海南省农村多维贫困及影响因素的空间分异

doi:10.18306/dlkxjz.2020.06.011

地理科学进展 ›› 2020, Vol. 39 ›› Issue (6): 1013-1023.doi: 10.18306/dlkxjz.2020.06.011

• 专辑 | 多维贫困与可持续生计 • 上一篇下一篇

海南省农村多维贫困及影响因素的空间分异

张金萍, 林丹, 周向丽, 余珍鑫, 宋伟, 程叶青^*()

海南师范大学地理与环境科学学院,海口571158

收稿日期:2020-01-08 修回日期:2020-05-09 出版日期:2020-06-28 发布日期:2020-08-28
通讯作者: 程叶青
作者简介:张金萍(1977— ),女,山东招远人,博士,副教授,主要研究方向为乡村地理学。E-mail: maryzhjp@126.com
基金资助:
国家自然科学基金项目(41661028);国家自然科学基金项目(41761118);海南省自然科学基金项目(417099);海南省自然科学基金项目(418MS052);海南省自然科学基金高层次人才项目(2019RC178);2019年海南省普通高等学院研究生创新科研课题(Hys2019-240)

Spatial difference of multidimensional poverty and its influencing factors in the rural areas of Hainan Province

ZHANG Jinping, LIN Dan, ZHOU Xiangli, YU Zhenxin, SONG Wei, CHENG Yeqing^*()

College of Geography and Environmental Sciences, Hainan Normal University, Haikou 571158, China

Received:2020-01-08 Revised:2020-05-09 Online:2020-06-28 Published:2020-08-28
Contact: CHENG Yeqing
Supported by:
National Natural Science Foundation of China(41661028);National Natural Science Foundation of China(41761118);Natural Science Foundation of Hainan Province(417099);Natural Science Foundation of Hainan Province(418MS052);High-level Talent Project of Natural Science Foundation of Hainan Province(2019RC178);Innovative Research Project for Postgraduates of Hainan Province in 2019(Hys2019-240)

摘要/Abstract

摘要：

贫困具有多维属性,根据不同社会群体和背景从多维视角定义贫困已成为贫困问题研究的共识。依据Alkire-Foster多维贫困框架,拓展精准扶贫的“两不愁,三保障”识别标准,建立了涵盖教育、健康、居住、生活和收入指标的海南省农户多维贫困评估指标体系,基于海南省70个乡镇、134个贫困村3924户入户调查数据,采用双重临界值法评估了农户及村域多维贫困状况,进而运用地理加权回归(Geographically Weighted Regression,GWR)模型,分析了村域多维贫困影响因素的空间分异。结果显示,调查农户多维贫困率达18.22%,多维贫困程度严重的村多维贫困发生率不一定高,“两不愁、三保障”及收入指标对多维贫困指数的贡献率低。中、西部连片贫困地区多维贫困主要表现为较差的资产状况、不清洁的炊事燃料、较高的家庭成员患病率和较低的家庭成员最高学历。GWR模型分析表明,作为多维贫困最重要的影响因素,户主性别、户主受教育水平、女性劳动力占比和抚养比4个变量估计系数的空间分异明显。总体上,女性户主和低学历户主为主的地区倾向于更易发生多维贫困,二者的影响分别表现为从东到西、从北到南有所增强。女性劳动力占比为负向影响,抚养比为正向影响,呈现出自北向南增强的趋势,体现了海南贫困地区劳动力弱、女性相对更勤劳等典型地域特征。

关键词: 多维贫困, Alkire-Foster法, GWR, 空间异质性, 海南省

Abstract:

