Multidimensional Poverty in Mountainous Regions: Shan and Chin in Myanmar

Poverty is complex and multidimensional. People living in mountainous regions are vulnerable and more likely to experience multiple deprivation. However, few studies have addressed multidimensional poverty in mountainous regions. Using data from 4290 households of poverty and vulnerability assessment survey and the Alkire–Foster methodology, this paper estimate and decompose multidimensional poverty in the states of Shan and Chin in Myanmar. The multidimensional poverty is measured in five dimensions and a set of twelve indicators. Nearly half of the population in Shan and three-quarters in Chin were multidimensionally poor. The average intensity of poverty was 44% in Chin and 38% in Shan. The multidimensional poverty index was 0.33 in Chin and 0.19 in Shan. The level of multidimensional poverty in Chin was similar to that in of Sub-Saharan Africa. In Chin, 60% of the population was both multidimensionally poor and consumption poor, but in Shan, it was 20%. About 28% of the population in Shan and 15% in Chin were multidimensionally poor but not consumption poor. Deprivation in education accounts for one-third of the multidimensional poverty in Shan; while deprivation in health accounts for one-third of the multidimensional poverty in Chin. A higher proportion of multidimensionally poor had experienced shocks such as the death of a household member, agricultural loss, or death of livestock compared to the multidimensional non-poor. Multidimensional poverty was significantly higher for rural household, households with lower educational attainment, consumption poor and among those who lived in Chin. Poverty reduction programs require a holistic understanding of poverty and its different dimensions as well as the main contributing factors for effective planning and program implementation. Geographical targeting of poverty reduction program and larger investment in food, health, water, energy and education can reduce the extent of multidimensional poverty in Shan and Chin.     

The Association Between Generalized Trust and Physical and Psychological Health Across Societies

This paper estimates a Multidimensional Poverty Index for Gauteng province of South Africa. The Alkire–Forster method is applied on Quality of Life survey data for 2011 and 2013 which offer an excellent opportunity for estimating poverty at smaller geographical areas. The results suggest that the Multidimensional Poverty Index for Gauteng is low but varies markedly by municipality and by ward, as well as across income groups. Not only are low income households more likely to be multidimensionally poor, they also suffer from higher intensities of poverty. Multidimensional poverty is highest in areas of low economic activity located on the edges of the province. However, pockets of multidimensional poverty do prevail even in better performing municipalities. Government, at all spheres, needs to devise policies that channel investments into lagging areas and avoid approaches that are indifferent to the heterogeneities that exist across localised geographical extents.     

Synergies Among Monetary,Multidimensional and Subjective Poverty: Evidence from Nepal

In this paper we construct a Nepal specific multidimensional poverty index using the Nepal Longitudinal Sample Survey (NLSS) for the period 1995–2010. The indicators for Nepal Multidimensional Poverty Index (NMP) have been chosen using the goals set by the Government of Nepal and the perceptions of adequacy as reported by households. In doing so this study combines multidimensional and subjective methods of measuring wellbeing. The subjective data is used to guide the choice of dimensions for the multidimensional analysis. Our findings show that Nepal has had a dramatic fall in multidimensional poverty along with the observed fall in consumption poverty in this period. Comparing the extent to which consumption poverty accurately identifies the multidimensionally poor, we find the error has reduced over time but remains large in proportion to the poverty rate implying the need for a multidimensional measure. For the different ethnic groups and regions the patterns of reduction in poverty are not homogenous and are different from those of consumption poverty with the NMP outperforming the consumption poverty in tracking targeted policy actions.     

Multidimensional Poverty in Nicaragua: Are Female-Headed Households Better Off?

