Assessment of a green credit policy aimed at energy-intensive industries in China based on a financial CGE model

  • Jing Yu Liu
  • , Yan Xia
  • , Ying Fan*
  • , Shih Mo Lin
  • , Jie Wu
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

A financial computable general equilibrium model is established to quantitatively calculate the systematic effects of a green credit policy. The punitive high-interest rate is applied to the energy-intensive industries as the green credit policy. This study is focused on the following industries: paper, chemical, cement, and iron and steel. Short-, medium- and long-term scenarios are used to conduct experiments representing the green credit policy. Then, a scenario is simulated wherein a green security policy and the green credit policy are carried out simultaneously. Finally, effects of the green credit policy, a differential electricity price policy, and a raised production tax policy towards the energy-intensive industries are compared. The results show that the green credit policy is effective in suppressing the investments in energy-intensive industries, and it is comparatively less effective in adjusting the industrial production structure. The green security policy helps the green credit policy to reduce the total financing of the target industries, but it brings more negative impacts on the economy. Although the policies of differential electricity prices and raising production taxes support the output structural adjustments, their negative effects are much larger than those of the green credit policy.

Original languageEnglish
Pages (from-to)293-302
Number of pages10
JournalJournal of Cleaner Production
Volume163
DOIs
StatePublished - 1 Oct 2017

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • China
  • Energy-intensive industries
  • Financial CGE model
  • Green credit policy

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