| China,as a major energy consuming country in the world,is facing a large pressure to reduce emissions in the coming period.As one of the primary sources of carbon and other pollutant emissions in China,it is particularly important to study the emission reduction behavior of its representative enterprises.Therefore,this paper takes coalfired power plants,a typical representative of the power sector’s emitting enterprises,as the research target,and selects 221 coal-fired power plants located in different regions as a sample to study their production and emission reduction behaviors.This paper firstly portrays a production system that contains both production and emission reduction stages,which are distinct but interrelated.Unlike other studies,this paper considers both the input and output linkages between the two stages,and uses them to measure the technical efficiency and marginal abatement costs of coal-fired power plants in both stages.In terms of method,this paper improves the assumption of estimation based on a global production frontier in the traditional method and adopts a combination of stochastic nonparametric envelopment of data(StoNED)model and convex quantile regression(CQR)model,which can effectively avoid the problem of overestimation of parameter estimates.In addition,a Tobit regression model is constructed using the measured results to analyze factors affecting the technical efficiency at each stage of the power plant and the level of marginal abatement costs.The heterogeneity in terms of installed capacity,environmental regulation intensity and ownership is also taken into account.The empirical results are used to provide reference for the Chinese government to formulate environmental economic policies and for enterprises to actively respond to related policies.According to the efficiency estimation results,there is still much room for improvement in both the abatement efficiency(AE)and the production efficiency(PE)of CFPPs in China.Large power plants perform better both in two stages on average.The huge electricity generation potential can be unlocked by eliminating inefficiencies in two stages.Specifically,the electricity generation potential ratio is greater for large(0.723)and small(0.99)power plants than for medium power plants(0.645).Additionally,a Tobit regression analysis is chosen to recognize the determinants of the inefficiency in the abatement stage and the production stage,respectively.For the two stages,factors such as load and annual operating hours are statistically significant.Furthermore,the heterogeneity analysis of influencing factors indicates that the capacity scale and environmental regulation can enlarge the difference in the impacts of factors on AE and PE scores.The average MAC prices for CO2 and SO2 are estimated to be 367.56 yuan/ton and 662.30 yuan/ton,respectively,indicating that the reduction of such emissions is still expensive.The heterogeneous characteristics show that large CFPPs,centralgovernment-controlled power plants(CGOPPs)and low-regulated CFPPs tend to possess lower CO2 MACs,while the distribution of the MACs of SO2 don’t exhibit obvious group difference except that large and medium power plants show significantly larger SO2 MACs compared with small ones.The regression models imply that both the setting of provincial reduction targets and power generation structure have significant positive impacts on CO2 MACs,while the MACs of SO2 tend to be positively affected by the total abatement cost and the abatement rate of the FGD equipment.Furthermore,we also find that the improvement of CFPPs’ operation indicators like carbon emission intensity,load,and hours can notably decrease the CO2 MACs,but show weak correlations with changes of the SO2 MACs.In addition,the heterogeneous analysis also indicates that the MACs of large CFPPs,CGOPPs,and high-regulated CFPPs are more likely to be affected by these factors.Finally,some appropriate recommendations are provided based on the findings. |
