The impact of environmental pollution on public health expenditure: dynamic panel analysis based on Chinese provincial data

被引:0
|
作者
Yu Hao
Shuang Liu
Zhi-Nan Lu
Junbing Huang
Mingyuan Zhao
机构
[1] Beijing Institute of Technology,Center for Energy and Environmental Policy Research
[2] Beijing Institute of Technology,School of Management and Economics
[3] Sustainable Development Research Institute for Economy and Society of Beijing,Thrombosis and Vascular Medicine Center, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital
[4] Collaborative Innovation Center of Electric Vehicles in Beijing,Cardiology Department
[5] Beijing Key Lab of Energy Economics and Environmental Management,School of Economics
[6] Chinese Academy of Medical Sciences and Peking Union Medical College,undefined
[7] Centro Hospitalar Conde de São Januário,undefined
[8] Southwestern University of Finance and Economics,undefined
关键词
Environmental pollution; Public medical expenditure; GMM model; China;
D O I
暂无
中图分类号
学科分类号
摘要
In recent years, along with rapid economic growth, China’s environmental problems have become increasingly prominent. At the same time, the level of China’s pollution has been growing rapidly, which has caused huge damages to the residents’ health. In this regard, the public health expenditure ballooned as the environmental quality deteriorated in China. In this study, the effect of environmental pollution on residents’ health expenditure is empirically investigated by employing the first-order difference generalized method of moments (GMM) method to control for potential endogeneity. Using a panel data of Chinese provinces for the period of 1998–2015, this study found that the environmental pollution (represented by SO2 and soot emissions) would indeed lead to the increase in the medical expenses of Chinese residents. At the current stage of economic development, an increase in SO2 and soot emissions per capita would push up the public health expenditure per capita significantly. The estimation results are quite robust for different types of regression specifications and different combinations of control variables. Some social and economic variables such as public services and education may also have remarkable influences on residential medical expenses through different channels.
引用
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页码:18853 / 18865
页数:12
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