中国省际人口迁移的多边效应机制分析

doi:10.11821/dlxb201602003

Abstract

Abstract:

Population migration flows between different regions are related to not only the origin- and destination-specific characteristics, but also to the migration flows to and from neighborhoods. Intuitively, changes in the characteristics of a single region will impact both inflows and outflows to and from other regions. In order to explore the spatial interaction mechanism driving the increasing population migration in China, this paper builds the spatial OD model of interprovincial migration flows based on the sixth national population census data and related social-economic data. The findings are as follows: (1) Migration flows show significant autocorrelation effects among origin and destination regions, which means that the migration behavior of migrants in some region is influenced by that of migrants in other places. The positive effects indicate the outflows from an origin or the inflows to a destination tend to cluster in a similar way. Simultaneously, the negative effects suggest the flows from the neighborhood of an origin to the neighborhood of a destination tend to disperse in a dissimilar way. (2) Multilateral effects of the regional economic and social factors through the spatial network system lead to the clustering migration flows across interrelated regions. Distance decay effect plays the most influential force in shaping the patterns of migration flows among all the factors and the negative spillover effect further aggravates the friction of distance. As for destinations, the influence of wage level and migration stocks is beyond that of GDP and the positive spillover effects of these factors enhance the attraction of neighborhood regions. The spillover effects of unemployment rate and college enrollment of higher education are significantly negative while the effect of population in a destination is not significant. As for origins, population and migration stocks lead to positive spillover effects on the neighborhoods while the effects of other factors are negative. (3) Changes in the regional characteristics will potentially lead to a series of events to the whole migration system, and the flows to and from the center of oscillation and its neighborhoods vibrate greatly compared with other regions. The simulation results of 5% GDP increase in Jiangsu province indicate that the outflows to other regions decrease while the inflows from all others increase to some different extent. Comparatively, the influence on the flows to and from the regions neighboring Jiangsu is significant while that of remote regions is much less, which cannot be explained by the traditional gravity model.

Key words: population migration flows, network autocorrelation, multilateral effects, spatial OD model, spatial mechanism analysis, China

Yingxia PU, Hongling HAN, Ying GE, Fanhua KONG. Multilateral mechanism analysis of interprovincial migration flows in China[J].Acta Geographica Sinica, 2016, 71(2): 205-.

Figures/Tables 3

Tab. 1

Tab. 2

Tab. 3

Simulation of the changes in migration flows from and to major regions by from and to major regions by 5% GDP increase in Jiangsu

省份	迁出地						目的地
省份	江苏	上海	浙江	安徽	山东	河南	江苏	上海	浙江	安徽	福建	山东
北京	-1261	-17	-54	-142	-285	-20	236	55	9	4	0	15
天津	-468	-5	-19	-46	-240	-7	147	31	6	2	0	15
河北	-241	-2	-12	-18	-65	4	1409	161	45	18	1	250
山西	-227	-1	-11	-15	-22	-8	851	108	27	7	1	63
内蒙古	-215	-1	-10	-13	-33	-4	346	57	16	4	1	94
辽宁	-285	-3	-13	-25	-57	-4	611	151	31	6	1	93
吉林	-92	-2	-6	-7	-21	-1	671	141	35	6	1	222
黑龙江	-123	-2	-5	-8	-30	-1	1156	237	60	8	2	487
上海	-11365	0	2258	5464	703	1845	1431	0	-47	-1	-4	2
江苏	0	1431	4706	44101	7010	17109	0	-11365	-2505	-799	-272	-972
浙江	-2505	-47	0	2176	114	1295	4706	2258	0	32	-41	51
安徽	-799	-1	32	0	12	106	44101	5464	2176	0	-50	164
福建	-272	-4	-41	-50	-15	20	2328	646	234	23	0	42
江西	-169	-7	-26	-19	-7	3	4455	1200	2215	43	167	36
山东	-972	2	51	164	0	501	7010	703	114	12	-15	0
河南	-209	-3	-11	-22	-33	0	17109	1845	1295	106	20	501
湖北	-247	-5	-21	-27	-13	4	6711	967	957	53	31	93
湖南	-117	-3	-14	-9	-8	-1	3391	547	806	28	24	39
广东	-818	-13	-68	-147	-72	-47	745	189	50	11	9	19
广西	-92	-2	-16	-10	-7	-2	761	118	151	7	7	10
海南	-62	-1	-5	-7	-4	-1	98	23	6	2	1	4
重庆	-104	-3	-11	-5	-7	-1	2986	546	642	14	43	29
四川	-199	-6	-21	-10	-15	-2	10866	1499	1350	38	88	103
贵州	-100	-2	-14	-7	-6	-1	4602	355	1630	28	50	29
云南	-103	-3	-20	-8	-7	-2	2357	168	448	25	11	53
西藏	-9	0	-1	-1	-1	-0	31	3	1	1	0	1
陕西	-217	-3	-15	-14	-20	-8	3456	302	182	14	6	58
甘肃	-121	-2	-10	-5	-7	-2	1699	228	68	6	2	50
青海	-84	0	-4	-4	-5	-2	231	27	9	2	0	15
宁夏	-61	0	-4	-6	-7	-2	117	24	6	1	0	9
新疆	-335	-5	-13	-28	-27	-16	358	69	16	3	1	28
合计	-21873	1290	6600	51250	6824	20757	124975	6756	10033	-296	87	1603

