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China has successfully eliminated absolute poverty and thus its poverty reduction efforts are now entering a new phase aimed at alleviating relative poverty. However, the existing studies do not yet statistically measure the effectiveness of these relative poverty alleviation efforts. Therefore, by extending the Alkire-Foster method, we adopt a \"triple cut-off approach\" to evaluate the effectiveness of multidimensional poverty reduction efforts in China. Furthermore, we construct two indices–the chronic multidimensional relative poverty alleviation index (CMAI) and the chronic multidimensional relative poverty return index (CMRI)–to measure China's relative poverty dynamics. The results show that: (1) the value of CMAI is greater than that of CMRI in China; (2) income, savings and educational expenses have a material impact on both the CMAI and the CMRI; and (3) the effectiveness of relative poverty alleviation efforts in each province can be measured along four dimensions. The government should therefore attach great importance to areas with low poverty reduction effectiveness by favoring these areas in their future poverty reduction policies and resource-allocation decisions. This paper provides a statistical measurement tool for assessing China's relative poverty management that considers the effectiveness of governance, reveals which regions are less effective in alleviating poverty or are at a greater risk of returning to poverty, and supports policy formulation in the post-2020 era. Keywords Relative poverty * Chronic Multidimensional Poverty Alleviation Index * Chronic Multidimensional Poverty Return Index * Decomposition of Poverty Index JEL Classification I32

As stated in the 2018 global Multidimensional Poverty Index (MPI) report, Ethiopia has the second largest multidimensionally poor population in Africa (after Nigeria). The global MPI was created to measure household’s multiple deprivations, but little systematic study has been carried out on the application of MPI measures on a smaller scale and vis-à-vis other measures of poverty. In addition, most of the few existing studies ignore any measure of inequality amongst the multidimensionally poor. This study explored multidimensional poverty in three different drought-prone agro-ecological settings of the Upper Blue Nile basin, Ethiopia. A preliminary participatory exercise was carried out at the study sites to select important indicators and then a structured survey was administered to 390 systematically and randomly selected households. The Alkire–Foster method was used to analyse multidimensional poverty and verified it with Correlation Sensitive Poverty Index (CSPI). Multidimensional poverty incidence, adjusted head count ratio and inequality were significantly different between study sites ( p  < 0.001). Results indicated a high incidence (88%, 82% and 80%), intensity (52%, 55% and 56%), MPI (46%, 45% and 45%) and inequality (53%, 60% and 63%) of poverty in Aba Gerima, Guder and Dibatie study sites, respectively. A high level of divergence was revealed between the MPI and CSPI in terms of identifying the poor. The living standard and land and livestock ownership dimensions contributed the most to MPI. The case study signifies the importance of inclusion of land and livestock indicators for the national MPI. Besides, it implies that researchers and policymakers need to account for smaller scale contextualised indicators and location differences when studying and designing anti-poverty interventions.

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.

Poverty, particularly in developing regions, is a complex, multifaceted issue deeply embedded in various interrelated factors. It extends beyond mere financial insufficiency, encompassing limited access to essential services such as healthcare, education, and overall living standards. This study examines both the unidimensional and multidimensional aspects of rural poverty in Suri Sadar Sub-Division, located in Eastern India. For the unidimensional aspect, this study employs the poverty headcount ratio and the Poverty Gap Index to gauge the incidence and intensity of poverty. In contrast, the multidimensional approach utilized three dimensions and 12 indicators to assess the incidence, severity, and multidimensional poverty index utilizing the Alkire–Foster (AF) methodology. The unidimensional analysis, focusing on income and consumption, highlights significant economic disparities, particularly in the western Community Development Blocks, namely, Khoyrasole, Md. Bazar, and Rajnagar. The highest levels of multidimensional poverty are generally consistent with the unidimensional findings, particularly in the western blocks. These results underscore the need for comprehensive poverty reduction strategies that address both economic and broader aspects of poverty. In areas like the western blocks, where both income-based and multidimensional poverty rates are high, strategies should integrate economic development, improved healthcare access, enhanced educational quality, and living standards improvement. Therefore, this study serves not only as an academic endeavor but also as a vital tool for informed policymaking in poverty alleviation, providing planners, administrative officials, and researchers with essential insights to develop effective, localized, and sustainable poverty reduction strategies.

