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Article

Measuring Green Total Factor Productivity in China’s Power Industry Based on Super-Efficiency SBM and GML Index Models

by
Shuo Yin
1,
Yao Lu
1,
Haixu Song
2,
Yiyang Liao
3 and
Sen Guo
3,*
1
State Grid Henan Economic Research Institute, Zhengzhou 450052, China
2
State Grid Energy Research Institute, Beijing 102209, China
3
School of Economics and Management, North China Electric Power University, Beijing 102206, China
*
Author to whom correspondence should be addressed.
Sustainability 2026, 18(1), 38; https://doi.org/10.3390/su18010038
Submission received: 26 October 2025 / Revised: 30 November 2025 / Accepted: 16 December 2025 / Published: 19 December 2025
(This article belongs to the Section Energy Sustainability)

Abstract

Against the backdrop of accelerating global energy transition, China, as the world’s largest energy producer and consumer, has a crucial impact on achieving carbon neutrality goals through the green development of its power industry. Green total factor productivity is an important indicator for measuring the green development of the power industry. Utilizing provincial panel data from 30 regions in China covering the period 2012–2023, using MATLAB R2021a software, this study firstly measures the static GTFP of China’s power industry using a Super-Efficiency Slack-Based Measure (SBM) model incorporating undesirable outputs. Subsequently, the dynamic GTFP is measured and analyzed using the Global Malmquist–Luenberger (GML) index model. The model decomposes GTFP change to examine the contributions of technical efficiency change and technological progress. The findings reveal that (1) the static GTFP of China’s provincial power industry is generally low, with significant regional disparities, with Jiangsu, Yunnan, Beijing, Zhejiang and Sichuan ranking among the top five nationally; (2) the average GTFPs in eastern and western China are higher than in the central region. Overall, the GTFP of China’s power industry exhibits an upward trend, which is primarily driven by technological progress. Based on these conclusions, the study proposes policy recommendations to enhance the power industry’s GTFP, which can offer theoretical insights for facilitating its green transition and sustainable development.
Keywords: China; global Malmquist-Luenberger index; green total factor productivity; power industry; super-efficiency SBM model; sustainability China; global Malmquist-Luenberger index; green total factor productivity; power industry; super-efficiency SBM model; sustainability

Share and Cite

MDPI and ACS Style

Yin, S.; Lu, Y.; Song, H.; Liao, Y.; Guo, S. Measuring Green Total Factor Productivity in China’s Power Industry Based on Super-Efficiency SBM and GML Index Models. Sustainability 2026, 18, 38. https://doi.org/10.3390/su18010038

AMA Style

Yin S, Lu Y, Song H, Liao Y, Guo S. Measuring Green Total Factor Productivity in China’s Power Industry Based on Super-Efficiency SBM and GML Index Models. Sustainability. 2026; 18(1):38. https://doi.org/10.3390/su18010038

Chicago/Turabian Style

Yin, Shuo, Yao Lu, Haixu Song, Yiyang Liao, and Sen Guo. 2026. "Measuring Green Total Factor Productivity in China’s Power Industry Based on Super-Efficiency SBM and GML Index Models" Sustainability 18, no. 1: 38. https://doi.org/10.3390/su18010038

APA Style

Yin, S., Lu, Y., Song, H., Liao, Y., & Guo, S. (2026). Measuring Green Total Factor Productivity in China’s Power Industry Based on Super-Efficiency SBM and GML Index Models. Sustainability, 18(1), 38. https://doi.org/10.3390/su18010038

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