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How does industrial agglomeration affect internal structures of green economy in China? An analysis based on a three-hierarchy meta-frontier DEA and systematic GMM approach

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  • Wang, Miao
  • Wu, Yi
  • Zhang, Xinmin
  • Lei, Lei

Abstract

It is well known that industrial agglomeration can affect economic growth. But it is not clear how industrial agglomeration will cause internal structural changes in economic growth. The aim of this study is to examine the internal structural effects of industrial agglomeration on green economy. By considering both industrial heterogeneity and regional heterogeneity, a three hierarchy meta-frontier DEA and global Malmquist index (GM) were constructed to measure green total factor productivity (GTFP) and decompose GTFP into technological change, industrial structure efficiency, regional coordinated development efficiency, scale efficiency, and resource allocation efficiency. Subsequently, a systematic GMM model was developed to investigate the nonlinear impact of industrial agglomeration on GTFP and its internal structural factors, thereby elucidating the mechanisms and influences of industrial agglomeration on GTFP. Results show that at the national level, there was an overall inverted U-shaped effect of industrial agglomeration on GTFP, which is mainly realized by inducing technological changes. However, at the regional level, the impacts of industrial agglomeration on GTFP showed distinct spatial heterogeneity. In the central and western regions, industrial agglomeration promoted the growth of GTFP by enhancing the efficiency of regional coordinated development, whereas this is not the case in the eastern region.

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  • Wang, Miao & Wu, Yi & Zhang, Xinmin & Lei, Lei, 2024. "How does industrial agglomeration affect internal structures of green economy in China? An analysis based on a three-hierarchy meta-frontier DEA and systematic GMM approach," Technological Forecasting and Social Change, Elsevier, vol. 206(C).
    • Handle: RePEc:eee:tefoso:v:206:y:2024:i:c:s0040162524003561
    DOI: 10.1016/j.techfore.2024.123560
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