TY - JOUR
T1 - Can China's regional carbon market pilots improve power plants' energy efficiency?
AU - Zhang, Ning
AU - Wang, Shuo
N1 - Publisher Copyright:
© 2023 Elsevier B.V.
PY - 2024/1
Y1 - 2024/1
N2 - 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.
AB - 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.
KW - Bootstrapped truncated difference-in-differences
KW - Carbon market
KW - Chinese power plant
KW - Energy efficiency
KW - Meta-frontier SFA
KW - Timing difference-in-differences
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U2 - 10.1016/j.eneco.2023.107262
DO - 10.1016/j.eneco.2023.107262
M3 - Article
AN - SCOPUS:85181097259
SN - 0140-9883
VL - 129
JO - Energy Economics
JF - Energy Economics
M1 - 107262
ER -