Electricity production, government effectiveness eco-innovation, and public health: Novel findings in the context of sustainability policies

Utilities Policy(2023)

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摘要
In the recent world of catastrophe, scholars and policymakers have empirically examined the influence of various economic and financial instruments on environmental quality. Still, the literature is limited in terms of displaying the factors affecting public health, particularly in case of China. This study aims is to examine the nexus between green electricity, government efficiency, and health issues to draw novel policies. The current study investigates role of electricity production, eco-innovation and institutional factors for overall public health in China using the data from 2000Q1-2021Q4, which is a novel contribution to the existing literature. For empirical analysis, the study employs cointegration analysis, quantile regression and fully modified ordinary least square methods. The empirical result found the validity of the long-run equilibrium relationship. However, the asymmetric distribution of all variables allows this study to use a non-parametric “quantile regression” approach. The empirics depicts that economic growth and renewable electricity production positively influence public health–increase health-related issues. On the contrary, eco-innovation and government effectiveness substantially reduces public health issues. The empirical results are authenticated by the applying three parametric approaches – fully modified ordinary least square, canonical cointegration regression, and dynamic ordinary least square. To explore the causal connection between the variables, this study uses granger causality test – validates the presence of unidirectional and bidirectional causalities between variables. This study suggests enhancement in government effectiveness, expenditure, and eco-innovation to reduce critical health issues in the country.
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关键词
Electricity production,Sustainability policies,Education expenditure,Eco-innovation,Government efficiency,Quantile regression
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