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The paper provides an overview of definitions, measurements and applications of the concept of multidimensional poverty through a systematic review. The literature is classified according to three research questions: (1) what are the main definitions of multidimensional poverty?; (2) what methods are used to measure multidimensional poverty?; (3) what are the dimensions empirically measured?. Findings indicate that (1) the research on multidimensional poverty has grown in recent years; (2) multidimensional definitions do not necessarily imply to leave behind the dominance of the economic sphere; (3) the most popular methods proposed in the literature deal with the Alkire–Foster methodology, followed by latent variable models. Recommendations for future research emerge: new methodologies or the improvement of current ones are rather relevant; intangible aspects of poverty start to deserve attention calling for new definitions; there is evidence of under researched geographical areas, thereby calling for new empirical works that expand the geographical scope.

This paper analyzes Colombian households’ vulnerability to multidimensional poverty. For this purpose, we apply the vulnerability as expected poverty approach and the multidimensional poverty index to obtain the probability of a household being poor in the future. The source of information was the Colombian Longitudinal Survey. By employing the Feasible Generalized Least Squares methodology in three stages, the results indicate that the percentage of vulnerable households is greater than the percentage of poor households. In addition, the pattern of vulnerability differs depending on the area (i.e., rural or urban) in which the households are located. These findings have important policy implications; specifically, they enable us to distinguish between groups of people that require particular policy strategies: households that are persistently poor require poverty alleviation interventions and those that are not poor, but have a high probability of becoming poor in the future, need poverty prevention strategies.

Mozambique experienced important reductions in the poverty rate until recently, before two major natural disasters hit, an armed insurgency stroke in the northern province of Cabo Delgado, and the country started suffering from a hidden debt crisis with associated economic slowdown. As the last available national household expenditure survey is from 2014/15, just before these crises started unfolding, there is need for a poverty assessment based on alternative data sources. We study the evolution of multidimensional poverty in Mozambique using survey data from the Demographic and Health Surveys (DHS). Using both the standard Alkire–Foster multidimensional poverty index and the first-order dominance (FOD) method, we find that the multidimensional poverty reduction trend observed between 2009–11 and 2015 halted between 2015 and 2018. Meanwhile, the number of poor people increased, mainly in rural areas and in the central provinces. Importantly, the poorest provinces did not improve their rankings over time, and between 2015 and 2018, no progress took place for most areas and provinces, as measured by the FOD approach.

Poverty is no longer a problem of income alone. Healthy poverty and capacity poverty have become key factors affecting the poverty reduction effectiveness. Based on \"double cut-offs\" multidimensional poverty identification method of Alkire and Foster (J Public Econ 95(7–8): 476–487, 2011), this paper proposes a \"triple cut-offs\" identification method of multidimensional poverty reduction effectiveness, and construct the chronic multidimensional poverty reduction index combined with chronic thinking of Foster (in: Addison T, Hulme D, Kanbur R (eds) Poverty dynamics: interdisciplinary perspectives. Oxford University Press, Oxford, pp 59–76, 2009). And this index can comprehensively and systematically measure the China's multidimensional poverty reduction effectiveness in terms of both poverty alleviation and poverty returning. In this paper, we find that China's chronic multidimensional poverty alleviation index is greater than the country's chronic poverty returning index, and the chronic multidimensional poverty alleviation/returning index in rural and western regions is greater than that in its cities and other regions in China. The chronic poverty alleviation of per capita net income and medical insurance have contributed a lot to the overall chronic multidimensional poverty alleviation of China's rural residents, while poverty returning caused by health and housing difficulties has contributed a lot (48.14%) to the chronic multidimensional poverty alleviation of the country's urban residents. These findings can provide more targeted guidance for poverty governance.

