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There has been a rapid expansion in the literature on the measurement of multidimensional poverty in recent years. This paper focuses on the longitudinal aspects of multidimensional poverty and its link to dynamic income poverty measurement. Using panel household survey data in Vietnam from 2007, 2008, and 2010, the paper analyses the prevalence and dynamics of both multidimensional and monetary poverty from the same dataset. The results show that the monetary poor (or non-poor) are not always multidimensionally poor (or non-poor) – indeed the overlap between the two measures is much less than 50 percent. Additionally, monetary poverty shows faster progress as well as a higher level of fluctuation than multidimensional poverty. We suggest that rapid economic growth as experienced by Vietnam has had a larger and more immediate impact on monetary than on multidimensional poverty.

Purpose: Most of the characterizations of inequality or poverty indices assume some invariance condition, be that scale, translation, or intermediate, which imposes value judgments on the measurement. In the unidimensional approach, Zheng (2007a, 2007b) suggests replacing all these properties with the unit-consistency axiom, which requires that the inequality or poverty rankings, rather than their cardinal values, are not altered when income is measured in different monetary units. The aim of this paper is to introduce a multidimensional generalization of this axiom and characterize classes of multidimensional inequality and poverty measures that are unit consistent.

Design/methodology/approach: Zheng (2007a, 2007b) characterizes families of inequality and poverty measures that fulfil the unit-consistency axiom. Tsui (1999, 2002), in turn, derives families of the multidimensional relative inequality and poverty measures. Both of these contributions are the background taken to achieve our characterization results.

Findings: This paper merges these two generalizations to identify the canonical forms of all the multidimensional subgroup- and unit-consistent inequality and poverty measures. The inequality families we derive are generalizations of both the Zheng and Tsui inequality families. The poverty indices presented are generalizations of Tsui's relative poverty families as well as the families identified by Zheng.

Originality/value: The inequality and poverty families characterized in this paper are unit and subgroup consistent, both of them being appropriate requirements in empirical applications in which inequality or poverty in a population split into groups is measured. Then, in empirical applications, it makes sense to choose measures from the families we derive.

A growing polarization of society accompanied by an erosion of the middle class is receiving increasing attention in recent German economic and social policy discussion. Our study contributes to this discussion in two ways: First, on a theoretical level we propose extended multidimensional polarization indices based on a constant elasticity of substitution (CES)-type well-being function and present a new measure to multidimensional polarization, the mean minimum polarization gap, 2DGAP. This polarization intensity measure provides transparency with regard to each single attribute, which is important for targeted policies, while at the same time respecting their interdependent relations. Second, in an empirical application, time is incorporated, in addition to the traditional income measure, as a fundamental resource for any activity. In particular, genuine personal leisure time will account for social participation in the sense of social inclusion/exclusion and Amartya Sen’s capability approach.

Instead of arbitrarily choosing the attribute parameters in the CES well-being function, the interdependent relations of time and income are evaluated by the German population. With the German Socio-Economic Panel (GSOEP) and detailed time use diary data from the German Time Use Surveys (GTUSs) 1991/1992 and 2001/2002, we quantify available and extended multidimensional polarization measures as well as our new approach to measuring the polarization of the working poor and affluent in Germany.

There are three prominent empirical results: Genuine personal leisure time in addition to income is an important and significant polarization attribute. Compensation is of economic and statistical significance. The new minimum 2DGAP approach reveals that multidimensional polarization increased in the 1990s in Germany.

The purpose of this study is to analyse the influence of household and community characteristics on multidimensional poverty in communities hosting public universities in Ondo state, Nigeria.

The study constructs Global Multidimensional Poverty Index (MPI) using Alkire-Foster methodology and uses logistic regression to analyse the likelihood of experiencing multidimensional poverty.

Findings from the study suggest that child schooling attendance, child mortality and asset ownership are the indicators in which households are mostly deprived in education, health and living standards consecutively. In addition, using logistic regression, the study finds multidimensional poverty reducing effects of education, age (before old), household size (having more economically active members), income and residing in urban areas. The study, however, documents that living far away from the universities increases the likelihood of experiencing multidimensional poverty in those communities.

To reduce multidimensional poverty in the communities of study, there is need to implement policies that will improve child schooling, reduce infant mortality, increase gainful employment and create enabling environment for asset ownership. This is in addition to upgrading infrastructure in those communities especially in their fringe areas so that development can spread, and multidimensional poverty reduction can follow in no distant future.

Unlike capturing the effect of location on possibility of experiencing poverty using rural or urban dummy, the authors, in addition to that, incorporate distance to university variable on the premise of distance decay mechanism.

