1985-2015年中国省际人口迁移网络特征

doi:10.18306/dlkxjz.2017.11.006

Abstract

Abstract:

With the rapid development of urban economy and the promotion of urbanization, great changes have taken place in the spatial pattern of population migration in China. Migration has played an important role in the economic, social, and cultural development of cities. Based on the provincial population migration matrix data of 31 provinces, autonomous regions, and municipalities in 1985-2015, a social network analysis was conducted to investigate the overall characteristics of interprovincial population migration network and the role of each node. The results show that: (1) Network density of interprovincial population migration has experienced a slow decline in 1985-2000 and a continuous increase in 2000-2015. The concentrated migration of population from the northwest, southwest, and central regions to the eastern developed areas has become the mainstream of development. (2) The inward center potential of population migration network rapidly increased in 1985-2005 and gradually declined in 2005-2015. It indicates that the number of important population moving areas were increasing gradually (such as Tianjin and Fujian), towards a "multi-polarization" development. The outward center potential was always at a low level and exhibited a trend of fluctuation. The inward center potential was clearly larger than the outward center potential. It indicates that the population migration area is relatively concentrated, and the population emigration area is relatively dispersed. (3) The interprovincial population migration network can be divided into 5 groups: Northeast-North China population linkage area, Central Plains-Yangtze River Delta population linkage area, Middle South-Pearl River Delta population linkage area, southwest population linkage area, and northwest population linkage area. Among them, the Central Plains-Yangtze River Delta population linkage area was the most closely linked between and within group; Middle South-Pearl River Delta population linkage area had the highest total population migration. The Northeast-North China population linkage area had a stronger internal connection and only strongly linked with the northwest region externally. (4) According to the population migration analysis, the 31 provinces, autonomous regions, and municipalities can be divided into three major categories: net population migration areas including eight provinces, autonomous regions, municipalities (Guangdong, Zhejiang, Beijing, Jiangsu, Shanghai, Tianjin, Fujian, and Xinjiang); population balanced areas including six provinces and autonomous regions (Hainan, Inner Mongolia, Tibet, Qinghai, Ningxia, and Liaoning), and population net emigration areas including 17 provinces, autonomous regions, and municipalities including Sichuan, Henan, and so on. (5) Based on the centrality analysis and the core-periphery structure, contributions of the provinces, autonomous regions, and municipalities to population migration was very different. In the interprovincial population migration network, a few core nodes had strong control over the total amount and path of population migration. About 25-30% core provinces controlled 70-80% of the population migration and path of the country, and the control power continued to rise. Among these provinces, Guangdong and Beijing had overall control significance. Jiangsu, Shaanxi, Sichuan, and Zhejiang were largely among the core control nodes. The role of Shanghai, Tianjin, Inner Mongolia, and Fujian as core areas had gradually increased. The role of Henan, Hubei, Hebei, and Xinjiang as core areas had declined. The overall migration path of the country is northward.

Key words: interprovincial migration, social network analysis, network characteristics, China

Mengjue ZHU, Fang LI. Spatial characteristics of China's interprovincial migration network during 1985-2015[J].PROGRESS IN GEOGRAPHY, 2017, 36(11): 1368-1379.

