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.     

ASPECTS OF POVERTY IN GREECE

Poverty in Greece is measured and decomposed using the primary consumption expenditure data of two Greek Household Expenditure Surveys (1974, 1981/82). Poverty is found to be associated with particular characteristics of the household or the household head. These characteristics are residence in rural areas, large household size, low educational level and old age of the household head. Poverty is also very high among members of households headed by farmers and retired persons. Both absolute and relative poverty declined substantially between 1974 and 1982. Changes in the structure of the population had a positive effect on poverty alleviation.     

“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。     

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.     

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.     

Household composition,Engel curves and welfare comparisons between households: A duality approach

This paper is about household composition effects in consumer theory. These are important for the specification and estimation of Engel curves and demand functions. The models examined here have important applications in the areas of the measurement of cost of living indices, the study of poverty and inequality and in certain aspects of social policy. The models are based on the approach of Barten (1964). Taste differences between households are parameterized in a way which has been called simple good augmenting or simple repackaging in the literature on quality change. In this theory, changes in household composition play an analogous role to price changes. ‘True household equivalent scales’ are developed which are analogous to true cost of living indices and permit welfare comparisons across households.     

To Work Oneself out of Poverty: The Dutch Experience 1989–96

This paper investigates the effect of finding work by one of the household members on the probability of escaping from poverty in the Netherlands. For households with non-active heads, finding work by the head of the household is the most important (investigated) event connected with exiting poverty, nearly a third of all poverty endings. However, finding a job by the head of the household does not guarantee one leaving poverty. In practice, the success rate yields 25 percent. A multivariate analysis shows that finding a job by the head of the household increases the chance of leaving poverty with 22 percent points. So, some exits from poverty are a result of other factors or are due to selectivity of the job-finders. This difference is much larger when partners or (adult) children find jobs.     

“When Life Gives You Lemons”: Using Cross-Sectional Surveys to Identify Chronic Poverty in the Absence of Panel Data

At the core of poverty eradication is the need to eliminate that poverty that is persistent over time (chronic poverty). Unfortunately, traditional approaches to identifying chronic poverty require longitudinal data that is rarely available. In its absence, this paper proposes an alternative approach that only requires 1 year of cross-sectional data on monetary and non-monetary poverty. It puts forth two conjectures and contends that the combined profile of a household as both income poor and multidimensionally poor can be used as a proxy of that household being chronically income poor. To explore the viability of this approach, we use a probit model and longitudinal data for three Latin American countries to estimate households’ probabilities of remaining in income poverty based on their past income and multidimensional poverty statuses. We find empirical support for the approach that is significant, consistent across countries, and robust to various controls and periods of analysis.     

The poor outside the lamplight: on the prevalence of poverty among population groups not included in household surveys

Poverty rate calculations are often based on household surveys that exclude some of the groups most vulnerable to poverty such as the homeless. This paper documents the nature of the excluded groups and the quantitative importance of their omission for the Czech Republic. Our study combines European Union Statistics on Income and Living Conditions data for 2011 with information from the 2011 Population Census. Our preferred estimate indicates an increase in the poverty rate by almost one percentage point. The paper contributes to accurately identifying the most vulnerable members of the society, which is essential for setting effective social policies.     

Is increased agricultural protection beneficial for South Africa?

Using a top down computable general equilibrium microsimulation model of South Africa, this paper explores the impact on household well being of an increase in agricultural protection. This issue is of broader relevance to developing countries that may be contemplating the use of World Trade Organisation permissible trade barriers so as to achieve a domestic policy objective. The model predicts that gross domestic product would be unaffected while real private consumption falls. The real exchange rate appreciates while unemployment levels are unaffected. Food, other manufactures, trade and hotels are the clear losers. All other industries experience small positive gains or no impact on their output. The impact on households depends on their factor endowments and their consumption patterns. The impacts on poverty reduction are very small. Poverty indicators increase more in urban areas than in rural areas. Poverty increases slightly more among Asian households, followed by White and then Coloured households. African households experience small declines in poverty.     

The Redistributive Effects of a Minimum Wage Increase in New Zealand: A Microsimulation Analysis

This paper examines the potential effects on inequality and poverty of a minimum wage increase, based on a microsimulation model that captures the details of household composition and the income tax and welfare benefit system and allows for labour supply responses. Results suggest that, largely due to the composition of household incomes, a policy of increasing the minimum wage has a relatively small effect on the inequality of income per adult equivalent person, and a money metric utility measure, using several inequality indices. Hence, the minimum wage policy does not appear to be particularly well targeted, largely due to many low wage earners being secondary earners in higher income households, while many low income households have no wage earners at all. These results are reinforced when allowing for wage spillovers further up the wage distribution. Nevertheless, a minimum wage increase can have a more substantial effect on some poverty measures for sole parents in employment.     

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.     

