检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
作 者:游晓东[1] 陈鎏鹏 严颖峥 董丙瑞 周子渭 黄慧媛 YOU Xiaodong;CHEN Liupeng;YAN Yingzheng;DONG Bingrui;ZHOU Ziwei;HUANG Huiyuan(College of Economics and Management,Fujian Agriculture and Forestry University,Fuzhou 350002,China;College of Rural Revitalization,Fujian Agriculture and Forestry University,Fuzhou 350002,China)
机构地区:[1]福建农林大学经济与管理学院,福州350002 [2]福建农林大学乡村振兴学院,福州350002
出 处:《林业经济问题》2024年第4期397-405,共9页Issues of Forestry Economics
基 金:福建农林大学科技创新专项基金项目(KCX23F25A);福建农林大学习近平生态文明思想研究院项目(KSBXK2316)。
摘 要:选取2012—2022年中国30个省份的面板数据,在定量测算林业绿色全要素生产率和数字乡村建设水平的基础上,使用双重机器学习模型进行估计,实证检验数字乡村建设对林业绿色全要素生产率的影响。研究发现:数字乡村建设对林业绿色全要素生产率具有显著促进作用,并且数字乡村建设能够通过优化林业产业结构从而提升林业绿色全要素生产率。异质性研究发现,东部地区数字乡村建设提升林业绿色全要素生产率的效应相较于中西部地区更为显著,并且数字基础设施和数字服务水平是提升林业绿色全要素生产率的关键因素。因此,政府应因地制宜地推进数字乡村建设,加快与林业产业的深度融合,不断优化林业产业结构,助力林业绿色全要素生产率的提升。⑴Background——The improvement of forestry green total factor productivity is the only way to cultivate new quality productive forces in forestry and accelerate high-quality development of forestry.However,the forestry development is faced with the problems of insufficient technological innovation ability and tight constraint of exploitable resources,and the forestry economy relying on extensive development has entered a slow period.The digital rural construction can break the limitation of time and space,accelerate the flow of resources,optimize the allocation of resources,and provide an important opportunity to improve the forestry green total factor productivity.⑵Methods——In this paper,forestry green total factor productivity was selected as the explained variable,digital rural construction level was selected as the core explanatory variable,forestry industry structure optimization degree was selected as the mechanism variable,urbanization rate,foreign trade dependence,government intervention degree,forestry development degree,rural production environment and rural human capital were selected as the control variables.Based on the panel data of 30 provinces(municipalities and autonomous regions)in China from 2012 to 2022,this paper first used the super-efficiency SBM model to measure the forestry green total factor productivity,and used the entropy method to measure the level of digital rural construction.Then,the Double Machine Learning model was used to estimate and empirically test the impact of digital rural construction on forestry green total factor productivity and its mechanism.⑶Results——Digital rural construction has a significant promoting effect on forestry green total factor productivity,and the conclusion is still valid after the robustness test and endogeneity test.Moreover,digital rural construction can improve forestry green total factor productivity by optimizing forestry industry structure.The results of heterogeneity study show that the effect of digital rural construction in
关 键 词:林业绿色全要素生产率 数字乡村建设 林业产业结构 双重机器学习模型
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.69