商业研究

商业研究

• 商经理论 • 上一篇    下一篇

中国林业全要素生产率空间关联网络结构及其影响因素

贯君，曹玉昆，朱震锋   

  1. （东北林业大学 经济管理学院，哈尔滨 150001）
  • 收稿日期:2019-03-01 出版日期:2019-09-16
  • 作者简介:贯君（1989-），女，哈尔滨人，东北林业大学经济管理学院讲师，管理学博士，研究方向：林业可持续发展；曹玉昆（1962-），女，山东茌平人，东北林业大学经济管理学院教授，博士生导师，管理学博士，研究方向：林业经济理论与政策；朱震锋（1987-），男，河南荥阳人，东北林业大学经济管理学院讲师，管理学博士，研究方向：林业经济理论与政策。
  • 基金资助:
    国家自然科学基金项目，项目编号：71802035；黑龙江省科学基金项目，项目编号：YQ2019G001；黑龙江省哲学社会科学研究规划项目，项目编号：18GLD289，18GLB022；中央高校基本科研业务费专项资助基金项目，项目编号：2572018BM07。

Spatial Linkage Network Structure of China′s Forestry Total Factor Productivity. and Its Influence Factors

GUAN Jun, CAO Yu-kun, ZHU Zhen-feng.   

  1. （College of Economics and Management, Northeast Forestry University, Harbin 150001, China）.
  • Received:2019-03-01 Online:2019-09-16

摘要： ：基于2005-2016年中国省域面板数据，本文运用DEA-Malmquist模型测度31个省域的林业全要素生产率，采用VAR Granger因果检验方法对省域间的空间溢出关系进行识别，在社会网络分析框架下对网络结构特征及其影响效应进行分析。研究发现中国省域林业全要素生产率的空间溢出效应普遍存在，省域间空间溢出呈现多重叠加现象；关联网络呈多核心发展趋势，跨省效率传递具有明显的“梯度”溢出特征；省域间市场化落差有助于林业市场边界的拓展，相似的创新水平和金融发展水平能够促进省域之间的林业生产技术交流与合作和林业增长的“马太效应”。因此，应更加重视林业生产效率的空间非均衡格局，通过宏观调控和市场体系建设，因地制宜制定林业发展政策，以发挥各地区的功能和优势。

关键词: 林业全要素生产率, 空间关联, 社会网络分析, DEA-Malmquist模型, VAR Granger因果检验.

Abstract: Abstract：Based on the DEA-Malmquist model and provincial panel dataset(2005-2016), this paper measured the provincial forestry total factor productivity(TFP) in China, and identified the spatial spillover relationships between provinces by the VAR Granger causality test. On this basis, in the framework of social network analysis, the structural characteristics of spatial correlation network and its effects are analyzed. The results showed that, the spatial spillover effect of forestry TFP was commonly existed in China, and there was multiple superposition in the inter-provincial spatial forestry TFP spillovers;the correlation network presented a trend of multi-core development, and the trans-provincial efficiency spillover showed an obvious gradient feature; the gap between provinces contributed to the expansion of forestry market′s boundaries, besides, similar innovation level and financial development level can promote technology exchange and cooperation between provinces,and the “Matthew effect” of forestry growth. Therefore, more attention should be paid to the spatial disequilibrium pattern of China′s forestry production efficiency. Through macro-control and market system construction, favorable conditions should be created for the cross-regional flow and efficient allocation of production factors, and forestry development policies should be formulated and implemented according to local conditions to give play to the functions and advantages of each region.

Key words: forestry total factor productivity, spatial network, social network analysis, DEA-Malmquist model, VAR Granger causality test