中国老年家庭的经济脆弱性与贫困

利用中国健康与营养调查(CHNS)2006和2009年的面板数据测度了老年家庭的经济脆弱性,检验各因素对经济脆弱性和贫困的相对影响力。老年家庭的经济脆弱性高于贫困;户主特征和家庭变量不同程度地影响到了经济脆弱性及贫困,代际间向上流动的私人转移支付对老年家庭的经济脆弱性和贫困没有作用;超过24%的非贫困家庭是经济脆弱性家庭;期望效用的脆弱性(VEU)方法表明,不平等虽然减少了脆弱性,但其影响经济脆弱性的力量最小,不可解释的风险是最重要的因素,异质性风险和协同性风险的力量居中。     

Challenges in Measuring Poverty and Understanding its Dynamics: A South Asian Perspective

South Asia’s success at reducing poverty does not imply that the topic has become passé. Poverty rates are by now low, but this is because poverty lines are low as well. And the assessment of living standards and their dynamics are blurred by measurement and interpretation challenges. This paper relies mostly on South Asian examples to highlight four tensions: poorer versus richer households, rural versus urban locations, monetary versus non‐monetary dimensions of wellbeing, and household characteristics versus context. The discussion is conducted against the backdrop of the two analytical approaches with South Asian roots that have shaped the debate for decades. This review leads to three main recommendations: household survey data has to be exploited in a more thorough manner, data that is increasingly available from other sources needs to be incorporated more systematically in the analysis, and the multiple dimensions of wellbeing should be better integrated in a common framework.     

四省藏区多维贫困空间分异及基层能力建设

四省藏区作为我国深度贫困地区的重要组成部分是精准扶贫精准脱贫中后程的重点和难点。基于2014年采集的“十二五”期间全国“整村推进”项目村基础数据,借鉴A-F多维贫困测度方法,对四省藏区村域多维贫困状况进行测度分解,并基于拓展的能力视角探讨了村级组织能力禀赋对四省藏区村域多维贫困状况的差异化缓解作用。结果发现:除经济贫困之外,四省藏区还遭受基础教育和生产生活条件等维度的多维贫困,且存在空间异质性,云南和青海藏区是四省藏区中多维贫困问题最严重的区域;生活水平条件和村域发展资本维度对四省藏区的多维贫困指数贡献率最高;基层组织能力禀赋会显著影响四省藏区村域的多维贫困状况、缩小地区差距,在深度贫困地区更加显著。根据研究结论,从覆盖基础教育设施、改善生产生活条件、提高基层组织能力建设三方面为深度贫困地区脱贫攻坚提供政策参考。     

Household poverty and inequality: the implication of migrants’ remittances in Nigeria

This article examines the nature of migrant remittances and the amount by which income poverty and inequality will be reduced given migrants’ remittances. We used the living standard survey (NLSS) data set produced by the government of Nigeria to help track poverty reduction progress. The unit of analysis was the household, upon which information on remittances was analysed. From the results, 94% of households received remittances through internal channels while less than 5% received them through international channels. Remittances alleviated poverty head count by 20% and helped to equalize household income inequality by 25%.     

Assessment of the effects of targeted poverty alleviation policy on differently poverty-stricken households: A multi-propensity score weighting model

Eliminating poverty is a multifaceted global challenge and a focal point of global development governance. With the implementation of targeted poverty alleviation (TPA), China's poverty alleviation efforts have had significant achievements. This study provides a new perspective by classifying poverty-stricken households based on poverty root causes at the household level, a multi-propensity score weighting model based on counterfactual inference is employed to examine the poverty reduction effect and policy precision on six non-equivalent poverty-stricken household groups in a Chinese county. The results reveal that the poverty reduction effects differed among poverty-stricken households with different root causes of poverty. Specifically, households impoverished due to disability have the lowest income of the six groups. The assistance policy effects also vary significantly and are found to be poorly suited to poverty-stricken households a lack of labor force and funds. A robustness test confirms this conclusion and a more nuanced analysis reveals that these differences are reflected in the wage and transfer incomes. Therefore, to ensure the stability of poverty reduction and the sustainability of income for poverty-stricken households, relevant associated aid policies need to place different emphases based on their household characteristics.     

THE IMPORTANCE OF CONSECUTIVE SPELLS OF POVERTY: A PATH‐DEPENDENT INDEX OF LONGITUDINAL POVERTY

In this paper we propose a new index of individual poverty in the longitudinal perspective, taking into account the way poverty and non‐poverty spells follow one another along individual life courses. The Poverty Persistence Index (PPI) is based on all the pairwise distances between the waves of poverty. The PPI is normalized and it assigns a higher degree of (longitudinal) poverty to people who experience poverty in consecutive, rather than separated, periods, for whom the distances from the poverty line are larger along time and moreover, when the worst years are consecutive and/or recent. We also propose an aggregate index of persistence in poverty (APPI) in order to measure the distribution of the persistence of poverty in a society, and evaluate at once the diffusion of poverty, its depth, duration, and recentness. The indices are tested in comparison with other measures from the literature both at the individual as well as at the societal level.     

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.