915 resultados para Multidimensional poverty
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As awareness of the limitations of relying solely on income to measure poverty has become more widespread, attention has been increasingly focused on multi-dimensional approaches, to the point where the EU has adopted a multidimensional poverty and social exclusion target for 2020. The rationale advanced is that the computation of a multidimensional poverty index is an effective way of communicating in a political environment, and a necessary tool in order to monitor 27 different national situations. By contrast with the rather ad hoc way in which the EU 2020 poverty target has been framed and rationalised, the adjusted head count ratio applied here has a number of desirable axiomatic properties. It constitutes a significant improvement on union and intersection approaches and allows for the decomposition of multidimensional poverty in terms of dimensions of deprivation and socio-economic attributes. Since understanding poverty as multidimensional does not necessarily require constructing a multidimensional poverty index, on the basis of our analysis we provide a more general consideration of the value of developing a multidimensional index of poverty for the European Union.
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We examine the measurement of multidimensional poverty and material deprivation following the counting approach. In contrast to earlier contributions, dimensions of well-being are not forced to be equally important but different weights can be assigned to different dimensions. We characterize a class of individual measures reflecting this feature. In addition, we axiomatize an aggregation procedure to obtain a class of indices for entire societies allowing for different degrees of inequality aversion in poverty. We apply the proposed measures to European Union member states where the concept of material deprivation was initiated.
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Includes bibliography
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This paper presents an indicator for measuring multidimensional poverty in the Lao People’s Democratic Republic applying the Alkire–Foster methodology to the Lao Expenditure and Consumption Survey 2002/2003 and 2007/2008. We calculated a multidimensional poverty index (MPI) that includes three dimensions: education, health, and standard of living. Making use of the MPI’s decomposability, we analyse how much each of the different dimensions and its respective indicators contribute to the overall MPI. We find a marked reduction in the multidimensional poverty headcount ratio over the study period, regardless of how the indicators are weighted or how the deprivation and poverty cut-offs are set. This reduction is based on improvements regarding all indicators except cooking fuel and nutrition. We observe no significant reduction in the intensity of poverty, however; there are wide disparities between the country’s regions and between urban and rural areas. The proportion of poor people in rural areas is more than twice as high as that in urban areas. By complementing the traditional income-based poverty measure, we hope to provide useful information that can support knowledge-based decision-making for poverty alleviation.
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This study compares monetary and multidimensional poverty measures for the Lao People’s Democratic Republic. Using household data of 2007/2008, we compare the empirical outcomes of the country’s current official monetary poverty measure with those of a multidimensional poverty measure. We analyze which population subgroups are identified as poor by both measures and thus belong to the category of the poorest of the poor; and we look at which subgroups are identified as poor by only one of the measures and belong either to the category of the income-poor (identified as poor only by the monetary measure) or to that of the overlooked poor (identified as poor only by the multidimensional poverty measure). Furthermore, we examined drivers of these differences using a multinomial regression model and found that monetary poverty does not capture the multiple deprivations of ethnic minorities, who are only identified as poor when using a multidimensional poverty measure. We conclude that complementing the monetary poverty measure with a multidimensional poverty index would enable more effective targeting of poverty reduction efforts.
