中国城市流动人口户籍迁移意愿的空间格局及影响因素——基于2012年全国流动人口动态监测调查数据

doi:10.11821/dlxb201610003

Abstract

Abstract:

Based on data from the 2012 national migrant population dynamic monitoring survey and related statistics, this article examines the spatial pattern and its determinants of migrants' intention of hukou transfer of China's 276 prefecture- and provincial-level cities, using GIS spatial analysis and statistical modelling. The results show that the overall level of migrants' hukou transfer intention of the cities is not high, and varies significantly among different cities. The intention of migrants' hukou transfer increases as the administrative level and/or the size of their destination cities increase. Meanwhile, migrants' hukou transfer intention is generally higher in coastal mega-city regions than in other cities, but it is also relatively high in some provincial capital cities and small and medium-sized cities in some inland regions with good transport location and resource endowment. The spatial pattern of migrants' intention of hukou transfer is shaped jointly by both the characteristics of the destination cities and migrants themselves characteristics, with the former exerting more influence than the latter. High level of socioeconomic development and good location of the destination cities can effectively promote their migrants' intention of hukou transfer; however, their level of basic public services does not have the same effect. The degree of migrants' social integration in the destination cities also exerts positive effects on their hukou transfer intention. However, having medical insurance, the concentration in the secondary labor market and higher household income are negatively related to such intention; furthermore, the individual and family characteristics of migrants do not have a significant impact on it. Finally, on the basis of the above findings, we put forward some suggestions for relevant policy making.

Key words: migrants, hukou transfer intention, spatial difference, prefecture- and provincial-level cities, China

LIN Liyue,ZHU Yu. Spatial variation and its determinants of migrants' Hukou transfer intention of China's prefecture- and provincial-level cities：Evidence from the 2012 national migrant population dynamic monitoring survey[J].Acta Geographica Sinica, 2016, 71(10): 1696-1709.

Figures/Tables 8

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城市类型	城市及数量	迁移意愿区间(%)	平均值(%)
I类(极高迁移意愿城市)	盐城市、临沂市、厦门市、泰安市、大连市、大庆市、七台河市、雅安市、酒泉市、上海市、北京市、克拉玛依市、中卫市、盘锦市14个城市	70.01~90.00	77.35
II类(高迁移意愿城市)	常州市、莱芜市、辽阳市、铜仁市、银川市、宜昌市、徐州市、惠州市、贵阳市、巴中市、聊城市、日照市、汕头市、防城港市、石嘴山市、无锡市、池州市、十堰市、朔州市、珠海市、洛阳市、铁岭市、丽江市、哈尔滨市、廊坊市、广州市、乌鲁木齐市、辽源市、河源市、深圳市、眉山市、青岛市、烟台市、威海市、天津市、营口市、濮阳市、伊春市、大同市、武汉市、德州市、南京市、济南市、通辽市、淮北市45个城市	50.01~70.00	55.97
III类(较高迁移意愿城市)	邯郸市、苏州市等66个城市	41.01~50.00	45.35
IV类(中等迁移意愿城市)	淮南市、临沧市和衡阳市等126个城市	20.01~41.00	31.29
V类(低迁移意愿城市)	揭阳市、潮州市、张掖市、汕尾市、安康市、丹东市、来宾市、天水市、信阳市、吉安市、贵港市、陇南市、平顶山市、孝感市、内江市、邢台市、宣城市、抚州市、铜川市、六盘水市、贺州市、莆田市、安庆市、吕梁市、永州市25个城市	0.00~20.00	12.40

理论框架	变量	机制/逻辑	归因方式
劳动力市场分割理论	流入地城市的社会、经济发展水平	社会、经济发展水平的正向回报机制	社会经济水平高,户籍的含金量高,户籍迁移意愿亦高
劳动力市场分割理论	流入地城市的劳动力市场特征和社保情况	一级劳动力部门与次级劳动力部门的差异	集中在次级劳动力市场导致收入水平低,工作缺乏稳定性,户籍迁移意愿低
社会融合理论	流动人口的社会融合程度、流动时间	社会融合的正向回报机制	流动时间长、社会融合程度高,对流入地的认同度和归属感高,户籍迁移意愿亦高
空间区位理论	流入地城市的区位特征	区位的差异	区位条件优越(位于东部和沿海),户籍迁移意愿高
新劳动力迁移经济学理论	流动人口的个体家庭特征、家庭收入与财富水平	家庭资源的正向激励机制	个人条件优越、在流入城市家庭成员多、家庭收入与财富水平高,生存能力强,户籍迁移意愿高

