Measuring and Analyzing Operational Efficiency and Returns to Scale in a Time Horizon: Assessment of China’s Electricity Generation & Transmission at Provincial Levels

Toshiyuki Sueyoshi, Ruchuan Zhang and Aijun Li ()
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Toshiyuki Sueyoshi: The Center for Economic Research, Shandong School of Development, Shandong University, Jinan 250100, China
Ruchuan Zhang: The Center for Economic Research, Shandong School of Development, Shandong University, Jinan 250100, China
Aijun Li: The Center for Economic Research, Shandong School of Development, Shandong University, Jinan 250100, China

Energies, 2023, vol. 16, issue 2, 1-23

Abstract: This study discusses the assessment of OE (operational efficiency) and RTS (returns to scale) over a time horizon. Many previous DEA (Data Envelopment Analysis) studies have discussed how to measure OE/RTS. However, their works did not consider the measurement over time. The important feature of the proposed approach is that our models are different from standard ones in terms of factor (inputs and outputs) unification. A problem with standard models is that they produce different efficiency measures for input and output orientations. Consequently, they yield different OE and RTS estimates depending upon which production factor is used for measurement. To handle the difficulty, we develop a new DEA formulation whose efficiency measure is determined after combining inputs and outputs, and then we discuss how to measure the types of RTS. The other methodological feature is that the proposed model incorporates a time horizon. As an empirical application, this study considers electricity generation and transmission across Chinese provinces from 2006 to 2019. The first key outcome is that the performance of China’s electricity generation and transmission system tends to improve with an annual growth rate of 0.45% across time. The second outcome is that, during the observed periods, China has more occurrences of decreasing rather than increasing RTS. As an implication, some provinces (e.g., Jiangxi and Hainan) need to increase their generation sizes to enhance their OE measures, while other provinces (e.g., Jiangsu and Zhejiang) should decrease their generation sizes. Finally, this study confirms significant technological heterogeneity across Chinese provinces and groups.

Keywords: data envelopment analysis; returns to scale; operational efficiency; electricity generation and transmission (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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