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<p>The escalating climate crisis poses profound challenges to sustainable urban development, especially in developing countries. However, the pathways through which climate change (CC) affects green total factor productivity (GTFP) at the municipal level remain insufficiently explored. This study quantifies GTFP across 278 Chinese cities from 2001 to 2022 using a non-desirable-output super-slack-based measure data envelopment analysis (SBM-DEA), which incorporates non-desirable outputs such as pollution and inefficiency in resource use. To assess the spatial and temporal dynamics, we employ a time- and space-fixed Spatial Durbin Model (SDM) that captures both direct and spillover effects of CC on GTFP. Our results reveal a significant U-shaped relationship between CC and GTFP, indicating that moderate levels of climate pressure may hinder productivity, while higher levels might trigger adaptive mechanisms that enhance GTFP. Furthermore, the spatial spillover effects follow an inverted U-shaped pattern: climate change in neighboring cities initially promotes local GTFP but becomes detrimental beyond a certain threshold. Mechanism tests show that industrial structure (IS) and urbanisation level (UL) mediate the CC–GTFP relationship. Moreover, the impacts of CC vary substantially across cities with different fiscal investment capacities (FI), population densities (PD), and economic development levels (GDP). These findings provide new evidence on the complex urban productivity responses to climate stress and offer actionable insights for policymakers aiming to enhance green growth and resilience in the face of accelerating climate risks.</p>

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How does climate change affect green total factor productivity?

  • 期刊论文

  • 发表日期：

    2025年5月26日

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  • Huifang Liu,
  • Weirong Fang,
  • Pengwei Yuan,
  • Xiaoqing Dong

摘要

The escalating climate crisis poses profound challenges to sustainable urban development, especially in developing countries. However, the pathways through which climate change (CC) affects green total factor productivity (GTFP) at the municipal level remain insufficiently explored. This study quantifies GTFP across 278 Chinese cities from 2001 to 2022 using a non-desirable-output super-slack-based measure data envelopment analysis (SBM-DEA), which incorporates non-desirable outputs such as pollution and inefficiency in resource use. To assess the spatial and temporal dynamics, we employ a time- and space-fixed Spatial Durbin Model (SDM) that captures both direct and spillover effects of CC on GTFP. Our results reveal a significant U-shaped relationship between CC and GTFP, indicating that moderate levels of climate pressure may hinder productivity, while higher levels might trigger adaptive mechanisms that enhance GTFP. Furthermore, the spatial spillover effects follow an inverted U-shaped pattern: climate change in neighboring cities initially promotes local GTFP but becomes detrimental beyond a certain threshold. Mechanism tests show that industrial structure (IS) and urbanisation level (UL) mediate the CC–GTFP relationship. Moreover, the impacts of CC vary substantially across cities with different fiscal investment capacities (FI), population densities (PD), and economic development levels (GDP). These findings provide new evidence on the complex urban productivity responses to climate stress and offer actionable insights for policymakers aiming to enhance green growth and resilience in the face of accelerating climate risks.