地理学报 ›› 2021, Vol. 76 ›› Issue (10): 2425-2438.doi: 10.11821/dlxb202110007
收稿日期:
2020-09-21
修回日期:
2021-06-18
出版日期:
2021-10-25
发布日期:
2021-12-25
通讯作者:
祁新华(1974-), 男, 博士, 教授, 博士生导师, 主要从事贫困地理、人文地理学与生态学教学与交叉研究。E-mail: fjqxh74@163.com作者简介:
严小燕(1992-), 女, 江西赣州人, 博士生, 研究方向为经济地理与区域发展。E-mail: yxynini@sina.com
基金资助:
YAN Xiaoyan1,2(), QI Xinhua1,2(
)
Received:
2020-09-21
Revised:
2021-06-18
Published:
2021-10-25
Online:
2021-12-25
Supported by:
摘要:
将贫困视为一个动态现象与过程逐渐成为学术界共识。尽管国内外相关成果丰硕,但迄今鲜有对贫困动态研究进行系统梳理。本文立足于现有文献,开展贫困动态研究的回顾与展望。首先,解析了贫困动态的内涵及类型;其次,分别从单维和多维角度归纳了贫困动态测度方法的原理、优缺点及数据来源;第三,从持续时间、家庭生命周期变化、代际传递和时空演变四方面系统梳理了贫困动态研究脉络;第四,基于经济学、社会学和地理学视角,分别从经济、发展和空间层面对贫困动态发生机制进行了解析。在对以上内容进行简要评述的基础上,展望了未来值得进一步探究的若干贫困动态议题,希望能够为贫困动态研究提供有益借鉴,并为巩固扶贫成果、完善扶贫政策提供理论支撑。
严小燕, 祁新华. 贫困动态的测度方法与演化机制[J]. 地理学报, 2021, 76(10): 2425-2438.
YAN Xiaoyan, QI Xinhua. The measurement method and evolution mechanism of poverty dynamics[J]. Acta Geographica Sinica, 2021, 76(10): 2425-2438.
表1
贫困动态的定义
定义 | 文献编号 | |
---|---|---|
贫困动态 | 1. 个人和家庭在一段时间内经历的福祉或不幸的变化 | [ |
2. 贫困转变和持续的流动模式 | [ | |
3. 讨论个人/家庭在生命周期过程中贫穷位置(地位)上的流动型态及地位转变的原因 | [ | |
4. 在较长的时期内,由贫困标准和个人/家庭福利状况改变导致个人/家庭进入或者退出贫困的状态 | [ | |
5. 分析家庭或个人在贫困位置上的流动状况(进入、停留或脱离)以及地位转变的原因 | [ | |
6. 在个人生活历史之中,由多种原因引起个人或家庭经历进入、保持或摆脱贫困状态的社会现象 | [ | |
7. 贫困群体在不同时期经历的包括陷贫、脱贫或持续贫困等的动态变化过程 | [ |
表3
贫困动态的主要测度方法
方法 | 主要原理 | 优点 | 缺点 | 文献编号 | ||
---|---|---|---|---|---|---|
单维 | ||||||
贫困率 | 测算一段时间内贫困率变化, 式中:H为贫困率;q为贫困人口数;n为总人口数 | 反映贫困广度 | 不能反映贫困深度、差异度变化 | [ | ||
转移矩阵法 | 测度不同年份农户在贫困和非贫困之间的转换概率 | 直观测算贫困与非贫困的转换规模 | 无法了解贫困程度变化 | [ | ||
贫困指数法 | Sen指数 | 通过测算一段时间内贫困指数的变化显示贫困动态 | | 满足单调公理和加性分解公理 | 缺乏连续性和复制不变性,强转移性公理不足 | [ |
SST指数 | $SST=\frac{1}{n^{2}} \sum_{i=1}^{q}\left[\frac{z-y_{i}}{z}\right] \times(2 n-2 i+1)$ | 调整Sen指数权重函数 | 不符合加性分解公理,不满足转移—敏感性公理 | |||
FGT指数 | $FGT=\frac{1}{n} \sum_{i=1}^{q}\left[\frac{z-y_{i}}{z}\right]^{\alpha}$ α ≥ 0,α为分布敏感参数 | 克服Sen指数和SST指数所缺乏的加性分解公理 | 难以确定α最优值 | |||
Spells法 | 考察特定时段个体贫困持续时间,以及依据多个时段内处于贫困状态时间是否长于某界线来区分慢性和暂时性贫困 | 简单直观、易操作 | 侧重贫困进入和退出转变,未考虑贫困深度 | [ | ||
组分法 | 基于“永久性收入假说”前提,将收入/消费分为永久性和暂时性部分,若前者低于贫困线则被认为是慢性贫困,其余为暂时性贫困,总贫困是二者总和 | 采用回归模型避免慢性和暂时性贫困的区分在时间长度上不统一 | 对长期贫困识别受贫困深度影响;贫困时间长度不敏感;对数据质量要求高 | [ | ||
生活 史法 | 通过参与式调查,访谈个人生活史,绘制生活史图表,以预先设定的等级标准衡量生活轨迹中的幸福水平 | 能获取个人生命历程中详细的生活福祉及幸福感变化的信息 | 难获取长时间序列面板数据,受主观性因素影响大 | [ | ||
多维 | ||||||
A-F双界线法 | 设置指标和缺失得分两个临界值,计算多维贫困指数(MPI)动态,并对广度、深度、维度和子群进行分解 | 运用广,克服多维贫困识别中“并集法”和“交集法”弊端 | 指标选取、临界值和权重设置具有主观性 | [ | ||
指标综合法 | 通过加权求和、主成分分析、人工神经网络或多面体法等方法汇总得出综合贫困指数,分析动态趋势或结合ESTDA法探索时空交互 | 灵活性较强,可与多元数据、多种方法相结合 | 受指标选择和赋权影响大;不好衡量各指标或维度贡献 | [ | ||
地理信息技术辅助法 | 借助3S技术提取多源遥感数据,社交媒体大数据,融合传统普查或调研数据,运用机器算法(随机森林、卷积神经网络等)测算、描述和预测多维贫困及其时空动态,实现可视化 | 时效性好、精度高、信息量大,有效弥补传统方法的滞后性和不充分性 | 对不同年份、不同来源的数据整合、精度校准技术要求高 | [ |
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