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In the course of integrating into the global market, especially since China’s WTO accession, China has achieved remarkable GDP growth and has become the second largest economy in the world. These economic achievements have substantially increased Chinese incomes and have generated more government revenue for social progress. However, China’s economic progress, in itself, is neither sufficient for achieving desirable development outcomes nor a guarantee for expanding peoples’ capabilities. In fact, a narrow emphasis on GDP growth proves to be unsustainable, and may eventually harm the life quality of Chinese citizens. Without the right set of policies, a deepening trade-openness policy in China may enlarge social disparities and some people may further be deprived of basic public services and opportunities. To address these concerns, this dissertation, a set of three essays in Chapters 2-4, examines the impact of China's WTO accession on income distribution, compares China’s income and multidimensional poverty reduction and investigates the factors, including the WTO accession, that predict multidimensional poverty. By exploiting the exogenous variation in exposure to tariff changes across provinces and over time, Chapter 2 (Essay 1) estimates the causal effects of trade shocks and finds that China’s WTO accession has led to an increase in average household income, but its impacts are not evenly distributed. Households in urban areas have benefited more significantly than those in rural areas. Households with members working in the private sector have benefited more significantly than those in the public sector. However, the WTO accession has contributed to reducing income inequality between higher and lower income groups. Chapter 3 (Essay 2) explains and applies the Alkire and Foster Method (AF Method), examines multidimensional poverty in China and compares it with income poverty. It finds that China’s multidimensional poverty has declined dramatically during the period from 1989-2011. Reduction rates and patterns, however, vary by dimensions: multidimensional poverty reduction exhibits unbalanced regional progress as well as varies by province and between rural and urban areas. In comparison with income poverty, multidimensional poverty reduction does not always coincide with economic growth. Moreover, if one applies a single measure ─ either that of income or multidimensional poverty ─ a certain proportion of those who are poor remain unrecognized. By applying a logistic regression model, Chapter 4 (Essay 3) examines factors that predict multidimensional poverty and finds that the major factors predicting multidimensional poverty in China include household size, education level of the household head, health insurance coverage, geographic location, and the openness of the local economy. In order to alleviate multidimensional poverty, efforts should be targeted to (i) expand education opportunities for the household heads with low levels of education, (ii) develop appropriate geographic policies to narrow regional gaps and (iii) make macroeconomic policies work for the poor.
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Traditionally Poverty has been measured by a unique indicator, income, assuming this was the most relevant dimension of poverty. Sen’s approach has dramatically changed this idea shedding light over the existence of many more dimensions and over the multifaceted nature of poverty; poverty cannot be represented by a unique indicator that only can evaluate a specific aspect of poverty. This thesis tracks an ideal path along with the evolution of the poverty analysis. Starting from the unidimensional analysis based on income and consumptions, this research enter the world of multidimensional analysis. After reviewing the principal approaches, the Foster and Alkire method is critically analyzed and implemented over data from Kenya. A step further is moved in the third part of the thesis, introducing a new approach to multidimensional poverty assessment: the resilience analysis.
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Over the past two to three decades, our understanding of poverty has broadened from a narrow focus on income and consumption to a multidimensional notion of education, health, social and political 1 participation, personal security and freedom and environmental quality. Thus, it encompasses not just low income, but lack of access to services, resources and skills; vulnerability; insecurity; and voicelessness and powerlessness. Multidimensional poverty is a determinant of health risks, health seeking behaviour, health care access and health outcomes. As analysis of health outcomes becomes more refined, it is increasingly apparent that the impressive gains in health experienced over recent decades are unevenly distributed. Aggregate indicators, whether at the global, regional or national level, often tend to mask striking variations in health outcomes between men and women, rich and poor, both across and within countries...
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There is abundant empirical evidence on the negative relationship between welfare effort and poverty. However, poverty indicators traditionally used have been representative of the monetary approach, excluding its multidimensional reality from the analysis. Using three regression techniques for the period 1990-2010 and controlling for demographic and cyclical factors, this paper examines the relationship between social spending per capita —as the indicator of welfare effort— and poverty in up to 21 countries of the region. The proportion of the population with an income below its national basic basket of goods and services (PM1) and the proportion of population with an income below 50% of the median income per capita (PM2) were the two poverty indicators considered from the monetarist approach to measure poverty. From the capability approach the proportion of the population with food inadequacy (PC1) and the proportion of the population without access to improved water sources or sanitation facilities (PC2) were used. The fi ndings confi rm that social spending is actually useful to explain changes in poverty (PM1, PC1 and PC2), as there is a high negative and signifi cant correlation between the variables before and after controlling for demographic and cyclical factors. In two regression techniques, social spending per capita did not show a negative relationship with the PM2. Countries with greater welfare effort for the period 1990-2010 were not necessarily those with the lowest level of poverty. Ultimately social spending per capita was more useful to explain changes in poverty from the capability approach.