Most poverty research has explored monetary poverty. This chapter presents and analyzes the global multidimensional poverty index (MPI) estimations for China. Using China Family Panel Studies (CFPS), we find China’s global MPI was 0.035 in 2010 and decreased significantly to 0.017 in 2014. The dimensional composition of MPI suggests that nutrition, education, safe drinking water, and cooking fuel contribute most to overall non-monetary poverty in China. Such analysis is also applied to subgroups, including geographic areas (rural/urban, east/central/west, provinces), as well as social characteristics such as gender of the household heads, age, education level, marital status, household size, migration status, ethnicity, and religion. We find the level and composition of poverty differs significantly across certain subgroups. We also find high levels of mismatch between monetary and multidimensional poverty at the household level, which highlights the importance of using both complementary measures to track progress in eradicating poverty.

The purpose of this paper is to assess the existence of critical tipping points for explanatory variables (age, government grants, education and household size) – in particular, household debt service-to-income on multidimensional poverty.

The paper applies a generalized additive model (GAM) using regression splines on National Income Dynamics Study data to establish threshold effects of the explanatory variables on multidimensional poverty.

The results show that the tipping point at which debt is associated with improved household welfare is 42.5 percent (level of debt service-to-income). With significant findings, household heads younger than 60 years of age and more children are associated with lower multidimensional poverty. Government grants may suffer from fungibility as they do not seem to be an effective tool for multidimensional poverty eradication. The ideal household size with negative significant correlation to multidimensional poverty is less than four members. And lastly, education proves to be the best instrument for households to escape multidimensional poverty.

High household indebtedness is a severe social problem. Its effects include deteriorating physical and mental health, relationship difficulties and breakdown. Significant social costs arise such as medical treatment and indirectly, reduction of productivity. Further effects on society include rising criminal behavior, children dropping out of school thereby transferring poverty to succeeding generations. Non-performing loans increase and in turn lead to reduced credit availability. The overall health of the economy is impacted due to reduced aggregate demand.

Macro studies have demonstrated the presence of thresholds on debt analyses. However, such is not known in micro analyses, this paper attempts to bridge this knowledge gap by applying GAM for analysis of debt-poverty nexus at the micro level.

Latin America has a longstanding tradition in multidimensional poverty measurement through the unsatisfied basic needs (UBN) approach. However, the method has been criticized on several grounds, including the selection of indicators, the implicit weighting scheme and the aggregation methodology, among others. The estimates by the UBN approach have traditionally been complemented (or replaced) with income poverty estimates. Under the premise that poverty is inherently multidimensional, in this chapter we propose three methodological refinements to the UBN approach. Using the proposed methodology we provide a set of comparable poverty estimates for six Latin American countries between 1992 and 2006.

The multidimensional nature of well-being is now widely recognized. However, multidimensional poverty measurement is still an expanding field of research and a consensus about the “best” composite indicator has not yet emerged. In this chapter, we provide an empirical analysis using three existing methodologies: Bourguignon and Chakravarty (2003), Alkire and Foster (2007), and Lemmi (2005); Chiappero Martinetti (2000). We present an empirical study of the convergence and divergence of poverty profiles for children in Uruguay considering the following dimensions: nutritional status, child educational achievement, housing condition, and household income. Our data gather information of 1,185 children attending public schools in Montevideo and the surrounding metropolitan area, and were specially gathered to carry out a multidimensional analysis of poverty.

Our results indicate that the three families of indexes yield very different cardinalizations of poverty. At the same time, the correlation coefficients among the three groups of measures for the generalized headcount ratio also highlight important differences in the children labeled as “more deprived.” For the generalized severity and intensity indexes the correlation coefficients increase significantly suggesting a high level of concordance among the three measures, particularly among the Bourguignon and Chakravarty methodology and the Alkire and Foster one.

The 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.

The 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.

Between 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.

This 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.

The purpose of this paper is to evaluate the impact of credit access on income and multidimensional poverty by providing an econometric framework.

The study is conducted in Assam, India and uses a quasi-experiment design to gather primary data. Econometric tools like Heckit procedure, Tobit selection equation and probit model are used for empirical purpose.

The paper finds that the level of individual welfare is influenced by equivalent factors. In addition, the study observes a larger incidence of poverty among treatment households of semiformal and informal borrowers. The study argues that formal sources are more effective in reducing the number of poor households by lifting those who are closest to the poverty line.

The study indicates a vicious circle of income and multidimensional poverty among semiformal and informal borrowers. By tradition, as rural Assam gets a dominant role of traditional community-based financial institutions, we should develop the banking structure by involving these institutions. The study excludes other probable explanatory variables while evaluating the impact of credit access on income and multidimensional poverty, and this limitation is left to future research.

This is probably the first empirical paper in Assam showing the impact of credit access on multidimensional poverty by adjusting for endogeneity and selection bias.