Measuring multidimensional poverty in three Southeast Asian countries using ordinal variables

Multidimensional Poverty and Its Discontents

Multidimensional poverty measurement and analysis is evolving rapidly. Notably, it has informed the publication of the Multidimensional Poverty Index (MPI) estimates in the Human Development Reports of the United Nations Development Programme since 2010, and the release of national poverty measures in Mexico, Colombia, Bhutan, the Philippines and Chile. The academic response has been similarly swift, with related articles published in both theoretical and applied journals. The high and insistent demand for in-depth and precise accounts of multidimensional poverty measurement motivates this book, which is aimed at graduate students in quantitative social sciences, researchers of poverty measurement, and technical staff in governments and international agencies who create multidimensional poverty measures. The book is organized into four elements. The first introduces the framework for multidimensional measurement and provides a lucid overview of a range of multidimensional techniques and the problems each can address. The second part gives a synthetic introduction of 'counting' approaches to multidimensional poverty measurement and provides an in-depth account of the counting multidimensional poverty measurement methodology developed by Alkire and Foster, which is a straightforward extension of the well-known Foster-Greer-Thorbecke poverty measures that had a significant and lasting impact on income poverty measurement. The final two parts deal with the pre-estimation issues such as normative choices and distinctive empirical techniques used in measure design, and the post-estimation issues such as robustness tests, statistical inferences, comparisons over time, and assessments of inequality among the poor.

Poverty is a multifaceted phenomenon that has always existed historically. In addition to discussions of poverty issues, aspects of poverty measurement are essential topics. A prominent poverty measurement system is the unidimensional measurement based on poverty line income (PLI). Therefore, the use of multidimensional poverty measurements is proposed, specifically the multidimensional poverty index (MPI), in assessing poverty, including non-monetary aspects. This study discusses the concept of unidimensional and multidimensional poverty measurement and the implementation of these concepts in Malaysia during the COVID-19 outbreak. Furthermore, it aims to contribute to the public debate on COVID-19 policy responses by quantifying the potential impact on global multidimensional poverty using the Global Multidimensional Poverty Index (MPI), which captures concurrent or overlapping deprivation at the household level. This study recommends policies by which members of the community and industry experts would be included in the poverty reduction program, in line with Maslow’s requirements. Overall, this research focuses on planning and orienting policy responses from a multidimensional perspective that integrates health, social and economic goals.

The present study uses secondary data collected from National Family Health Survey (NFHS) rounds 4 and 5 to track the progress in the multidimensional poverty status of the Indian population. We use differential methodology to identify poor individuals in both rural and urban areas. Further, the multidimensional poverty index (MPI) and agriculture are closely associated, and this is also reflected in the study. Among the agro-climatic regions, it was found that MPI is relatively higher in the Middle Gangetic Plains Region, while MPI in the West Coast Plains and Hills Region is relatively lower compared with other agro-climatic regions. As we develop a new MPI for different agro-climatic zones (ACZ), it has significant policy relevance. We believe that this new index provides a substantial contribution to the literature on poverty measurement and could be an important tool to track progress towards the achievement of SDG 1.

Poverty is a complex issue that involves more than just income levels, affecting various aspects of life such as health, education, and living conditions. The ongoing discussion about how to measure poverty, whether through absolute or relative terms, reflects the challenges in assessing it. Absolute poverty is based on a set standard that focuses on meeting basic needs for survival, while relative poverty looks at income disparities within a society. This study explores existing research on multidimensional poverty and examines the debate between absolute and relative poverty measures, considering their respective advantages and disadvantages. A notable conclusion from the research is that multidimensional poverty indices (MPIs), like the Multidimensional Poverty Index, provide a broad view of deprivation by including multiple factors. MPIs help policymakers design more targeted interventions in areas such as education, healthcare, and living standards. However, absolute poverty measures, such as the World Bank’s $1.90-per-day threshold, are still essential for tracking extreme poverty in developing nations, offering a clear benchmark for international comparisons. In contrast, relative poverty measures are particularly relevant in wealthier nations, where inequality and social exclusion are more prominent factors in poverty. This study highlights gaps in how these different approaches are integrated and calls for further research to improve models that address both absolute and relative poverty. The findings suggest that combining multidimensional, absolute, and relative poverty measures is important for fully understanding poverty and creating effective strategies to reduce it, adapted to the needs of specific regions and contexts.

India has seen enormous reductions in poverty in the past few decades. However, much of this progress has been unequal throughout the country. This paper examined the 2019–2021 National Family Health Survey to examine small area variations in four measures of household poverty. Overall, the results show that clusters and states were the largest sources of variation for the four measures of poverty. These findings also show persistent within-district inequality when examining the bottom 10th wealth percentile, bottom 20th wealth percentile, and multidimensional poverty. Thus, these findings pinpoint the precise districts where between-cluster inequality in poverty is most prevalent. This can help guide policy makers in terms of targeting policies aimed at reducing poverty.

The accurate accounting of where and for whom deprivations occur is fundamental to addressing poverty. In the United States, the official poverty measure considers only a person’s income, although poverty is increasingly understood internationally as a set of multiple, interlinked deprivations. This article introduces a decomposable multidimensional poverty (MDP) measure that addresses these shortcomings by using thirteen American Community Survey microdata indicators to identify education, health, housing, and economic security deprivations for individuals. In 2017, the national poverty rate was 13.7 percent when measured using MDP and 13.1 percent using official poverty. Although similar at the national scale, Hispanic, Asian, and older persons had higher poverty rates using the multidimensional measure, whereas Black and young persons had higher rates when using official poverty. MDP tended to be higher than official poverty in dense urban areas, whereas official poverty tended to be higher in rural areas. Further, MDP was a stronger correlate with COVID-19 death rates than official poverty through the first three waves of the pandemic. The design of MDP recognizes that individuals can experience poverty in different ways and provides a more holistic view of people and places.

