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<p>With escalating environmental concerns, promoting industrial green development has become a critical policy objective for developing countries. Using panel data from 278 Chinese cities spanning the period 2006–2021, this study evaluates industrial green development efficiency (IGDE) through a super-efficiency slack-based measure (SBM) model with multidimensional inputs and outputs. Moving beyond the traditional linear framework, a spatial autoregressive threshold panel (SARTP) model, which integrates a spatial lagged dependent variable and threshold nonlinearity of explanatory variables, is employed to examine the effects of financial agglomeration (FA) on IGDE across distinct development regimes. The empirical findings reveal that China’s IGDE remains generally low, accompanied by widening regional disparities and growing spatial divergence. In contrast, FA exhibits a relatively stable spatial structure with a declining trend in polarization. Additionally, IGDE exhibits a positive spatial spillover effect and its driving mechanisms vary substantially between the two regimes defined by differing FA levels. Accordingly, local governments should strengthen intercity cooperation to jointly enhance IGDE. Cities with low FA should expand green finance, promote innovation and build green industrial clusters while enforcing stricter environmental standards for foreign investment. Cities with high FA need to improve green financial governance, enhance environmental regulation to prevent capital misallocation and increase investment in green infrastructure to support sustainable industrial transformation.</p>

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Impact of financial agglomeration on industrial green development efficiency: evidence from 278 Chinese cities

  • 期刊论文

  • 发表日期：

    2026年4月10日

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  • Lingxin Bao,
  • Fen Li,
  • Hanrong He,
  • Qiuping Lu,
  • Kunming Li

摘要

With escalating environmental concerns, promoting industrial green development has become a critical policy objective for developing countries. Using panel data from 278 Chinese cities spanning the period 2006–2021, this study evaluates industrial green development efficiency (IGDE) through a super-efficiency slack-based measure (SBM) model with multidimensional inputs and outputs. Moving beyond the traditional linear framework, a spatial autoregressive threshold panel (SARTP) model, which integrates a spatial lagged dependent variable and threshold nonlinearity of explanatory variables, is employed to examine the effects of financial agglomeration (FA) on IGDE across distinct development regimes. The empirical findings reveal that China’s IGDE remains generally low, accompanied by widening regional disparities and growing spatial divergence. In contrast, FA exhibits a relatively stable spatial structure with a declining trend in polarization. Additionally, IGDE exhibits a positive spatial spillover effect and its driving mechanisms vary substantially between the two regimes defined by differing FA levels. Accordingly, local governments should strengthen intercity cooperation to jointly enhance IGDE. Cities with low FA should expand green finance, promote innovation and build green industrial clusters while enforcing stricter environmental standards for foreign investment. Cities with high FA need to improve green financial governance, enhance environmental regulation to prevent capital misallocation and increase investment in green infrastructure to support sustainable industrial transformation.