Measurement and spatial evolution of green total factor productivity in China’s wheat production based on the three-stage DEA-GML model - Liu, Liping; Zheng, Bin; Zhao, Junye; Hao, Shuai (Frontiers in Sustainable Food Systems, 2025)
Improving production efficiency and promoting green transformation are essential pathways toward ensuring food security and advancing sustainable agricultural development. This study focused on 15 major wheat-producing provinces in China and employed a three-stage DEA-GML model to measure the green total factor productivity (GTFP) of wheat from 2004 to 2022, adjusting for environmental variables and random disturbances. The evolution and spatial dynamics of GTFP were further examined using both global and local Moran’s I indices, along with kernel density estimation. The study produced the following results: (1) After adjusting with the three-stage DEA–GML model, the average GTFP of major wheat-producing areas was 1.006, lower than the first-stage unadjusted mean of 1.028. This indicates that eliminating the influence of external environmental factors and random errors enhances the robustness and scientific validity of the efficiency estimates. (2) Over time, the adjusted GTFP of wheat exhibited a fluctuating upward trend, with technological progress (TC) contributing slightly more to GTFP growth than technical efficiency (EC). At the regional level, the Huang-Huai-Hai wheat advantage zone achieved the highest average GTFP of 1.016, with strong performance in both EC and TC. In contrast, the Southwest wheat zone recorded the lowest average GTFP of 0.986, where lagging technological progress constrained overall efficiency. (3) Spatial analysis revealed significant positive spatial autocorrelation in wheat GTFP from 2005 to 2012, followed by a weakening of spatial clustering and an expansion of interregional disparities after 2012. Kernel density analysis further showed that the distribution of wheat GTFP evolved from a unimodal to a bimodal or multimodal pattern, indicating an intensifying spatial divergence in green production efficiency. These findings provide valuable insights for enhancing wheat productivity and advancing the green transformation of agriculture.