Decomposition of inter-regional poverty gap in India: a spatial approach

This paper examines the impact of various socio-economic factors on consumption in rural West Bengal, an eastern state of India, using a regression-based technique reformulated in a spatial framework. The difference of incidences of poverty (head count ratios) in two parts (North and South) of rural West Bengal is then decomposed using the familiar Oaxaca decomposition methodology into an aggregate characteristics effect, which is interpreted as a resource effect and an aggregate coefficients effect, which is interpreted as an efficiency effect. An important observation from the present analysis is that the poorer North Bengal has a scarcity in terms of availability of characteristics (resources) compared to that in South Bengal and the resource scarcity in North Bengal is the dominant factor causing the poverty gap between the two parts of West Bengal. Thus, attention needs to be paid to North Bengal with respect to enhancement of important policy variables like education level, Government aid, and employment opportunities.     

Impact of Socio-Economic factors on Consumption Expenditure through Public Distribution System in rural India

Impact of public distribution system (PDS) on poverty in rural India is established; however, how the households from different socio-economic backgrounds are procuring through PDS, relatively, needs study. With this objective, influence of factors like poverty status, family size, social group, religion, gender and occupation on probability of household incurring consumption expenditure through PDS has been studied by using unit level data of consumer expenditure survey of National Sample Survey Office (NSSO) and multinomial logistic regression technique. The study is restricted to food grains rice and wheat and reveals that probability of consumption, through PDS, of minorities, economically and socially backward classes are higher, in general.

     

“收入导向型”多维贫困的识别与流动性研究*——基于CFPS调查数据农村子样本的考察

本文结合收入及健康、教育、生活状况、卫生状况和食物支出五个非收入指标,构建了“收入导向型”多维贫困指数,采用中国家庭追踪调查（CFPS）数据的农村子样本,考察多维贫困的识别、追踪和流动性问题。在比较了6维贫困指标和多维贫困指标对贫困识别的效果后研究发现,仅依据收入、教育和生活状况三个维度即可有效识别和追踪贫困家庭,并且在这三个维度下均处于贫困状态的农村家庭跳出贫困陷阱的概率显著低于一般收入贫困家庭。研究表明,扶贫政策应当在减少收入贫困基础上更多关注多重剥夺对贫困家庭整体福利的影响,并致力于提高贫困家庭的持续脱贫能力以增强其跳出贫困陷阱的可能性。     

POVERTY IN RURAL INDIA: CASTE AND TRIBE

This paper analyzes the determinants of rural poverty in India, contrasting the situation of scheduled caste (SC) and scheduled tribe (ST) households with the non-scheduled population. The incidence of poverty in SC and ST households is much higher than among non-scheduled households. By combining regression estimates for the ratio of per capita expenditure to the poverty line and an Oaxaca-type decomposition analysis, we study how these differences in the incidence of poverty arise. We find that for SC households, differences in characteristics explain the gaps in poverty incidence more than differences in transformed regression coefficients. In contrast, for ST households, differences in the transformed regression coefficients play the more important role.     

Profiling the Fuzzy Latent Structure of Multidimensional Poverty: Toward Valuable Insights for Poverty Policymakers

Abstract

Several multidimensional poverty indices have been proposed, and have been extensively studied in the literature. On the other hand, the need for aggregation of poverty indicators into one multidimensional index has been questioned. It has been argued even so that this aggregation can be misleading for political targeting strategies. Subsequently, some researchers have advocated that the use of the latent class analysis would address these issues. However, this setting does not allow to take into account the fuzzy nature of the latent poverty concept. The contribution here is to use the Grade-of-Membership (GoM) model to profile the fuzzy latent structure of multidimensional poverty, for a more realistic handling of this phenomenon. The application of the GoM methodology to multivariate poverty data for the Tunisian case reveals four most prevalent multidimensional poverty profiles. The results emphasize the role played by contextual effects. Indeed, the rural cluster is suffering more intense deprivation and groups in the central and coastal regions have a more comfortable status in comparison with the group of households residing in inland regions. A thorough analysis of these patterns is put forward in this research, giving valuable insights to policy makers.     

Adding value through the mechanization of post-harvest cassava processing,and its impact on household poverty in north-eastern Zambia

This article investigates the impact of adopting a mechanized cassava processing system on household poverty levels in Zambia. An Foster, Greer and Thorbecke (FGT) poverty measure was used to compare poverty levels among households using a mechanized cassava processing system against those households using a nonmechanized process. Based on the FGT poverty measure’s specifications, a significantly lower poverty status of 49% was found among households using the mechanized process when compared to the 58% found among households using the nonmechanized process. The significant factors contributing to these differences in poverty levels include whether households are using a mechanized process or not, the number of years’ schooling among household members, the number of years’ farming experience, household income and membership of associations. The study concludes that the mechanization of cassava processing, particularly if done on the right scale, can transform primary production activities, in turn leading to higher incomes and reduced poverty levels in rural villages. Thus, policies should be introduced aimed at encouraging the promotion of mechanized post-harvest cassava processing technologies among rural households, so as to enhance crop productivity and household income levels, as well as reduce poverty among rural households.     

