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A health insurance pricing model based on prevalence rates: Application to critical illness insurance |
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| Institution: | 1. Department of Economics and Management, University of Florence, Italy;2. Department of Statistics, Sapienza University of Rome, Italy;1. Brigham Young University, USA;2. University of California, Santa Cruz, USA;3. University of Connecticut, USA;1. University of Technology, Sydney, The Finance Discipline Group, UTS Business School, PO Box 123, Broadway, NSW, 2007, Australia;2. Auckland University of Technology, Department of Finance, Private Bag 92006, 1142 Auckland, New Zealand;3. Università degli Studi di Padova, Dipartimento di Matematica, Via Trieste 63, Padova, Italy;4. Devinci Finance Lab, Pôle Universitaire Léonard de Vinci, 92916 Paris La Défense Cedex, France;5. Quanta Finanza srl, Via Cappuccina 40, Mestre (Venezia), Italy;1. Department of Mathematics, University of Michigan, Ann Arbor, MI, 48109, USA;2. Department of Mathematics, York University, Toronto, Ontario, Canada M3J 1P3;2. Daman, National Health Insurance Company, Abu Dhabi, United Arab Emirates |
| Abstract: | The Italian health insurance market is currently undersized. The paucity of assured data and the discontinuous statistical surveys carried out by the National Institute of Statistics (ISTAT) represent one of the main obstacles to the insurance market development. The paper sets forth a parametric model to estimate technical basis for health insurance policies when data are limited and only aggregated information on mortality and morbidity is available. The probabilistic framework is based on a multiple state continuous and time inhomogeneous Markov model. We provide an estimate of transition intensities from the healthy state to the sickness state when only prevalence rates of sickness are available, according to an extension and modification of the methodology proposed in Olivieri (1996) for Long Term Care insurance. We assume that mortality intensity of both healthy and sick lives is modelled by two independent Gompertz–Makeham models. |
| Keywords: | Multiple state models Transition intensities Gompertz–Makeham Prevalence rates Critical illness insurance |
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