Tab. 3

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变量名称	变量描述	变量预期效应
变量名称	变量描述	迁出地变量	目的地变量
pop	2010年中国各省总人口(人)	+	-
GDP	2010年中国各省地区国内生产总值(亿元)	-	+
uemp	2010年中国各省城镇登记失业率(%)	+	-
wage	2010年中国各省城镇实际工资率(%)	-	+
stu	2010年中国各省高等院校在校大学生比例(%)	-	+
flows	1995-2000年间中国省际迁移人口存量(人)	+	+
Dist	目的地和迁出地省会城市之间铁路里程(km)	-

变量	重力模型			空间OD模型
变量	系数		t值	系数	t值	多边效应	t值
const	-1.0026	-0.5529		-2.6240^*	-1.6877	-3.2204	-1.4902
D_pop	-0.2527	-1.7736		-0.0142	-0.1232	-0.0314	-0.7387
D_GDP	0.5587^***	3.9851		0.2076^*	1.8285	0.4579^***	5.2578
D_wage	1.0361^***	4.7452		0.5564^***	3.1511	1.2269^***	6.7115
D_uemp	-0.5202^***	-3.3278		-0.3058^**	-2.4435	-0.6744^***	-3.8168
D_stu	-0.4109^***	-3.2120		-0.3004^***	-2.9186	-0.6626^***	-6.5182
D_flows	0.5262^***	9.0630		0.3834^***	7.8925	0.8454^***	12.2943
O_pop	0.9158^***	6.3453		0.4422^***	3.5926	0.9751^***	13.0867
O_GDP	-0.3522^***	-3.0305		-0.0813	-0.8283	-0.1792^**	-2.2690
O_wage	-0.5262^**	-2.2819		-0.5571^***	-2.9173	-1.2285^***	-6.8218
O_uemp	0.1458	0.9810		-0.1164	-0.9590	-0.2567	-1.4547
O_stu	-0.0478	-0.3876		-0.1515	-1.5279	-0.3340^***	-3.4703
O_flows	0.3550^***	7.3797		0.1823^***	4.5848	0.4020^***	9.8791
Distance	-1.1374^***	-23.3270		-0.6375^**	-13.4866	-1.4058^***	-19.9182
ρ_o				0.3796^***	14.4158
ρ_d				0.3705^***	14.2417
ρ_w				-0.2030^***	-5.9458
Log-LIK	-822.86			652.70
AIC	1673.72			1339.40

Multilateral mechanism analysis of interprovincial migration flows in China

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