文章摘要
范巧,Hudson Darren.一种新的包含可变时间效应的内生时空权重矩阵构建方法[J].数量经济技术经济研究,2018,(1):131-149
一种新的包含可变时间效应的内生时空权重矩阵构建方法
A New Endogenous Spatial Temporal Weight Matrix Based on Ratios of Global Moran's I
  
DOI：
中文关键词: 权重矩阵  时间效应  变异性  Moran指数
英文关键词: Weight Matrices  Changeable Transfering Effects  Variation Properties of Estimators  Moran's I
基金项目:本文获得2017年度重庆市教委人文社会科学规划项目“两江新区辐射带动区县发展的能力评价及提升对策研究”（17SKG198）、2016年度重庆市社会科学规划培育项目“基于空间计量的国家级新区辐射带动力及其实现机制研究”（2016PY65）的资助。
作者单位
范巧 重庆科技学院法政与经贸学院 
Hudson Darren 得州理工大学农业与应用经济系 
中文摘要:
      研究目标：引入一种基于年度全局Moran指数比的内生时空权重矩阵构建方法，并评估其合理性。研究方法：基于标准化的空间权重矩阵和以年度全局Moran指数比为基础的时间权重矩阵，经过克罗内克积组合形成内生时空权重矩阵；并以两江新区辐射带动力影响因素分解问题为例，评估了内生时空权重矩阵的引入合理性。研究发现：相对于传统的外生时空权重矩阵而言，内生时空权重矩阵能够模拟空间溢出效应在时间上的动态转移和传导效应，却不会导致模型估计结果变异性质发生明显改变。研究创新：构建了一种新的内生性的、包含可变时间效应的时空权重矩阵。研究价值：为面板数据空间计量模型建模实践构建了一种更为精准的时空权重矩阵设计方式。
英文摘要:
      Research Objectives：Introduce a new way to construct endogenous spatial temporal weight matrices (STWMs). Research Methods: Construct endogenous STWMs through Kronecker products between standardized temporal weight matrices (TWMs) based on global Moran's I in different years and standardized spatial weight matrices (SWMs), and assess the scientificity of above endogenous STWMs through 4 different SWMs and 3 different spatial econometrical models and 5 different periods through comparing average variation properties of estimators in the case models of decomposition of influencing factors of Liangjiang National New Area's development impacts. Research Findings: Endogenous STWMs above are better than traditional exogenous STWMs to explain the spatial spillover effects and their transfering effects in different periods, but don't change the variation properties of estimators at a large level. Models employing spatial error models and endogenous STWMs based on distances between regions are better than the case models. Research Innovations: Obtain a new method to construct endogenous STWMs with changeable transfering effects in different periods. Research Value: Provide accurate endogenous STWMs for spatial econometrical modeling.
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