中国城市流动人口居留意愿影响因素的空间分异特征

doi:10.11821/dlxb202002003

Abstract

Abstract:

It is demonstrated that the determinants of China's urban floating population's settlement intention are different among geographic units, which seems to be ignored by previous researches. Based on the data from the 2015 national migrant population dynamic monitoring survey (CMDS) and related statistics, this article uses the Semiparametric Geographically Weighted Regression (SGWR) model and k-means cluster method to examine the spatial variation of the factors influencing floating population's settlement intention in 282 prefecture- and provincial- level cites of China. Results provide the following conclusions. (1) The settlement intention of urban floating population is mainly influenced by the floating population characteristics instead of the destination characteristics. (2) Social and economic factors are closely related to the floating population's settlement intention. Meanwhile, the demographic, family and mobility factors exert a significant impact on such an intention. To be specific, there exists an inhibitory effect on floating population's settlement intention in factors such as income, marriage, and cross provincial mobility. However, housing expenditure, participation rate, number of children and other factors can effectively contribute to such intention. (3) Zonal spatial differentiation patterns of the influencing factors' coefficients are illustrated by the SGWR model, which can be further divided into four categories ("E-W", "N-S", "NE-SW" and "SE-NW"): The positive influences of ethnic and family factors are decreasing from the northern to southern regions, while the influence of employment ratio in the secondary industry is declining from the northwest to the southeast regions, and the impacts of factors such as the number of children and per capita GDP are diminishing from the northeast to the southwest regions. In eastern developed areas, the settlement intention of floating population with higher income is comparatively lower, while migrants with higher housing expenditure in southern China have a stronger intention to settle down. (4) Four influencing zones are detected by the k-means method: Floating population's settlement intention in North China, Central China and East China is significantly affected by multiple factors; In the northwest region and part of the southwest region, migrants' settlement intention is mainly influenced by demographic and social factors; The northeast region and the eastern part of Inner Mongolia's floating population's willingness to stay is mainly related to economic and family factors; Apart from housing expenditure, coefficients of other factors are relatively small in southern China and part of the central, eastern and southwestern regions. Additionally, this paper puts forward some suggestions on the service and management of the floating population in China.

Key words: floating population's settlement intention, determinants, spatial variation, semiparametric geographically weighted regression, China

GU Hengyu, MENG Xin, SHEN Tiyan, CUI Nana. Spatial variation of the determinants of China's urban floating population's settlement intention[J].Acta Geographica Sinica, 2020, 75(2): 240-254.

Figures/Tables 6

Tab. 1

Tab. 2

Overall results of OLS, GWR and SGWR models

	模型1：OLS模型		模型2：传统GWR模型		模型3：SGWR模型
	$β$	$t$	$β ˉ$	$\vert{\overline{t}}\vert$	$β ˉ$	$\vert{\overline{t}}\vert$
AGE	0.0016	0.3942	0.0018	0.4226	0.0012	0.2731
SEX	0.0055	0.4848	0.0049	0.4330	0.0048	0.4231
MARRY	-0.4552^**	4.0304	-0.4461^**	3.8601	-0.4566^**	3.9238
ETHNIC	0.1733^*	2.1338	0.1893^*	2.1730	0.1968^*	2.1989
SCHOOL	-0.0246^*	2.0710	-0.0213	1.7384	-0.0209	1.6877
STAY	0.0177^**	3.9468	0.0179^**	3.7273	0.0202^**	3.9823
DIST	-0.2008^**	6.1205	-0.2154^**	6.3245	-0.2193^**	6.3742
INCOME	-1.5270^*	2.1863	-1.6669^*	2.3516	-1.6902^*	2.3657
HIRE	0.0520	0.8212	0.0472	0.7093	0.0503	0.7491
AGRI	-0.0988	0.9629	-0.0649	0.6227	-0.0648	0.6194
INSUR	0.2494^**	3.0624	0.2798^**	3.3896	0.2785^**	3.3462
SINDUS	-0.1651^*	2.5394	-0.1607^*	2.3969	-0.1581^*	2.3335
DRIFT	-0.2125	0.9911	-0.1220	0.5354	-0.1137	0.4912
HOUSING	0.4989^*	1.9758	0.5784^*	2.2298	0.5993^*	2.2868
LIV	0.0837^**	3.4278	0.0761^**	3.0288	0.0718^**	2.8044
CHILD	0.2270^**	3.1028	0.1861^*	2.3878	0.1789*	2.2643
PAYMENTS	0.0193	0.7178	0.0252	0.9336	0.0261	0.9661
PGDP	0.1045^**	2.9659	0.0910^*	2.5095	0.0879*	2.4039
GDPI	-0.0016	0.6464	-0.0013	0.4975	-0.0010	0.4019
SAV	-0.0197	0.5751	-0.0193	0.5571	-0.0192	0.5533
DENS	0.0163	0.7163	0.0239	1.0346	0.0258	1.1056
EMP	0.0108	1.3097	0.0110	1.3219	0.0107	1.2934
UNEMP	-0.0894	0.4513	-0.0739	0.3381	-0.1083	0.5534
WAGE	-0.0570	0.7534	-0.0507	0.6202	-0.0468	-0.5620
TEACH	-0.0001	0.2983	0.0001	0.3507	0.0001	0.3672
常量	0.4748	1.4295	0.4417	1.3039	0.4624	1.3562
样本数量	282		282		282
R²	0.6055		0.6594		0.6665
调整后R²	0.5653		0.5930		0.5995
AICc	-456.8397		-467.1891		-470.2394
AICc减小值			10.3494		13.3997

