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The effects of ageing population on health expenditure and economic growth in China: A Bayesian-VAR approach

The effects of ageing population on health expenditure and economic growth in China: A Bayesian-VAR approach

Lopreite, Milena and Zhu, Zhen ORCID: 0000-0003-0258-1454 (2020) The effects of ageing population on health expenditure and economic growth in China: A Bayesian-VAR approach. Social Science & Medicine, 265:113513. ISSN 0277-9536 (doi:https://doi.org/10.1016/j.socscimed.2020.113513)

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Abstract

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.

Item Type: Article
Uncontrolled Keywords: Bayesian-VAR models; ageing population structure; health spending; policy implications; China
Subjects: H Social Sciences > HB Economic Theory
Faculty / Department / Research Group: Faculty of Business
Faculty of Business > Department of International Business & Economics
Faculty of Business > Networks and Urban Systems Centre (NUSC)
Faculty of Business > Networks and Urban Systems Centre (NUSC) > Centre for Business Network Analysis (CBNA)
Last Modified: 27 Jul 2021 09:45
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
Selected for REF2021: None
URI: http://gala.gre.ac.uk/id/eprint/30122

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