木材加工产业集聚对劳动生产率影响的空间效应分解——基于1998—2016年省际空间面板数据的实证研究  

The Spatial Effects Decomposition of Industrial Agglomeration on Labor Productivity in the Wood Processing Industry: An Empirical Study Based on 1998—2016 Spatial Panel Data

作　　者：夏永红 沈文星[1] 李存芳 Xia Yonghong;Shen Wenxing;Lr Cunfang(College of Economics and Management,Nanjing Fores,University Nanjing 210037;Business School,Jiangsu Normal University Xuzhou,221116)

机构地区：[1]南京林业大学经济管理学院,南京210037 [2]江苏师范大学商学院,徐州221116

出　　处：《林业科学》2019年第9期157-165,共9页Scientia Silvae Sinicae

基　　金：国家自然科学基金项目“资源枯竭型企业跨区转移行为的溢出效应与胁迫效应研究”(71573110);国家林业和草原局林业软科学研究项目“林业产业国内价值链培育的协同创新机制与实施路径研究”(2015-R28);徐州市社会科学研究项目“新常态下徐州制造业集聚效应与高质量发展对策研究”(19XSZ-049)

摘　　要：【目的】研究木材加工产业集聚对产业劳动生产率影响的直接效应和溢出效应,为促进木材加工产业提质增效提供发展路径,为优化木材加工产业区域布局提供理论依据。【方法】基于1998—2016年省际面板数据,利用全局Moran指数测量木材加工产业劳动生产率的空间依赖性;在控制人力资本、固定资产投资和交通运输条件等变量的基础上,采用空间计量模型实证检验省际木材加工产业集聚对产业劳动生产率影响的直接效应和溢出效应。【结果】1)木材加工产业劳动生产率的全局Moran指数在0.3上下波动,且存在空间依赖性(P<0.05)。2)空间计量模型的系数估计结果显示:木材加工产业劳动生产率存在空间滞后和空间误差自相关性(P<0.01)。3)空间效应分解结果显示:木材加工产业集聚水平对产业劳动生产率影响的直接效应和溢出效应分别为0.260 6和0.029 2(P<0.01);木材加工产业人力资本水平、人均固定资产投资水平和省际交通运输条件3个控制变量对产业劳动生产率影响的直接效应和溢出效应分别为0.089 8(P<0.01)和0.010 1(P<0.05)、0.843 4和0.094 6(P<0.01),以及0.771 8和0.085 1(P<0.01)。木材加工产业集聚水平、人力资本水平、人均固定资产和交通运输条件4个变量对产业劳动生产率影响的溢出效应约占总效应的10%左右,反馈效应相对较小,占模型系数估计结果的1%以下。【结论】木材加工产业劳动生产率具有空间依赖性特征,存在空间自相关性,木材加工产业集聚水平、人力资本水平、人均固定资产和交通运输条件对木材加工产业劳动生产率的影响存在正向的直接效应和溢出效应,其中,直接效应包括较小的反馈效应。基于此,提出建议:优化木材加工产业布局,推进产业集聚化发展;优化产业内部结构调整,加大固定资产投资力度;提高木材加工产业从业人员素养,加强专业人才梯度培养;【Objective】 The direct and spillover effects of the agglomeration of wood processing industry on labor productivity were studied in order to improve the quality and efficiency of the industry and to provide a theoretical basis for optimizing its deployment in the region. 【Method】 Based on the inter-provincial panel data from 1998 to 2016, the global Moran index was used to measure the spatial autocorrelation of labor productivity in the wood processing industry. By controlling variables such as human capital, fixed asset investment and transportation conditions, the spatial econometrics model was used to examine empirically the direct effects and spillover effects of the wood processing industry agglomeration on industrial labor productivity. 【Result】 1) The global Moran index of labor productivity fluctuated around 0.3, which was spatial dependence(P<0.05) in the wood processing industry. 2) The coefficient estimation of spatial econometric model showed that the wood processing industrial labor productivity had a spatial lag and spatial error autocorrelation(P<0.01). 3) The spatial effects decomposition showed that the direct and spillover effects of the wood processing industry agglomeration on industrial labor productivity were 0.260 6 and 0.029 2(P<0.01), respectively. For the control variables, the direct and spillover effects of human capital, per capita fixed asset investment, and inter-provincial transportation conditions on industrial labor productivity of the wood processing industry were 0.089 8(P<0.01) and 0.010 1(P<0.05), 0.843 4 and 0.094 6(P<0.01), and 0.771 8 and 0.085 1(P<0.01), respectively. The spillover effects of the wood processing industry agglomeration, human capital level, fixed assets per capita and transportation conditions on industrial labor productivity accounted for approximately 10% of the total effects, while the feedback effects were relatively small, accounting for less than 1% of the estimated coefficients of the model.【Conclusion】 The labor productivity of the

关 键 词：木材加工产业 产业集聚 就业密度 劳动生产率 直接效应 溢出效应 

分 类 号：F307.2[经济管理—产业经济]