Impact of climate-smart agricultural technology on multidimensional poverty in rural Ethiopia

A large body of empirical literature showed that the adoption of agricultural technologies reduces poverty. However, dominants of those studies so far used one-dimensional income or expenditure-based measures of poverty which may not reflect other types of deprivations. Therefore, the major objective of this study is to examine the impact of adopting climate-smart agricultural technology, which refers to a joint application of row planting methods and the use of chemical fertilizers, on the multidimensional poverty status of rural households in Ethiopia. To estimate the impact of the stated technologies, this study employs propensity score matching and endogenous switching regression methods. To measure the multidimensional poverty index, the study also uses the Alkire and Foster counting approach. Using the Ethiopian Socioeconomic Survey(ESS), collected in 2015-Wave 3, the results of the study show that the adoption of these technologies reduces deprivation score and one of its component, the standard of living part. Regionally, a high reduction in deprivation is observed in Amhara and Oromiya regions. The results also show that the impact is significantly higher in severely deprived households. It is also observed that the reduction in multidimensional poverty due to the technology is through an increase in income/consumption via improvement in production gain. The impact channels more through the non-food expenditure pathway. Finally, this study also sheds light on the effects that technology adoption has on multidimensional poverty reduction.

Analyzing multidimensional measures of poverty and their influences in China's Qinba Mountains

We use the Alkire–Foster poverty measure and decomposition method to study multidimensional poverty in the Qinling–Daba contiguous poor area of China's Henan Province.We examine absolute,relative,and multidimensional poverty focusing on heads of household and family characteristics as constituents of escaping each.We find that the multidimensional poverty index declines to a low level as values of k increase.Combining first-order random dominance with second-order stochastic dominance quickly determines rankings in the multidimensional poverty index.Increasing non-agricultural income emerges as the most important influence on escaping rural poverty,whereas households with elderly and children are at greatest risk for falling into poverty.

Investigating poverty in rural Iran: The multidimensional poverty approach

In this study, rural poverty in Iran is investigated applying a multidimensional approach, association rules mining technique, and Levine, F and Tukey tests to household data of 2008. The results indicate that poverty in its multi-dimensions is an epidemic problem in rural Iran. The results also exhibit that there are 11 patterns of poverty in the rural areas including four main patterns with 99.62% coverage and seven sub-patterns with nearly 0.38% coverage. In these patterns, housing and household education are the most important dimensions of poverty and income poverty is the least important dimension. Government income support policy to households, in enforcement the law of targeting subsidies, cannot be regarded as pro poor policy but it follows other political aspects.

Achievements and Outlook of China's Multidimensional Poverty Reduction

Since the founding of the People's Republic of China in 1949, the Chinese government has made great achievements in reducing poverty through human capital development(education, healthcare, gender equality, maternal and infant health, and prevention and treatment of iodine deficiency), infrastructure construction(transportation,electric power, ICT application and access to safe drinking water), improvement of living conditions(toilet hygiene, stove renovation and resettlement) and rural social security("five-guarantees" system, subsistence allowance, rural pension insurance, natural disaster relief and agricultural insurance). Since the 18th CPC National Congress in 2012, the Chinese government has made remarkable progress in eradicating poverty and enhancing village governance. However, serious challenges will still exist after China's poverty eradication in 2020 and may lead to re-impoverishment.

Multidimensional Poverty and Poverty Reduction Policies in Rural China during 1995-2013

Using the multidimensional poverty index(MPI), this paper measures the intertemporal change in poverty in China's rural areas during 1995-2013, decomposes major poverty reduction factors, and creates a correlation between poverty reduction factors and national pro-farmer and poverty reduction policies. Our findings suggest that multidimensional poverty has been greatly alleviated in rural China on all fronts beyond the income dimension. Specifically, the burden of out-of-pocket medical expenses contributed the most to the overall poverty of farmers in the 1990s; this gap was subsequently mitigated by the New Rural Cooperative Medical Insurance System. Lack of economic empowerment-the second most prominent manifestation of poverty two decades ago-has been alleviated with public welfare improvements. In the present stage, health and healthcare are the primary difficulties facing poor farmers multidimensionally. Sub-groups such as elders,those less educated and those living in western China or in poor counties suffer from a high degree of poverty. This implies that multidimensional poverty is concentrated among the underprivileged groups and in less developed regions, whom should be policy priorities.Robustness tests suggest that the paper's conclusion still holds after changing the proxy variables of the subdimensions, revising weights or removing some dimensions.

