Is Carbon Dioxide (CO 2 ) Emission an Important Factor Affecting Healthcare Expenditure? Evidence from China, 2005–2016

Linhong Chen, Yue Zhuo, Zhiming Xu, Xiaocang Xu and Xin Gao
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Linhong Chen: School of Public Administration, Sichuan University, Chengdu 610065, China
Yue Zhuo: School of Public Administration, Sichuan University, Chengdu 610065, China
Zhiming Xu: Department of Business, ESCP Europe Business School, 75011 Paris, France
Xiaocang Xu: School of Economics, Chongqing Technology and Business University, Chongqing 400067, China
Xin Gao: Business School, Hohai University, Nanjing 211100, China

IJERPH, 2019, vol. 16, issue 20, 1-14

Abstract: As a result of China’s economic growth, air pollution, including carbon dioxide (CO 2 ) emission, has caused serious health problems and accompanying heavy economic burdens on healthcare. Therefore, the effect of carbon dioxide emission on healthcare expenditure (HCE) has attracted the interest of many researchers, most of which have adopted traditional empirical methods, such as ordinary least squares (OLS) or quantile regression (QR), to analyze the issue. This paper, however, attempts to introduce Bayesian quantile regression (BQR) to discuss the relationship between carbon dioxide emission and HCE, based on the longitudinal data of 30 provinces in China (2005–2016). It was found that carbon dioxide emission is, indeed, an important factor affecting healthcare expenditure in China, although its influence is not as great as the income variable. It was also revealed that the effect of carbon dioxide emission on HCE at a higher quantile was much smaller, which indicates that most people are not paying sufficient attention to the correlation between air pollution and healthcare. This study also proves the applicability of Bayesian quantile regression and its ability to offer more valuable information, as compared to traditional empirical tools, thus expanding and deepening research capabilities on the topic.

Keywords: Carbon dioxide (CO 2 ) emission; Income; Health care expenditure (HCE); Government financial expenditure; Bayesian quantile regression (BQR); Traditional empirical methods (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2019
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