SPATIO-TEMPORAL EVOLUTION AND INFLUENCING FACTORS OF AGRICULTURAL ECO-EFFICIENCY IN GUANGDONG PROVINCE UNDER"DUAL CARBON"TARGET
Agricultural ecological efficiency is closely related to agricultural modernization and the"Dual Carbon"target.This research is intended to construct an evaluation index system,so as to evaluate the agricultural eco-efficiency of Guangdong.Specifically,the spatiotemporal evolution characteristics of agricultural eco-efficiency from 2010 to 2020 were analyzed by using the super-efficiency SBM model of undesired output and the kernel density estimation model.The influencing factors of agricultural eco-efficiency were explored by the Tobit regression model.The outcomes were indicated as follows.(1)In terms of temporal evolution,the agricultural eco-efficiency of Guangdong showed a trend of first increasing and then decreasing.Among them,2010-2016 was a period of rising fluctuations,and 2016-2020 was a period of declining fluctuations.(2)In terms of spatial evolution,the agricultural eco-efficiency of Guangdong decreased from the inner city to the outer ones,showing ladder-type distributions.(3)In terms of dynamic evolution,there was serious spatial non-equilibrium for the agricultural eco-efficiency in Guangdong.The overall kernel density curve shifted from the left to the right.There was a phenomenon of"double peaks",which showed a gradient effect and a trend of polarization.(4)Several influencing factors played a major role in the spatiotemporal evolution of agricultural eco-efficiency in Guangdong under the"Dual Carbon"target,such as the tertiary industry ratio,fertilizer use intensity,per capita cultivated land,per capita GDP,and fiscal expenditure on agriculture,etc.So,in order to improve agricultural eco-efficiency,we not only promote agricultural production technology,but also make a rational allocation of agricultural resources.Moreover,we should draw up appropriate green low-carbon development policies according to the agricultural features of different regions.
agricultural eco-efficiency(AEE)influencing factorsSuper-SBM modelTobit modelGuangdong province
NETL
NSTL
万方数据