Using Multiple Correspondence Analysis to Measure Multidimensional Poverty in Congo

The following analysis is based on a multidimensional understanding of poverty using a nonmonetary basic needs approach. It is ground on data from the first survey on household living conditions for poverty assessment, conducted by the National Institute of Statistics of Congo in 2005. Multiple Correspondence Analysis is applied to construct a composite indicator by aggregating several attributes likely to reflect the poverty of individuals or households. The application shows that Congolese households are not affected by the same type of poverty. Three types of non-monetary poverty are identified: infrastructure poverty, vulnerability of human existence and poverty of comfort. These households were then classified according to the composite indicator of Poverty. The results show that the incidence of poverty corresponds to the weight of poor class of about 70.67%.

Measuring Multidimensional Poverty Reduction for the Chinese Elderly——Based on 2010 and 2016 Data from the China Family Panel Studies(CFPS)

Based on data gathered from the China Family Panel Studies(CFPS)in 2010 and 2016,this paper examines income poverty and multidimensional poverty among the Chinese elderly.Compared with the non-elderly population,poverty incidence was relatively lower among China’s elderly population in 2010,but the elderly poor were significantly more poor.By 2016,the level of poverty became more or less the same between elderly and non-elderly people.Compared with 2010,the poverty incidence on various deprived dimensions and the average share of deprivation for the elderly fell sharply in 2016 by an average of 30 and 10 percentage points,respectively.Reduction in poverty incidence was 10 percentage points higher for the rural elderly than for the urban elderly.After estimating the multidimensional poverty index for the elderly by the“two no worries and three guarantees”criteria,we found that the intensity of multidimensional poverty was only about half that of the income poverty.The“two worries,”i.e.the lack of food and clothing,contributed more to multidimensional poverty than did what the“three guarantees”target i.e.education,healthcare and housing,especially on income and residential energy dimensions.Elderly healthcare contributed more than 20%to the“three guarantees.”

Fiscal Livelihood Spending’s Effects on Multidimensional Poverty Reduction in China

This paper investigates how fiscal spending on livelihood improves multidimensional household poverty in China.Based on the panel data of the“China Health and Nutrition Survey”(CHNS)for 2004-2015,we measured the chronic multidimensional poverty index for Chinese households.We have created a multitiered model for empirical analysis.Our findings suggest that multidimensional poverty in China is predominantly capacity poverty.Fiscal spending on livelihoods significantly reduces multidimensional poverty for Chinese households,especially rural households.Investments on livelihoods are more poverty-reducing than transfer spending on livelihoods.As an innovation,this paper offers a dynamic analysis of the effects of livelihood spending on multidimensional household poverty controlling for heterogeneity between individual households and across regions.Our conclusion suggests that the government should improve policy arrangements to increase social opportunities and support sustainable development capacities for the poor,while enhancing protective social security systems.

Multidimensional Relative Poverty of Farmers in Tibetan Areas - Based on a Data Analysis on Micro Surveys

In 2020,the issue of absolute poverty has been solved,and China is building a well-off society in an all-round way.The issue of relative poverty is an important content of poverty reduction.Based on a survey data from Danba County in October 2020,this paper uses the AF method to calculate the incidence of multidimensional poverty and the multidimensional poverty index.The results showed that 44.65%of the farmers have multidimensional deprivation of any three indicators of relative poverty,and 2.79%of the farmers have serious multidimensional deprivation;the incidence of one-dimensional poverty in terms of“educational level index of head of household,”“per capita non-transfer income of households in 2019,”and“per capita household income in 2019”is the highest;at the same time,the contribution rate of the three indicators to the multidimensional poverty index is also higher than other indicators.Therefore,several suggestions have been put forward to alleviate the multidimensional relative poverty in the region from the aspects of industry development and education.

CCT and Rural Long-Term Poverty Reduction:International Experiences and China’s Practice

China’s anti-poverty strategy in the post-2020 era will focus on reducing chronic poverty and alleviating relative poverty.As a common international approach for long-term multidimensional poverty reduction,conditional cash transfer(CCT)payments reduce current poverty,prevent future poverty,and improve income distribution by providing poor households with cash allowances and promoting children’s human capital accumulation.For such reasons,CCT serves as an anti-poverty policy instrument worth referencing for China.This paper systematically reviewed the theoretical basis and development journey of CCT,the short-term and long-term implementation effects,as well as the decision-making basis,design and potential limitations.In this paper,we have further analyzed the poverty-reducing effects and problems of China’s rural public transfer payment policies in the current stage and discussed the achievements and inadequacies of China’s ongoing CCT pilot programs.Results indicate that the further development of CCT in China calls for a combination top-down and bottom-up policy-making approaches in project design and implementation,as well as an evolving poverty governance system complementary with other relevant policies.

