基于空间自相关的中国省际人口迁移流分布模式与动力机制研究

发布时间：2018-12-09 18:20

【摘要】：人口迁移作为一种空间行为,在空间上具有明显的指向性,表现为迁入地和迁出地在地域上呈现一定的空间集聚特征。然而,大量对于我国人口迁移状况的研究都忽视了这一空间指向性对于分布模式和机制的影响。本文利用全国第五次人口普查省际人口迁移数据和相关资料,以空间自相关分析为基础,对1995-2000年间我国省际人口迁移的空间模式与动力机制进行了初步分析。在空间分布模式方面：通过对比各省迁移量指标发现,我国省际人口迁移流中存在明显的地域集聚特征,中部地区为迁出流高值集聚区域,而东部地区尤其是东部沿海地区则为迁入流的高值集聚区域；采用全局Moran指数研究迁移流中的迁入地和迁出地空间自相关,发现我国省际人口迁移空间指向性明显,从一个区域出发(或抵达该区域)的人口迁移流均受到周边地区人口迁移的影响；采用迁移流局部空间自相关分析指数Gij挖掘我国省际人口迁移流中的局部关联模式,发现中国省际人口迁移数据中有5个省份的迁入流和9个省份的迁出流存在显著的高值集聚区域,且迁移流局部关联模式规律性明显。在迁移机制方面：文中先后采用重力模型(仅用距离变量来捕捉人口迁移中距离衰减效应)和空间OD模型(采用因变量空间滞后的形式对迁移流的空间指向性加以考虑)来研究中国省际人口迁移的动力机制,并量化空间自相关对迁移机制的影响。通过对重力模型和空间OD模型的估计结果进行对比后发现：(1)空间OD模型在参数估计和模型拟合等方面均优于传统的重力模型。在选取相同解释变量的情况下,空间OD模型的残差平方和仅为传统重力模型的47%；其模型拟合指标AIC的值也比传统重力模型的相应值大大缩小；(2)在对于中国人口迁移动力机制的研究中,如果不考虑人口迁移流之间的空间自相关(空间指向性)现象,将会导致对各社会、经济等变量作用和距离衰减效应的过高估计,且过高估计程度最高达80%。
[Abstract]:As a kind of spatial behavior, population migration has obvious directivity in space. However, a large number of studies on the situation of population migration in China have ignored the influence of this spatial directivity on distribution patterns and mechanisms. Based on the data of interprovincial migration and related data of the fifth national census, this paper makes a preliminary analysis of the spatial pattern and dynamic mechanism of interprovincial population migration in China from 1995 to 2000 on the basis of spatial autocorrelation analysis. In terms of spatial distribution pattern: by comparing the index of migration quantity between provinces, it is found that there are obvious regional agglomeration characteristics in interprovincial migration flow in China, and the central region is the high value gathering area of emigration flow. The eastern region, especially the eastern coastal area, is the high value concentration area of the inflow current. Using the global Moran index to study the autocorrelation between the migration space and the migration space in the migration flow, it is found that the spatial orientation of the inter-provincial population migration in China is obvious. Migration flows from (or arriving in) a region are affected by population movements in the surrounding area; Using the local spatial autocorrelation analysis index (Gij) of migration flow to mine the local correlation model in the migration flow of interprovincial population in China. It is found that there are significant high value concentration areas in the migration flows of 5 provinces and 9 provinces in the data of interprovincial migration in China, and the regularity of local correlation model of migration flows is obvious. In the aspect of migration mechanism, gravity model (only distance variable is used to capture distance attenuation effect in migration) and spatial OD model (spatial directivity addition of dependent variable space lag) are adopted in this paper. To study the dynamic mechanism of interprovincial population migration in China, The effect of spatial autocorrelation on migration mechanism is quantified. By comparing the estimation results of gravity model and spatial OD model, it is found that: (1) the spatial OD model is superior to the traditional gravity model in parameter estimation and model fitting. When the same explanatory variables are selected, the sum of residual square of spatial OD model is only 47 times that of traditional gravity model, and the value of model fitting index AIC is much smaller than that of traditional gravity model. (2) in the study of the dynamic mechanism of population migration in China, if the spatial autocorrelation (spatial directivity) between migration flows is not taken into account, it will lead to the development of social relations. The effect of economic iso-variable and distance attenuation is overestimated, and the degree of overestimation is as high as 80%.
【学位授予单位】：南京大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：C922

【引证文献】