On the power of indicators: how the choice of fuel poverty indicator affects the identification of the target population

In light of the creation of the EU Energy Poverty Observatory (EPOV) in January 2018 and the increase in debates on how fuel poverty is measured, we propose a critical analysis of fuel poverty indicators and demonstrate that choosing a given indicator is central to the identification of the fuel-poorpopulation.

First, we conducted an inter-indicator analysis to show how profiles of fuel-poor households vary depending on the indicator selected. We designed a multidimensional approach based on a multiple correspondence analysis and a hierarchical and partitioning clustering analysis to study characteristics of fuel-poor households. We highlight the difficulty of identifying a fuel-poor ‘typical profile’ and show that the composition of the population depends on the choice of the indicator.

Second, we applied an intra-indicator analysis using two objective expenditure-based indicators with thresholds. In particular, we conducted a sensitivity analysis based on a logit model including variables describing household and dwelling characteristics. We show that the profiles of fuel-poor households as well as the drivers of fuel poverty vary considerably with the chosen threshold level.Given these findings, we stress the need to review how we currently rely on conventional fuel poverty indicators to identify target groups and give some recommendations.     

Can microcredit reduce vulnerability to poverty? Evidence from rural Vietnam

Extant literature has extensively explored microcredit's impacts, confirming its essential role in poverty alleviation. However, most studies focus on poverty measures that exclusively emphasize current poverty status without adequately addressing the potential of falling into or remaining in poverty. Furthermore, the role of credit services in helping the poor in rural areas appears to be underexamined in the literature. To address this knowledge gap, this study investigates whether rural microcredit can reduce household vulnerability to poverty. A theoretical framework is developed to capture the mechanism by which microcredit borrowing has a vital role in household businesses and impacts the probability of being poor in the future. The Vietnam Access to Resources Household Survey data set from 2008 to 2016 is used to explore this issue. The findings indicate that rural Vietnam's access to microcredit significantly reduces vulnerability to poverty. Moreover, better-off households are seemingly the most effective at using microcredit, whereas the opposite is found among worse-off households. These results are found to be robust using the propensity score matching method.     

Non-farm Income and Consumption Expenditures in Rural Bangladesh: Empirical Evidence from Multilevel Regression Modelling

This study examines the effects of non-farm income on household consumption expenditures in rural Bangladesh. A two-stage endogenous treatment effect model is built on data from a nationally representative Household Income Expenditure Survey (HIES) 2010 to control selection bias. The HIES follows a hierarchical data structure because the survey is based on two-stage stratified sampling. A multilevel mixed-effects linear regression model is used to capture the unobserved heterogeneity between clusters (PSUs) along with revealing important factors. Results reveal that non-farm income has a significant positive effect on household’s consumption expenditures and non-farm income recipient households spend about 29% more than their counterparts. In addition, higher level of per capita income, education, smaller family size and lower dependency ratio are found to be more effective in increasing consumption expenditures of rural households. Significant cluster-level variations are observed in the analyses. This study recommends that non-farm income generating activities should be encouraged among rural households as this would raise their consumption expenditures and hence, improve welfare and living standards among them.

     

中国贫困的多维测度

本文认为,用单一的收入标准来了解贫困会低估个体真实的贫困状况,很难全面反映个体贫困的复杂性、脆弱性和持久性。本文基于Sen的能力方法,使用中国健康营养调查数据,利用模糊集方法测度中国的多维贫困状况。结论显示,相对于收入贫困,个体的教育、健康和医疗保险等贫困状况更为严重;多维贫困关于测度方法、权重较敏感,等权重下的AF多维贫困被其它方法与权重下的多维贫困严格占优,而在Betti＆Verma权重下的AF多维贫困中,则住房、卫生设施和健康对多维贫困的贡献更大;多维贫困在西部、农村及女性中依然更严重。     

Gender Bias in Education in West Bengal

This paper attempts to capture gender bias at two different levels of education, namely, below class-10 and above class-10 using NSSO 64th round education expenditure data on West Bengal. The analysis for the below class-10 level involves an intra household framework and Heckman’s two step model. Further, for this section the analysis is split up into classes 1–8 and classes 9–10 in view of the Right to Education act (2005). For above class-10 level, gender bias has been captured through a multinomial logit model for selection of subjects across households.

