TY - JOUR
T1 - How Does Green Investment Affect Environmental Pollution? Evidence from China
AU - Ren, Siyu
AU - Hao, Yu
AU - Wu, Haitao
N1 - Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer Nature B.V.
PY - 2022/1
Y1 - 2022/1
N2 - China is currently undergoing an important stage wherein it is adjusting its development mode and upgrading its industrial structure. Green investment has become a major driving force through which China can achieve green and sustainable development. Based on the panel data of 30 Chinese provinces for the 2006–2017 period, this paper uses a spatial Durbin model and a dynamic threshold model to empirically analyze the impact of green investment and institutional quality on environmental pollution. The research results show that China’s environmental pollution is significantly characterized by spatial dependence. Local environmental pollution is negatively impacted by green investment, but it is not affected by green investment in neighboring areas; this conclusion remains valid after a series of robustness tests. Green investment can reduce environmental pollution by improving efficiency of energy conservation and emission reduction, expanding technological innovation capabilities and upgrading the industrial structure. The regression results of the dynamic threshold model show that green investment has a nonlinear impact on environmental pollution that is dependent on institutional quality. A higher degree of regional corruption can lead to a gradual decrease in the role of green investment in reducing environmental pollution. However, improvements in marketization and intellectual property protection can increase the positive influence of green investment in reducing environmental pollution. Significant regional heterogeneity is also found in the impact of green investment on environmental pollution, and this impact gradually decreases from the eastern coast to the western region.
AB - China is currently undergoing an important stage wherein it is adjusting its development mode and upgrading its industrial structure. Green investment has become a major driving force through which China can achieve green and sustainable development. Based on the panel data of 30 Chinese provinces for the 2006–2017 period, this paper uses a spatial Durbin model and a dynamic threshold model to empirically analyze the impact of green investment and institutional quality on environmental pollution. The research results show that China’s environmental pollution is significantly characterized by spatial dependence. Local environmental pollution is negatively impacted by green investment, but it is not affected by green investment in neighboring areas; this conclusion remains valid after a series of robustness tests. Green investment can reduce environmental pollution by improving efficiency of energy conservation and emission reduction, expanding technological innovation capabilities and upgrading the industrial structure. The regression results of the dynamic threshold model show that green investment has a nonlinear impact on environmental pollution that is dependent on institutional quality. A higher degree of regional corruption can lead to a gradual decrease in the role of green investment in reducing environmental pollution. However, improvements in marketization and intellectual property protection can increase the positive influence of green investment in reducing environmental pollution. Significant regional heterogeneity is also found in the impact of green investment on environmental pollution, and this impact gradually decreases from the eastern coast to the western region.
KW - Environmental pollution
KW - Green investment
KW - Institutional quality
KW - Spatial Durbin model
UR - http://www.scopus.com/inward/record.url?scp=85118614108&partnerID=8YFLogxK
U2 - 10.1007/s10640-021-00615-4
DO - 10.1007/s10640-021-00615-4
M3 - Article
AN - SCOPUS:85118614108
SN - 0924-6460
VL - 81
SP - 25
EP - 51
JO - Environmental and Resource Economics
JF - Environmental and Resource Economics
IS - 1
ER -