Relationship between FDI inflow, CO2 emissions, renewable energy consumption, and population health quality in China

Frontiers in Environmental Science

Environmental Science

Levente Dimen¹  Florian Marcel Nuță²  Irfan Ullah³  Zhou Yihan³  Yao Junchen³  Si Xuanye³  Chen Yi³  Ziwei Zhang⁴ 

[1] Faculty of Computer Science and Engineering, 1 Decembrie 1918 University of Alba Iulia, Alba Iulia, Romania;Faculty of Economics, Danubius University, Galați, Romania;Reading Academy, Nanjing University of Information Science and Technology, Nanjing, China;School of Economics and Management, Binzhou University, Binzhou, China;

关键词: FDI inflow;    CO emissions;    renewable energy consumption;    health quality;    China;   

DOI  :  10.3389/fenvs.2023.1120970

 received in 2022-12-10, accepted in 2023-01-18,  发布年份 2023

来源: Frontiers

【 摘 要 】

China has received significant foreign direct investment in the last few decades; the FDI inflow could affect the environment, income, and people’s health. Therefore, this paper aims to investigate the relationship between FDI, renewable energy consumption, CO2 emissions, and Population health quality in China for the period 1980–2020. We applied the VECM method for the data analysis for the short and long-run effects of the independent variables. In the short run, FDI and CO2 emissions did not affect health quality in China; however, in the long run, FDI and CO2 emissions improved life expectancy. Renewable energy has both run and long implications for the health quality in China. These results reflect that FDI creates more jobs in China and improves the overall income of Chinese citizens, contributing to more accessible healthcare services in the long run. Therefore, the government should provide incentives to increase the FDI inflow, which uses renewable energy in production. Furthermore, to mitigate the CO2 emissions government should implement a carbon tax on the industries which has substantial CO2 emissions in the country.

【 授权许可】

Unknown   
Copyright © 2023 Zhang, Nuță, Dimen, Ullah, Xuanye, Junchen, Yihan and Yi.