How does China's carbon emissions trading (CET) policy affect the investment of CET-covered enterprises?

The carbon emissions trading (CET) policy realizes the internalization of emission reduction costs of related enterprises, which may affect their investment and management decisions, but has seldom received attention. Therefore, based on the panel data of A-share listed enterprises in eight energy-and‑carbon-intensive industries in China during 2009–2018, this paper employs the difference-in-differences (DID) and the difference-in-differences based propensity score matching methods (PSM-DID) to empirically evaluate the impact of China's CET policy on investment expenditure of CET-covered enterprises in seven pilot regions. The results indicate that: first of all, the investment expenditure of CET-covered enterprises has been reduced by 0.2449% due to China's CET policy during the sample period in general. Second, this impact shows significant industrial and regional heterogeneity. The CET policy reduces the investment expenditure of related enterprises in the building material and steel industries, but not in the other six industries. It also has a reducing impact on the investment expenditure of related enterprises in Beijing and Guangdong, but not in the other five pilot regions. Third, the impact began to appear in the second year of the implementation of CET policy, and it has shown an increasingly strengthening trend with continuous implementation. In addition, the central findings remain robust when we test the parallel trend assumption and apply the difference-in-differences-in-differences (DDD) method to further eliminate the interference of other factors. •The DID and PSM-DID method is used to evaluate the effect of China's CET policy.•China's CET policy has reduced the investment of CET-covered enterprises in general.•The effect of China's CET policy has some industry and regional heterogeneity.•The policy impact began to appear in 2013, and gradually strengthened.•The DDD model is used to further verify the robustness of the research results.