The lack of access to safe drinking water and the insufficient provision of individual drinking water needs are among the defining characteristics of slum areas. This study investigates the extent of this problem in Gresik Regency, East Java, Indonesia, a region characterized by the ubiquity of slum settlements across all sub-districts. The study aims to provide a comprehensive understanding of clean water access, water quality, and community capacity in managing water resources with implications for achieving sustainable housing. This study assesses water poverty levels using the Water Poverty Index (WPI), which considers five dimensions: resource availability, accessibility, capacity, usage efficiency, and environmental sustainability. The result shows the WPI of Gresik Regency revealed a score of 73.95, indicating a low level of water poverty, suggesting that the region's water security is in a good condition. Among the five dimensions constituting the WPI, the environmental dimension falls into the category of relatively high WPI or environmental poverty, with a score of under 50. This indicates that while access to water is available and affordable, issues related to waste management and future water resilience remain low. Water scarcity in the Gresik District is an illustration of global challenges related to water poverty, such as in Myanmar, India and South Africa, which have WPI values below 55. This research emphasizes the importance of a holistic approach in managing water resources by prioritizing environmental quality as the main priority

Watershed Development is a very common phenomenon in the river basins in India due to its dynamic and continuously changing nature, which are interconnected via. Land use/land cover (LULC) change and water poverty scenario over time. In the present study, the samples were chosen from seven sampled villages for the Water Poverty Index (WPI) in the upper Tons River Basin. Among them, Ghunwara and Maihar Village exhibit the highest and lowest WPI, i.e., 98.1 and 62.91 out of 100, respectively. This indicates that villages with a high WPI face challenges in their water requirements, regardless of the seasonal river serving the basin area. Conversely, villages with a low WPI can satisfy their water needs solely from the basin. The present analysis of the Upper Tons River Basin suggests that Land Use and Land Cover (LULC) will undergo influences or adjustments at various stages, ultimately affecting agricultural land in the impact region. It also becomes evident that areas with limited land use and land cover (LULC) extensions exhibit lower Water Productivity Index (WPI), primarily due to their reliance on agricultural land. It is observed that alterations, reductions, or modifications in LULC lead to changes in multiple aspects of agricultural land, resulting in noticeable variations in various metrics. The present paper not only evaluates the land use in the Upper Tons River Basin spanning from 2001 to 2021 but also highlights the changing patterns that impact water resources and their utilization capacity. Furthermore, the study estimates the influence of reducing specific features on the distribution of WPI and other LULC parameters. The Upper Tons River Basin faces challenges such as unfavorable rainfall patterns and inadequate planning for irrigation at the fundamental and local levels. Additionally, its geographical location in a rainfed area negatively affects the WPI.

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 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.

Energy poverty is a serious problem affecting many people in the world. To address it and alleviate it, the first action is to identify and measure the intensity of the population living in this condition. This paper seeks to generate information regarding the actual state of energy poverty by answering the research question: is it possible to measure the intensity of energy poverty between different Latin American countries with sufficient and equivalent data? To achieve this, the Multidimensional Energy Poverty Index (MEPI), proposed by Nussbaumer et al., was used. The results present two levels of lack of access to energy services: Energy Poverty (EP) and Extreme Energy Poverty (EEP). The last one, is a concept introduced by the authors to evaluate energy poverty using MEPI. Results of people living on EP (EEP within parentheses) are as follow: Colombia 29% (18%), Dominican Republic 32% (14%), Guatemala 76% (61%), Haiti 98% (91%), Honduras 72% (59%), Mexico 30% (17%) and Peru 65% (42%). A clear correlation between the Human Development Index (HDI) and MEPI is displayed, however some countries have relatively high values for the HDI, but do not perform so well in the MEPI and vice versa. Further investigation is needed.

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.