相对贫困视角下的精准扶贫多维减贫效应研究——以宁夏彭阳县为例

doi:10.11821/dlyj020181292

摘要/Abstract

摘要：

2020年是精准扶贫的收官之年,中国脱贫攻坚的重点将转向解决相对贫困。建立解决相对贫困长效机制,亟需科学评价精准扶贫政策的减贫成效,通过补齐减贫短板,优化扶贫资源配置,实现区域精准化扶持。本研究在测度彭阳县多维贫困程度的基础上,利用倾向得分匹配法量化了精准扶贫的多维减贫效应,并分析了扶贫的困境。主要结论：① 精准扶贫多维减贫成效显著,农户多维贫困指标数量k减少了51.66%;② 各维度贫困指标剥夺程度均有降低,降低最明显的维度是生活、资产、住房和收入维度,教育和健康维度次之;③ 根据各维度减贫效应的差异找出减贫短板,分析了彭阳扶贫的困境。最后对如何摆脱减贫困境、推进建立解决相对贫困机制提出了相应的建议。

关键词: 精准扶贫, 相对贫困, 多维减贫, 倾向得分匹配, 黄土高原

Abstract:

The 13th Five-Year Plan Period (2016-2020) is the final rush time for China’s poverty relief. At the present stage, our main task in developing socialism is to realise our first centenary goal: building a moderately prosperous society in all respects by 2020. Targeted poverty alleviation is a pillar of China’s new and innovative anti-poverty and development strategy. It is the key to implementing the moderate prosperity program in an all-round way. Addressing relative poverty is a key focus of China's post-2020 poverty alleviation campaign. Currently, quantifying and verifying the policy implementation effect is helpful for optimising resource allocation, implementing differentiation support, and promoting the establishment of mechanisms to address relative poverty. This is important for the promotion of the targeted poverty alleviation strategy and the implementation of the rural revitalisation strategy. This study chooses Pengyang, a poverty-stricken county located on the Loess Plateau, as the study area. The study relied on the approach of Alkire and Foster to measure multidimensional poverty, and used PSM to analyse poverty reduction effects. The main conclusions were as follows: (1) The Pengyang county has achieved remarkable results in targeted poverty alleviation and multi-dimensional poverty reduction. The index number of multidimensional poverty, k, decreased by 51.66%. (2) The poverty reduction effects varied from different dimensions, which were (from high to low) life, assets, housing, income, education, and health dimensions. (3) Based on the poverty reduction effect, this paper analyses the poverty alleviation plight of Pengyang county and proposes further research on its optimisation strategy. These new strategies could enable the resolution of problems from the root, such as providing public goods and services that fill gaps in the current health care, housing options, and the operation of transport facilities at the village level. This could help mitigate welfare loss by farmers and reduce the negative impact on health, housing, education, and other dimensions of poverty. Finally, we put forward the corresponding suggestions on the establishment of the mechanism of relative poverty.

Key words: targeted poverty alleviation, relative poverty, multidimensional poverty reduction, propensity score matching, Loess Plateau

施琳娜, 文琦. 相对贫困视角下的精准扶贫多维减贫效应研究——以宁夏彭阳县为例[J]. 地理研究, 2020, 39(5): 1139-1151.

SHI Linna, WEN Qi. Effects of the targeted poverty alleviation policy on poverty reduction from the perspective of relative poverty in Loess Plateau[J]. GEOGRAPHICAL RESEARCH, 2020, 39(5): 1139-1151.

