广西生猪养殖绿色全要素生产效率及影响因素研究OACSTPCD
Research on Green Total Factor Production Efficiency and Influencing Factors of Pig Breeding in Guangxi Based on Super-efficiency DEA Model and Panel Regression Analysis
基于2010-2021年广西及其5个分区生猪养殖投入—产出和污染物排放数据,运用SE-SBM模型、GML指数以及面板回归模型研究了广西生猪养殖GML的时空演变特征和关键影响因素.结果表明,2010-2021年广西生猪养殖GML呈现出波动变化状态,GML高值区为桂东地区,技术效率(EC)高值区为桂西地区,技术进步(TC)高值区为桂东地区,其中,贵港、玉林市的技术效率和技术进步明显高于其他城市,贵港市具有纯技术效率变化增长优势.面板回归分析结果表明,GML主要受城镇居民人均可支配收入、生猪主产品价格、医疗防疫费、污水处理率等变量的显著影响.综上,可将贵港、玉林市作为增长极推进规模化养殖,着重针对桂东、桂西、桂北三个地区提升技术进步水平,协同促进广西生猪养殖高质量发展.
Based on input-output and pollutant emission data of pig breeding in Guangxi from 2010 to 2021,SE-SBM model,GML index and panel regression model were applied to study the spatiotemporal evolution and key influencing factors of GML in pig breeding in Guangxi.The results show that the GML of pig breeding experiences fluctuation in Guangxi from 2010 to 2021.The high value area of GML is in eastern Guangxi,while the high value area of technical efficiency(EC)is in western Guangxi,and the high value area of technical progress(TC)is in eastern Guangxi.Among them,the technical efficiency and technological progress of Guigang and Yulin are significantly higher than other cities,and Guigang has the advantage of pure technical efficiency change and growth.The GML is mainly significantly influenced by the per capita disposable income of urban resident,the price of pig,the medical expenses for epidemic prevention and the sewage treatment rate.In conclusion,It indicates that we can take Guigang and Yulin as growth poles to promote large-scale breeding,focus on improving the level of technological progress in the eastern,western and northern of Guangxi,and jointly promote the high-quality development of pig breeding in Guangxi.
尹娟;谭宓;李杨;庞洁;杨宇;黄中琪
广西财经学院 管理科学与工程学院,广西 南宁 530007||广西财经学院 广西金融与经济研究院,广西 南宁 530007广西民族大学 经济学院,广西 南宁 530006广西财经学院 管理科学与工程学院,广西 南宁 530007
经济学
生猪绿色全要素生产效率时空演变因素
PigGreen total factor production efficiencySpatiotemporal evolutionFactor
《江西农业学报》 2024 (012)
118-126 / 9
广西哲学社会科学研究课题(21FGL034;23FGL019);统计学广西一流学科建设项目资助(桂教科研[2022]1号);广西壮族自治区自然资源厅科技项目(GXZC2022-C3-002124-GYZB).
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