Abstract: In this study, by constructing an input-output system, we used a super-efficiency epsilon-based measure (EBM) model based on non-oriented scores and variable returns to scale, and a global Malmquist-Luenberger (GML) index to measure and analyze the green total factor productivity (GTFP) of animal husbandry in 31 provinces in China from 2011 to 2020. On this basis, Dagum's Gini coefficient decomposition and kernel density estimation methods were used to explore the regional differences and dynamic evolution of the GTFP of animal husbandry, and the fixed-effect model and Driscoll-Kraay standard error estimators were used to test its influencing factors. The results show that the overall level of the GTFP of animal husbandry in China from 2011 to 2020 was low, and it showed a decreasing gradient pattern of 'northeast-east-central-west'. Sustainable technological progress was the main driving force of regional and national GTFP of animal husbandry in China; the regional difference showed a continuous upward trend with a polarization phenomenon and gradient effect. Interregional difference was the main source of regional differences in the GTFP of animal husbandry; the difference between eastern and western regions was the largest, and the difference between northeast and central regions was the smallest. In terms of influencing factors, industrial agglomeration, financial support for agriculture, and per capita GDP had significant negative effect on China's animal husbandry GTFP, and transport accessibility had a significant positive effect. The results of this study provide a basis for the promotion of sustainable development of animal husbandry in China.

Key words: green total factor productivity of animal husbandry (GTFP), super-EBM model, temporal and spatial difference, influencing factor