Multidimensional poverty indices

Multidimensional Poverty and Its Discontents

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 European Union (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. In contrast with the rather ad hoc way in which the EU 2020 poverty target has been framed and rationalized, 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 EU.

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.

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.

Multidimensional Poverty Indices: A Critical Assessment

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.

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 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 examines the persistence and structure of regional inequality in human development within Karnataka, India, through the lens of the human capability approach. Moving beyond income and growth rates, it analyses how freedoms and opportunities are unevenly distributed across districts and taluks, and how these disparities intersect with gender, caste, minority status and infrastructure gaps. The study relies exclusively on secondary data drawn primarily from the Karnataka State Human Development Report 2022, earlier state HDRs (1999, 2005, 2015), Census 2011, multidimensional poverty measures and micro-level district and taluk studies. Adopting a descriptive–analytical strategy rather than formal econometric modelling, it tracks long-term patterns in HDI, Gender Equality Index, SC/ST Multidimensional Poverty Index, minority HDI and key social infrastructure indicators. The findings reveal a striking stability in the state’s development hierarchy. Coastal and southern districts such as Bengaluru Urban, Dakshina Kannada, Udupi and Kodagu continue to record high human development, while Kalyana Karnataka districts—including Raichur, Yadgir, Koppal, Ballari and Kalaburagi—remain clustered at the bottom. Low HDI is closely associated with weak gender equality, high intensity of SC/ST deprivation, very low minority and ST HDI in specific taluks, and deficits in drinking water, sanitation, housing, electricity and health facilities. Taluk-level evidence shows that severe deprivation can be concealed within seemingly moderate districts, underscoring the limits of district averages for policy design. The paper argues that Karnataka’s development pattern is structurally “two-speed”: dynamic in the south and coast, stagnant in the north, with multiple disadvantages reinforcing one another over time. It concludes that incremental, scheme-based interventions are inadequate. Instead, a long-term, regionally differentiated strategy is required, centred on girls’ education, gender equality, targeted support for SC/ST and minority communities, infrastructure strengthening in lagging districts, and a need-based reorientation of public expenditure towards high-deprivation taluks. By integrating regional, social and gendered dimensions of deprivation within a single analytical framework, the study contributes evidence useful for more finely targeted human development planning in Karnataka.

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.

Assessing poverty using multiple dimensions of deprivation provides a comprehensive picture of poverty. No one factor, like income or any monetary-based indicator is uniquely able to capture all of the factors that contribute to poverty. This study attempts to evaluate the multidimensional poverty measure among Malaysian Employee Provident Fund (EPF) retirees by using Alkire and Foster multidimensional poverty index to a set of deprivation dimensions. The findings indicate that around 84% of EPF retirees were identified as multidimensionally poor, meaning that they are in acute poverty. On average, poor retirees are deprived of 48% of weighted indicators. The results also show that women are more multidimensionally poor compared to men in terms of transportation, income, home ownership and education. The study discovered that Indian retirees are more deprived than other ethnic groups, followed by Malays. In this regard, it is necessary to strengthen current retirement savings institutions to reduce the impacts of the retirement crisis. The government needs to provide a Social Security system that rolls back the decline of Malaysian’s retirement savings.

BackgroundAlthough global poverty rates have declined in the last decade, the fall in the Asia-Pacific region has been slow relative to the rest of the world. Poverty continues to be a major cause of poor maternal and newborn health, and a barrier to accessing timely antenatal care. Papua New Guinea has one of the highest poverty rates and some of the worst maternal and neonatal outcomes in the Asia-Pacific region. Few studies have investigated equity in antenatal care utilization in this setting. We explored equity in antenatal care utilization and the determinants of service utilization, which include a measure of multidimensional poverty in Papua New Guinea.MethodsTo explore the association between poverty and antenatal care utilization this study uses data from a ten-cluster randomized controlled trial. The poverty headcount, average poverty gap, adjusted poverty headcount, and multidimensional poverty index of antenatal clinic attendees are derived using the Alkire-Foster method. The distribution of service utilization is explored using the multidimensional poverty index, followed by multivariate regression analyses to evaluate the determinants of service utilization.ResultsThe poverty headcount was 61.06%, the average poverty gap 47.71%, the adjusted poverty headcount 29.13% and the average multidimensional poverty index was 0.363. Further, antenatal care utilization was regressive with respect to poverty. The regression analyses indicated that older women; being a widow (small number of widows (n = 3) asserts interpreting result with caution); or formally employed increase the likelihood of accessing antenatal care more often in pregnancy. Travelling for over an hour to receive care was negatively associated with utilization.ConclusionThis study indicated high levels of multidimensional poverty in PNG and that ANC utilization was regressive; highlighting the need to encourage pregnant women, especially those who are economically more vulnerable to visit clinics regularly throughout pregnancy.

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...

The relationship between poverty and tuberculosis (TB) is well-documented, as socio-economic deprivation constitutes a risk factor that drives TB transmission and progression while hindering treatment adherence. Despite the importance of controlling for socio-economic status (SES) in TB research, no universally accepted tool exists to measure multidimensional poverty’s impact on TB-affected households. This article provides an overview of existing SES assessment tools, including income-based measures, wealth indices like the Demographic and Health Survey (DHS) and the International Wealth Index (IWI), and multidimensional indices, such as the global Multidimensional Poverty Index (MPI). Each method’s strengths and limitations are considered, particularly in light of the complex deprivations relevant to TB. Recognizing the distinct SES determinants of TB, we emphasize the need for multidimensional, standardized SES measures that are contextually relevant and feasible for TB epidemiology, programmatic evaluations, and translational research. By advancing poverty metrics in TB studies, the global community can better address socio-economic drivers of TB and prioritize pro-poor interventions, fostering equitable health outcomes.

Objetivo: Analizar la relación entre la pobreza y las actitudes hacia las prácticas de cuidado infantil en áreas rurales y urbanas de Colombia. Método: El presente artículo es un estudio transversal correlacional en el departamento del Atlántico, al norte de Colombia. Se indagó sobre las actitudes hacia el cuidado infantil y las condiciones de vida en 1189 cuidadores de niños en edad preescolar. Se tuvo en cuenta el índice de pobreza multidimensional y el área de procedencia de los participantes (urbana o rural). Resultados: No se encontró una relación directa entre las actitudes hacia el cuidado infantil y el índice de pobreza multidimensional. Sin embargo, se observó que los participantes de áreas urbanas provenientes de zonas vulnerables presentaron un mayor índice de pobreza y mostraron actitudes menos positivas hacia el cuidado infantil, especialmente en el cuidado cognitivo, del sueño y de la salud. Se evidenció un efecto moderador del área sobre las actitudes de cuidado. Conclusiones: El estudio destaca la influencia de la pobreza y la vulnerabilidad social en las actitudes de cuidado infantil, especialmente en áreas urbanas. Estos hallazgos subrayan la importancia de considerar las condiciones socioeconómicas y geográficas al abordar el cuidado infantil. Además, se resalta la necesidad de implementar estrategias específicas para promover prácticas de cuidado positivas en contextos más vulnerables, con el fin de mejorar el desarrollo de la primera infancia en Colombia