Poverty has multidimensional attributes, and it has become a consensus to study poverty from a multidimensional perspective according to different social groups and backgrounds. In order to measure the multidimensional poverty situation in the rural areas where the poor population is concentrated in Hainan Province, we expanded the index system based on the exit criteria for targeted poverty alleviation fulfilling the basic needs of food and clothing and guaranteeing compulsory education, basic medical care, and housing, and established a multidimensional poverty assessment conceptual model for rural households in Hainan Province that covers education, health, housing, livelihood, and income indicators. Then, based on household survey data from 3924 households in 70 towns and 134 poor villages of Hainan Province in 2018, we used the double threshold Alkire-Foster (A-F) method to evaluate the multidimensional poverty status of rural households and villages, and then used the geographically weighted regression (GWR) model to analyze the spatial heterogeneity of the influencing factors of multidimensional poverty in villages. The study results show that: 1) The incidence of multidimensional poverty of the surveyed households was 18.22%. But the incidence of multidimensional poverty in villages with severe multidimensional poverty is not necessarily high. 2) The four indicators of farming households' asset status, cooking fuels, family members' diseases, and family members’ highest academic qualifications contribute the most to multidimensional poverty, while the contribution ratio of indicators belonging to the standard of fulfilling basic needs of food and clothing and guaranteeing compulsory education, basic medical care, and housing, as well as income are generally not high. The multidimensional poverty in the contiguous poverty areas in the central and western regions of the province is mainly manifested by poor asset conditions, unclean cooking fuels, high prevalence of disease of family members, and lower education levels. 3) The GWR model analysis showed that as the most important influencing factors of multidimensional poverty, spatial heterogeneity of the estimated coefficients of the four variables, gender of the household head, education level of the household head, ratio of female labor force, and dependency ratio, have very obvious impacts. In general, areas with more female-headed and low-education attainment individual headed households tend to be more prone to multidimensional poverty, and their impacts increased from east to west and from north to south, separately. With an increasing trend from north to south, the effect of the proportion of female labor force is negative and that of the dependency ratio is positive, which reflects the typical regional characteristics of weak labor force and relatively more industrious women in Hainan poverty-stricken areas.

Key words: multidimensional poverty, Alkire-Foster (A-F) method, geographically weighted regression (GWR), spatial heterogeneity, Hainan Province

张金萍, 林丹, 周向丽, 余珍鑫, 宋伟, 程叶青. 海南省农村多维贫困及影响因素的空间分异[J]. 地理科学进展, 2020, 39(6): 1013-1023.

ZHANG Jinping, LIN Dan, ZHOU Xiangli, YU Zhenxin, SONG Wei, CHENG Yeqing. Spatial difference of multidimensional poverty and its influencing factors in the rural areas of Hainan Province[J]. PROGRESS IN GEOGRAPHY, 2020, 39(6): 1013-1023.

图/表 13

表1

表2

多维贫困测算的变量及方法"

变量	计算方法
剥夺临界值Z	各指标的贫困标准z_j,j=1, 2, …, d,其中d为指标数量
加权剥夺矩阵G_w	g_ij(i=1, 2, … , n; j=1, 2, … , d)表示第i个农户在第j指标上是否被剥夺,如果第i个农户的第j个指标的观测值低于z_j则赋值为1,否则赋值为0;加权后的剥夺矩阵为G_w,w_j为第j个指标的权重, $∑ j = 1 d w j = 10$
被剥夺指标数k	k表示农户贫困维度总数,1≤k≤d,k的取值一般介于2~d之间
多维贫困剥夺矩阵C	$c ij k = ∑ j = 1 d g ij w j ∑ j = 1 d g ij w j ≥ k 0 其他$ (k=1, 2, 3, …, d)
多维贫困个体剥夺矩阵Q	$q ij (k) = 1 c ij k > 0 0 其他$
多维贫困率H(k)	$H (k) = ∑ i = 1 n q ij (k) / n$ ,n为研究区域农户总数
平均剥夺份额A(k)	$A (k) = ∑ i = 1 n c ij k / ∑ i = 1 n q ij (k) × d$
多维贫困指数MPI(k)	MPI(k)表示研究区域多维贫困状况,MPI(k)=H(k)×A(k)
指标贡献率λ_j(k)	$λ j (k) = ∑ i = 1 m g ij (k) ∑ i = 1 m ∑ j = 1 d g ij (k)$ ,其中m表示第k维贫困情况下被剥夺的农户数量