People with disabilities are more likely than individuals without disabilities to face higher levels of deprivation and multidimensional poverty, and those deprivations might be associated with the extra costs of living with a disability. However, there has not been an analysis of how multidimensional poverty measures are related to the extra costs of disability or whether these measures can be used as a proxy of the standard of living in the analysis of the extra costs of disability. This paper aims to analyse whether multidimensional poverty measures can be used to study the extra costs of disability and, based on the capability approach, how multidimensional poverty is related to the extra costs of disability. This paper discusses theoretical, technical, and methodological aspects to be considered when studying the relationship between extra costs and multidimensional poverty, and we used data from Chile and Nigeria to illustrate this relationship. We conclude that when analysing the extra costs of disability, multidimensional measures might be an option; however, it is necessary to clearly stablish the relationship among income, deprivation, and the extra costs of disability.

The main goal of this chapter is to undertake a multidimensional poverty analysis in relation to five southern Mediterranean countries, namely Egypt, Lebanon, Morocco, Tunisia, and Turkey. We rely on a broader concept of poverty by considering the deprivations in women’s educational attainments, the possession of durable goods and the consequences of housing conditions, each of which we operationalize by making use of recent developments in multidimensional poverty measurement. This analysis is based on an axiomatic approach to poverty and on the use of stochastic dominance tools to achieve robust results that do not hinge on the choice of poverty line and weighting scheme. Our findings provide comparisons over time for each country and between countries that cannot be obtained when each dimension of poverty is analysed separately, as the approaches take into account the correlations which may exist between different kinds of poverty. Furthermore, in contrast to rankings drawn from cardinal poverty measures (for example, from the Multidimensional Poverty Index), multidimensional tests make it possible to nuance the performance levels reached by certain countries.

As a result of the development of the Functionings and Capabilities Approach to wellbeing assessment, Multidimensional Poverty and Deprivation measurement has become popular in recent years. To this end, Efficiency Analysis techniques have been borrowed from the multidimensional production theory literature and implemented in the wellbeing measurement paradigm to explore the extent of poverty in multidimensional environments. Two basic approaches prevail in the literature, a parametric isoquant estimation approach and a non-parametric data envelopment approach. This chapter outlines the two basic approaches and their origins and discusses their respective merits in their application to wellbeing measurement.

This paper states the need to design a multidimensional poverty index for the Latin America region (LA-MPI) that can monitor poverty trends in a cross-country comparable way, yet is also relevant to the particular regional context. We review the region's rich experience with multidimensional poverty measurement, as well as Europe's experiences with multidimensional measurement. We set a number of requirements for the LA-MPI to satisfy and specify the methodological criterions necessary to fulfill such requirements. Drawing from the review, we outline an LA-MPI composed of five dimensions: basic consumptions, education, health, housing and basic services, and work. We list the indicators within those dimensions that are desirable, as well as what indicators are feasible given existing data constraints.

In order to realize the poverty alleviation of China's current standards to achieve total poverty alleviation by 2020, the state has proposed a strategic plan for precision poverty alleviation. Based on the multidimensional poverty analysis methods and latest research results proposed by Alklre and Foster [1]. Taking the existing poverty data sources in Fengqing County of Yunnan Province as the research object, the selection of poverty dimension indicators is carried out. The multi-dimensional poverty threshold deprivation index system of five dimensions and seven indicators is designed, the multidimensional poverty measurement model is designed, and the RBF (radial basis function) neural network technology is used to measure the poverty depth of poor households. Using Python programming to achieve model programming, embedding the platform to achieve poverty measurement function, and constructing a scientific and accurate data analysis model for poverty alleviation, providing decision support for the government to carry out accurate poverty alleviation.

Multidimensional Poverty Indices: A Critical Assessment

ObjectivesTo identify the chronic health conditions associated with multidimensional poverty.DesignCross-sectional study of the nationally representative Survey of Disability, Ageing and Carers, conducted by the Australian Bureau of Statistics.SettingAustralian population in...

According to official statistics, the incidence of absolute poverty in Italy has sharply risen from 3.6 in 2005 to 7.7 percent in 2020, and this number is likely to rise in the post-pandemic period. However, standard poverty measures only consider the monetary aspect of poverty, neglecting the multidimensional nature of the phenomenon. The last decades have offered solid empirical evidence to guide political efforts to tackle both multidimensional wellbeing and poverty. In these times of rising inequalities, these efforts seem particularly valuable for identifying the most vulnerable groups. While Italy has made significant progress in defining multidimensional wellbeing, less attention has been given to multidimensional poverty. Hence, the goal of this paper is to offer a means for measuring multidimensional poverty (MPI) in Italy based on the Alkire-Foster method by using a widely recognized national framework for wellbeing (BES equitable and sustainable wellbeing) as the normative basis for the construction of the index. The contribution of the paper is twofold: (1) on the theoretical side, it seeks to increase the usability of national and international frameworks for wellbeing by proposing a national assessment scheme as a normative base for defining the dimensions of poverty; (2) on the empirical side, it provides evidence on the frequency and composition of multidimensional poverty in Italian regions. The results show that multidimensional poverty in Italy has increased over time, with the percentage of individuals considered as multidimensionally poor rising from 9.5 percent in 2005 to 17.5 percent in 2015. Moreover, a dimensional breakdown across regions and logistic regression shows that being older, female, from the South and married or widowed increases the probability of facing multidimensional poverty.