Modeling Health and Disability Trajectories in Later Life: A Multi-state Approach Using HRS Data

Domenico De Giovanni (), Massimiliano Menzietti (), Marco Pirra () and Fabio Viviano ()
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Domenico De Giovanni: University of Calabria, Department of Economics, Statistics and Finance
Massimiliano Menzietti: University of Salerno, Department of Economics and Statistics
Marco Pirra: University of Calabria, Department of Economics, Statistics and Finance
Fabio Viviano: University of Calabria, Department of Economics, Statistics and Finance

A chapter in New Perspectives in Mathematical and Statistical Methods for Actuarial Sciences and Finance, 2025, pp 108-119 from Springer

Abstract: Abstract This paper develops a continuous-time multi-state Markov model to analyze health and disability transitions in later life using data from the Health and Retirement Study (HRS). We define five distinct states combining health and functional status, allowing for 12 possible transitions including recovery and death. Transition intensities are estimated via a proportional hazards framework, incorporating individual-specific and time-dependent covariates. Model selection is guided by likelihood-based criteria, and results highlight significant heterogeneity by age, gender, and baseline condition. We derive one-year transition probabilities and compute dynamic life expectancies by initial state. Our findings reveal persistent disparities in ageing trajectories and underscore the importance of distinguishing between health and disability dimensions. The model offers practical insights for projecting future health burdens and designing long-term care strategies.

Keywords: Multi-state Markov models; Functional disability; Health conditions; Health and Retirement Study (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-032-05551-4_10

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DOI: 10.1007/978-3-032-05551-4_10

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