Figures/Tables 8

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References 34

[1]	丁金宏, 刘振宇, 程丹明, 等. 2005. 中国人口迁移的区域差异与流场特征[J]. 地理学报, 60(1): 106-114. doi: 10.3321/j.issn:0375-5444.2005.01.012
	[Ding J H, Liu Z Y, Cheng D M, et al.2005. Areal differentiation of inter-provincial migration in China and characteristics of the flow field[J]. Acta Geographica Sinica, 60(1): 106-114.] doi: 10.3321/j.issn:0375-5444.2005.01.012
[2]	董上, 蒲英霞, 马劲松, 等. 2014. 中国省际人口迁移的复杂网络研究[J]. 南方人口, 29(2): 54-61. doi: 10.3969/j.issn.1004-1613.2014.02.007
	[Dong S, Pu Y X, Ma J S, et al.2014. A study of the complex network of China's interprovincial migration[J]. South China Population, 29(2): 54-61.] doi: 10.3969/j.issn.1004-1613.2014.02.007
[3]	段成荣. 2000. 影响我国省际人口迁移的个人特征分析: 兼论“时间”因素在人口迁移研究中的重要性[J]. 人口研究, 24(4): 14-22.
	[Duan C R.2000. Individual level determinants of interprovincial migration in China: On the effects of time sequence in migration studies[J]. Population Research, 24(4): 14-22.]
[4]	胡小武. 2011. 人口“就近城镇化”: 人口迁移新方向[J]. 西北人口, 32(1): 1-5.
	[Hu X W.2011. Neighborhood urbanization strategy and China's town-urbanization road rethinking[J]. Northwest Population, 32(1): 1-5.]
[5]	李德辉. 1981. 关于人口迁移规律的初探: 人口迁移的历史回顾、目前状况及未来趋势[J]. 人口学刊, (2): 41-47.
	[Li D H.1981. Guanyu renkou qianyi guilv de chutan: Renkou qianyi de lishi huigu, muqian zhuangkuang ji weilai qushi, (2): 41-47.]
[6]	李扬, 刘慧, 汤青. 2015. 1985-2010年中国省际人口迁移时空格局特征[J]. 地理研究, 34(6): 1135-1148.
	[Li Y, Liu H, Tang Q.2015. Spatial-temporal patterns of China's interprovincial migration during 1985-2010[J]. Geographical Research, 34(6): 1135-1148.]
[7]	刘望保, 汪丽娜, 陈忠暖. 2012. 中国省际人口迁移流场及其空间差异[J]. 经济地理, 32(2): 8-13.
	[Liu W B, Wang L N, Chen Z N.2012. Flow field and its regional differentiation of iner-provincial migration in China[J]. Economic Geography, 32(2): 8-13.]
[8]	刘晏伶, 冯健. 2014. 中国人口迁移特征及其影响因素: 基于第六次人口普查数据的分析[J]. 人文地理, 2014, 29(2): 129-137.
	[Liu Y L, Feng J.2014. Characteristic and impact factors of migration in China: Based on the analysis of the sixth census data[J]. Human Geography, 29(2): 129-137.]
[9]	刘颖, 邓伟, 宋雪茜, 等. 2017. 基于综合城镇化视角的省际人口迁移格局空间分析[J]. 地理科学, 37(8): 1151-1158.
	[Liu Y, Deng W, Song X Qet al.2017. Spatial pattern of interprovincial population migration from the comprehensive urbanization perspective[J]. Scientia Geographica Sinica, 37(8): 1151-1158.]
[10]	逯进, 郭志仪. 2014. 中国省域人口迁移与经济增长耦合关系的演进[J]. 人口研究, 38(6): 40-56.
	[Lu J, Guo Z Y.2014. The evolution of coupling relationship between population migration and economic growth in China[J]. Population Research, 38(6): 40-56.]
[11]	马侠, 王维志. 1988. 中国城镇人口迁移与城镇化研究: 中国74城镇人口迁移调查[J]. 人口研究, 12(2): 1-7.