     

Can China's new rural pension scheme alleviate the relative poverty of rural households? An empirical analysis based on the PSM-DID method

Based on five-period panel data from the China Family Panel Studies 2010–2018, this paper uses the propensity score matching difference-in-differences (PSM-DID) method to comprehensively evaluate the effects of the New Rural Pension Scheme (NRPS) on alleviating rural households' relative poverty. At the same time, based on the theory of sustainable livelihoods of rural households, the mediating effects model is applied to analyse the mechanism of rural households' livelihood capital. The results of the study are as follows. (1) The NRPS helps alleviate the relative poverty of rural households. (2) The livelihood capital of rural households is an important mechanism for the NRPS to alleviate the relative poverty of rural households, and social capital, financial capital, and human capital all play a part in the mediating effect. (3) The results of the heterogeneity tests based on the stage of rural households' participation in the NRPS and the region of participation in the NRPS indicate that the governance effects of the NRPS on rural households' relative poverty are more significant among households in the contributory stage and the central and western regions. Additionally, the results are supported by robustness tests, such as replacing the dependent variable and the PSM method. The findings of this paper have important implications for the establishment of a long-term mechanism to address relative poverty and the construction of a more efficient and inclusive rural social pension insurance system in China and other developing countries.     

Financial inclusion and poverty: a tale of forty-five thousand households

ABSTRACT

Using a new nationally representative survey data covering approximately 45,000 Indian households, we examine the effects of financial inclusion on poverty. We construct a multidimensional indicator of financial inclusion and examine the effects of financial inclusion on multiple measures of poverty including the household Poverty Probability Index (PPI), household deprivation scores, and poverty line. We find that financial inclusion has a strong poverty-reducing effect. This finding is consistent across the different measures of poverty used, and alternative ways of measures financial inclusion. These results underpin the importance of financial inclusion and the need for its promotion across countries.     

医疗保险与城乡反贫困:1989-2006

文章利用中国健康与营养调查(CHNS)数据,估计了1989-2006年医疗保险对中国城乡家庭的反贫困效应。结果发现:发生灾难性卫生支出的城乡家庭比例较高,最穷的群体其医疗费用超过收入的比例增加,医疗保险对减少收入不平等只起到微弱作用。TIP贫困曲线表明,近几年,医疗保险补偿后,城乡患病家庭的贫困并没有减轻,医疗保险在减少贫困上的作用很小。分析贫困特征的多元回归模型显示,家庭成员数量、教育程度、抚养比率、参保人数等都影响了贫困,而条件多元回归模型则显示,医疗保险对贫困的变动没有影响。     

中国农村人口贫困变动研究——基于多维脱贫指数测度

本文通过多维贫困识别方法构建相应指数，提出了在返贫和脱贫不同方向上对多维贫困的变动进行分解的思路。同时，用2010—2014年中国家庭追踪调查数据对中国农村人口多维贫困的变动进行了分解，得出以下结论：第一，收入依然是农村人口多维贫困的主要维度，但在改善收入贫困的同时应该防范健康维度返贫的风险。第二，农村人口的多维贫困状况在不断改善，但是由于返贫的影响，脱贫的效果受到了较大削弱，因此在注重脱贫的同时，不应忽视返贫的风险。第三，持续贫困人口贫困状况虽然后来有所改善，但是2012年的恶化状况提示我们对于暂时未能脱贫的人口，还需要采取措施缓解其贫困状况。     

Non-monetary poverty in Togo: a multidimensional approach

The monetary approach is not sufficient to understand the multiple dimension of poverty. The purpose of this research is therefore to measure and analyze multidimensional poverty reduced to a single non-monetary dimension and according to the characteristics of household heads. Based on the non-monetary variables provided by the most recent country survey (QUIBB 2006), we use Multidimensional Correspondence Analysis techniques to construct a Composite Poverty Indicator. The results of the non-poverty index suggest that the poorest are large families and households in rural areas. The deprivation is also more serious in households whose heads are male, aged between 51 and 99 and less educated. The findings are the same for the monetary approach at the poverty line, leading to the conclusion that both types of poverty are quite strongly and positively correlated. Finally, we propose some recommendations for socioeconomic policies.     

Pro-poor targeting and accountability of local governments in West Bengal

A commonly alleged pitfall of decentralization is that poverty, socio-economic inequality and lack of political competition allow local elites to capture local governments. This hypothesis is empirically examined using a longitudinal sample of 89 West Bengal villages concerning targeting of credit, agricultural input kits, employment programs and fiscal grants spanning the period 1978–98. Higher poverty, land inequality and low caste composition of the poor was associated with negligible adverse effects on targeting of private goods to the poor within villages, but with lower employment generation out of allotted funds, and significantly lower allocation of resources to the village as a whole. Political competition or literacy levels among the poor were not systematically related to targeting.     

A SHAPLEY DECOMPOSITION OF MULTIDIMENSIONAL CHRONIC POVERTY IN ARGENTINA

This paper proposes a Shapley decomposition to analyse the evolution of chronic poverty in a multivariate setting using a chronic poverty measure proposed by Alkire and colleagues. The decomposition makes possible to assess a vast array of information to find the drivers of change in chronic poverty, and could be a valuable tool in the way public policy programmes focus resources. We present an empirical application of the changes in chronic poverty in Argentina during the period 2004–12 using the Permanent Household Survey. We found that households with older adults show great persistence of multidimensional chronic poverty in time while the employment indicators is found to be an important driver of the intensity of chronic poverty.