空间权重矩阵的设定方法研究

空间权重矩阵作为实际观测数据到空间计量模型的映射,使得空间溢出效应的量化成为可能,是当前计量经济学的研究热点。空间权重矩阵设定方法的研究逻辑是首先对外生构建的空间权重矩阵基于邻接关系和距离函数进行分类研究,针对不同结构的空间单元进行多种设定方法的适用性分析,进而讨论利用Voronoi图构建离散点空间权重矩阵的应用方法。研究发现,实证分析中应针对具体问题和不同的空间单元,设定多个空间权重矩阵,并进一步检测不同设定方法对模型估计结果的影响以及不同形式矩阵的敏感性。     

基于不同空间权重矩阵的我国省域经济空间效应研究

运用Geoda空间分析软件,针对我国31个省市(港澳台除外)的2001-2020年GDP,运用不同权重矩阵进行空间相关分析和动态变化分析.基于"后"型、K-最近邻和欧式距离空间权重矩阵进行全局和局部空间自相关分析.结果表明不同权重矩阵的全局Moran'sI指数检验都有显著的空间相关性,其中K最近邻矩阵时达到最大.我国省域经济呈现局部聚集性分布,不同空间权重矩阵在检测省域经济中,"高-高""低-低""高-低""低-高"空间聚集性方面存在一定差异.结论我国省域经济存在显著全局及局部自相关性.结合不同的空间权重矩阵进行综合分析,有助于深入掌握我国省域经济分布特征,为合理配置资源提供依据.     

基于空间非均衡视角的"大城市病"成因研究

本文通过多次实验,选取空间自相关程度最为显著的距离阈值,设定空间权重矩阵,使得空间权重矩阵更加符合我国城市分布特征,充分体现人口在城市集聚过程中的空间自回归机制,并结合广义空间模型和广义空间两阶段最小二乘法,实证探查“大城市病”成因,研究发现:就业机会、流通经济布局和公共服务的空间非均衡是导致人口过度集聚,从而引致“大城市病”的显著相关因素,并针对以上因素给出了对策建议。     

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

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。     

区域创新活动的空间效应及影响因素研究

研究目标：探究区域创新活动的空间效应及影响因素。研究方法：采用1998～2014年中国30个省份的面板数据,运用空间计量经济学,建立静态与动态空间面板模型,并从地理特征与社会经济特征两方面构建5个空间权重矩阵进行实证分析。研究发现：区域创新活动具有正向空间相关性,并呈现明显的空间集聚现象;地理特征与社会经济特征对区域创新活动均产生影响,其效果以社会经济特征更大;利用动态空间面板模型进行估计优于静态空间面板模型。研究创新：根据地理距离空间矩阵进行的空间相关性检验与R&D资本存量新估算方法使模型结果更准确;交通水平距离空间矩阵构建合理。研究价值：进行区域创新空间相关性分析时,可准确选择适当模型、估算方法及影响因素。     

生产性服务业集聚、空间溢出与制造业绿色创新

基于邻接空间、地理距离和经济距离三类权重矩阵，以空间杜宾模型考察生产性服务业集聚对制造业绿色创新的影响及空间溢出效应。研究结果表明，生产性服务业集聚可有效带动本省制造业绿色创新，但会抑制邻省制造业绿色创新。生产性服务业集聚对制造业绿色创新影响的空间溢出效应在邻接空间、地理距离、经济距离下存在明显差异，其中地理邻近地区更显著。多维度空间效应分解结果显示，生产性服务业集聚对制造业绿色创新的直接效应在地理距离权重矩阵下呈“梯度递减分布”特征。数字化产业发达省份的生产性服务集聚对邻省制造业绿色创新具有较强“虹吸效应”，不利于整体制造业绿色创新发展。是以，未来应优化生产性服务业集聚发展环境，施行区域差异化产业发展策略，加快推进制造业绿色转型升级。     

物流产业集聚的工业减排效应——基于长三角空间面板模型

根据物流产业的发展和工业新型绿色发展理念,选取长三角地区2004-2016年物流业集聚和工业污染排放的空间面板数据,构建"反距离平方"空间权重矩阵。根据Moran指数揭示长三角工业二氧化硫排放的空间集聚情况和空间格局,并对比不同时期工业二氧化硫排放空间分布特征。建立空间面板杜宾模型来考察物流业集聚对工业排放的影响。结果发现:长三角的工业二氧化硫排放集聚水平有增高趋势。物流业集聚水平降低了工业的废气排放,对于其他地区的溢出效应不明显。     

