数字乡村建设对林业绿色全要素生产率的影响OA北大核心CHSSCDCSTPCD
The Impact of Digital Rural Construction on Forestry Green Total Factor Productivity
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.
⑴ Background——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 forest-ry 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. ⑵ Methods——In this paper,forestry green total factor productivity was selected as the explained varia-ble,digital rural construction level was selected as the core explanatory variable,forestry industry structure opti-mization degree was selected as the mechanism variable,urbanization rate,foreign trade dependence,govern-ment 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 forest-ry 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 pro-ductivity,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 re-sults of heterogeneity study show that the effect of digital rural construction in eastern China on improving forestry green total factor productivity is more significant than that in central and western China,and digital infrastructure and digital service level are the key to improving forestry green total factor productivity.Although digital capital investment and digital industry development have a positive promoting effect on the improvement of forestry green total factor productivity,it is not significant. ⑷ Conclusions and Discussions——Based on the above research conclusions,the following policy sug-gestions are put forward:First,continue to implement digital rural development actions and improve the level of digital empowerment in the forestry industry.Accelerate the construction of digital projects such as 5G base sta-tions and rural power grid transformation,encourage the participation of social capital,and form a multi-party force to jointly promote the digital upgrading of the forestry industry.Second,develop digital villages according to local conditions.The eastern region should focus on the application of high-end technology and market informa-tion services,and can appropriately deploy advanced digital infrastructure in rural areas.The central and western regions should promote the construction of rural digital infrastructure to ensure that forest areas and remote areas have access to high-speed and stable internet services.Third,optimize the forestry industry structure mainly through the establishment of forestry development fund,the introduction of tax relief policies and the development of green credit products.
游晓东;陈鎏鹏;严颖峥;董丙瑞;周子渭;黄慧媛
福建农林大学 经济与管理学院,福州 350002福建农林大学 乡村振兴学院,福州 350002
经济学
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
forestry green total factor productivitydigital rural constructionforestry industry structureDouble Machine Learning model
《林业经济问题》 2024 (004)
397-405 / 9
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(KS-BXK2316)
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