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Green fiscal policies, economic growth target constraints and carbon emission efficiency: Evidence from DID and double machine learning

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  • Jiang, Hongli
  • Hu, Wenjie
  • Hou, Yan
  • Jiang, Pengcheng
  • Lu, Na

Abstract

Green fiscal policies are vital for low-carbon transition. Economic growth target (EGT) management plays an important role in economic development. Nevertheless, few literatures have investigated their impact on carbon emission efficiency (CEE) in a unified frame. This study investigates the influence mechanism of green fiscal policies on CEE, the impact of the interplay between green fiscal policies and EGT constraints on CEE, and the role of digital infrastructure, by using staggered DID approach and double machine learning (DML) approach. The results reveal that green fiscal policies enhance CEE through promoting low-carbon technology innovation, improving energy efficiency, and facilitating industrial structure upgrading. The enhancing effect of green fiscal policies on CEE is more pronounced in cities with higher human capital, higher government environmental concern, and lower government fiscal pressure. Hard EGT constraints and top-down amplification of EGT weaken the positive effect of the green fiscal policies on CEE. Furthermore, green fiscal policies and digital infrastructure construction synergistically promote CEE, and digital infrastructure construction mitigates the constraining effect of EGT on the positive relationship between green fiscal policies and CEE. This study provides important insights from the perspective of policy and institutional synergy for governments to promote low-carbon economic development.

Suggested Citation

  • Jiang, Hongli & Hu, Wenjie & Hou, Yan & Jiang, Pengcheng & Lu, Na, 2025. "Green fiscal policies, economic growth target constraints and carbon emission efficiency: Evidence from DID and double machine learning," Energy, Elsevier, vol. 339(C).
  • Handle: RePEc:eee:energy:v:339:y:2025:i:c:s0360544225046031
    DOI: 10.1016/j.energy.2025.138961
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