背景下进行的 涵盖与健康有关的部分，如医疗保健的自付支出、护理的长期护理 豪斯和LTCI。我们将使用两种互补的建模方法：第一种方法构建一个丰富的 仿真模型基于对初始条件的经验估计，考虑了 家庭和相关的过渡率(支出、健康、死亡率、长期护理状况)按以下情况分层 婚姻状况、性别和教育程度。这些估计被用来模拟一个人耗尽财富的风险 死前，无论有没有LTCI。财富枯竭的风险对人口的一部分 减去低于某个定义水平的LTCI将提供对LTCI的额外需求的估计 参与者理性行为以最大化其福利的市场。第二种建模方法 将构建和评估已婚和单身人士的动态规划模型。这两款车型都将是 用于模拟不同长期护理保险政策的效果，包括 阶级法案。这项研究结合了健康和退休研究的数据，包括详细的 来自其补充研究消费和活动邮件调查的支出数据，以及新收集的 关于消费者偏好的数据，以更好地了解行为或信息障碍(例如，错误信息 关于进入养老院的概率)到购买LTCI。它还包括对如何 个人关于医疗补助规则和私人保险的信息与个人的私人 关于他们自己需要长期护理以影响人们购买决定的可能性的信息 LTCI。这些结果与对保险特性如何影响市场渗透率的估计相结合。 跨不同人群设计更符合不同市场需求的保险套餐 细分市场，潜在地增加了接受率。