Impact of green credit on industrial structure in China: theoretical mechanism and empirical analysis.,Environmental Science and Pollution Research

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Impact of green credit on industrial structure in China: theoretical mechanism and empirical analysis.
Environmental Science and Pollution Research ( IF 5.8 ) Pub Date : 2020-01-15 , DOI: 10.1007/s11356-020-07717-4
Yiqin Hu _{1,

2} , Hongying Jiang ₁ , Zhangqi Zhong _{1,

2}

Affiliation

Chinese industrial structure is characterized by a large proportion of industries with high energy consumption and high pollution, such as coal, steel, and cement production, and with only a small proportion of green and environment protection industries. In order to optimize this structure, the Chinese government has clearly proposed to upgrade the industrial structure by solving funding problems in the field of environmental protection in the 13th 5-year plan. However, there are no systematic researches on how green credit affects industrial structure and what the corresponding effects are in the current theoretical circle. Therefore, by analyzing current situations of green credit and the industrial structure, this research explores mechanisms concerning the effects of green credit on the industrial structure. Furthermore, this study conducts an empirical research by using a fixed effects model constructed based on sample data from eastern, central, and western China from 2006 to 2016. The results find that (1) green credit mainly influences the industrial structure through capital and funding channels of enterprises. (2) On the whole, China's green credit has significant effects on the transformation of the industrial structure. (3) Influences of green credit in China on the industrial structure are significantly different in each region. In order to effectively upgrade the industrial structure, for the related stakeholders, some effective ways are to establish a sound legal system for green credit, raise depth of understanding on green credit, and implement green credit according to local conditions.

更新日期：2020-01-15

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