Abstract

Agricultural ecological efficiency is not only the key link between green development and high-quality development of agriculture, but also an important regulatory indicator for China’s rural revitalization. Based on provincial panel data of China from 2000 to 2019, using land, mechanical, labor, fertilizer, pesticide, and agricultural film as input variables and economic output and agricultural carbon emissions as output variables, the inter-provincial agricultural ecological efficiency is calculated by a super-efficient SBM model, and the traditional spatial Markov probability transfer matrices are constructed based on time series and spatial correlation analyses. By exploring the spatial and temporal dynamic evolution characteristics of agricultural ecological efficiency, it is found that the agricultural ecological efficiency of China increased steadily with fluctuations. In addition, the provincial gap has been narrowing, but the overall level is still at a low level; thus, there is still a large space for improvement in agricultural ecological efficiency. The overall trend of agricultural ecological efficiency shifting to a high level in China is significant, but its evolution has the stability to maintain the original state, and achieving leapfrog transfer is relatively hard. The geospatial pattern plays an important role in the spatial-temporal evolution of agricultural ecological efficiency, with significant spatial agglomeration characteristics. Provinces with high agricultural ecological efficiency enjoy positive spillover effects, while provinces with low agricultural ecological efficiency have negative spillover effects; thus, gradually forming a “club convergence” phenomenon of “high agglomeration, low agglomeration, high radiation, and low suppression” in the spatial pattern. In addition, support for the improvement of agricultural ecological efficiency will be provided in this study.

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