Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
Power plants are facing huge climate change and policy risks. This paper identifies the effect of China's carbon emissions trading system (ETS) on plants' energy efficiency. For this purpose, we use a two-step approach. In the first stage, we apply a Meta-frontier Stochastic Frontier Analysis (MSFA) method to estimate the total-factor energy efficiency of China's large coal power plants. In the second stage, we use a bootstrapped truncated difference-in-differences (BT-DID) estimator to investigate the ETS' impact on power plants. Results show that the ETS trading policy significantly improves participating plants' energy efficiency by 0.043, compared to non-ETS plants, while the announcement policy doesn't. Besides, several other methods are introduced to solve the potential autocorrelation and heteroskedasticity problems in the second-stage regression. Further, we unveil that the trading policy improves plants' energy efficiency by reducing coal consumption without affecting power generation. Finally, the heterogeneity analysis proves that China Southern Power Grid, local plants, and plants with high carbon prices benefit more from ETS.