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En Colombia, la pobreza y el conflicto están estrechamente relacionados. Este estudio usa medidas de disuasión del gobierno como instrumentos de varias variables específicas de conflicto para estimar el impacto del conflicto sobre la pobreza en Colombia. Usando datos del censo a nivel municipal para el año 2005, evalúo el efecto sobre la incidencia urbana y rural del recientemente-desarrollado Índice de Pobreza Multidimensional. Los resultados sugieren que el conflicto aumenta significativamente la pobreza rural. Esto es consistente con el hecho que la mayor parte del conflicto en Colombia ocurre en las áreas rurales. También evalúo el efecto rezagado del conflicto en la pobreza para concluir que éste dura por al menos tres años pero que decae en el tiempo. Finalmente, pruebo que mis resultados son robustos a una batería de especificaciones adicionales, incluyendo una versión modificada de mi variable dependiente y el uso de una base alternativa de conflicto.
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Incluye Bibliografía
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A partir do aporte teórico da Abordagem das Capacitações e tendo como referência metodológica a técnica dos Conjuntos Fuzzy, este artigo apresenta um indicador-síntese de pobreza multidimensional para os estados brasileiros. Todavia, diferentemente de outros estudos, a contribuição deste artigo é diminuir o grau de arbitrariedade na escolha das dimensões da pobreza, considerando o cumprimento das metas dos Objetivos do Desenvolvimento do Milênio (PNUD, 2003). Os resultados apontam uma delimitação espacial bem definida no país, com os estados das Norte e Nordeste situando-se entre os dez de maiores índices, com exceção do estado do Rio Grande do Sul.
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In this paper we make use of the 9-year old wave of the Growing Up in Ireland study to analyse multidimensional deprivation in Ireland. The Alkire and Foster adjusted head count ratio approach (AHCR; 2007, 2011a, 2011b) applied here constitutes a significant improvement on union and intersection approaches and allows for the decomposition of multidimensional poverty in terms of dimensions and sub-groups. The approach involves a censoring of data such that deprivations count only for those above the specified multidimensional threshold leading to a stronger set of interrelationships between deprivation dimensions. Our analysis shows that the composition of the adjusted head ratio is influenced by a range of socio-economic factors. For less-favoured socio-economic groups dimensions relating to material deprivation are disproportionately represented while for the more advantaged groups, those relating to behavioral and emotional issues and social interaction play a greater role. Notwithstanding such variation in composition, our analysis showed that the AHCR varied systematically across categories of household type, and the social class, education and age group of the primary care giver. Furthermore, these variables combined in a cumulative manner. The most systematic variation was in relation to the head count of those above the multidimensional threshold rather than intensity, conditional on being above that cut-off point. Without seeking to arbitrate on the relative value of composite indices versus disaggregated profiles, our analysis demonstrates that there is much to be gained from adopting an approach with clearly understood axiomatic properties. Doing so allows one to evaluate the consequences of the measurement strategy employed for the understanding of levels of multidimensional deprivation, the nature of such deprivation profiles and socio-economic risk patterns. Ultimately it permits an informed assessment of the strengths and weaknesses of the particular choices made.
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Sur le plan conceptuel, un consensus s’est dégagé depuis quelques années arguant que la pauvreté est un phénomène multidimensionnel. Vu que, la pauvreté en Tunisie est traitée dans la plupart des rapports suivant une approche monétaire et que cette dernière témoigne d'une diminution très appréciable de la pauvreté, nous élargissons la notion de la pauvreté en adoptant une approche multidimensionnelle et en se référant, dans un premier temps, aux réalisations du pays en termes de satisfaction aux Objectifs du Millénaire pour le Développement (OMD). En second lieu, nous procédons, en utilisant la méthode ACP, au calcul d’un indice composite de bien-être pour chaque gouvernorat. Les résultats dégagés à partir de la construction dudit indice montrent une forte disparité entre les régions et une persistance de la pauvreté dans nombre de gouvernorats. Une analyse plus approfondie au niveau de chaque gouvernorat caractérisé comme pauvre nous a permis de localiser, avec précision, les poches de pauvreté persistantes.
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Individual well-being is multidimensional and various aspects of the quality of life need to be jointly considered in its measurement. The axiomatic literature on the subject has proposed many indices of multidimensional poverty and deprivation and explored the properties that are at the basis of these measures. The purpose of this chapter is to add intertemporal considerations to the analysis of material deprivation. We employ the EU-SILC panel data set, which includes information on different aspects of well-being over time. EU countries are compared based on measures that take this additional intertemporal information into consideration. Journal of Economic Literature Classi cation No.: D63.