中国物流业、经济增长与技术创新——基于2002～2017年向量自回归模型的实证研究  

Logistics Growth,Economic Growth and Technological Innovation Based on VAR Model

作　　者：吴桐雨[1] 王健[1] Wu Tongyu;Wang Jian(Logistics Research Centre,Fuzhou University,Fuzhou 350002,China)

机构地区：[1]福州大学物流研究中心,福州350002

出　　处：《工业技术经济》2019年第3期116-122,共7页Journal of Industrial Technological Economics

基　　金：国家社会科学基金项目"新时代物流业高质量发展的动力变革研究"(项目编号:18BGL018)

摘　　要：本文将物流业增长划分为物流运力与物流规模,通过建立向量自回归模型(VAR)进行脉冲响应函数分析与方差分解分析,提出以货物周转量、物流业增加值、GDP以及物流专利数量作为研究变量。根据我国2002年第一季度至2017年第四季度的数据,运用所建模型表明,经济增长与物流运力、物流技术创新和物流业增长存在单向因果关系,经济增长与物流规模、经济增长与物流技术创新存在双向因果关系,且有时间滞后性。为相关物流业、经济增长与技术创新的研究提供依据。This article constructs the vector auto-regression model to empirical test the impulse response and variance decomposition on logistics growth,economic growth and technological innovation.This paper divides logistics growth into capacity and scale.We use turnover volume of freight transport,add-value of logistics industry,gross domestic product and the number of logistics patent as research variables.Using the quarterly data during the period of 2002 to 2017,the results show that there is one-way relationship between the growth of economic and logistics capacity,and there also exists in technological innovation and logistics growth.Besides,there exists bidirectional causality between economic growth and logistics scale,and there also exists in economic growth and technological innovation.However,there are some kinds of lag in time.

关 键 词：物流业 经济增长 技术创新 向量自回归模型 脉冲响应函数 方差分解 

分 类 号：F506[经济管理—产业经济] F224