我国林业绿色全要素生产率测度及其影响因素

Measurement and influencing factors of the total green factor productivity of forestry in China

【目的】化解林业经济价值、生态价值与环境污染、能源消耗间的矛盾,加速林业经济增长模式从以传统要素为主导向以高级生产要素为内核转变,推进区域绿色林业协调高质量发展。【方法】通过构建投入产出指标体系,运用非角度、非径向的SBM模型和GML指数对2002—2020年中国30个省域林业绿色全要素生产率进行测算。在此基础上,利用空间相关性分析深层次揭示邻近省域林业绿色全要素生产率对区域整体演变趋势产生的影响,采用邻接空间权重矩阵建立面板空间计量模型探究林业绿色全要素生产率的影响因素。【结果】整体来看,林业绿色全要素生产率呈上升态势,说明我国林业可持续化发展趋向良好;技术进步是林业绿色全要素生产率的主要增长源,而技术效率则对林业绿色全要素生产率具有一定抑制作用。空间相关性分析显示:我国林业绿色全要素生产率的空间正相关性正渐趋弱化,“高-高”集聚特征重点体现在上海、江苏等华东区域,“低-低”集聚特征则主要分布于四川、甘肃等地。影响因素研究显示:产业发达程度、宏观经济发展水平、环境规制与林业绿色全要素生产率之间存在正相关关系,而城镇化水平和能源消费结构则与其具有负相关关系。【结论】对策建议如下:1)全方位建立健全有关政策及法律保障体系;2)深层次统筹林业绿色发展和区域一体化战略;3)多维度补齐林业绿色发展要素,为我国林业高质量发展提供明确方向。

【Objective】The article aimed to resolve the contradiction between the economic value,ecological value of forestry and environmental pollution as well as energy consumption,accelerate the transformation of the forestry economic growth model from a traditional factors-oriented form into a new form with the advanced production factors as the core,to promote the coordinated and highquality development of regional green forestry.【Method】By constructing an input-output index system,the non-angular and nonradial SBM model and GML index were used to measure the total green factor productivity of forestry in 30 provinces in China from 2002 to 2020.Based on that,the spatial correlation analysis was used to deeply reveal the influence of the total factor green productivity of forestry in the adjacent provinces on the overall evolution trend of the region.The adjacent spatial weight matrix was used to establish a panel spatial econometric model to explore the influencing factors of the total green factor productivity of forestry.【Result】Overall,the total green factor productivity of forestry is increasing,indicating that the sustainable development of forestry in China tends to be good.The progress in technology development is the main source for the growth of the total green factor productivity of forestry,while technical efficiency has a significant inhibitory impact on that.The spatial correlation analysis shows that the positive spatial correlation of China’s total green factor productivity of forestry is gradually weakening,the“high-high”agglomeration characteristics are mainly reflected in eastern China such as Shanghai and Jiangsu,and the“low-low”agglomeration characteristics are mainly distributed in regions such as Sichuan and Gansu.The regression results show that the total green factor productivity of forestry is positively correlated with the degree of industrial development,the level of macroeconomic development and environmental regulation,however,it is negatively correlated with the urbanization level and energy consumption structure.【Conclusion】The countermeasures and suggestions are as follows:1)establishing and improving relevant policies and legal guarantee systems comprehensively;2)in-depth coordination of the green development and regional integration strategies of forestry;3)multi-dimensionally complementing the green development elements of forestry,so as to provide a clear direction for the high-quality development of forestry in China.