Tab. 2

Fig. 1

Fig. 2

Fig. 3

Tab. 3

References 41

[1]	Department of Migrant Population, National Health and Family Planning Commission of the People's Republic of China. 2017 Report on China's Migrant Population Development. Beijing: China Population Publishing House, 2017.
	[ 国家卫生和计划生育委员会流动人口司. 中国流动人口发展报告2017. 北京: 中国人口出版社, 2017.]
[2]	Li Qiang . An analysis of push and pull factors in the migration of rural workers in China. Social Sciences in China, 2003(1):125-136.
	[ 李强 . 影响中国城市流动人口的推力与拉力因素分析. 中国社会科学, 2003(1):125-136.]
[3]	Lewis W A . Economic development with unlimited supplies of labour. Manchester School, 1954,22(2):139-191.
[4]	Todaro M P . A model of labor migration and urban unemployment in less developed countries. American Economic Review, 1969,59(1):138-148.
[5]	Massey D S, Arango J, Hugo G , et al. Theories of international migration: A review and appraisal. Population & Development Review, 1993,19(3):431-466.
[6]	Stark O, Bloom D E . The new economics of labor migration. The American Economic Review, 1985,75(2):173-178.
[7]	Stark O, Levhari D . On migration and risk in LDCs. Economic Development & Cultural Change, 1982,31(1):191-196.
[8]	Gu H, Liu Z, Shen T . Spatial pattern and determinants of migrant workers' interprovincial hukou transfer intention in China: Evidence from a National Migrant Population Dynamic Monitoring Survey in 2016. Population, Space and Place, 2019: 2250. .
[9]	Zhu Y, Chen W . The settlement intention of China's floating population in the cities: Recent changes and multifaceted individual-level determinants. Population,Space and Place, 2010,16(4):253-267.
[10]	Zhu Y . China's floating population and their settlement intention in the cities: Beyond the Hukou reform. Habitat International, 2007,31(1):65-76.
[11]	Hu F, Xu Z, Chen Y . Circular migration, or permanent stay? Evidence from China's rural-urban migration. China Economic Review, 2011,22(1):64-74.
[12]	Yue Z, Li S, Feldman M W , et al. Floating choices: A generational perspective on intentions of rural-urban migrants in China. Environment and Planning A, 2010,42(3):545-562.
[13]	Chen J, Wang W . Economic incentives and settlement intentions of rural migrants: Evidence from China. Journal of Urban Affairs, 2018: 1-18.
[14]	Li Shuzhuo, Wang Weibo, Yue Zhongshan . A comparative study on settlement intentions between self-employed and employed migrants. Population & Economics, 2014(2):12-21.
	[ 李树茁, 王维博, 悦中山 . 自雇与受雇农民工城市居留意愿差异研究. 人口与经济, 2014(2):12-21.]
[15]	Yang Chuankai, Liu Ye, Xu Wei , et al. The determinants for peasants' migration intentions of moving to cities in China: An analysis based on the CGSS 2010. Geographical Research, 2017,36(12):2369-2382.
	[ 杨传开, 刘晔, 徐伟 , 等. 中国农民进城定居的意愿与影响因素: 基于CGSS2010的分析. 地理研究, 2017,36(12):2369-2382.]
[16]	Hou Jianming, Li Xiaogang . The analysis of the status of China's floating elderly population and its influencing factors. Population Journal, 2017,39(6):62-70.
	[ 侯建明, 李晓刚 . 我国流动老年人口居留意愿及其影响因素分析. 人口学刊, 2017,39(6):62-70.]
[17]	Yu Xiao, Chen Xinzao . The influence of income and social status on the urban residence intention of the floating population: An empirical study based on Guangdong Province. Social Sciences in Guangdong, 2017(3):181-190.
	[ 于潇, 陈新造 . 经济收入与社会地位对流动人口城市居留意愿的影响: 基于广东省的实证研究. 广东社会科学, 2017(3):181-190.]
[18]	Huang Y, Guo F, Cheng Z . Market mechanisms and migrant settlement intentions in urban China. Asian Population Studies, 2018,14(1):22-42.
[19]	Liu Z, Wang Y, Chen S . Does formal housing encourage settlement intention of rural migrants in Chinese cities? A structural equation model analysis. Urban Studies, 2017,54(8):1834-1850.
[20]	Fan C C . Settlement intention and split households: Findings from a survey of migrants in Beijing's urban villages. China Review, 2011: 11-41.
[21]	Zheng S, Long F, Fan C C , et al. Urban villages in China: A 2008 survey of migrant settlements in Beijing. Eurasian Geography and Economics, 2009,50(4):425-446.
[22]	Haug S . Migration networks and migration decision-making. Journal of Ethnic and Migration Studies, 2008,34(4):585-605.
