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Does political risk spur environmental issues in China?

pmid: 35411513
China is one of the largest emitters of carbon dioxide (CO2) emissions in the world. Therefore, it is essential to explore the determinants of CO2 emissions in China. But previous studies so far have not examined how the political risk of this country can affect its CO2 emissions due to the lack of a long-term dataset. Hence, this study aims to capture the effect of political risk on China's CO2 emissions while controlling renewable energy consumption, technological innovation, and the economy's economic growth. We employ Bayer and Hanck cointegration, FMOLS, DOLS, CCR, and frequency domain causality tests to establish the relationship among the variables mentioned above. The outcome of the study reveals that political stability is an important predictor of environmental degradation in China. Moreover, political stability is helpful to lower CO2 emissions, while technological innovation and renewable energy consumption can reduce CO2 emissions, economic growth further deteriorates environmental quality by increasing its carbon emissions. Therefore, the present study recommends that policymakers in China should control political tension in the country to control CO2 emissions and, at the same time, promote technological innovation and renewable energy consumption.
- European University of Lefke Turkey
- Cyprus International University Cyprus
- University of Alberta Canada
- Nişantaşı University Turkey
- Cyprus International University Cyprus
China, Carbon Dioxide, Inventions, Economic Development, Renewable Energy
China, Carbon Dioxide, Inventions, Economic Development, Renewable Energy
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).32 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
