Analyzing energy innovation-emissions nexus in China: A novel dynamic simulation method

Danish D., ULUCAK R.

ENERGY, cilt.244, 2022 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 244
  • Basım Tarihi: 2022
  • Doi Numarası: 10.1016/j.energy.2021.123010
  • Dergi Adı: ENERGY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Aerospace Database, Applied Science & Technology Source, Aquatic Science & Fisheries Abstracts (ASFA), CAB Abstracts, Communication Abstracts, Computer & Applied Sciences, Environment Index, INSPEC, Metadex, Pollution Abstracts, Public Affairs Index, Veterinary Science Database, Civil Engineering Abstracts
  • Anahtar Kelimeler: Energy innovation, Environmental Kuznets curve, Pollution haven hypotheses, Dynamic ARDL Method, ENVIRONMENTAL KUZNETS CURVE, FOREIGN DIRECT-INVESTMENT, ECONOMIC-GROWTH, CO2 EMISSIONS, EMPIRICAL-EVIDENCE, RENEWABLE ENERGY, TECHNOLOGICAL-INNOVATION, AIR-POLLUTION, TIME-SERIES, CONSUMPTION
  • Erciyes Üniversitesi Adresli: Evet

Özet

Rising climate change and global warming issues highlight the potential role of research and development in the energy sector. By considering this critical role, the current study outlines the impact of energy innovation on carbon dioxide (CO2) emissions for China. For this, the study produces empirical outputs by conducting a newly developed, dynamic autoregressive distributed lag simulation method. The study discloses robust findings that point out a mitigating effect of energy innovation on carbon dioxide emissions and validate the Environmental Kuznets Curve hypothesis. Empirical results highlight the significant role of energy innovation to decrease environmental pollution and inspire policymakers to increase the spending of the public budget on energy research development and demonstration as well as supporting innovative attempts and enterprises. On the other hand, empirical findings do not provide concrete evidence to support the pollution haven hypothesis in China. (C)& nbsp;2022 Elsevier Ltd. All rights reserved.