[23]	Zhang Huachu, Cao Yue, Wang Menggong . The influence of social integration on the migrants' willingness of long-term residence in Guangzhou City. Northwest Population, 2015(1):7-11.
	[ 张华初, 曹玥, 汪孟恭 . 社会融合对广州市流动人口长期居留意愿的影响. 西北人口, 2015(1):7-11.]
[24]	Goodkind D, West L A . China's floating population: Definitions, data and recent findings. Urban Studies, 2002,39(12):2237-2250.
[25]	Tang S, Hao P . Floaters, settlers, and returnees: Settlement intention and hukou conversion of China's rural migrants. China Review, 2018,18(1):11-33.
[26]	Khoo S E, Hugo G, McDonald P . Which skilled temporary migrants become permanent residents and why? International Migration Review, 2008,42(1):193-226.
[27]	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. Acta Geographica Sinica, 2016,71(10):1696-1709.
	[ 林李月, 朱宇 . 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. 地理学报, 2016,71(10):1696-1709.]
[28]	Wei Zhixin . A region-specific comparative study of factors influencing the residing preference among migrant population in different areas: Based on the dynamic monitoring & survey data on the migrant population in five cities of China. Population & Economics, 2013(4):12-20.
	[ 蔚志新 . 分地区流动人口居留意愿影响因素比较研究: 基于全国5城市流动人口动态监测调查数据. 人口与经济, 2013(4):12-20.]
[29]	Yang Dongliang . A comparative study on settlement intention of the floating population in Northeast China. Population Journal, 2016,38(5):34-44.
	[ 杨东亮 . 东北流出流入人口的城市居留意愿比较研究. 人口学刊, 2016,38(5):34-44.]
[30]	Liang Haiyan . Characteristics and residence intention of floating population in border areas. Population and Society, 2017,33(2):59-67.
	[ 梁海艳 . 边疆地区流动人口基本特征及居留意愿. 人口与社会, 2017,33(2):59-67.]
[31]	Yu Xiao, Chen Xinzao . The influence of income and social status on the urban residence intention of the floating population: An empirical study based on Guangdong Province. Social Sciences in Guangdong, 2017(3):181-190.
	[ 于潇, 陈新造 . 经济收入与社会地位对流动人口城市居留意愿的影响: 基于广东省的实证研究. 广东社会科学, 2017(3):181-190.]
[32]	Gu Hengyu, Shen Tiyan, Zhou Lin , et al. Measuring street layout's spatio-temporal effects on housing price based on GWR and sDNA Model: The case study of Guangzhou. Economic Geography, 2018,38(3):82-91.
	[ 古恒宇, 沈体雁, 周麟 , 等. 基于GWR和sDNA模型的广州市路网形态对住宅价格影响的时空分析. 经济地理, 2018,38(3):82-91.]
[33]	National Bureau of Statistics of People's Republic of China. 2016 China City Statistical Yearbook. Beijing: China Statistics Press, 2017.
	[ 国家统计局. 中国城市统计年鉴2016. 北京: 中国统计出版社, 2017.]
[34]	Piore M J . Birds of Passage: Migrant Labor and Industrial Societies. Cambridge: Cambridge University Press, 1979.
[35]	Hu Angang, Li Chunbo . New poverty during the new century: Knowledge poverty. Social Sciences in China, 2001(3):70-81.
	[ 胡鞍钢, 李春波 . 新世纪的新贫困: 知识贫困. 中国社会科学, 2001(3):70-81.]
[36]	Fotheringham A S, Brunsdon C, Charlton M . Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. England: Wiley, 2003.
[37]	Fotheringham A S, Kelly M H, Charlton M . The demographic impacts of the Irish famine: Towards a greater geographical understanding. Transactions of the Institute of British Geographers, 2013,38(2):221-237.
[38]	Shen Y, Karimi K . The economic value of streets: Mix-scale spatio-functional interaction and housing price patterns. Applied Geography, 2017,79:187-202.
[39]	Windle M J S, Rose G A, Devillers R , et al. Exploring spatial non-stationarity of fisheries survey data using geographically weighted regression (GWR): An example from the Northwest Atlantic. Journal of Vlsi Signal Processing Systems for Signal Image & Video Technology, 2010,42(3):285-296.
[40]	Gu Hengyu, Qin Xiaoling, Shen Tiyan . Spatial variation of migrant population's return intention and its determinants in China's prefecture and provincial level cities. Geographical Research, 2019,38(8):1877-1890.
	[ 古恒宇, 覃小玲, 沈体雁 . 中国城市流动人口回流意愿的空间分异及影响因素. 地理研究, 2019,38(8):1877-1890.]
[41]	Yin Jiangbin . Advances in research on driving factors of return migration and employment behavior of migrants. Progress in Geography, 2015,34(9):1084-1095.
	[ 殷江滨 . 劳动力回流的驱动因素与就业行为研究进展. 地理科学进展, 2015,34(9):1084-1095.]

