Efficiency analysis and poverty measurement

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.

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.

Multidimensional Poverty and Its Discontents

PurposeThe purpose of this paper is to compare the assessment of poverty/deprivation using different conceptions of this phenomenon including the traditional money‐metric measure and different forms of multidimensional constructs.Design/methodology/approachThe data were drawn from a household survey conducted in Nsukka, Nigeria. Interviewer‐administered questionnaires were used in data collection from about 410 households across urban and rural localities. The counting and FGT methodologies were used to assess impoverishment, while regression analyses were used to assess the determinants of deprivation across different constructs.FindingsBetween 70 per cent and 78 per cent of the study population were identified as poor/deprived. However, more than 11 per cent of those living on less than USD1.25/day were classified as non‐poor using different measures of multidimensional poverty. Similarly, more than 62 per cent of individuals who live on more than 1.25USD/day (i.e. non‐poor) are classified as poor using different measures of multidimensional deprivation. There is some level of correlation between measures, some inevitably stronger than others. The major determinants of deprivation across the various constructs of deprivation include large family size, low level of education, poor employment, rural location, and poor health.Originality/valueThis paper uses novel datasets that incorporate variables relating to the capability approach in understanding deprivation. Specifically, it analyses the so‐called missing dimensions of poverty. It also applies a new methodology for the assessment of impoverishment and deprivation. It highlights the importance of the capability approach in explaining poverty.

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.

This paper aims to highlight the contribution of the recent methodological refinements of poverty measures based on counting approaches using ordinal variables to the understanding of the evolution of poverty in Cambodia, Indonesia and the Philippines. Using the general framework proposed by Silber and Yalonetzky (2013), this paper compares multidimensional poverty measures such as the Multidimensional Poverty Index used by the UNDP (an index based on the approach of Alkire and Foster [2011]) with others which are sensitive to the distribution of deprivation counts across individuals. To the latter family belong the poverty measures introduced by Chakravarty and D’Ambrosio (2006) and Rippin (2010) and those based on the extension of the approach of Aaberge and Peluso (2012), as suggested by Silber and Yalonetzky (2013). Poverty is estimated using Demographic and Health Surveys for three different years for Cambodia (2000, 2005, and 2010), for Indonesia (1997, 2003, and 2007), and for the Philippines (1997, 2003, and 2008) by considering the deprivations in education, health and standard of living. Our findings indicate that Cambodia shows the highest level of poverty, followed by Indonesia and the Philippines, irrespective of the poverty measures used. At the national level, all countries reduced their multidimensional poverty over time using poverty measures as the one based on the approach of Alkire and Foster (2011) and those that are sensitive to the concentration of deprivations across individuals. As in most of Asian developing countries, poverty is largely a rural phenomenon. However, when examining the evolution of poverty over time for each country, conclusions drawn from the use of various poverty measures may differ regarding trends in poverty over time by area of residence as well as by region of residence.

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.

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.

Multidimensional Poverty Indices: A Critical Assessment

<p>This paper attempts to exercise the Oxford Poverty and Human Development Initiative’s methodology to measure the multidimensional poverty at the local (village) level. Various measures of Multidimensional poverty has been estimated and decomposed to the various sub groups of the sampled household of the then Bhalam VDC of the Kaski District, in West Nepal. Stratified random technique was applied to select the 150 sample households to conduct household survey to get required data for the measurement and analysis of poverty. The results of the analysis follows almost similar pattern of various measures of multidimensional poverty estimates of the Oxford latest study. It is also revealed from the study that multidimensional poverty incidence and intensity were highly associated with the household socioeconomic characteristics such as Caste and ethnicity, land holding, gender and educational level of the household head and the family size.</p><p>Economic Literature Vol.12 2014: 16-25</p>

This working paper introduces the notation and basic concepts that are used throughout the OPHI Working Papers 82-91. The Paper has five sections. First we review unidimensional poverty measurement with particular attention to the well-known Foster-Greer-Thorbecke measures of income poverty as many methods presented in OPHI Working Paper 84 (Chapter 3 -Overview of Methods for Multidimensional Poverty Assessment) as well as the measure presented in OPHI

The objective of this paper is to design a multidimensional poverty index, based on the Alkire-Foster (AF) method, to identify people vulnerable to COVID-19 and risk factors. The use of the Demographic and Health Survey (DHS) dataset has led to the choice of the following dimensions: Education, Hygiene, Staying at home, Physical distance, and recovery capacity. Each dimension is composed of indicators found in the global multidimensional poverty index. The findings show that 61.4% of Senegalese are vulnerable to COVID-19 because they suffer deprivation in at least a third of the indicators. Also, among the vulnerable 47.05% are poor according to the wealth index. The deprivation in electricity, housing, sanitation, and cooking fuel are the most important risk factors in the Senegalese context. The regions located in the South and East are those where the populations are more vulnerable. However, the number of confirmed cases is higher in the northern and western regions where there are fewer vulnerable people. In these regions, the greatest risk factor is promiscuity. Difficulty in observing physical and social distance and having a suitable living environment are major factors of vulnerability to emerging infectious diseases such as COVID-19 in a developing country like Senegal.

This book looks at the major policy challenges facing developing Asia and how the region sustains rapid economic growth to reduce multidimensional poverty through socially inclusive and environmentally sustainable measures. Asia is facing many challenges arising from population growth, rapid urbanization, provision of services, climate change and the need to redress declining growth after the global financial crisis. This book examines poverty and related issues and aims to advance the development of new tools and measurement of multidimensional poverty and poverty reduction policy analysis. The book covers a wide range of issues, including determinants and causes of poverty and its changes; consequences and impacts of poverty on human capital formation, growth and consumption; assessment of poverty strategies and policies; the role of government, NGOs and other institutions in poverty reduction; rural-urban migration and poverty; vulnerability to poverty; breakdown of poverty into chronic and transitory components; and a comparative study on poverty issues in Asia and other regions. The book will appeal to all those interested in economic development, resources, policies and economic welfare and growth.

This methodological article covers four elements: A) It analyzes the Latin American experience in the multidimensional measurement of poverty from 1986 to 1992, when the region became the world's methodological forefront in poverty measurement by developing and applying the original variant (OV) of IPMM (Integrated Poverty Measurement Method) that combined income and UBN (unsatisfied basic needs) indicators, promoted by the Regional Project to Overcome Poverty UNDP (RLA/86/004), as well as the events that led to its abandonment and to the return to the one-dimensional measurement of income poverty. The text describes the regional and personal conditions which allowed me to develop the original variant of IPMM, which the aforementioned project applied in 10 Latin American countries. B) Describes two events that enabled Mexico to move in another direction: the development (and sustained application for Mexico) of the improved variant of IPMM (which adds the time dimension to UBN and income, and modifies the indicators and procedures for their combination) and the enactment of the General Law of Social Development (LGDS) which makes multidimensional measurement of poverty official and binding. C) Analyzes the current situation in Mexico where two official multidimensional poverty measurement methods are applied every two years: one applied in the whole country instituted by the LGDS (and developed by Coneval, Federal Government agency) and the other (the improved variant of IPMM) adopted by the Government of the Federal District. At this point an explanation and discussion of both methods with some data illustrating the results is included. D) Discussion of whether the Mexican experience could serve as a guide to develop a method of multidimensional poverty measurement applicable to Latin America and a comparison with some currently world-wide circulating multidimensional methodologies (such as Alkire-Foster or UNDP) are carried out.