共同富裕背景下女性多维贫困变动及分解

党的二十届三中全会指出,完善覆盖农村人口的常态化防止返贫致贫机制。本文根据多维贫困的分析框架,利用中国家庭追踪调查(CFPS)的四期个体微观调查数据,构建中国女性多维贫困指数,并进行了测算和分解。研究发现,2014—2020年,中国女性多维贫困状况总体上有所改善,但改善程度不均衡。处于严重贫困状态的女性改善程度较小。维度分解结果表明,教育、时间赤字和收入是影响女性贫困的主要因素,而健康和心理则是相对次要的因素。并且,相较于收入因素,其余因素的影响渐增。从城乡比较来看,城镇女性所面临的贫困状况一般优于农村女性。城镇女性的最主要致贫因素是收入,而农村女性则是教育和时间赤字。从不同婚姻状态的群体比较来看,丧偶女性面临的多维贫困状况最为严重,离婚女性多维贫困改善较已婚女性显著。本文深入反映了中国女性在多维贫困方面的困境,为中国新发展阶段防止返贫致贫机制的完善和可持续发展目标的实现提供了启示和建议。

可行能力视角下的老年信息贫困:概念建构与结构关系

信息技术快速发展和广泛应用导致老年群体陷入信息贫困境地,厘清老年信息贫困的概念内涵是老年信息贫困有效治理的前提。基于可行能力理论探究老年信息贫困的概念内涵和结构关系,将老年信息贫困分为信息能力贫困和信息功能贫困两个维度,并使用CLASS 2020调查数据实证分析老年信息能力贫困与信息功能贫困的关系。研究发现,老年群体信息能力贫困状况不容乐观,信息接入、信息获取、信息使用和信息感知等维度能力贫困与信息功能贫困显著相关,通过倾向得分匹配(PSM)检验后结果依然稳健。故需构建兼顾信息能力提升和信息功能救助的治理方略以解决老年信息贫困问题。

可视化知识图谱分析:多维贫困测度研究回溯与前瞻

运用Cite Space文献计量分析软件,对中国知网2005年1月至2023年1月间多维贫困测度的核心期刊文献进行可视化分析.研究结果表明,多维贫困测度研究呈现出初步探索阶段弱关注、迅猛发展阶段热研究、持续升温阶段热关注的特点,多维贫困、精准扶贫、相对贫困、贫困测度是该领域的研究热点.

后扶贫时代川陕革命老区相对贫困治理机制研究

基于川陕革命老区的实地调研数据,采用Alkire-Foster多维贫困测量法,对川陕革命老区农村居民多维相对贫困进行测度和分解.测度结果显示:单维相对贫困发生率差异明显,多维贫困发生率仍然较高.在后扶贫时代,川陕革命老区相对贫困治理需要从教育扶贫、产业扶贫、生态扶贫、联动扶贫、保障扶贫等方面建立长效机制.

基于多维贫困脆弱性视角的数字普惠金融防止农户返贫效果研究

选取2014—2018年中国家庭追踪调查的微观数据和北京大学数字普惠金融指数构建三期平衡面板数据,采用Probit模型对数字普惠金融防止返贫的效果进行实证研究并进行异质性分析。结果表明,数字普惠金融能显著缓解农户多维贫困脆弱性,具有较好的防止返贫效果。就渠道效应而言,其覆盖广度和使用深度对农户多维贫困脆弱性的缓解作用更强。进一步异质性分析揭示了数字普惠金融对低收入农户和东中部地区居民的贫困脆弱性缓解效果更为明显。

数字普惠金融对多维贫困脆弱性的影响研究

数字普惠金融发展对贫困多维性和动态性的影响尚未得到充分关注。基于中国家庭追踪调查数据构建多维贫困脆弱性变量,采用北京大学数字普惠金融指数,探讨数字普惠金融对家庭多维贫困脆弱性的影响、异质性效应和内在机制。研究发现,数字普惠金融的发展显著缓解了家庭多维贫困脆弱性,在进行一系列稳健性检验后,结果依然显著。异质性分析表明,数字普惠金融对物质资本较低家庭、社会资本较低家庭、政治地位较低和农村家庭的多维贫困脆弱性缓解程度更大。机制分析显示,数字普惠金融通过促进人力资本投资,提升家庭商业保险支出和缓解不确定性风险冲击三种渠道缓解家庭多维贫困脆弱性。细分维度发现,数字普惠金融对收入、教育、健康和生活质量维度的贫困缓解作用较为显著,与机制分析的结果较为符合。

