Assessing the total factor productivity of China’s thermal power industry using a network DEA approach with cross-efficiency

Abstract

In the current tough business environment, improving total factor productivity (TFP) is essential to the survival and development of China’s thermal power industry. On the basis of a network production structure, this research uses a Data Envelopment Analysis (DEA) approach with cross-efficiency to measure the overall and two-stage (power generation and pollutant treatment) TFPs of this industry in China’s 30 provinces. Moreover, the Tobit regression method is introduced to recognize the impact factors on TFP changes. Empirical results reveal that: (1) The overall TFP of the eastern region is the highest (0.6269), and the TFP levels of the central and western regions are relatively close (0.5182 and 0.5378, respectively). (2) Generally, the TFP of the power generation stage is higher than that of the pollutant treatment stage. The mean values of the two stages are 0.5765 and 0.3998, respectively. (3) Economic development and fuel prices are positively associated with the TFP level, whereas technological progress is surprisingly negatively associated. (4) Major policy directions recommended include establishing the power auxiliary service market, implementing the flexibility transformation of small and medium thermal power units, reducing the cross-subsidy to household electricity consumption, removing interregional barriers of electricity transmission, reforming the electricity price system to mitigate the rebound effect, and reducing inefficient investment in pollution treatment retrofit of thermal power plants.

Keywords

• Thermal power industry
• Total factor productivity
• Network DEA
• Cross-efficiency
• Tobit regression