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Regulating environmental pollution through natural resources and technology innovation: Revisiting the environment Kuznet curve in China through quantile-based ARDL estimations

handle: 11541.2/35011
Refereed/Peer-reviewed The dark side of the consumption of Natural Resources (NTR) is the carbon dioxide emissions (CO2) resulting from the extraction of NTR as well as the increasing level of consumption within the economy. Besides, the massive expansion and growth of the Chinese economy have also meant its CO2 is at an all-time high, thus making China one of the leading contributors to global warming. Hence the current study fills a knowledge vacuum by analyzing the relationships governing NTR and technological innovation (TIN) in countering the environmental damage due to CO2, by revisiting the EKC in the Chinese context through “Quantile Autoregressive Distributed Lag” (QARDL). The results validate the EKC where NTR consumption worsens the environment further; however, TIN is a potential solution in countering CO2. In accordance with the findings, it is recommended that government institutions need to ensure the preservation of NTR without conceding the economic benefits and prosperity.
- Vinh University Viet Nam
- Asian University Taiwan
- Beijing Institute of Technology China (People's Republic of)
- China Medical University Hospital Taiwan
- Hang Seng Management College China (People's Republic of)
China, QARDL, rule of law, technology innovation, pollution, natural resources
China, QARDL, rule of law, technology innovation, pollution, natural resources
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).10 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).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
