摘要
随着中国农村绝对贫困的消除,扶贫主题转向缓解相对贫困。然而目前对集中连片特困区域相对贫困的测度、时空格局演化及驱动因素研究较为薄弱,例如,对县域层面上相对贫困的测度、时空格局的研究相对较少,对贫困空间分异影响因素效应的时间变异性关注有待提升;在影响因素定量识别的模型选择方面,缺少同时控制空间滞后效应和空间误差效应的模型,使得模型估计效果不佳。本文以武陵山片区为研究区,利用FGT指数、贫困距离指数、SARAR模型等揭示了2001—2018年武陵山片区县域相对贫困的时空演化特征及其驱动因素。结果表明:(1)片区县域相对贫困发生率平均为69.6%,其变动态势可分为波动、平稳和逐渐下降三个阶段,县域相对贫困的广度较高,相对贫困深度先缓慢增加后缓慢下降,相对贫困强度低且年际变化小;(2)不同等级相对贫困县域的空间分布格局变化特征不同,不同时期内不同贫困等级县域的转移格局也不同;(3)第一产业增加值占GDP比重、人均财政支出、人均固定资产投资、人均GDP、地形起伏度、空间效应等因素对县域相对贫困空间差异有影响,并且不同因素的影响效应随着时间变迁呈现不同的模式,包括持久模式、"U"型模式、衰减模式等,这些时空变异的因素共同驱动着县域相对贫困时空格局的演变。本研究将丰富已有区域相对贫困研究成果,并为新时期国家乡村振兴实践提供参考。
With the elimination of absolute poverty in rural China,the theme of poverty alleviation shifts to the alleviation of relative poverty.However,research on measurement,temporal-spatial patterns evolution and driving factors of relative poverty in concentrated and contiguous poverty-stricken areas is relatively weak.For example,there are relatively few studies on measurement and spatial-temporal patterns of relative poverty at the county level.More attention needs to be paid to temporal variability of the effects of the factors influencing spatial differentiation of poverty.As for the model for quantitatively identifying the influencing factors,there is a lack of the model that control both spatial lag effects and spatial error effects,which makes the model estimation poor.This study used Foster-Greer-Thorbecke(FGT)index,poverty distance index and SARAR(Spatial Autoregressive Model with Spatial Autoregressive Disturbances)model to analyze temporal-spatial evolutionary characteristics and driving factors of relative poverty at the county level in Wuling Mountainous area from 2001 to 2018.The results show that:(1)The average incidence of relative poverty at county level was 69.6%,and its changing trend could be divided into three stages:fluctuation,steady and gradual decline.The breadth of relative poverty at county level was relatively high.The depth of relative poverty slowly increased at first and then decreased.The intensity of relative poverty was low,and inter-annual change of this intensity was small.(2)The changing characteristics of spatial distribution patterns of relative-poverty counties with different poverty levels were different,and the shifting patterns of counties with different poverty levels were also different in different periods.(3)The driving factors,including the proportion of added value of the primary industry in GDP,per capita fiscal expenditure,per capita fixed asset investment,per capita GDP,topography and spatial effects,significantly impacted the relative poverty at county level.These factors’effects presented different patterns over time,including persistent pattern,U-shaped pattern,decay patterns,etc.These factors with spatial-temporal variations drived the spatial-temporal evolution of relative poverty at county level.This study enriches the literature on regional relative poverty and provides a theoretical reference for implementing the rural revitalization strategy in China.
作者
王永明
王美霞
WANG Yongming;WANG Meixia(College of Tourism,Hunan Normal University,Changsha 410081,China;College of Arts and Humanities,Hunan University of Finance and Economics,Changsha 410205,China)
出处
《山地学报》
CSCD
北大核心
2021年第4期576-586,共11页
Mountain Research
基金
国家自然科学基金(41761023,41761029)。
关键词
相对贫困
时空格局
贫困距离指数
SARAR模型
武陵山片区
relative poverty
temporal-spatial patterns
poverty distance index
SARAR model
Wuling Mountainous Area