长三角都市圈空间集聚扩散效应研究

文章以空间经济学为理论基础,考察了长三角都市圈16个城市1981年至2010年间区域集聚扩散功能的演化,并将影响该功能的潜在动因划分为城市空间效应和总体经济增长效应。随后构建空间权重矩阵,利用空间计量经济学方法考察区域之间的互动关系,实证研究证明,在过去近三十年间长三角都市圈呈现明显的经济扩散效应,这种扩散效应既是长三角都市圈内城市之间存在空间竞争效应和空间补充效应的结果,也是部分城市存在空间总体经济增长效应的结果。     

一种空间矩阵选取的非嵌套检验方法

本文发展了一个在空间矩阵间进行选取的非嵌套检验方法,即基于伪嵌套检验的一个变形,利用回归残差的双重检验,在备选的空间矩阵中,比较其描述空间结构的优劣。利用中国省域空间矩阵进行的Monte Carlo模拟实验发现,该方法对于中国省域空间矩阵具有一定的区分效力;而空间系数的大小、模型的设定结构及是否利用行标准化的矩阵,对于空间矩阵比较的结果具有较大的影响。     

批发零售业水平对物流业竞争力的空间影响

物流业与批发零售业同为我国基础支柱产业,在国民经济发展过程中起到不可或缺的推动作用。物流业作为商品流通的支撑服务,是连接各个经济部门的纽带,其发展水平直接影响到商品的流通效率、流通成本和流通质量,进而影响到国家经济的整体效益。批发零售业作为国民经济中的第三产业,直接面向消费者,是连接生产者和消费者的桥梁,其发展水平不仅关系到消费者的消费水平和生活质量,同时对物流业的发展有着深远的影响。因此,研究我国批发零售业水平对物流业竞争力的空间影响,对促进批发零售业和物流业的发展具有重要意义。本文基于我国2011—2020年物流业与批发零售业的省际面板数据,运用熵权TOPSIS法量化我国物流业竞争力与批发零售业水平,利用空间杜宾模型实证检验批发零售业水平对物流业竞争力的空间效应,并将我国省份分为东、中、西部三个地区进行区域异质性分析,同时引入地理距离矩阵和经济距离矩阵作为空间权重矩阵,以此检验模型的稳健性。研究发现：全局空间自相关检验结果呈现我国物流业竞争力的空间集聚程度较高且波动上升的特征,局部空间自相关检验说明了中、东部地区大部分省份呈现“高—高”集聚态势,西部地区大部分省份呈现“低—低”集聚...     

A two-step approach to account for unobserved spatial heterogeneity

A two-step approach to account for unobserved spatial heterogeneity. Spatial Economic Analysis. Empirical analysis in economics often faces the difficulty that the data are correlated and heterogeneous in some unknown form. Spatial econometric models have been widely used to account for dependence structures, but the problem of directly dealing with unobserved spatial heterogeneity has been largely unexplored. The problem can be serious particularly if we have no prior information justified by economic theory. In this paper we propose a two-step procedure to identify endogenously spatial regimes in the first step and to account for spatial dependence in the second step. This procedure is applied to hedonic house price analysis.     

Spatial Growth Regressions: Model Specification,Estimation and Interpretation

Abstract

We attempt to clarify a number of points regarding use of spatial regression models for regional growth analysis. We show that as in the case of non-spatial growth regressions, the effect of initial regional income levels wears off over time. Unlike the non-spatial case, long-run regional income levels depend on: own region as well as neighbouring region characteristics, the spatial connectivity structure of the regions, and the strength of spatial dependence. Given this, the search for regional characteristics that exert important influences on income levels or growth rates should take place using spatial econometric methods that account for spatial dependence as well as own and neighbouring region characteristics, the type of spatial regression model specification, and weight matrix. The framework adopted here illustrates a unified approach for dealing with these issues.     

Raising the bar (10)

This editorial summarizes the papers published in issue 14(1) so as to raise the bar in applied spatial economic research and highlight new trends. The first paper applies the Shapley-based decomposition approach to determine the impact of firm-, linkage- and location-specific factors to the survival probability of enterprises. The second paper applies Bayesian comparison methods to identify simultaneously the most likely spatial econometric model and spatial weight matrix explaining new business creation. The third paper compares the performance of continuous and discrete approaches to explain subjective well-being across space. The fourth paper applies a multiple imputation approach to determine regional purchasing power parities at the NUTS-3 level using data available at the NUTS-2 level. Finally, the last paper constructs a regional input–output table for Japan from its national counterpart using and comparing the performance of four non-survey techniques.     