The recognition of poverty as a multidimensional concept has led to the development of more adequate tools for its identification. By allowing for subgroup and regional decompositions, those instruments are useful to allocate public action where most needed. This paper applies the Alkire and Foster (2011a) Multidimensional Poverty Index (MPI) to study single-mother and biparental families in Nicaragua, modifying its original structure to match more closely with the country’s current structural problems. Using Nicaragua’s last Demographic and Health Survey (DHS 2011/2012), our multidimensional poverty figures contrast with the government’s national poverty line estimates, suggesting that income poverty overestimates the number of poor people. Thus, our MPI can help as a complement for traditional consumption poverty and Basic Needs analysis; even extending the exploration by using other official household surveys. On the other hand, multidimensional poverty analysis found poverty dominance of male-headed families over single-mother and female-headed biparental families, which serves to contradict the notion of women being more vulnerable than men. Within the MPI, the most important contributor was the Living Standards dimension, composed by indicators directly related to housing conditions, and the second most deprived dimension was Education. A strong policy implication that arises from our findings is the reduction of the urban–rural poverty gap. Specifically, our findings exalt the need for governmental policies directed to reduce Nicaragua’s housing and educational deficits as a priority, particularly in rural areas.     

Composite Indices of Development and Poverty: An Application to MDGs

The measurement of development or poverty as multidimensional phenomena is very difficult because there are several theoretical, methodological and empirical problems involved. The literature of composite indicators offers a wide variety of aggregation methods, all with their pros and cons. In this paper, we propose a new, alternative composite index denoted as MPI (Mazziotta-Pareto Index) which, starting from a linear aggregation, introduces penalties for the countries or geographical areas with ‘unbalanced’ values of the indicators. As an example of application of the MPI, we consider a set of indicators in order to measure the Millennium Development Goals (MDGs) and we present a comparison between HDI (Human Development Index) methodology, HPI (Human Poverty Index) methodology and MPI.     

A Different Perspective on Poverty in Lao PDR: Multidimensional Poverty in Lao PDR for the Years 2002/2003 and 2007/2008

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.     

Tracking Poverty Reduction in Bhutan: Income Deprivation Alongside Deprivation in Other Sources of Happiness

This paper analyses poverty reduction in Bhutan between two points in time—2003 and 2007—from a multidimensional perspective. The measures estimated include consumption expenditure as well as other indicators which are directly (when possible) or indirectly associated to valuable functionings, namely, health, education, access to electricity, safe water, improved sanitation, enough room per person in dwelling, access to roads and land ownership. Interestingly, most of these indicators have been identified as sources of happiness in the 2007 Gross National Happiness Survey. Twelve different measures are estimated with a variety of values for the different parameters involved for robustness analysis. Also, estimates are bootstrapped creating 95 % confidence intervals. We find that over the study period there was an unambiguous reduction in multidimensional poverty regardless of the indicators’ weights, deprivation cutoffs and identification criterion of the poor. This reduction was mainly led by a reduction in the proportion of the poor which was accompanied by a reduction in the intensity of poverty among those who were less intensively poor, although not among those who were more intensively poor. Rather than accomplishing this poverty reduction by improving achievements in one or two indicators, there were significant reductions in several deprivations, especially in access to roads, electricity, water, sanitation, and education. We also find that when income alone is used to target the poor, inclusion errors are marginal but exclusion errors are sizeable. Despite Bhutan’s significant progress, challenges remain as poverty is still high in rural areas. A multidimensional measure in the lines proposed in this paper can prove useful for monitoring poverty reduction, prioritizing groups and evaluating upon investment.     

Spatial and Temporal Trends in Multidimensional Poverty in the United States over the Last Decade

This paper undertakes a comprehensive analysis of multidimensional poverty in the United States over the last decade. It provides estimates of multidimensional poverty over more than a decade, from 2008 to 2019, which covers the Great Recession and the recovery following the recession when major policy changes such as the Affordable Care Act were implemented. For the first time, spatial trends in estimates of multidimensional poverty are also provided. We measure annual poverty levels in 4 regions, 50 states and examine the relation between multidimensional poverty and neighborhood characteristics. We find that on average, 13 percent of the United States population was multidimensional poor. Poverty rates were high in the South and the West and among young adults, immigrants and Hispanics. Alternative indices of multidimensional poverty show consistent trends; multidimensional poverty in the United States rose between 2008 and 2010 and then gradually declined. However, more than a quarter of individuals with incomes above the poverty threshold remained multidimensional poor. This underscores the fact that income does not always capture deprivation experienced by individuals. Policies geared towards affordable housing, health insurance and higher education will help reduce multidimensional poverty in the United States.