	[Ma X, Wang W Z.1988. Zhongguo chengzhen renkou qianyi yu chengzhenhua yanjiu: Zhongguo 74 chengzhen renkou qianyi diaocha[J]. Population Research, 12(2): 1-7.]
[12]	蒲英霞, 韩洪凌, 葛莹, 等. 2016. 中国省际人口迁移的多边效应机制分析[J]. 地理学报, 26(2): 205-216. doi: 10.11821/dlxb201602003
	[Pu Y X, Han H L, Ge Y, et al.2016. Multilateral mechanism analysis of interprovincial migration flows in China[J]. Acta Geographica Sinica, 26(2): 205-216.] doi: 10.11821/dlxb201602003
[13]	唐家龙. 2008. 论时变性因素对人口迁移选择性的影响: 基于数据处理方法的视角[J]. 中国人口科学,(2): 65-71, 96. doi: 10.3969/j.issn.1000-7881.2008.02.008
	[Tang J L.2008. The impact of time varying properties on migration selectivity: A perspective from data management[J]. Chinese Journal of Population Science,(2): 65-71, 96.] doi: 10.3969/j.issn.1000-7881.2008.02.008
[14]	王桂新. 1989. 不同地域层次间人口迁移问题的研究: 根据中间地域层次小城镇角度分析[J]. 西北人口, (2): 30-37.
	[Wang G X.1989. Butong diyu cengcijian renkou qianyi wenti de yanjiu: Genju zhongjian diyu cengci xiaochengzhen jiaodu fenxi[J]. Northwest Population, (2): 30-37.]
[15]	王桂新, 潘泽瀚, 陆燕秋. 2012. 中国省际人口迁移区域模式变化及其影响因素: 基于2000和2010年人口普查资料的分析[J]. 中国人口科学,(5): 2-13, 111.
	[Wang G X, Pan Z H, Lu Y Q.2012. China's inter-provincial migration patterns and influential factors: Evidence from year 2000 and 2010 population census of China[J]. Chinese Journal of Population Science,(5): 2-13, 111.]
[16]	王珏, 陈雯, 袁丰. 2014. 基于社会网络分析的长三角地区人口迁移及演化[J]. 地理研究, 2014, 33(2): 385-400. doi: 10.11821/dlyj201402016
	[Wang J, Chen W, Yuan F.2014. Human mobility and evolution based on social network: An empirical analysis of Yangtze River Delta[J]. Geographical Research, 33(2): 385-400.] doi: 10.11821/dlyj201402016
[17]	杨传开, 宁越敏. 2015. 中国省际人口迁移格局演变及其对城镇化发展的影响[J]. 地理研究, 34(8): 1492-1506. doi: 10.11821/dlyj201508008
	[Yang C K, Ning Y M.2015. Evolution of spatial pattern of inter-provincial migration and its impacts on urbanization in China[J]. Geographical Research, 34(8): 1492-1506.] doi: 10.11821/dlyj201508008
[18]	杨义武, 林万龙, 张莉琴. 2017. 地方公共品供给与人口迁移: 来自地级及以上城市的经验证据[J]. 中国人口科学,(2): 93-103, 128.
	[Yang Y W, Lin W L, Zhang L Q.2017. The supply of local public goods and population migration: Empirical evidence from 260 cities at the prefecture level or above[J]. Chinese Journal of Population Science,(2): 93-103, 128.]
[19]	臧玉珠, 周生路, 周兵兵, 等. 2016. 1995-2010年中国省际人口迁移态势与空间格局演变: 基于社会网络分析的视角[J]. 人文地理, 31(4): 112-118.
	[Zang Y Z, Zhou S L, Zhou B B, et al.2016. The volume changes and spatial pattern dynamics of China's interprovincial migration: A perspective of social network analysis[J]. Human Geography, 31(4): 112-118.]
[20]	钟奕纯, 冯健. 2017. 城市迁移人口居住空间分异: 对深圳市的实证研究[J]. 地理科学进展, 36(1): 125-135. doi: 10.18306/dlkxjz.2017.01.012
