| Abstract |
Previous studies have examined the effect of green credit policy (GCP) on innovation, the environment, and corporate performance. However, few studies have focused on GCP's impact on carbon reduction of high-polluting and high-energy-consuming ("two high") enterprises. Based on millions of unbalanced panel data from the China Taxation Survey database from 2009 to 2016, this study considers the most acclaimed GCP ("Green Credit Guideline" in 2012) as a quasinatural experiment and adopts a difference-in-difference (DID) method along with interactive fixed effects to study the impact of GCP on the carbon emission intensity of "two high" enterprises. In general, we find that GCP significantly reduces the carbon emission intensity of "two high" enterprises. This effect is achieved by optimizing the energy structure, promoting technology transformation, and increasing the intensity of innovation input. A heterogeneous analysis shows that the GCP has a significant suppression effect on "two high" enterprises in eastern and western regions, although its impact is less evident in central areas. Moreover, it shows that non -state-owned, unsubsidized, medium-scale, and large-scale "two high" enterprises are more significantly negatively impacted by the GCP. Finally, to further address the endogeneity problem, the propensity score matching-difference-in-difference (PSM-DID) estimation is conducted and pragmatic policy implications are proposed to improve the development and effectiveness of the GCP. |