地理加权空间经济计量模型的GMM估计及区域金融发展收敛性实证研究
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摘要
同时处理横截面数据间的空间异质性与空间相关性一直是国际学术界有待解决的难点。目前仅有地理加权空间经济计量模型，从局部视角综合处理横截面数据间的空间相关性与空间异质性。Brunsdon等（Brunsdon，1998）从全局窗宽的视角对地理加权空间经济计量模型之地理加权空间滞后模型进行了最大似然（Maximum Likelihood，简称ML）估计研究；Paze等（Paze，2002）从局部窗宽的角度采用ML法，对地理加权空间经济计量模型进行估计。然而，用ML方法估计地理加权空间经济计量模型存在两点不足：其一，ML估计要求随机误差项服从正态分布或其他已知分布；其二，ML估计计算量巨大，特别是在大样本情况下ML法几乎无法完成计算。这是因为，在地理加权空间经济计量模型估计中涉及到最优窗宽的选择，其计算量远甚于一般空间经济计量模型。由于ML估计的局限性，地理加权空间经济计量模型实际应用受到很大限制。换言之，在误差项分布未知的情形下，保证估计量一致，快捷有效的估计地理加权空间经济计量模型，尚是经济管理空间计量研究中需要进一步解决的课题。
本研究针对最大似然估计的两点不足，拟提出地理加权空间经济计量模型的GMM估计框架，对地理加权空间经济计量模型估计进行数理推导和统计推断研究。在此基础上，以浙江省67个县市区数据，进行浙江省金融发展收敛性实证研究，弥补同类研究中中国数据文献不足；最后，从金融发展收敛性角度，为浙江省金融发展战略提供政策建议。具体说，本研究工作分两大步：
第一步，理论研究。主要完成以下两项工作：进行数理经济和经济计量文献阅读，完成地理加权空间经济计量模型理论研究，并用GAUSS软件解决编程技术。进行相关经济理论及实证研究文献梳理，总结已有研究成果取得的成就和存在的缺陷；
第二步，实证研究。分别运用地理加权回归模型分析方法和空间经济计量模型分析方法以及地理加权空间经济计量模型分析方法，依次进行基于空间异质性的实证研究、基于空间相关性实证研究、基于空间异质性与空间相关性并存的实证研究。
本研究对地理加权空间经济计量模型的数理推导研究的主要结论为，本研究提出的GMM估计方法能够有效减少模型估计中的计算量，解决了地理加权空间经济计量模型在估计中误差分布已知的前提限制，拓展了地理加权空间经济计量模型的估计方法。
本研究对浙江省县市区金融发展收敛性实证研究的主要结论有：
1.1997年与2008年浙江省县市区金融发展水平的地理格局全局看，发展水平相近的地区形成空间集聚，即发达地区与发达地区相邻，而落后地区与落后地区相邻；局部看，局部热点现象明显，产生了分别以杭州、温州以及金华衢州为中心的三个金融增长极，金融发展初始水平较低的地区主要分布在浙江安徽交界处与浙南除温州外的沿海地区（后者在2008年步入金融发达地区）。
2.1997-2008年间，作为金融大省的浙江，其县市区的金融发展总体上呈现出绝对收敛趋势。
3.1997-2008年间，作为金融大省的浙江，其县市区的金融发展总体上呈现出显著的空间异质性与空间相关性。空间异质性与空间相关性的并存没有改变绝对收敛趋势，但使得各县市区的收敛速度互不相同且收敛速度下降，其中，浙北各县市区的金融发展收敛速度低于浙南各县市区。
This paper set up a GMM framework to estimate and infer Spatial GeographicalWeighted Regression Model. GMM estimates can effectively reduce the computationalcomplexity, and solved the unknown error distribution restrictions, expanding the estimationmethod for SGWR model. The following major elements:
1、This paper set up a2SLS framework to estimate and infer GWR-SL model (GeographicallyWeighted Regression with Spatially Lagged Objective Variable Model).2SLS estimates caneffectively reduce the computational complexity, and solved the unknown error distributionrestrictions, expanding the GWR-SL model’s estimation method.
2、 This paper set up a GMM framework to estimate and infer GWR-SEA model(Geographically Weighted Regression with Spatial Error Autocorrelation Model). GMMestimates can effectively reduce the computational complexity, and solved the unknown errordistribution restrictions, expanding the GWR-SEA model’s estimation method.
3、 Using techniques of spatial econometrics、 GWR and SGWR model,we study theconvergence of financial development across67counties or cities rolling over12years inZhejiang Province.It is evident that the Spatial heterogeneity and spatial dependence acrossregions is strong enough to distort the traditional measure of Convergence. Taking Spatialheterogeneity and spatial dependence into account, we find that there was a significantabsolute convergence in Zhejiang province, but the speed of financial convergence issignificantly decreased, and the convergence speed of counties or cities in Zhejiang Provinceare difference. The south counties or cities’s speed of financial development are faster thanthe northern counties’. The financial development which is relatively backward can expect tocatch up with the relatively well-developed counties.
