TY - JOUR
T1 - Environmental credit constraints and pollution reduction
T2 - Evidence from China's blacklisting system for environmental fraud
AU - Di, Danyang
AU - Li, Guoxiang
AU - Shen, Zhiyang
AU - Song, Malin
AU - Vardanyan, Michael
N1 - Publisher Copyright:
© 2023 Elsevier B.V.
PY - 2023/8
Y1 - 2023/8
N2 - Environmental performance-based credit mechanisms are among the tools policymakers can use to influence the polluting firms' behavior. In this study, we use China's blacklisting system for environmental fraud as a quasi-natural experiment to analyze the pollution-reducing effect of environmental credit constraints (ECCs). We operationalize our approach using a sample of 287 Chinese cities for the period 2008–2018 and find that ECCs help reduce emission intensity—a result that is both statistically significant and robust. Furthermore, our analysis suggests that ECCs can motivate producers to increase investment in technological innovation and optimize their factor allocation structure to improve green total factor productivity, thereby helping reduce their environmental impact. We demonstrate that the ECC-based schemes could be particularly effective in helping reduce pollution in regions with high enterprise credit dependence and relatively heavy presence of the manufacturing industry. In addition, these pollution-reducing effects are significant in regions with relatively strict environmental regulation. Hence, we argue that environmental credit systems could help policymakers provide polluting companies with additional incentives to voluntarily cut their emission levels and thus offer opportunities for diversifying the strategies policymakers can use to mitigate adverse environmental impacts.
AB - Environmental performance-based credit mechanisms are among the tools policymakers can use to influence the polluting firms' behavior. In this study, we use China's blacklisting system for environmental fraud as a quasi-natural experiment to analyze the pollution-reducing effect of environmental credit constraints (ECCs). We operationalize our approach using a sample of 287 Chinese cities for the period 2008–2018 and find that ECCs help reduce emission intensity—a result that is both statistically significant and robust. Furthermore, our analysis suggests that ECCs can motivate producers to increase investment in technological innovation and optimize their factor allocation structure to improve green total factor productivity, thereby helping reduce their environmental impact. We demonstrate that the ECC-based schemes could be particularly effective in helping reduce pollution in regions with high enterprise credit dependence and relatively heavy presence of the manufacturing industry. In addition, these pollution-reducing effects are significant in regions with relatively strict environmental regulation. Hence, we argue that environmental credit systems could help policymakers provide polluting companies with additional incentives to voluntarily cut their emission levels and thus offer opportunities for diversifying the strategies policymakers can use to mitigate adverse environmental impacts.
KW - Credit constraints
KW - Environmental regulation
KW - Green technology innovation
KW - Pollution emissions
UR - http://www.scopus.com/inward/record.url?scp=85154623504&partnerID=8YFLogxK
U2 - 10.1016/j.ecolecon.2023.107870
DO - 10.1016/j.ecolecon.2023.107870
M3 - Article
AN - SCOPUS:85154623504
SN - 0921-8009
VL - 210
JO - Ecological Economics
JF - Ecological Economics
M1 - 107870
ER -