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Towards Carbon Neutrality: The Innovation Efficiency of China’s Forestry Green Technology and Its Spatial Spillover Effects

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  • Hangbiao Shang

    (School of Economics and Management, Northeast Forestry University, Harbin 150040, China)

  • Chuwei Yang

    (School of Economics and Management, Northeast Forestry University, Harbin 150040, China)

Abstract

This study evaluates China’s forestry green technology innovation efficiency (FGTIE) using slack-based Data Envelopment Analysis (DEA) based on Chinese provincial panel data from 2011 to 2020. This research endeavours to explore the spatiotemporal dynamics of FGTIE in China and identify its influencing factors. The results demonstrate obvious spatial distribution differences among Chinese FGTIEs, with the southwestern region being relatively stable and the central and southeastern regions being more variable, revealing a general state of clustered development. FGTIE demonstrates a significant spatial correlation. The correlation intensity reveals a ‘W’-shaped, ‘down–up–down’ trend, suggesting that a universal spatial pattern of FGTIE has not yet developed a steady state and that stable spatial aggregation characteristics among provinces are evident. The influencing factors of FGTIE are confirmed to have significant spillover effects. Increases in social security, foreign direct investment and environmental policy stringency will promote efficiency improvements in neighbouring provinces through positive spillover effects, and the economic development level and forestry scale will inhibit efficiency improvements in neighbouring provinces through negative spillover effects.

Suggested Citation

  • Hangbiao Shang & Chuwei Yang, 2022. "Towards Carbon Neutrality: The Innovation Efficiency of China’s Forestry Green Technology and Its Spatial Spillover Effects," Land, MDPI, vol. 11(7), pages 1-18, July.
  • Handle: RePEc:gam:jlands:v:11:y:2022:i:7:p:1081-:d:862934
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    References listed on IDEAS

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    1. Jan Oosterhaven & Lourens Broersma, 2007. "Sector Structure and Cluster Economies: A Decomposition of Regional Labour Productivity," Regional Studies, Taylor & Francis Journals, vol. 41(5), pages 639-659.
    2. Zhang Yiwen & Shashi Kant & Hexing Long, 2020. "Collective Action Dilemma after China’s Forest Tenure Reform: Operationalizing Forest Devolution in a Rapidly Changing Society," Land, MDPI, vol. 9(2), pages 1-18, February.
    3. Shilong Piao & Jingyun Fang & Philippe Ciais & Philippe Peylin & Yao Huang & Stephen Sitch & Tao Wang, 2009. "The carbon balance of terrestrial ecosystems in China," Nature, Nature, vol. 458(7241), pages 1009-1013, April.
    4. Huaming Zhang & Zhishuang Zhu & Yingjun Fan, 2018. "The impact of environmental regulation on the coordinated development of environment and economy in China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 91(2), pages 473-489, March.
    5. Wade, Chrisopher M. & Baker, Justin S. & Latta , Greg & Ohrel, Sara B., 2019. "Evaluating Potential Sources of Aggregation Bias with a Structural Optimization Model of the U.S. Forest Sector," Journal of Forest Economics, now publishers, vol. 34(3-4), pages 337-366, November.
    6. Shilei Wang & Yanbo Qu & Weiying Zhao & Mei Guan & Zongli Ping, 2022. "Evolution and Optimization of Territorial-Space Structure Based on Regional Function Orientation," Land, MDPI, vol. 11(4), pages 1-26, March.
    7. Stephen Broadberry & Bishnupriya Gupta, 2006. "The early modern great divergence: wages, prices and economic development in Europe and Asia, 1500–1800," Economic History Review, Economic History Society, vol. 59(1), pages 2-31, February.
    8. Wolfgang Keller & Arik Levinson, 2002. "Pollution Abatement Costs and Foreign Direct Investment Inflows to U.S. States," The Review of Economics and Statistics, MIT Press, vol. 84(4), pages 691-703, November.
    9. Clausen, Tommy H., 2009. "Do subsidies have positive impacts on R&D and innovation activities at the firm level?," Structural Change and Economic Dynamics, Elsevier, vol. 20(4), pages 239-253, December.
    10. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    11. Xu, Guangyue & Dong, Haoyun & Xu, Zhenci & Bhattarai, Nishan, 2022. "China can reach carbon neutrality before 2050 by improving economic development quality," Energy, Elsevier, vol. 243(C).
    12. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    13. Chen, Yao & Liang, Liang, 2011. "Super-efficiency DEA in the presence of infeasibility: One model approach," European Journal of Operational Research, Elsevier, vol. 213(1), pages 359-360, August.
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