The theoretical innovation of above three parts in this research separately lies in:1、This study to resolve the error term distribution in unknown conditions, provide a newresearch approach to SGWR model has important theoretical value.2、The method is applied in the study which developed provinces and cities of regionalfinancial development convergence empirical analysis, not only geographically verifiableWeighted Generalized Method of Moments Estimation for Spatial Econometric ModelResearch on the actual feasibility of, and will be extended GMM application; the same time,the first time, spatial heterogeneity and spatial correlation into the convergence of regionalfinancial development empirical research, develop regional financial developmentconvergence study.
本研究针对最大似然估计的两点不足，拟提出地理加权空间经济计量模型的GMM估计框架，对地理加权空间经济计量模型估计进行数理推导和统计推断研究。在此基础上，以浙江省67个县市区数据，进行浙江省金融发展收敛性实证研究，弥补同类研究中中国数据文献不足；最后，从金融发展收敛性角度，为浙江省金融发展战略提供政策建议。具体说，本研究工作分两大步：
第一步，理论研究。主要完成以下两项工作：进行数理经济和经济计量文献阅读，完成地理加权空间经济计量模型理论研究，并用GAUSS软件解决编程技术。进行相关经济理论及实证研究文献梳理，总结已有研究成果取得的成就和存在的缺陷；
第二步，实证研究。分别运用地理加权回归模型分析方法和空间经济计量模型分析方法以及地理加权空间经济计量模型分析方法，依次进行基于空间异质性的实证研究、基于空间相关性实证研究、基于空间异质性与空间相关性并存的实证研究。
本研究对地理加权空间经济计量模型的数理推导研究的主要结论为，本研究提出的GMM估计方法能够有效减少模型估计中的计算量，解决了地理加权空间经济计量模型在估计中误差分布已知的前提限制，拓展了地理加权空间经济计量模型的估计方法。
本研究对浙江省县市区金融发展收敛性实证研究的主要结论有：
1.1997年与2008年浙江省县市区金融发展水平的地理格局全局看，发展水平相近的地区形成空间集聚，即发达地区与发达地区相邻，而落后地区与落后地区相邻；局部看，局部热点现象明显，产生了分别以杭州、温州以及金华衢州为中心的三个金融增长极，金融发展初始水平较低的地区主要分布在浙江安徽交界处与浙南除温州外的沿海地区（后者在2008年步入金融发达地区）。
2.1997-2008年间，作为金融大省的浙江，其县市区的金融发展总体上呈现出绝对收敛趋势。
3.1997-2008年间，作为金融大省的浙江，其县市区的金融发展总体上呈现出显著的空间异质性与空间相关性。空间异质性与空间相关性的并存没有改变绝对收敛趋势，但使得各县市区的收敛速度互不相同且收敛速度下降，其中，浙北各县市区的金融发展收敛速度低于浙南各县市区。
This paper set up a GMM framework to estimate and infer Spatial GeographicalWeighted Regression Model. GMM estimates can effectively reduce the computationalcomplexity, and solved the unknown error distribution restrictions, expanding the estimationmethod for SGWR model. The following major elements:
1、This paper set up a2SLS framework to estimate and infer GWR-SL model (GeographicallyWeighted Regression with Spatially Lagged Objective Variable Model).2SLS estimates caneffectively reduce the computational complexity, and solved the unknown error distributionrestrictions, expanding the GWR-SL model’s estimation method.
2、 This paper set up a GMM framework to estimate and infer GWR-SEA model(Geographically Weighted Regression with Spatial Error Autocorrelation Model). GMMestimates can effectively reduce the computational complexity, and solved the unknown errordistribution restrictions, expanding the GWR-SEA model’s estimation method.
3、 Using techniques of spatial econometrics、 GWR and SGWR model,we study theconvergence of financial development across67counties or cities rolling over12years inZhejiang Province.It is evident that the Spatial heterogeneity and spatial dependence acrossregions is strong enough to distort the traditional measure of Convergence. Taking Spatialheterogeneity and spatial dependence into account, we find that there was a significantabsolute convergence in Zhejiang province, but the speed of financial convergence issignificantly decreased, and the convergence speed of counties or cities in Zhejiang Provinceare difference. The south counties or cities’s speed of financial development are faster thanthe northern counties’. The financial development which is relatively backward can expect tocatch up with the relatively well-developed counties.
The theoretical innovation of above three parts in this research separately lies in:1、This study to resolve the error term distribution in unknown conditions, provide a newresearch approach to SGWR model has important theoretical value.2、The method is applied in the study which developed provinces and cities of regionalfinancial development convergence empirical analysis, not only geographically verifiableWeighted Generalized Method of Moments Estimation for Spatial Econometric ModelResearch on the actual feasibility of, and will be extended GMM application; the same time,the first time, spatial heterogeneity and spatial correlation into the convergence of regionalfinancial development empirical research, develop regional financial developmentconvergence study.
引文
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