Measurement of Production Efficiency and Analysis of Influencing Factors in Major Sugarcane-Producing Regions of China

Chuanmin Yan, Xingqun Li (), Lei Zhan, Zhizhuo Li and Jun Wen
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Chuanmin Yan: College of Agriculture, Guangxi University, Nanning 530004, China
Xingqun Li: College of Agriculture, Guangxi University, Nanning 530004, China
Lei Zhan: College of Agriculture, Guangxi University, Nanning 530004, China
Zhizhuo Li: Business School, Riddle Hall, Queen’s University Belfast, International Business, Belfast BT7 1NN, UK
Jun Wen: College of Agriculture, Guangxi University, Nanning 530004, China

Agriculture, 2025, vol. 15, issue 8, 1-27

Abstract: Enhancing production efficiency in major sugarcane-producing regions is of strategic significance for ensuring the security of China’s sugar industry and promoting its industrial upgrading. Using the DEA–Malmquist–Tobit modeling framework, this study dynamically evaluates production efficiency from 2011 to 2023, spanning China’s 12th to 14th Five-Year Plan periods, with a focus on the primary sugarcane-producing regions: Guangdong, Guangxi, Yunnan, and Hainan. Results indicate a U-shaped fluctuation in national comprehensive technical efficiency, with a historical low in 2022 due to a collapse in scale efficiency, pinpointing scale management as the central constraint. Regionally, Guangdong consistently maintained optimal dual efficiency. Yunnan stabilized its efficiency through rigid policy mechanisms. Guangxi experienced setbacks due to competition between eucalyptus and sugarcane cultivation, while Hainan faced a precipitous decline in scale efficiency following industry exits. Total factor productivity (TFP) analysis revealed that stagnation in technological advancement was the primary cause of productivity decline, leading to asynchronous regional technology diffusion and subsequent reliance on scale adjustments. During the 12th Five-Year Plan, Hainan led in TFP growth but experienced a sharp downturn in the 13th period due to policy tightening. In contrast, Guangdong achieved notable TFP growth in the 14th period through technological breakthroughs, whereas Yunnan lagged behind Guangxi due to technological inertia. Analysis of the driving mechanisms showed that urbanization rates significantly boosted efficiency through intensified land use.

Keywords: sugarcane; production efficiency; DEA–Malmquist model; Tobit model (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2025
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