     

Multi-Dimensional Deprivation in the U.S.

This paper presents a comprehensive analysis of multidimensional deprivation in the U.S. since the Great Recession, from 2008 to 2013. We estimate a Multidimensional Deprivation Index by compiling individual level data on several well-being dimensions from the American Community Survey. Our results indicate that the proportion of the population that is multidimensional deprived averages about 15 percent, which exceeds the prevalence of official income poverty. Lack of education, severe housing burden and lack of health insurance were some of the dimensions in which Americans were most deprived in. Though deprivation increased during the recession, it trended towards a decline between 2010 and 2013. Unlike the official and the supplemental poverty measure which did not show any decline, the deprivation index better reflects the economic recovery since the recession. Overall, the prevalence of deprivation was higher in the southern and the western states and among the Asian and the Hispanic population. Importantly, there was not much overlap between individuals who were income poor and those who were multidimensional deprived. In fact, almost 30 % of individuals with incomes slightly above the poverty threshold experienced multiple deprivations. Our analysis underscores the need to look beyond income based poverty statistics in order to fully realize the impact of the recession on individuals’ well-being.     

"Struggling to Keep the Wolf from the Door"? Analysis of Rural Poverty Using a Consumption-Based Approach in West Belesa District,Ethiopia

Ethiopia has one of the highest poverty rates in the world where 24% of the population lives in extreme poverty. While urban poverty reduced from 26% in 2011 to 15% in 2016, rural poverty reduced only from 30 to 26% in the same periods. Improper identification of the rural poor and ill-understanding of the extent of rural poverty is among the challenges in designing appropriate poverty reduction interventions in rural areas. Thus, this study analyzes the extent of rural poverty employing a consumption-based approach and identifies the determinants of rural poverty at a household level. A household survey was conducted and data were randomly collected from 194 households from four representative villages in the west Belesa district of Ethiopia. The food and non-food consumption measurement calculated by the cost of basic need approach were 2949.40 ETB (ETB is Ethiopian Birr, which is the Ethiopian currency. 1 ETB is equivalent to 0.025 US$) and 1485.78 ETB per year per Adult Equivalent (AE), respectively. The rural poverty indices (i.e. headcount index, poverty gap, and squared poverty gap) calculated based on the consumption-based poverty line were 38.1, 8.84, and 3.1%, respectively. The binary logit analysis shows that having a bigger family had a significant and positive relationship with rural poverty. Conversely, larger landholding, plowing oxen, and livestock ownership as well as a higher amount of non/off-farm income have a significant and negative relationship with the poverty status of households. The study found that rural poverty is deep and complex in the study area calling for the design of location-specific and holistic poverty reduction strategies.

     

Uneven dynamics and regional disparity of multidimensional poverty in China

Qualifying the official minimum of “Two no worries and three guarantees” (certainty of food and clothing, guarantees of compulsory education, basic medical care, and housing) is essential to evaluate the targeted poverty alleviation program since 2013 in China. Using the poverty monitoring dataset and the multidimensional poverty indicator system, the uneven dynamics and regional disparity of multidimensional poverty and its driving factors in poverty-stricken areas in China during 2014–2018 are explored in this paper. The incidence rate of multidimensional poverty was reduced by 61.72%, and the poverty reduction rate within the six dimensions ranged from 52.29 to 76.36%. Multidimensional poverty and its six dimensions displayed narrowing regional disparity. Impoverished and moderately poor areas shrank, whereas low-poverty areas expanded. All 22 provinces have become low-poverty areas in 2018. The contribution of each dimension to multidimensional poverty varies for different types at different stages. Income and expenditure contribute the most to poverty status, followed by transportation, housing conditions, education, communication, and medical care and health. The contribution of each indicator among different dimensions varied with different trends from 2014 to2018. This paper helps incorporate the official minimums of “Two no worries and three guarantees” into a more operational evaluation system to promote sustainable policies for governments at all levels by 2020 and beyond, as well as provide valuable references for poverty alleviation in other developing countries worldwide.

