空间计量经济学模型的研究

【作者】 王森；

【导师】 魏传华；

【作者基本信息】 中央民族大学 ， 概率论与数理统计， 2011， 硕士

【摘要】 在传统的统计学中,研究变量之间相互关系时很少考虑到空间相关性,比如经典的时间学列分析,还有在时间序列和截面数据的基础上产生的面板数据(Panel Data)。然而,随着理论研究与应用实践的不断发展,越来越多学者开始注意研究变量之间的在空间上的相依关系。空间自相关的概念来源于时间序列的自相关,它反映的是在空间域上某一位置与其邻近位置上同一变量的相关性。例如两个邻近省份的经济、教育等发展程度有无类似或者截然相反等等。在研究空间数据的相关性时,通常需要建立一些可以反映空间变量特征的模型来研究变量之间的关系。常用的模型有空间自回归模型(Spatial Autoregression model)、地理加权回归模型(Geographical weighted regression model),本文所要研究的空间面板误差分量模型和地理加权回归模型的嵌套形式,就是在这两种模型的基础上产生的。空间误差分量模型是Kelejian和Robinson于1993年和1995年提出了一种空间回归模型,它是在空间自回归模型的基础上,对回归干扰项提出的一种新的假设,从根本上说,是对干扰项是否存在异质性的一种假设。本文在此模型的基础上将它与面板数据相结合,兼顾了截面间的截面效应和空间关系,比单纯使用空间数据和单纯使用面板数据的研究方法要更加优越,具有很高的应用价值。地理加权回归模型是一个局部空间模型,它将空间地理位置嵌入到回归系数之中,既能反映自变量与因变量的关系,又能反映数据的空间特性。本文在此模型的基础上引入了区域嵌套的概念,将原空间单元划分为几个区域,这样在研究数据空间特性时,更多了考虑了同区域中空间单元的共性和不同区域间的异质性。更多还原

【Abstract】 In the traditional statistics, when we study the relationship between variables, we rarely consider about the spatial dependence, like classic time serial, and the panel data based on time serial and cross data. However, with the development of theoretical study and practical application, more and more scholars have began to pay attention to study the spatial dependence between variables.the concept of spatial dependence come from the dependence of time serial, and it shows the relativity of the same variable between one area and its neighboring area. For example, if there is similarity in the developing degree of the economic or education of two adjacent provinces, or they are right obverse, and so on. When studying the relativity, usually we need to erect some models that could show the character of spatial variables in order to study the relationship between variables. The normal models are Spatial Auto-regression model and Geographical weighted regression model. The nested format of spatial panel error weighted model and the geographical weighted regressive model that this thesis is going to study is just based on these two models.Spatial panel error weighted model is one kind of spatial regression model that was put forward by Kelejian and Robinson in 1993 and in 1995 separately. It suggested one new hypothesis to disturbing item based on the spatial model. Essentially, it is a hypothesis about if there is heterogeneity. This thesis combines it with panel data and considers the cross effect and spatial relationship between cross sections. It is more outstanding and has much more practical value comparing with the method that purely using spatial data and purely using panel data.Geographical weighted regressive model is one local spatial model and it embeds spatial geographical location in regression coefficients. It not only shows the relationship between independent variable and dependent variable, but also shows the spatial character of data. This thesis introduces the concept of zone based on this model, and divides the initial spatial area into different zone. Thus, when studying the spatial character of data, we consider the commonness of the same zone and heterogeneity of different zone.更多还原