变量类型		变量名称	变量描述	预期效应
流动人口特征	人口变量	AGE	城市流动人口平均年龄(岁)	+
		SEX	流动人口性别比例(%)	未知
		MARRY	未婚流动人口比重(%)	-
		ETHNIC	少数民族流动人口比重(%)	未知
		SCHOOL	流动人口平均受教育年限(年)^①	+
	流动特征变量	STAY	流入地平均停留时间(年)	+
	流动特征变量	DIST	跨省流动比重(%)	未知
	社会变量	HIRE	流动人口中雇员比重(%)	-
		AGRI	农业户口流动人口比重(%)	-
		INSUR	城镇职工保险参保率(%)	+
		SINDUS	第二产业就业流动人口比重(%)	+
		DRIFT	无固定职业流动人口比重(%)	-
	经济变量	INCOME	流动人口平均收入(元)	+
		HOUSING	家庭每月住房支出(元)	+
		PAYMENTS	家庭总收入与总支出比(%)	+
	家庭变量	LIV	家庭同住人数(人)	+
	家庭变量	CHILD	流动人口子女个数(人)	+
流入城市特征	经济变量	PGDP	流入地人均GDP(万元)	+
		GDPI	流入地年GDP增长率(%)	+
		SAV	人均城乡居民年末储蓄余额(元)	+
	社会变量	DENS	市辖区人口密度(人/km²)	+
		EMP	流入地就业人数(人)	+
		UNEMP	流入地在岗职工平均失业率(%)	-
		WAGE	流入地在岗职工平均工资(元)	+
	教育水平变量	TEACH	流入地人均小学教师数(人/人)	+

