【摘要】：人口遷移作為一種空間行為,在空間上具有明顯的指向性,表現(xiàn)為遷入地和遷出地在地域上呈現(xiàn)一定的空間集聚特征。然而,大量對于我國人口遷移狀況的研究都忽視了這一空間指向性對于分布模式和機(jī)制的影響。本文利用全國第五次人口普查省際人口遷移數(shù)據(jù)和相關(guān)資料,以空間自相關(guān)分析為基礎(chǔ),對1995-2000年間我國省際人口遷移的空間模式與動(dòng)力機(jī)制進(jìn)行了初步分析。 在空間分布模式方面：通過對比各省遷移量指標(biāo)發(fā)現(xiàn),我國省際人口遷移流中存在明顯的地域集聚特征,中部地區(qū)為遷出流高值集聚區(qū)域,而東部地區(qū)尤其是東部沿海地區(qū)則為遷入流的高值集聚區(qū)域；采用全局Moran指數(shù)研究遷移流中的遷入地和遷出地空間自相關(guān),發(fā)現(xiàn)我國省際人口遷移空間指向性明顯,從一個(gè)區(qū)域出發(fā)(或抵達(dá)該區(qū)域)的人口遷移流均受到周邊地區(qū)人口遷移的影響；采用遷移流局部空間自相關(guān)分析指數(shù)Gij挖掘我國省際人口遷移流中的局部關(guān)聯(lián)模式,發(fā)現(xiàn)中國省際人口遷移數(shù)據(jù)中有5個(gè)省份的遷入流和9個(gè)省份的遷出流存在顯著的高值集聚區(qū)域,且遷移流局部關(guān)聯(lián)模式規(guī)律性明顯。 在遷移機(jī)制方面：文中先后采用重力模型(僅用距離變量來捕捉人口遷移中距離衰減效應(yīng))和空間OD模型(采用因變量空間滯后的形式對遷移流的空間指向性加以考慮)來研究中國省際人口遷移的動(dòng)力機(jī)制,并量化空間自相關(guān)對遷移機(jī)制的影響。通過對重力模型和空間OD模型的估計(jì)結(jié)果進(jìn)行對比后發(fā)現(xiàn)：(1)空間OD模型在參數(shù)估計(jì)和模型擬合等方面均優(yōu)于傳統(tǒng)的重力模型。在選取相同解釋變量的情況下,空間OD模型的殘差平方和僅為傳統(tǒng)重力模型的47%；其模型擬合指標(biāo)AIC的值也比傳統(tǒng)重力模型的相應(yīng)值大大縮�。�(2)在對于中國人口遷移動(dòng)力機(jī)制的研究中,如果不考慮人口遷移流之間的空間自相關(guān)(空間指向性)現(xiàn)象,將會(huì)導(dǎo)致對各社會(huì)、經(jīng)濟(jì)等變量作用和距離衰減效應(yīng)的過高估計(jì),且過高估計(jì)程度最高達(dá)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%.
【學(xué)位授予單位】：南京大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2012
【分類號】：C922

【引證文獻(xiàn)】

相關(guān)碩士學(xué)位論文 前1條

1 張佳琦;陜西省人口遷移與經(jīng)濟(jì)發(fā)展差異性研究[D];西北大學(xué);2013年

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本文編號：2369829