The present study has made a thorough investigation into the spatial clustering, trend, and intensity of multidimensional poverty in India between 2005–2006 and 2021. Data has been obtained from the global multidimensional poverty report [developed by the Oxford Poverty and Human Development Initiative (OPHI) and UNDP] and the national report of the Multidimensional Poverty Index (MPI) for 2021 [prepared by NITI Aayog] for India based on the NFHS-3 and NFHS-4 datasets. The study shows that, despite significant interstate disparities, multidimensional poverty in India has decreased from 0.279 in 2005–2006 to 0.118 in 2021. States like Bihar, Jharkhand continue to experience extreme multidimensional poverty. The study demonstrates that even though the intensity of poverty has remained relatively constant, the poorer states are significantly more advanced in reducing poverty than the nation’s wealthier states. This suggests a pattern of pro-poor poverty reduction. Besides the study explores indicator-wise deprivation of MPI among the states and it is witnessed that Chhattisgarh, Jharkhand, Tripura, and Bihar have made splendid progress in reducing deprivation in different indicators (antenatal care, electricity, drinking water, assets) of multidimensional poverty, while the magnitude of deprivation is acute in several indicators like nutrition, cooking fuel, sanitation, and housing in these states. Based on the analysis, the present study suggests that India should undertake target-based interventions in poverty-prone regions to reduce poverty.

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.

This paper explores the incidence and extent of multidimensional poverty for the households in Purulia district, the western most backward district of West Bengal in India. In context of Purulia district the decompositions of multidimensional poverty index (MPI) across the social castes and across the indicators have also been explained. MPI and its decomposition across the sub-groups have been computed using the methodology developed by Alkire and Foster (2007) and Alkire et al. (2011). This study covers twelve non income indicators under three dimensions education, health and living conditions. Collecting a set of primary data from 698 households in Purulia district during 2018, this study reveals that the incidence of multidimensional poverty in the district of Purulia is higher than that in national level. But the breadth of poverty is almost equal to that in India as a whole. In respect of poverty there is wide variation across the social castes. Among the indicators, use of dirty cooking fuel, not having improved sanitation have highest contribution to the district MPI.

In this paper, we propose a hybrid Watts-MPI multidimensional poverty measure that combines the multidimensional Watts poverty index (MWPI), which can accommodate continuous poverty dimensions, with the multidimensional poverty index (MPI), which can accommodate binary poverty dimensions. Unlike the stand-alone MPI that entails total loss of dimension-specific information on both poverty intensity with respect to shortfall and inequality, the proposed hybrid Watts-MPI measure entails only partial loss of such information since poverty intensity and inequality estimates can still be obtained for the continuous poverty dimensions included in the hybrid measure. The hybrid Watts-MPI also specializes to the stand-alone MWPI and MPI when all the poverty dimensions are continuous and binary, respectively. Furthermore, formation of the hybrid Watts-MPI does not entail loss of normative properties by either the constituent MWPI or MPI. The seemingly unrelated regression approach to the estimation of the hybrid Watts-MPI is described and an empirical example demonstrating its efficacy is provided.

The literature on the concept and measurement of poverty has significantly improved from the traditional unidimensional (income/expenditure) analysis to the multidimensional concept of poverty and well-being. Following the Multidimensional Poverty Assessment Tool (MPAT), the study explored the potential of combining counting and participatory approaches in determining levels of deprivations and well-being in an upland farming community in the Philippines. Data from a random sample of 153 farming households and analyzed following Alkire and the Foster's methodology revealed that 3 out of 4 households are multidimensionally poor. Results of the study also show that farming households' ability to generate farm- and non-farm income in addition to the high degree of exposure to idiosyncratic and covariate shocks contribute to the high multidimensional poverty index. Further, the study presents implications of these results for antipoverty policy in the rural context.

The persistency of poverty around the world is one of the most serious problems that humanity has to face, so in order to arise awareness, it is essential that the measurement of such problem is improved. These improvements also give the incentive to carry out motivating actions, design good policies, gauging progress, and enable holding political leaders accountable for meeting targets. To help make this possible, we provide an examination of how poverty is currently measured, bringing together evidence on the nature and extent of poverty in 91 countries around the world. This article presents research using the Rasch model, an inductive method which uses a synthetic-analytical process. This method enables us to provide a comparison of poverty among countries and identifies the main factors that contribute to it.