变量	Ⅰ类区	Ⅱ类区	Ⅲ类区	Ⅳ类区
PGDP	0.092	0.086	0.103	0.077
MARRY	-0.448	-0.512	-0.441	-0.435
DIST	-0.214	-0.240	-0.169	-0.232
INCOME	-1.757	-1.512	-1.802	-1.680
INSUR	0.276	0.302	0.276	0.267
SINDUS	-0.163	-0.174	-0.160	-0.140
ETHNIC	0.214	0.202	0.405	0.090
HOUSING	0.595	0.609	0.465	0.650
LIV	0.073	0.073	0.081	0.066
CHILD	0.215	0.096	0.377	0.111
人口比例(%)	49.01	16.26	7.53	27.20
城市数(个)	113	57	31	81

Spatial variation of the determinants of China's urban floating population's settlement intention

RichHTML

PDF (PC)

Like

Knowledge

Cited

Abstract

Cite this article

share this article

Figures/Tables 6

References 41

Related Articles 15

Metrics

Comments

[1]	SUN Pingjun, WANG Kewen. Identification and stage division of urban shrinkage in the three provinces of Northeast China [J]. Acta Geographica Sinica, 2021, 76(6): 1366-1379.
[2]	WEI Shimei, PAN Jinghu. Network structure resilience of cities at the prefecture level and above in China [J]. Acta Geographica Sinica, 2021, 76(6): 1394-1407.
[3]	YANG Ren, PAN Yuxin. Spatial patterns, formation mechanism and coping strategies of rural vulnerability in China at the county level [J]. Acta Geographica Sinica, 2021, 76(6): 1438-1454.
[4]	YIN Jiangbin, LI Shangqian, JIANG Lei, CHENG Zhe, HUANG Xiaoyan, LU Gaigai. The spatio-temporal variations and driving factors of non-farm employment growth in contiguous destitute areas of China [J]. Acta Geographica Sinica, 2021, 76(6): 1471-1488.
[5]	HU Pan, CHEN Bo, SHI Peijun. Spatiotemporal patterns and influencing factors of rainstorm-induced flood disasters in China [J]. Acta Geographica Sinica, 2021, 76(5): 1148-1162.
[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.
[7]	MA Zuopeng, LI Chenggu, ZHANG Pingyu. Characteristics, mechanism and response of urban shrinkage in the three provinces of Northeast China [J]. Acta Geographica Sinica, 2021, 76(4): 767-780.
[8]	HUANG Xiaodong, MA Haitao, MIAO Changhong. Connectivity characteristics for city networks in China based on innovative enterprises [J]. Acta Geographica Sinica, 2021, 76(4): 835-852.
[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.
[10]	XIA Xingsheng, PAN Yaozhong, ZHU Xiufang, ZHANG Jinshui. Monthly calibration and optimization of Ångström-Prescott equation coefficients for agricultural comprehensive area in China [J]. Acta Geographica Sinica, 2021, 76(4): 888-902.
[11]	FAN Zemeng. Spatial identification and scenario simulation of ecotone distribution in China [J]. Acta Geographica Sinica, 2021, 76(3): 626-644.
[12]	XU Yu, LI Xiubin, XIN Liangjie. Differentiation of scale-farmland transfer rent and its influencing factors in China [J]. Acta Geographica Sinica, 2021, 76(3): 753-763.
[13]	LI Gang, XUE Shuyan, MA Xueyao, ZHOU Junjun, XU Tingting, WANG Jiaobei. Spatio-temporal pattern evolution and formation mechanism of missing person incidents in China [J]. Acta Geographica Sinica, 2021, 76(2): 310-325.
[14]	GU Hengyu, SHEN Tiyan. Spatial evolution characteristics and driving forces of Chinese highly educated talents [J]. Acta Geographica Sinica, 2021, 76(2): 326-340.
[15]	ZHU Shengjun, JIN Wenwan. Local export variety, regional institutions and firm related diversification [J]. Acta Geographica Sinica, 2021, 76(2): 398-414.