Modeling Disability in Long-Term Care Insurance

Pritchard, D

doi:10.1080/10920277.2006.10597413

Cited by 37 publications

(23 citation statements)

References 14 publications

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“…We then build a model assuming the transitions between health and disability states follow a continuous‐time Markov process that varies with age and gender, similar to the one described by Robinson () and used by Brown and Finkelstein (, ) who study transitions in and out of disability states for purposes of estimating the costs of long‐term care insurance. A related literature that studies disability dynamics and active life expectancy that relies on estimating disability transition rates by applying Markov models to panel data has also emerged (e.g., Land, Guralnik, and Blazer, ; Stallard and Yee, ; Laditka and Wolf, ; Pritchard, )…”

Section: Methodsmentioning

confidence: 99%

The Life Care Annuity: A New Empirical Examination of an Insurance Innovation That Addresses Problems in the Markets for Life Annuities and Long‐Term Care Insurance

Brown¹,

Warshawsky²

2013

J of Risk & Insurance

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The life care annuity-the integration of the life annuity with long-term care insurance coverage-is intended to deal with major problems in the currently separate markets for life annuities and long-term care insurance. The integration would allow the inclusion of most of the population currently rejected by underwriting-those in poor health or lifestyles but who would not go immediately into long-term care claim-who also have lower life expectancies. We make use of the Health and Retirement Study, on individuals in retirement and their disability incidence, exploiting the panel nature of the survey to estimate transition probabilities in and out of disability states according to numerous demographic and health characteristics. This allows for analysis of disability and mortality risk across a number of dimensions. We find that different risk groups at age 65 have similar projected long-term care expenses, but that the level-periodicpremium structure of most long-term care insurance policies creates incentives for individuals to separate into different risk pools according to observable characteristics, justifying the underwriting observed on the market. Yet we also find that gender-rated life care annuities could succeed in pooling risks currently segmented in the market for long-term care insurance, thus qualifying individuals at or near retirement for permanent long-term care insurance coverage who do not currently qualify, and allowing for life annuities to be purchased more cheaply than in the stand-alone annuity market now subject to adverse selection. Jason Brown is at the U.S. Treasury Department, Office of Economic Policy. Mark Warshawsky is at Towers Watson, Corporate Research and Innovation Center. Jason Brown can be contacted via e-mail: jason.brown@treasury.gov. Our thanks to Valeria D'Amato, Luca Guerrieri, Ilyana Kuziemko, Olivia Mitchell, and participants at a 2010 Wharton School seminar and at a session at the 2011 Longevity Risk conference in Frankfurt for helpful comments and suggestions. Any opinions expressed are those of the authors alone.

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Section: Methodsmentioning

confidence: 99%

The Life Care Annuity: A New Empirical Examination of an Insurance Innovation That Addresses Problems in the Markets for Life Annuities and Long‐Term Care Insurance

Brown¹,

Warshawsky²

2013

J of Risk & Insurance

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“…Inclusion of recoveries adds complexity to the model. However, as mentioned above, Pritchard (2006) found that excluding recoveries results in overstating the cost of benefits. For this reason, in our model it is possible to recover from functional disabilities.…”

Section: Model Of Old Agementioning

confidence: 98%

“…3.7.1. Functional ability transition intensities are taken to be those derived by Akodu (2007), who fitted functions to using the penalised least squares method of Pritchard (2006). This is the only study that calculates age-dependent incidence of functional ability for a UK population.…”

Section: Model Of Old Agementioning

confidence: 99%

Adverse selection in a start-up long-term care insurance market

Adams¹,

Donnelly²,

Macdonald³

2014

Br. Actuar. J.

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Common to all previous studies assessing the cost of adverse selection associated with genetics has been the assumption of an established market, i.e., the adverse selectors have been buying insurance at that rate for such a period that premiums have already absorbed it. Their analyses involve calculating the percentage difference between premiums in a market with adverse selection and one without adverse selection. They can shed no light on how the premiums would get to this stage over time and what losses might be incurred in the process. We take the modelling further by outlining a multiple state Markov model for a start-up market of long-term care insurance. With this model, we explicitly show the progression of adverse selection costs using the development of information that an insurer would gain from analysing the claims history of its existing business, to reprice premiums for new business. To overcome the complication of insurance benefit amounts, which depend on the value of previous benefit payments, we develop a simulation approach of estimating the expected present values of insurance benefits and premium payments. In applying our modelling to a UK setting, we find genetic testing of the apolipoprotein E gene (whose variants can cause a high risk of developing dementia) to be of a relatively small impact compared with our hypothetical state of intermediate dementia progression. Furthermore, we find that the government’s cap on care costs has little effect on adverse selection costs as it benefits only a small proportion of people.

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“…Pritchard (2006) constructs a continuous-time, multiple-state model using the U.S. National Long-Term Care Study from 1982, 1984, 1989 to describe the disability process of aging and suggests adapting this model to price specific LTCI products. Meiners and Trapnell (1984) use traditional actuarial methods of the era (specified in an unpublished report) to provide premium estimates at the intersections of several important variables for prototype LTCI policies using data from the 1976 National Nursing Home Discharge Survey.…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

Predictive Modeling in Long-Term Care Insurance

Lally

Hartman

2016

North American Actuarial Journal

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The accurate prediction of long-term care insurance (LTCI) mortality, lapse, and claim rates is essential when making informed pricing and risk management decisions. Unfortunately, academic literature on the subject is sparse and industry practice is limited by software and time constraints. In this article, we review current LTCI industry modeling methodology, which is typically Poisson regression with covariate banding/modification and stepwise variable selection. We test the claim that covariate banding improves predictive accuracy, examine the potential downfalls of stepwise selection, and contend that the assumptions required for Poisson regression are not appropriate for LTCI data. We propose several alternative models specifically tailored toward count responses with an excess of zeros and overdispersion. Using data from a large LTCI provider, we evaluate the predictive capacity of random forests and generalized linear and additive models with zero-inflated Poisson, negative binomial, and Tweedie errors. These alternatives are compared to previously developed Poisson regression models.Our study confirms that variable modification is unnecessary at best and automatic stepwise model selection is dangerous. After demonstrating severe overprediction of LTCI mortality and lapse rates under the Poisson assumption, we show that a Tweedie GLM enables much more accurate predictions. Our Tweedie regression models improve average predictive accuracy (measured by several prediction error statistics) over Poisson regression models by as much as four times for mortality rates and 17 times for lapse rates.

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Modeling Disability in Long-Term Care Insurance

Cited by 37 publications

References 14 publications

The Life Care Annuity: A New Empirical Examination of an Insurance Innovation That Addresses Problems in the Markets for Life Annuities and Long‐Term Care Insurance

The Life Care Annuity: A New Empirical Examination of an Insurance Innovation That Addresses Problems in the Markets for Life Annuities and Long‐Term Care Insurance

Adverse selection in a start-up long-term care insurance market

Predictive Modeling in Long-Term Care Insurance

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