Abstract
The new round of electricity market reform in 2015 completely changed the profit pattern of power grid enterprises (PGEs) in China, and directly affected their investment plans. Under the new electricity market reform (NEMR), the government regulatory authority made higher requirements for the investment efficiency of PGEs, and the investment effectiveness hence became the core criterion for investment plans. Therefore, the PGEs are now attaching great importance to the investment efficiency. According to their geographical differences, this paper divides the Chinese provincial PGEs into three groups, namely eastern, central and western region enterprises. Based on the NEMR, we developed an evaluation system of investment efficiency for the above-mentioned enterprises. Moreover, this paper selects GDP per capita, electricity consumption in industry, and electrification rate as external environment variables, and conducts an empirical research on the investment efficiency of 31 provincial PGEs in China in 2017. The analysis reveals that three external environment variables have considerable impacts on the investment efficiency. Though the increase of GDP per capita and electricity consumption in industry are not conducive to improving investment efficiency, the advancement of electrification plays a positive role in its improvement. And from the real efficiency results, Tianjin, Liaoning, Jiangsu, and Fujian have relatively higher investment efficiency, while Henan, Shandong, and Shanghai exhibit lower investment efficiency. By comparing the investment efficiency of PGEs in the first and third stage, conclusions can be drawn that in the first stage the investment efficiency of PGEs was overestimated, and the inefficient investments prevailed some provincial PGEs, which caused by low scale efficiency.
Highlights
In the modern society, the development of electric power industry is a critical index of a country’s economy
data envelopment analysis (DEA) is an efficiency evaluation methodology proposed by the famous American operations researchers Charnes, Cooper and Rhodes in 1978 [5]
The initial input–output data of 31 decision-making units (DMUs) are used, and the BCC correction model with variable returns of scale is used for DEA analysis
Summary
The development of electric power industry is a critical index of a country’s economy. The efficiency of investment in the electric power industry, especially in PGEs, has not received its deserved attention He et al [3] studied the impact of transmission and distribution price policy on the development of. DEA method is a practical linear programming method, and is capable of establishing an investment efficiency evaluation system for the electric power industry under special circumstances, to more accurately measure the efficiency of investment in PGEs. Since the DEA model was introduced by Charnes et al [5] in 1978, both the development of the theory and its application to actual cases have achieved remarkable advancement. Though many studies used three-stage DEA model to analyze the electric power industry, they merely touched limited areas, such as power grid operation, economic efficiency, and social and environmental efficiency.
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