     

Poverty,Inequality and Deprivation in South Africa: An Analysis of the 1993 SALDRU Survey

This paper analyses poverty and inequality in South Africa based on data from a comprehensive multi-purpose household survey undertaken in 1993 to provide baseline statistics on poverty and its determinants to the new government. The paper shows that South Africa has among the highest levels of income inequality in the world and compares poorly in most social indicators to countries with similar income levels. Much of the poverty in the country is a direct result of apartheid policies that denied equal access to education, employment, services, and resources to the black population of the country. As a result, poverty has a very strong racial dimension with poverty concentrated among the African population. In addition, poverty is much higher in rural areas, and particularly high in the former homelands. Poverty among female-headed households and among children is also higher than average. Moreover, poverty is closely related to poor education and lack of employment. The poor suffer from lack of access to education, quality health care, basic infrastructure, transport, are heavily indebted, have little access to productive resources, and are heavily dependent on remittances and social transfers, particularly social pensions and disability grants. The paper uses an income-based definition of poverty for most of the analysis. In addition, it develops a broad-based index of deprivation including income, employment, wealth, access to services, health, education, and perceptions of satisfaction as its components. While on average the two indicators correspond fairly closely, the income poverty measure misses a considerable number of people who are severely deprived in many of the non-income measures of well-being. This group of severely deprived not identified by the income poverty measure consists predominantly of Africans living in rural areas, concentrated particularly in the province of KwaZulu/Natal.     

Selecting a Targeting Method to Identify BPL Households in India

This paper proposes how to select a methodology to target multidimensionally poor households, and how to update that targeting exercise periodically. We present this methodology in the context of discussions regarding the selection of a targeting methodology in India. In 1992, 1997, and 2002 the Indian government identified households that are below the poverty line (BPL) and in updating the 2002 methodology, alternative methods have been proposed and vigorously debated. A fourth BPL method was published and a corresponding Socio Economic Caste Census (SECC), implemented. Using the third National Family Health Survey (NFHS-3), this paper illustrates how a BPL targeting method using SECC variables might be calibrated to a multidimensional poverty measure. This paper compares the fit between a benchmark measure of multidimensional poverty and several plausible targeting methods to determine which method(s) approximate it—as well as related measures—most closely. We find a ten-item binary scoring method, which uses variables already available in the SECC questionnaire, provides a strong proxy. The emphasis of this paper is to illustrate how a particular targeting method can be justified, rather than to advocate any particular solution.     

A Distributional Analysis of Uni-and Multidimensional Poverty and Inequalities in Ethiopia

Social Indicators Research - This study analyzes uni-and multidimensional poverty and inequalities in rural and small towns in Ethiopia. Unlike the unidimensional measure, the multidimensional...     

First Order Dominance Techniques and Multidimensional Poverty Indices: An Empirical Comparison of Different Approaches

In this empirically driven paper we compare the performance of two techniques in the literature of poverty measurement with ordinal data: multidimensional poverty indices and first order dominance techniques (FOD). Combining multiple scenario simulated data with observed data from 48 Demographic and Health Surveys around the developing world, our empirical findings suggest that the FOD approach can be implemented as a useful robustness check for ordinal poverty indices like the multidimensional poverty index (MPI; the United Nations Development Program’s flagship poverty indicator) to distinguish between those country comparisons that are sensitive to alternative specifications of basic measurement assumptions and those which are not. To the extent that the FOD approach is able to uncover the socio-economic gradient that exists between countries, it can be proposed as a viable complement to the MPI with the advantage of not having to rely on many of the normatively binding assumptions that underpin the construction of the index.     

Gender and Multidimensional Poverty in South Africa: Applying the Global Multidimensional Poverty Index (MPI)

Recent work has shown that the gender gap in income poverty has widened in post-apartheid South Africa even though overall poverty levels have declined. One of the main criticisms of money-metric studies of gendered poverty differences is that income is only one dimension of poverty and that other measures of welfare may better reflect the relative well-being of women and female-headed households. This article presents a multidimensional approach to measuring the gender poverty gap in post-apartheid South Africa. Using data from the 2008 wave of the South African National Income Dynamic Study, the internationally comparable multidimensional poverty index (the MPI) is used to estimate gender differences in a number of different achievements. The findings suggest that the multidimensional gender poverty gap is similar to the poverty gap measured by the conventional money-metric approach at several national poverty lines. However, the MPI poverty differential between female- and male-headed households is slightly narrower than the income poverty gap between these two household types. In order to explore these findings further, the paper decomposes the components of multidimensional poverty by gender and for both female- and male-headed households. The paper concludes by considering how greater investments in health care delivery and in basic services, particularly in rural areas, may yield progress towards gender equality.     