	经济发展水平(F₁)	社会发展水平(F₂)	公共服务设施水平(F₃)	区位特征(F₄)
公共财政预算收入	0.929	0.226	0.180	0.122
公共财政一般预算内支出	0.920	0.135	0.295	0.049
年末单位从业人员数	0.870	0.233	0.330	0.130
经济总量GDP	0.811	0.387	0.326	0.205
社会消费品零售总额	0.803	0.351	0.382	0.193
制造业就业人员	0.784	0.321	0.237	0.293
在岗职工平均工资	0.570	0.539	-0.186	0.154
外商直接投资实际使用额	0.486	0.458	0.414	0.193
人均城乡居民储蓄年末余额	0.174	0.863	0.053	0.201
人均图书馆图书册数	0.153	0.789	0.103	0.002
人均GDP	0.350	0.694	-0.196	0.320
城镇居民可支配收入	0.393	0.595	0.033	0.490
是否为省会、副省级城市	0.442	0.533	0.331	-0.134
普通中学在校学生数	0.137	-0.087	0.917	0.066
普通中学专任教师数	0.461	-0.006	0.844	0.114
医院床位数	0.443	0.219	0.777	-0.019
区位(东中西)	-0.025	0.114	0.142	0.866
是否为沿海城市群内	0.179	0.177	0.056	0.833
是否沿海	0.164	0.040	-0.029	0.667
载荷因子累计贡献率	31.361	50.246	66.485	79.996

	就业特征(F₅)	家庭收入与财富水平(F₆)	个体和家庭基本特征(F₇)	流动时间(F₈)	社会融合程度(F₉)	社会保险情况(F₁₀)
在私营企业就业比例	0.842	0.039	0.159	-0.108	-0.029	-0.079
制造业从业人员比重	0.830	0.242	0.013	0.039	-0.145	0.056
雇员比例	0.773	-0.113	0.421	-0.042	-0.030	0.057
第三产业从业比重	-0.741	0.264	0.096	-0.078	0.028	0.007
跨省流入比重	0.436	0.366	0.015	0.003	-0.408	0.408
家庭月收入	-0.014	0.966	-0.045	0.051	-0.041	-0.014
家庭年储蓄金额	0.151	0.909	0.052	-0.023	-0.044	-0.036
个人月均收入	-0.195	0.833	-0.028	-0.105	0.015	0.143
平均受教育年限	-0.268	0.046	0.735	-0.320	0.134	-0.028
白领比例	0.216	0.156	0.719	0.240	0.040	-0.024
本地家庭规模	-0.262	0.100	-0.716	0.272	0.097	-0.252
已婚比例	-0.142	0.155	-0.626	0.366	0.117	-0.085
在外流动时间	0.049	0.046	-0.115	0.842	-0.047	0.014
本地滞留时间	-0.063	-0.148	-0.178	0.825	0.051	0.045
社区活动参与度	-0.038	-0.018	-0.038	-0.247	0.788	0.250
社会心理认同度	-0.111	-0.021	0.027	0.260	0.739	-0.210
享有城镇职工医保比重	-0.035	0.042	0.125	0.057	0.031	0.897
载荷因子累计贡献率	17.792	34.354	47.547	58.867	67.158	74.140

	非标准化系数	标准化系数	t值	Sig.
(常量)	39.248		54.599	0.000
社会融合程度(F₉)	6.277	0.405	8.475	0.000
社会发展水平(F₂)	5.243	0.339	6.972	0.000
经济发展水平(F₁)	5.008	0.324	6.617	0.000
流动时间(F₈)	3.789	0.247	5.285	0.000
社会保险情况(F₁₀)	-2.173	-0.139	-2.919	0.004
城市区位(F₄)	3.558	0.229	3.966	0.000
就业特征(F₅)	-2.885	-0.188	-3.346	0.001
家庭收入与财富水平(F₆)	-1.706	-0.110	-2.205	0.028

Spatial variation and its determinants of migrants' Hukou transfer intention of China's prefecture- and provincial-level cities：Evidence from the 2012 national migrant population dynamic monitoring survey

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[6]	LIU Zhenhai, WANG Shaoqiang, CHEN Bin. Spatial and temporal variations of frozen ground and its vegetation response in the eastern segment of China-Mongolia-Russia economic corridor from 2000 to 2015 [J]. Acta Geographica Sinica, 2021, 76(5): 1231-1244.
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[9]	WANG Lucang, LIU Haiyang, LIU Qing. China's city network based on Tencent's migration big data [J]. Acta Geographica Sinica, 2021, 76(4): 853-869.
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[15]	ZHU Shengjun, JIN Wenwan. Local export variety, regional institutions and firm related diversification [J]. Acta Geographica Sinica, 2021, 76(2): 398-414.