Modeling Multi-State Health Transitions in China: A Generalized Linear Model with Time Trends

ARC Centre of Excellence in Population Ageing Research (CEPAR) Working Paper No. 2017/10

21 Pages Posted: 22 May 2017 Last revised: 28 Aug 2017

See all articles by Katja Hanewald

Katja Hanewald

UNSW Sydney - School of Risk & Actuarial Studies and ARC Centre of Excellence in Population Ageing Research (CEPAR)

Han Li

University of New South Wales - ARC Centre of Excellence in Population Ageing Research (CEPAR)

Adam Wenqiang Shao

University of New South Wales - ARC Centre of Excellence in Population Ageing Research (CEPAR); Milliman

Date Written: May 12, 2017

Abstract

Rapid population aging in China has urged the need to understand health transitions of older Chinese to assist the development of social security programs and financial products aimed at funding long-term care. In this paper, we develop a new flexible approach to modeling health transitions in a multi-state Markov model that allows for age effects, time trends and age-time interactions. The model is implemented in the generalized linear modeling framework. We apply the model to evaluate health transitions of Chinese elderly using individual-level panel data from the Chinese Longitudinal Healthy Longevity Survey for the period 1998–2012. Our results confirm that time trends and age-time interactions are important factors explaining health transitions in addition to the more commonly used age effects. We document that differences in disability and mortality rates continue to persist between urban and rural older Chinese. We also compute life expectancies and healthy life expectancies based on the proposed model as inputs for the development of aged care and financial services for older Chinese.

Keywords: generalized linear models (GLMs), health transitions, multi-state model, long-term care, healthy life expectancy, China

JEL Classification: J11

Suggested Citation

Hanewald, Katja and Li, Han and Shao, Adam Wenqiang, Modeling Multi-State Health Transitions in China: A Generalized Linear Model with Time Trends (May 12, 2017). ARC Centre of Excellence in Population Ageing Research (CEPAR) Working Paper No. 2017/10 . Available at SSRN: https://ssrn.com/abstract=2971798 or http://dx.doi.org/10.2139/ssrn.2971798

Katja Hanewald

UNSW Sydney - School of Risk & Actuarial Studies and ARC Centre of Excellence in Population Ageing Research (CEPAR) ( email )

School of Risk & Actuarial Studies
UNSW Sydney
Sydney, New South Wales NSW 2052
Australia

Han Li (Contact Author)

University of New South Wales - ARC Centre of Excellence in Population Ageing Research (CEPAR) ( email )

Level 6, Central Lobby (enter via East Lobby)
Australian School of Business Building
Sydney, New South Wales NSW 2052
Australia
02 93855294 (Phone)

Adam Wenqiang Shao

University of New South Wales - ARC Centre of Excellence in Population Ageing Research (CEPAR) ( email )

CEPAR, Level 3
East Wing, NICTA Building, UNSW
Sydney, New South Wales NSW 2052
Australia

Milliman ( email )

One Pennsylvania Plaza 38th Floor
New York, NY 10119
United States

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