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变量名称	变量说明	总体组		控制组		处理组
变量名称	变量说明	均值	标准差	均值	标准差	均值	标准差
协变量
户主性别（x₁）	女=0,男=1	0.921	0.270	0.962	0.192	0.878	0.329
户主年龄（x₂）	>0	48.931	11.895	45.337	10.412	52.286	12.254
户主民族（x₃）	回族=0,汉族=1	0.493	0.501	0.543	0.501	0.439	0.499
户主受教育层次（x₄）	小学及以下=1;初中=2;高中=3;职校、中专=4;本科（大专）及以上=5	1.296	0.537	1.133	0.369	1.469	0.629
户籍人口（x₅）	>0	3.571	1.435	3.819	1.460	3.306	1.365
无劳动能力人数（x₆）	<16岁或>60岁以上人口	1.177	1.033	1.295	1.151	1.051	0.878
家庭成员健康状况（x₇）	不健康=0,健康=1	0.232	0.423	0.286	0.454	0.173	0.381
常年在外务工人数（x₈）	在本镇以外务工人数	0.448	0.646	0.524	0.761	0.367	0.485
结果变量
家庭人均纯收入（income）	单位：万元	0.931	3.339	0.344	0.324	1.560	4.73
个体多维贫困指标数量（k）	0~10	2.463	1.362	3.305	1.057	1.561	1.036
个体指标被剥夺强度（i）	1≥ i ≥ 0	0.289	0.185	0.396	0.167	0.176	0.128
收入维度指标剥夺程度（a）	1≥ a ≥ 0	0.261	0.308	0.164	0.173	0.189	0.244
教育维度指标剥夺程度（b）	1≥ b ≥ 0	0.109	0.207	0.072	0.114	0.072	0.176
健康维度指标剥夺程度（c）	1≥ c ≥ 0	0.357	0.238	0.207	0.095	0.294	0.268
住房维度指标剥夺程度（d）	1≥ d ≥ 0	0.264	0.250	0.207	0.095	0.102	0.203
生活维度指标剥夺程度（e）	1≥ e ≥ 0	0.291	0.267	0.222	0.094	0.128	0.242
资产维度指标剥夺程度（f）	1≥ f ≥ 0	0.485	0.448	0.426	0.125	0.092	0.220

变量	方法	控制组	处理组	差值	T-test
income	邻近匹配（1对1）	0.340	1.123	0.782	4.480***
	半径匹配（卡尺=0.1）	0.385	1.123	0.737	4.280***
	核匹配	0.377	1.123	0.746	4.320***

变量	方法	控制组	处理组	差值	T-test
k	邻近匹配（1对1）	3.282	1.564	-1.718	-7.730***
	核匹配	3.214	1.564	-1.650	-8.440***
	半径匹配（卡尺=0.1）	3.211	1.564	-1.647	-8.750***
i	邻近匹配（1对1）	0.383	0.177	-0.206	-5.79***
	核匹配	0.384	0.177	-0.207	-6.91***
	半径匹配（卡尺=0.1）	0.382	0.177	-0.206	-7.06***

变量	方法	控制组	处理组	差值	T-test
a（收入）	邻近匹配（1对1）	0.322	0.186	-0.136	-1.990**
	核匹配	0.365	0.186	-0.179	-3.020***
	半径匹配（卡尺=0.1）	0.353	0.196	-0.157	-2.720***
b（教育）	邻近匹配（1对1）	0.223	0.149	-0.074	-0.820
	核匹配	0.193	0.149	-0.044	-0.560
	半径匹配（卡尺=0.1）	0.200	0.149	-0.052	-0.680
c（健康）	邻近匹配（1对1）	0.404	0.304	-0.100	-2.010***
	核匹配	0.411	0.304	-0.107	-2.560***
	半径匹配（卡尺=0.1）	0.395	0.323	-0.072	-1.660*
d（住房）	邻近匹配（1对1）	0.404	0.101	-0.303	-6.690***
	核匹配	0.411	0.101	-0.310	-8.490***
	半径匹配（卡尺=0.1）	0.395	0.108	-0.287	-7.400***
e（生活）	邻近匹配（1对1）	0.104	0.011	-0.093	-12.440***
	核匹配	0.104	0.011	-0.093	-15.540***
	半径匹配（卡尺=0.1）	0.104	0.009	-0.095	-16.070***
f（资产）	邻近匹配（1对1）	0.423	0.051	-0.372	-14.840***
	核匹配	0.425	0.051	-0.374	-18.150***
	半径匹配（卡尺=0.1）	0.423	0.041	-0.382	-18.690***