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Influence Mechanism of Industrial Agglomeration and Technological Innovation on Land Granting on Green Total Factor Productivity

Author

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  • Haoran Yang

    (School of Law and Political Science, Nanjing Tech University, Nanjing 211816, China
    School of Public Administration, Nanjing Agricultural University, Nanjing 210095, China)

  • Yaoben Lin

    (School of Law and Political Science, Nanjing Tech University, Nanjing 211816, China)

  • Yang Hu

    (School of Ecology and Environment, Ningxia University, Yinchuan 750021, China
    Breeding Base for State Key Laboratory of Land Degradation and Ecological Restoration in Northwestern China, Yinchuan 750021, China)

  • Xueqing Liu

    (School of Public Administration, Nanjing Agricultural University, Nanjing 210095, China
    Faculty of Sciences, Ghent University, 9000 Ghent, Belgium)

  • Qun Wu

    (School of Public Administration, Nanjing Agricultural University, Nanjing 210095, China)

Abstract

The influence of land granting on green total factor productivity (GTFP) and its mechanisms remain under-explored. Based on dynamic spatial panel data of 30 provincial administrative regions in China from 2007 to 2017, this study attempts to establish the framework of a transmission mechanism among land granting, manufacturing agglomeration and technological innovation, and green total factor productivity, and measures their interactions by the mixed directional distance function and Global Malmquist–Luenberger index model containing undesirable output. Then, this paper empirically estimates the impacts of land granting, industrial agglomeration and technological innovation on green total factor productivity in China with a dynamic spatial mediating effect model. The results show that the development paradigm of China’s industrial green economy is characterized by path dependence, and industrial GTFP has a significant spatial effect. Local governments rely on low-price competition to obtain cost advantages and facilitate the agglomeration of local manufacturing industries, and promote the impact of negotiation on industrial GTFP through the mediating effect of manufacturing agglomeration. There exists a non-linear relationship between manufacturing agglomeration and industrial GTFP. The land acquired through negotiation has a promoting effect on green technology innovation, and will foster industrial GTFP through the intermediary effect of technological innovation. No obvious non-linear relationship is observed between technological innovation and industrial GTFP. The grant of “Tender, Auction and Listing” has no significant influence on the industrial GTFP, and the mediating conduction effect on the GTFP of industry is not established. Industrial structure, government management and infrastructure will significantly promote the improvement of industrial GTFP, while the level of transportation will inhibit the improvement of industrial GTFP. Through administrative intervention in low-production capacity departments, local governments can integrate regional resource endowments, give play to the comparative advantages of industries, and achieve industrial structure upgrades and core competitiveness, which will be conducive to the improvement of industrial GTFP. High-level transportation conditions increase energy consumption and greenhouse gas emissions in transportation operation, which makes no contribution to the enhancement of industrial GTFP.

Suggested Citation

  • Haoran Yang & Yaoben Lin & Yang Hu & Xueqing Liu & Qun Wu, 2022. "Influence Mechanism of Industrial Agglomeration and Technological Innovation on Land Granting on Green Total Factor Productivity," Sustainability, MDPI, vol. 14(6), pages 1-17, March.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:6:p:3331-:d:769597
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    References listed on IDEAS

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    1. Feng, Guohua & Serletis, Apostolos, 2014. "Undesirable outputs and a primal Divisia productivity index based on the directional output distance function," Journal of Econometrics, Elsevier, vol. 183(1), pages 135-146.
    2. Daron Acemoglu, 2002. "Technical Change, Inequality, and the Labor Market," Journal of Economic Literature, American Economic Association, vol. 40(1), pages 7-72, March.
    3. Du, Juan & Chen, Yao & Huang, Ying, 2018. "A Modified Malmquist-Luenberger Productivity Index: Assessing Environmental Productivity Performance in China," European Journal of Operational Research, Elsevier, vol. 269(1), pages 171-187.
    4. Ananda, Jayanath & Hampf, Benjamin, 2015. "Measuring environmentally sensitive productivity growth: An application to the urban water sector," Ecological Economics, Elsevier, vol. 116(C), pages 211-219.
    5. Shiying Hou & Liangrong Song, 2021. "Market Integration and Regional Green Total Factor Productivity: Evidence from China’s Province-Level Data," Sustainability, MDPI, vol. 13(2), pages 1-19, January.
    6. Hampf, Benjamin & Ananda, Jayanath, 2015. "Measuring environmentally sensitive productivity growth: An application to the urban water sector," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 77008, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    7. Li, Ye & Chen, Yiyan, 2021. "Development of an SBM-ML model for the measurement of green total factor productivity: The case of pearl river delta urban agglomeration," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    8. Yining Zhang & Zhong Wu, 2021. "Intelligence and Green Total Factor Productivity Based on China’s Province-Level Manufacturing Data," Sustainability, MDPI, vol. 13(9), pages 1-16, April.
    9. King, Ian & Ferguson, Don, 1993. "Dynamic inefficiency, endogenous growth, and Ponzi games," Journal of Monetary Economics, Elsevier, vol. 32(1), pages 79-104, August.
    10. J. Paul Elhorst, 2014. "Dynamic Spatial Panels: Models, Methods and Inferences," SpringerBriefs in Regional Science, in: Spatial Econometrics, edition 127, chapter 0, pages 95-119, Springer.
    11. Yuegang Song & Feng Hao & Xiazhen Hao & Giray Gozgor, 2021. "Economic Policy Uncertainty, Outward Foreign Direct Investments, and Green Total Factor Productivity: Evidence from Firm-Level Data in China," Sustainability, MDPI, vol. 13(4), pages 1-16, February.
    12. Tinghui Li & Jiehua Ma & Bin Mo, 2021. "Does the Land Market Have an Impact on Green Total Factor Productivity? A Case Study on China," Land, MDPI, vol. 10(6), pages 1-19, June.
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    Cited by:

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    2. Xie, Rui & Yao, Siling & Han, Feng & Zhang, Qi, 2022. "Does misallocation of land resources reduce urban green total factor productivity? An analysis of city-level panel data in China," Land Use Policy, Elsevier, vol. 122(C).
    3. Hao Yao & Xiulin Gu & Qing Yu, 2023. "Impact of Graduate Student Expansion and Innovative Human Capital on Green Total Factor Productivity," Sustainability, MDPI, vol. 15(2), pages 1-15, January.
    4. Fan, Min & Zhou, Yun & Lu, Zhixi & Gao, Sen, 2024. "Fintech's impact on green productivity in China: Role of fossil fuel energy structure, environmental regulations, government expenditure, and R&D investment," Resources Policy, Elsevier, vol. 91(C).
    5. Qingyan Zhu, 2023. "How Will the Relationship between Technological Innovation and Green Total Factor Productivity Change under the Influence of Service-Oriented Upgrading of Industrial Structure?," Sustainability, MDPI, vol. 15(6), pages 1-16, March.
    6. Du, Congcong & Cao, Yunhui & Ling, Yushan & Jin, Zebin & Wang, Shibo & Wang, Daoping, 2024. "Does manufacturing agglomeration promote green productivity growth in China? Fresh evidence from partially linear functional-coefficient models," Energy Economics, Elsevier, vol. 131(C).

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