	[Zhong Y C, Feng J.2017. Residential spatial differentiation of migrant population within the city: A case study of Shenzhen[J]. Progress in Geography, 36(1): 125-135.] doi: 10.18306/dlkxjz.2017.01.012
[21]	周皓, 梁在. 2006. 中国的返迁人口: 基于五普数据的分析[J]. 人口研究, 30(3): 61-69. doi: 10.3969/j.issn.1000-6087.2006.03.012
	[Zhou H, Liang Z.2006. Return migration in China: An analysis of the Fifth Census data[J]. Population Research, 30(3): 61-69.] doi: 10.3969/j.issn.1000-6087.2006.03.012
[22]	Chun Y W.2008. Modeling network autocorrelation within migration flows by eigenvector spatial filtering[J]. Journal of Geographical Systems, 10(4): 317-344. doi: 10.1007/s10109-008-0068-2
[23]	de Montis A, Barthélémy M, Chessa A, et al.2007. The structure of interurban traffic: A weighted network analysis[J]. Environment and Planning B: Planning and Design, 34(5): 905-924. doi: 10.1068/b32128
[24]	de Vries J J, Nijkamp P, Rietveld P.2009. Exponential or power distance-decay for commuting? An alternative specification[J]. Environment and Planning A, 41(2): 461-480. doi: 10.1068/a39369
[25]	Gargiulo F, Lenormand M, Huet S, et al.2012. Commuting network models: Getting the essentials[J]. Journal of Artificial Societies and Social Simulation, 15(2): 6. doi: 10.18564/jasss.1964
[26]	Jeanty P W, Partridge M, Irwin E.2010. Estimation of a spatial simultaneous equation model of population migration and housing price dynamics[J]. Regional Science and Urban Economics, 40(5): 343-352. doi: 10.1016/j.regsciurbeco.2010.01.002
[27]	Lee E S.1966. A theory of migration[J]. Demography, 3(1): 47-57. doi: 10.2307/2060063
[28]	Lewis W A.1954. Economic development with unlimited supplies of labour[J]. The Manchester School, 22(2): 139-191. doi: 10.1111/j.1467-9957.1954.tb00021.x
[29]	Noulas A, Scellato S, Lambiotte R, et al.2012. A tale of many cities: Universal patterns in human urban mobility[J]. PLoS One, 7(5): e37027. doi: 10.1371/journal.pone.0037027 pmid: 3466163
[30]	Ravenstein E G.1885. The laws of migration[J]. Journal of the Statistical Society of London, 48(2): 167-235. doi: 10.2307/2979181
[31]	Schultz T W.1962. Reflections on investment in man[J]. The Journal of Political Economy, 70(5): 1-8. doi: 10.1086/258723
[32]	Simini F, González M C, Maritan A, et al.2012. A universal model for mobility and migration patterns[J]. Nature, 484: 96-100. doi: 10.1038/nature10856
[33]	Todaro M P.1969. A model of labor migration and urban unemployment in less developed countries[J]. American Economic Review, 59(1): 138-148. doi: 10.1111/j.1467-8624.1997.tb01934.x
[34]	Zipf G K.1946. The P1 P2/D hypothesis: On the intercity movement of persons[J]. American Sociological Review, 11(6): 677-686. doi: 10.2307/2087063

