期刊
SOCIAL SCIENCE & MEDICINE
卷 265, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.socscimed.2020.113513
关键词
Bayesian-VAR models; Ageing population structure; Health spending; Policy implications; China
The increasing proportion of the population aged 65 or over has generated a global rise of health spending due to higher demand for medical and long-term care services, which has become a growing challenge to the sustainability of public finances across countries. This phenomenon is especially prominent in China, which has experienced accelerated rates of both economic growth and population ageing over the past four decades. Using Bayesian-VAR (B-VAR) models we compute the impulse response functions (IRFs) and the forecast error variance decomposition functions (FEVDs) to empirically examine the dynamic relationships between ageing index, life expectancy, economic growth and health expenditure in China. We compare China with the USA which has distinct trajectories of population structure and economic development to better understand the former's dynamic patterns. We find a pronounced response for both the USA and China of ageing index to life expectancy and of health spending per capita to GDP per capita, while ageing population induces a relatively strong reaction from health expenditure per capita in China. Our results are robust with either nominal or real variables. These findings suggest that, in China, a well-rounded policy accommodating economic, social and health factors is needed to improve the quality of life of the ageing population for a sustainable development of the economy.
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