The spatial dynamics of new firm births during an economic crisis: the case of Great Britain, 2004–2012

Abstract

Spatial variations in entrepreneurial activity have been shown to be a time persistent phenomenon in many countries. This paper analyses how these spatial variations have been affected by the recent financial crisis within the context of theories of regional resilience and adaptability. The analysis applies Exploratory Spatial Data Analysis techniques to data on firm births across Local Authority Districts of Great Britain during the period 2004–2012. The results demonstrate that, whilst the overall shape of the spatial distribution of firm births remained persistent, there is evidence of an increase in regional inequality. This is primarily associated with a divergence between London and the rest of the distribution. London, together with part of its surrounding area, appears to constitute a resilient entrepreneurial regime that has generated a dynamic, adaptive response to the crisis with high rates of new firm formation in contrast to other regions which have remained locked into lower rates of entrepreneurship. This supports the view that regional entrepreneurship is a path dependent process: entrepreneurial regions are more adaptable to the effects of an exogenous shock than less entrepreneurial regions. Accordingly, entrepreneurship is a critical factor influencing the resilience of regions in responding to an economic crisis.     

Penalty and related estimation strategies in the spatial error model

Spatial autoregressive models are powerful tools in the analysis of data sets from diverse scientific areas of research such as econometrics, plant species richness, cancer mortality rates, image processing, analysis of the functional Magnetic Resonance Imaging (fMRI) data, and many more. An important class in the host of spatial autoregressive models is the class of spatial error models in which spatially lagged error terms are assumed. In this paper, we propose efficient shrinkage and penalty estimators for the regression coefficients of the spatial error model. We carry out asymptotic as well as simulation analyses to illustrate the gain in efficiency achieved by these new estimators. Furthermore, we apply the new methodology to housing prices data and provide a bootstrap approach to compute prediction errors of the new estimators.     

Do jobs follow people or people follow jobs? A meta-analysis of Carlino–Mills studies

Do jobs follow people or people follow jobs? A meta-analysis of Carlino–Mills studies. Spatial Economic Analysis. This study examines the classic question as to whether ‘jobs follow people’ or ‘people follow jobs’ by performing a meta-analysis of 321 results from 64 Carlino–Mills studies. It is found that the results are highly divergent, but that more results point towards ‘jobs following people’ than towards ‘people following jobs’. When it comes to the reasons for the variation in results, we find that the results are mostly shaped by the geographical location, spatial resolution, and population and employment characteristics present in the data, as well as by the model’s specification, its functional form and the spatial weight matrix specification.     

The interplay between the Bayesian and frequentist approaches: a general nesting spatial panel data model

The interplay between the Bayesian and Frequentist approaches: a general nesting spatial panel-data model. Spatial Economic Analysis. An econometric framework mixing the Frequentist and Bayesian approaches is proposed in order to estimate a general nesting spatial model. First, it avoids specific dependency structures between unobserved heterogeneity and regressors, which improves mixing properties of Markov chain Monte Carlo (MCMC) procedures in the presence of unobserved heterogeneity. Second, it allows model selection based on a strong statistical framework, characteristics that are not easily introduced using a Frequentist approach. We perform some simulation exercises, finding good performance of the properties of our approach, and apply the methodology to analyse the relation between productivity and public investment in the United States.     

空间加权矩阵设置与空间面板参数估计效率

总结了常用的空间加权矩阵的一般构建方法和研究领域内新提出的空间加权矩阵的构建方法,从宏观与微观层面,量化分析了空间加权矩阵设置对于空间面板参数估计效率、空间效应识别的影响效应。结论表明：宏观数据层面,随着空间加权矩阵复杂程度的提高,无论是空间面板固定效应模型还是空间面板随机效应模型,参数估计的有效性与一致性都显著提高并且广义矩参数估计方法优于拟极大似然估计方法,复合的空间加权矩阵条件下,拉格朗日乘子检验方法的功效更高;微观数据层面,回归结果表明四种不同类型的空间加权矩阵的设置,对于聚集外部性引致的企业全要素生产率增长的空间边界的识别具有显著影响,复合的空间加权矩阵更有效。     

我国空间规划体系的时代困境与模式重构

我国现行的空间规划体系成形于计划经济时期,虽伴随国家公共政策的变化经过多次调整,但规划体系仍不完善,规划的运行也出现了诸多问题,不仅降低了规划的有效性,并且浪费了大量运行成本。空间规划是协调人地关系和促进区域发展的重要手段,在实践中必须实现规划行政体系整合、规划编制体系整合和规划法规体系整合。本文提出了整合模式的初步设想,试图为空间规划体系的改革提供参考。