A multiple state model for the working-age disabled population using cross-sectional data

Poontavika Naka, María del Carmen Boado-Penas*, Gauthier Lanot

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

A multiple state model describes the transitions of the disability risk among the states of active, inactive and dead. Ideally, estimations of transition probabilities and transition intensities rely on longitudinal data; however, most of the national surveys of disability are based on cross-sectional data measuring the disabled status of an individual at one point in time. This paper aims to propose a generic method of the estimation of the expected transition probabilities when the model allows recovery from disability using the UK cross-sectional data. The disability prevalence rates are modelled by taking into consideration the effect of age and time. Under some plausible assumptions concerning the death rates among inactive and active people, the estimated prevalence rates of disability are used to decompose survival probabilities in each state.

Original languageEnglish
Pages (from-to)700-717
Number of pages18
JournalScandinavian Actuarial Journal
Volume2020
Issue number8
DOIs
Publication statusPublished - 13 Sept 2020

Keywords

  • cross-sectional data
  • Disability
  • multiple state model
  • transition probabilities
  • working-age people

ASJC Scopus subject areas

  • Statistics and Probability
  • Economics and Econometrics
  • Statistics, Probability and Uncertainty

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