Multidimensional Measurement of Poverty Among Women in Sub-Saharan Africa

Since the seminal work of Sen, poverty has been recognized as a multidimensional phenomenon. The recent availability of relevant databases renewed the interest in this approach. This paper estimates multidimensional poverty among women in fourteen Sub-Saharan African countries using the Alkire and Foster multidimensional poverty measures, whose identification method is based on a counting approach. Four dimensions are considered: assets, health, schooling and empowerment. The results show important differences in poverty among the countries of the sample. The multidimensional poverty estimates are compared with some alternative measures such as the Human Development Index, income poverty, asset poverty and the Gender-related Development Index. It is found that including additional dimensions into the analysis leads to country rankings different from those obtained with the mentioned four measures. Decompositions by geographical area and dimension indicate that rural areas are significantly poorer than urban ones and that a lack of schooling is, in general, the highest contributor to poverty. The paper also conducts robustness and sensitivity analyses of the multidimensional estimates with respect to the number of dimensions in which deprivation is required in order to be considered poor, as well as to the poverty lines within each dimension. Several cases of dominance between countries are found in the first robustness test.     

A Proposal for a Model-Based Composite Indicator: Experience on Perceived Discrimination in Europe

Social Indicators Research - The multidimensional poverty index (MPI) is generally credited for better capturing the various components of poverty. Where such indexes have a spatial component,...     

Layoffs and Urban Poverty in the State-Owned Enterprise Communities in Shaanxi Province,China

This paper applies a mixed methods approach that combines qualitative and quantitative methods to examine urban poverty in China’s state-owned enterprise communities where laid-off workers concentrate. A sequential explanatory model using interviews, Participatory Poverty Assessments and a community household survey on textile and military industries in Shaanxi Province of north-western China shows that low-income households suffered multidimensional disadvantages. Qualitative techniques have helped to reveal the hidden aspects of poverty while statistical tools have captured holistic information on the communities. These approaches together (Q-squared) consider both the outsiders’ and insiders’ views on the laid-off poor and benefit the making of effective anti-poverty policies.     

A New Generalized Variance Approach for Measuring Multidimensional Inequality and Poverty

The paper suggests a new generalized variance concept for measuring multidimensional inequality of a stratified society, based on multivariate statistical methods, where the members of society form a cloud in the oblique space of dimensions of inequality, such as income, expenditure and property. The cloud presents the multidimensional inequality capsulized in the cloud. The goal is to condense all the inequality information embodied by the cloud into a composite compact metric characterizing both the shape and the inner structure of the cloud. Contrary to the conventional literature that considers multidimensionality as a unidimensional weighted combination of the dimensions, our new composite index measures the inequality of the configuration of the points in the cloud. Our aim is twofold. First, we introduce the Inequality Covariance Matrix (ICM) assigned to the cloud, with elements measuring the correlations among dimensions. Having ICM, we propose the Generalized Variance (GV) of ICM to measure the composite Generalized Variance Inequality (GVI) level. Second, to evaluate the stratum-specific structure of the overall inequality, we suggest a new two-stage procedure. In the first stage, we divide the total GVI into between-groups and within-groups effects. Then, in the second stage the contributions of the strata to the within-groups inequality and, the contributions of the dimensions to the between-groups inequality are calculated. This GVI approach is sensitive to the correlation system, decomposable into stratum effects and, the number of dimensions is not limited. Moreover, including the log-dimensions in the analysis, GVI yields an Entropy Covariance Matrix giving a new Generalized Variance Entropy index. Finally, the GVI of censored poverty indicators means multidimensional poverty measurement. This special complex task is not yet solved in the traditional literature so far.