河池市农村基本公共服务与多维贫困的耦合关系探析

农村基本公共服务是乡村综合发展状况的重要表征,研究其与多维贫困的关系对指导稳定脱贫和缓解相对贫困具有重要参考意义。本文以河池市652个重点帮扶村为研究对象,分析其基本公共服务综合水平,构建了村域尺度上基本公共服务和多维贫困测度模型,并基于耦合模型结果深入探索二者之间的耦合协调关系及影响机制,为进一步推动乡村振兴和可持续发展提供参考依据。结果表明:研究区内基本公共服务水平呈现由中心向四周递减,而多维贫困水平由西北向东南递增,呈现出分散与集中并存的特点。空间上,基本公共服务和多维贫困的耦合态势并不均衡,虽整体分布均匀,但在特定区域存在规律性集中。在耦合协调发展地区,二者负相关明显,提升基本公共服务水平能够有效缓解多维贫困,促进服务集中和经济迅速发展,从而减轻贫困状况,为公共服务提供更好的发展条件;而在非协调区域,二者呈正相关,基本公共服务水平的提升并不能有效解决贫困问题,甚至加剧经济下滑和失衡。当地政府在实施乡村振兴战略时,应建立科学系统的基本公共服务和脱贫帮扶机制,改善农户的生存环境,提高生活质量,确保稳定脱贫和可持续发展。

中国居民多维健康贫困的测度与分解研究

目的:构建多维健康贫困指标体系,分析居民健康贫困现状,为我国相对贫困治理提供参考。方法:将多维贫困的A-F方法引入多维健康贫困的测度,使用中国家庭追踪调查(CFPS)2018年数据,从健康权利、健康能力、健康风险三个维度进行健康贫困测度。结果:随着临界值k增大,多维健康贫困的广度不断减小,深度逐渐增大,当k=0.3时,健康能力、健康权利和健康风险对健康贫困的贡献度分别为47.42%、27.94%和24.63%;二级指标中,受教育程度的贡献度最大,是否参加医疗保险的贡献度最小;从省份来看,甘肃、河南、辽宁、广东、四川、河北对健康贫困的贡献度较大。结论:资源不平等会削弱居民获得健康资源的能力,增加陷入健康贫困的风险,因此在相对贫困治理过程中政府应保障居民公平获取教育、卫生、就业和基础设施等资源,继续健全多层次社会保障体系,在健康贫困抵御上渗透发力。

基于夜光遥感数据的广西县域农村多维脱贫分析

巩固脱贫攻坚成果,衔接乡村振兴战略,防止返贫是我国目前经济建设的重要任务。2022年中央农村工作会议重点强调了要“坚决守住不发生规模性返贫底线”。在多维贫困的基础上,动态客观地监测县域农村贫困程度的时空演变,对国家防返贫工作十分重要。随着遥感卫星的快速发展,高信息量和高质量的遥感数据影像逐渐丰富并被广泛应用,相比于传统的统计类数据,夜光遥感数据具有与社会经济要素高度相关、相对客观性强和时间跨度相对较长等优点。该文以DMSP/OLS和NPP/VIIRS夜光遥感数据为基础,提取夜间灯光强度指数,结合多维脱贫指数构建两者关系模型,对2010—2020年广西县域农村贫困程度进行时空演变研究,分析存在的返贫原因,为乡村振兴和脱贫攻坚提供科学参考和预防措施。

中国少年多维贫困水平及时空演变

少年时期是个体从儿童向青年转变的关键阶段,然而迄今关注这个群体多维贫困问题的研究相对较少。基于2014—2018年中国家庭追踪调查(CFPS)数据,以中国24个省、市、自治区为研究区,采用Alkire-Foster方法从生存、照料、教育、营养、健康、参与等6个维度测算10~15岁少年多维贫困的水平,并结合空间自相关分析探究其时空演变格局。结果表明:2014—2018年间,多维视角下的少年群体中存在较为严重的相对贫困问题,其中营养维度对少年多维贫困的贡献率最高,其次是生存、照料和参与维度,教育和健康维度的贡献率较低。中国少年多维贫困状况逐步改善,全局空间上呈现“随机分布-弱集聚-强集聚”的变化趋势,但农村少年多维贫困比例始终高于城镇,东中西部地区各省域间也存在一定差异。因此,针对少年群体的减贫政策需要重视不同维度的影响,不断缩小区域间差异。