表2

图1

表3

图2

表4

图3

表5

图4

表6

表7

图5

图6

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子系统	指标	剥夺临界值Z	指标描述
教育	家庭成员最高学历	1	初中以下赋值为1,初中及以上为0
教育	儿童就学情况^*	1	家中义务教育阶段辍学儿童≥1赋值为1,否则为0
健康	购买新农合保险情况^*	1	家庭成员中未购买人数≥1赋值为1,否则为0
健康	患病情况	1	家中大病或长期慢性病患者或残疾人≥1赋值为1,否则为0
居住	安全住房^*	1	居住在危房中或无住房或人均住房面积<10 m²赋值为1,否则为0
生活	营养状况^*	1	缺口粮或每月吃蛋白质食品≤1次赋值为1,否则为0
	穿衣状况^*	1	无应季换洗衣服、被褥、鞋赋值为1,否则为0
	冲水厕所	1	家中没有冲水厕所赋值为1,否则为0
	炊事燃料	1	使用畜禽粪便或柴草、木炭等薪柴等非清洁能源赋值为1,否则为0
	资产状况	1	拥有冰箱、电视机、空调、电热水器、电磁炉、洗衣机、电脑、电饭锅、电话等家用电器数量≤1或自行车、电动车、摩托车、小汽车等交通工具数量<1赋值为1,否则为0
收入	家庭年人均纯收入^*	3523	≤3523元赋值为1,否则为0

子系统	教育		健康		居住	生活					收入
子系统	家庭成员最高学历	儿童就学情况	新农合情况	患病情况	安全住房	营养状况	穿衣状况	冲水厕所	炊事燃料	资产状况	家庭年人均纯收入
剥夺农户数量/户	803	17	6	1554	389	13	19	390	1237	1010	285
贫困率/%	20.5	0.4	0.2	39.6	9.9	0.3	0.5	9.9	31.5	25.7	7.3

k	多维贫困率H/%	平均剥夺份额A	多维贫困指数MPI
1	76.33	0.1725	0.1317
2	40.93	0.2431	0.0995
3	18.22	0.3195	0.0582
4	6.45	0.4050	0.0261
5	2.17	0.4866	0.0105
6	0.54	0.5844	0.0031
7	0.18	0.6623	0.0012
8	0.05	0.7273	0.0004

子系统	教育		健康		居住	生活					收入
子系统	家庭成员最高学历	儿童就学情况	新农合情况	患病情况	安全住房	营养状况	穿衣状况	冲水厕所	炊事燃料	资产状况	家庭年人均纯收入
贡献率	14.88	0.36	0.24	18.27	8.83	0.52	0.76	9.39	19.14	19.90	7.72
合计	15.24		18.50		8.83	49.70					7.72

变量	变量说明	预设作用方向	最小值	最大值	平均值	中位数
户主性别x₁	1为女性户主家庭,0为男性户主家庭	正向	0	1.00	0.084	0
户主受教育水平x₂	小学及以下为1,初中为2,高中、职中、职专为3,大学及以上为4;数值越大表示受教育水平越高	负向	1.00	2.33	1.621	1.630
女性劳动力占比x₃	农户女性劳动力占全部劳动力之比	正向	0.21	2.00	0.699	0.620
抚养比x₄	农户家中单位劳动力供养的60岁以上老人和16岁以下未成年人数量	正向	0.49	3.78	1.506	1.295

海南省农村多维贫困及影响因素的空间分异

Spatial difference of multidimensional poverty and its influencing factors in the rural areas of Hainan Province

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参考文献 28

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变量	OLS模型				变量	GWR模型
变量	回归系数	标准差	t统计值	P值	变量	回归系数范围	回归系数平均值
截距	0.1358	0.0253	5.3765	0.0007^***	截距	0.0084~0.1895	0.0957
x₁	0.0529	0.0247	2.1406	0.0342^**	x₁	-0.0197~0.1453	0.0416
x₂	-0.0573	0.0147	-3.8948	0.0002^***	x₂	-0.0847~0.0070	-0.0370
x₃	-0.0985	0.0256	-3.8541	0.0002^***	x₃	-0.1812~-0.0275	-0.1171
x₄	0.0505	0.0110	4.5918	<0.0001^***	x₄	0.0269~0.0806	0.0622
F	11.6624^***				局部R²	0.1667~0.4057
R²	0.2656				R²	0.4419
调整R²	0.2428				调整R²	0.3598
残差平方和	0.2249				残差平方和	0.1709
残差Moran's I	0.1746 (P=0.0004)				残差Moran's I	0.0554 (P=0.2190)
AICc	781.1336				AICc	764.1921

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