Re-Estimating China’s Cotton Green Production Efficiency with Climate Factors: An Empirical Analysis Using County-Level Panel Data from Xinjiang

Yang Yang (), Wei Chang and Kouadio Konan Jules
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Yang Yang: School of Economics and Management, Shihezi University, Shihezi 832000, China
Wei Chang: School of Economics and Management, Shihezi University, Shihezi 832000, China
Kouadio Konan Jules: School of Economics and Management, Shihezi University, Shihezi 832000, China

Sustainability, 2025, vol. 17, issue 8, 1-21

Abstract: Enhancing the green production efficiency of cotton contributes significantly to achieving carbon neutrality and agricultural sustainability. Based on county-level panel data from 2002 to 2020 and daily average temperature and precipitation data from 53 meteorological stations in Xinjiang, this study employs a non-desirable output super-efficiency slack-based measure model, the Malmquist index, and Moran’s index to analyze the temporal and spatial changes in the green production efficiency of cotton across counties in Xinjiang. From a dynamic evolution perspective, without considering non-desirable outputs, the overall cotton production efficiency at the county level exhibits an upward trend; however, when non-desirable outputs are taken into account, the green production efficiency of cotton shows a declining trend, with a general convergence trend among counties (cities). From 2002 to 2020, the overall green production efficiency of cotton in Xinjiang counties decreased from 0.531 to 0.442, with an annual average decline rate of −0.882%. Spatially, as temperatures rise in northern Xinjiang and rainfall increases in the west, high-value areas for cotton green production efficiency have shifted northward and westward, transforming the spatial distribution pattern from “high in the south and low in the north” to “high in the north and low in the south”. The spatial clustering effect among counties is significant, exhibiting a “clustered distribution” pattern. To improve the green production efficiency of cotton, it is recommended to promote ecological protection efforts, disseminate advanced agricultural technologies, implement differentiated strategies, leverage spatial clustering effects, and strengthen theoretical and technological research.

Keywords: climate change; cotton green production efficiency; non-desirable output super-efficiency slack-based measure model; Malmquist index; Moran’s index (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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