Measurement of eco-efficiency in the horse industry, spatiotemporal evolution and convergence analysis

The horse industry constitutes a vital economic sector in Xinjiang, China. This study quantitatively assesses the sector's sustainable development through eco-efficiency analysis across northern Xinjiang counties from 2001 to 2021. The research employs four analytical methods: the S-SBM model for efficiency measurement, kernel density estimation for distribution analysis, Moran's index for spatial autocorrelation examination, and convergence tests for long-term trend assessment. Results demonstrate a consistent decline in eco-efficiency, decreasing from 0.821 in 2001 to 0.444 in 2021, with an average value of 0.557. Significant regional disparities emerge, with efficiency scores ranging from 0.499 to 1.285 across different prefectures. Spatial analysis reveals pronounced clustering effects, particularly in Yili Prefecture. Convergence tests indicate the presence of β-convergence but the absence of σ-convergence, suggesting narrowing efficiency gaps over time despite persistent regional inequalities. These empirical findings provide substantive evidence for policymakers seeking to enhance Xinjiang's equine economy sustainability and resource efficiency. The study contributes to the limited literature on ecological efficiency measurement in animal husbandry sectors.