摘要
利用1997—2013年31个省份的面板数据,通过构建半参数空间面板向量自回归模型(SSPVAR)及时空脉冲响应函数,实证检验我国技术选择、产业结构升级和经济增长之间的时空传导效应,并探讨对外开放度对三者的异质性影响。结果发现,技术选择、产业结构升级及经济增长受到彼此的冲击后,大部分都呈现出正向的响应特征。其中,技术选择推进本省份及周边省份的产业结构升级,并在短期阻碍了经济增长,但长期内促进整体区域经济增长;产业结构升级不仅推进整体区域产业结构升级,还促进本省份及周边省份经济增长;经济中心的拉动效应较强且持久,经济增长会促进整个区域的技术选择、产业结构升级。此外,对外开放度对技术选择、产业结构升级的效应呈现出"N"形特征,对外开放度对经济增长的效应前期较为平稳,随后呈现出"倒U"形特征。
By using panel data of 31 Chinese provinces from 1997 to 2013 and building semi-parameter spatial panel vector autoregression model（ SSPVAR） and impulse response function of space and time,this paper empirically analyzes the conduction effect of time and space among technology choice,industrial structure upgrading and economic growth,and discusses the heterogeneous effects of degree of openness on those three aspects. The study finds that despite the impacts from each other,technology choice,industrial structure upgrading and economic growth all show positive responses after the impact. Specifically,the technology choice promotes the upgrading of overall regional industrial structure,and contributes to the overall regional economic growth in the long term though hindered it in the short term. The industrial structure upgrading promotes not only the overall regional industrial upgrading,but also the economic growth of this province and of surrounding provinces. The pulling effect of economic center is strong and lasting in that economic growth promotes technology choices and upgrading of the industrial structure throughout the region. In addition,the effect of the degree of openness to the outside world on technology choice and the industrial structure upgrading has been in a state of fluctuation. The effect is relatively positive and stable in early stage but turns negative and then turns again in later stage,presenting an＂N＂from a derivative map view.
出处
《经济经纬》
CSSCI
北大核心
2017年第5期87-92,共6页
Economic Survey
基金
国家自然科学基金项目(71571046)
教育部高等学校博士点基金项目(20120161110034)
关键词
技术选择
产业结构升级
经济增长
半参数面板空间向量自回归模型
Technology Choice
Upgrading of Industrial Structure
Economic Growth
Semi-Parameter Panel Space Vector Auto Regression Model