网络指标	1985-1990年	1990-1995年	1995-2000年	2000-2005年	2005-2010年	2010-2015年	1985-2000年年均增幅/%	2000-2010年年均增幅/%	2010-2015年年均增幅/%	1985-2015年年均增幅/%
网络密度	0.607	0.543	0.505	0.510	0.531	0.563	-1.81	0.50	1.48	-0.31
内向中心势	0.508	0.469	0.703	0.736	0.691	0.639	3.31	-0.17	-1.94	0.96
外向中心势	0.187	0.147	0.221	0.184	0.140	0.122	1.71	-4.47	-3.34	-1.75

凝聚子群		指标	东北—华北人口联动区	中原—长三角人口联动区	中南—华南人口联动区	西南人口联动区	西北人口联动区
东北—华北人口联动区	北京、天津、河北、黑龙江、吉林、辽宁、内蒙古、山东、山西	迁移量/万人	2279.28	615.06	363.87	128.11	165.42
东北—华北人口联动区	北京、天津、河北、黑龙江、吉林、辽宁、内蒙古、山东、山西	网络密度	0.51	0.15	0.06	0.03	0.04
中原—长三角人口联动区	江苏、上海、浙江、安徽、河南	迁移量/万人	889.74	2693.24	1064.68	214.80	284.95
中原—长三角人口联动区	江苏、上海、浙江、安徽、河南	网络密度	0.06	0.60	0.19	0.08	0.00
中南—华南人口联动区	广东、广西、海南、福建、湖北、湖南、江西	迁移量/万人	403.97	1352.71	4136.61	388.59	103.71
中南—华南人口联动区	广东、广西、海南、福建、湖北、湖南、江西	网络密度	0.02	0.29	0.57	0.07	0.00
西南人口联动区	四川、云南、重庆、贵州、西藏	迁移量/万人	347.21	1177.90	1652.93	549.78	190.75
西南人口联动区	四川、云南、重庆、贵州、西藏	网络密度	0.06	0.29	0.25	0.33	0.05
西北人口联动区	陕西、甘肃、宁夏、青海、新疆	迁移量/万人	303.37	271.21	229.49	89.51	277.33
西北人口联动区	陕西、甘肃、宁夏、青海、新疆	网络密度	0.24	0.20	0.09	0.10	0.45

省区	1985-1990年	1990-1995年	1995-2000年	2000-2005年	2005-2010年	2010-2015年	省区	1985-1990年	1990-1995年	1995-2000年	2000-2005年	2005-2010年	2010-2015年
北京	0.210	0.224	0.289	0.436	0.463	0.375	河南	0.151	0.099	0.014	0.204	0.010	0.010
广东	0.213	0.300	0.582	0.310	0.327	0.286	河北	0.087	0.137	0.088	0.003	0.028	0.006
内蒙古	0.024	0.040	0.041	0.116	0.306	0.222	云南	0.011	0.020	0.037	0.026	0.001	0.003
天津	0.022	0.011	0.011	0.014	0.037	0.215	辽宁	0.041	0.080	0.017	0.202	0.028	0.003
陕西	0.131	0.104	0.088	0.015	0.232	0.210	吉林	0.001	0.001	0.006	0.002	0.004	0.003
江苏	0.151	0.162	0.166	0.146	0.196	0.143	山西	0.027	0.023	0.033	0.017	0.014	0.002
新疆	0.014	0.173	0.245	0.182	0.195	0.128	黑龙江	0.003	0.001	0.006	0.002	0.002	0.002
浙江	0.056	0.121	0.094	0.222	0.251	0.124	湖南	0.037	0.008	0.002	0.000	0.000	0.001
四川	0.148	0.250	0.033	0.074	0.024	0.070	江西	0.012	0.001	0.000	0.002	0.001	0.001
上海	0.025	0.066	0.052	0.069	0.091	0.066	安徽	0.075	0.009	0.002	0.004	0.000	0.000
湖北	0.092	0.045	0.022	0.008	0.013	0.043	广西	0.014	0.004	0.000	0.000	0.000	0.000
福建	0.017	0.058	0.021	0.062	0.039	0.043	青海	0.002	0.009	0.004	0.011	0.004	0.000
甘肃	0.062	0.093	0.097	0.093	0.139	0.041	宁夏	0.002	0.002	0.000	0.000	0.000	0.000
重庆	0.000	0.000	0.025	0.013	0.000	0.023	海南	0.002	0.006	0.000	0.000	0.000	0.000
山东	0.158	0.202	0.267	0.244	0.056	0.021	西藏	0.000	0.000	0.000	0.000	0.000	0.000
贵州	0.022	0.006	0.000	0.017	0.067	0.016

时段	核心节点
1985-1990	广东、北京、山东、江苏、河南、四川、陕西、湖北、河北
1990-1995	广东、北京、四川、山东、新疆、江苏、河北、浙江、陕西、河南
1995-2000	广东、北京、山东、新疆、江苏、浙江、河北、陕西
2000-2005	北京、广东、山东、浙江、陕西、新疆、江苏、四川
2005-2010	北京、广东、内蒙古、浙江、陕西、江苏、新疆、上海
2010-2015	北京、广东、内蒙古、天津、陕西、江苏、浙江、四川、上海、福建

Spatial characteristics of China's interprovincial migration network during 1985-2015

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