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Relationships between energy technology patents and CO2 emissions in China: An empirical study

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  • Zhaohua Wang
  • Zhongmin Yang
  • Yixiang Zhang

Abstract

This paper explores dynamic relationships between energy technology patents and CO2 emissions in China during 1985-2009. Based on vector autoregression (VAR), cointegration and vector error correction model (VECM) are adopted to uncover relationships in both long-run and short-run; also dynamic interactions are identified to establish these relationships between variables through impulse response functions and variance decomposition methods. Results show that: (1) the increase of energy technology patents does not reduce CO2 emissions in both long-run and short-run; (2) in the long-run, the increase of energy technology patents helps to reduce CO2 emissions intensity; while it does not for the short term. The present empirical study clearly indicates that Chinese government should attach more importance to investigating and improving energy technology patent system and formulating related energy technology policies for CO2 emissions reduction.

Suggested Citation

  • Zhaohua Wang & Zhongmin Yang & Yixiang Zhang, 2012. "Relationships between energy technology patents and CO2 emissions in China: An empirical study," CEEP-BIT Working Papers 34, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    • Handle: RePEc:biw:wpaper:34
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    Cited by:

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    2. Xiaosan, Zhang & Qingquan, Jiang & Shoukat Iqbal, Khattak & Manzoor, Ahmad & Zia Ur, Rahman, 2021. "Achieving sustainability and energy efficiency goals: Assessing the impact of hydroelectric and renewable electricity generation on carbon dioxide emission in China," Energy Policy, Elsevier, vol. 155(C).
    3. Lin, Boqiang & Li, Zheng, 2022. "Towards world's low carbon development: The role of clean energy," Applied Energy, Elsevier, vol. 307(C).
    4. Tobias Wendler & Daniel Töbelmann & Jutta Günther, 2019. "Natural resources and technology - on the mitigating effect of green tech," Bremen Papers on Economics & Innovation 1905, University of Bremen, Faculty of Business Studies and Economics.
    5. Zhang, Gupeng & Duan, Hongbo & Wang, Shouyang & Zhang, Qianlong, 2018. "Comparative technological advantages between China and developed areas in respect of energy production: Quantitative and qualitative measurements based on patents," Energy, Elsevier, vol. 162(C), pages 1223-1233.
    6. Yıldırım, Durmuş Çağrı & Esen, Ömer & Yıldırım, Seda, 2022. "The nonlinear effects of environmental innovation on energy sector-based carbon dioxide emissions in OECD countries," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    7. Yang, Yuan & Cai, Wenjia & Wang, Can, 2014. "Industrial CO2 intensity, indigenous innovation and R&D spillovers in China’s provinces," Applied Energy, Elsevier, vol. 131(C), pages 117-127.
    8. Wang, Huiqing & Wei, Weixian, 2020. "Coordinating technological progress and environmental regulation in CO2 mitigation: The optimal levels for OECD countries & emerging economies," Energy Economics, Elsevier, vol. 87(C).
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    11. Liang Li & Gang Li & Ilhan Ozturk & Sana Ullah, 2023. "Green innovation and environmental sustainability: Do clean energy investment and education matter?," Energy & Environment, , vol. 34(7), pages 2705-2720, November.
    12. Shobande, Olatunji A. & Ogbeifun, Lawrence, 2023. "Pooling cross-sectional and time series data for estimating causality between technological innovation, affluence and carbon dynamics: A comparative evidence from developed and developing countries," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
    13. Wong, Chan-Yuan & Fatimah Mohamad, Zeeda & Keng, Zi-Xiang & Ariff Azizan, Suzana, 2014. "Examining the patterns of innovation in low carbon energy science and technology: Publications and patents of Asian emerging economies," Energy Policy, Elsevier, vol. 73(C), pages 789-802.

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    More about this item

    Keywords

    CO2 emissions; CO2 emission intensity; energy technology patents; GDP; VAR/VECM;
    All these keywords.

    JEL classification:

    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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