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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.

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.

This chapter critically examines the causes and effects of continuous poverty in two sub-Saharan African (SSA) countries, despite various poverty alleviation strategies adopted by each country. It reveals the theoretical framework and the accompanying set of programmatic and policy tools for poverty alleviation in SSA.

This paper argues that the assumption of a homogeneous workforce, which is implicitly invoked in the decomposition analysis of changes in welfare indicators, hides the role that schooling and its returns may have on the understanding of these changes. Using Peruvian cross-sectional data for a period of 10 years (2004–2013) and counterfactual simulations, this paper finds that the main factor contributing to poverty reduction has been individuals’ changes in labor earnings, and the role of these changes has been less important in reducing income inequality. The main driving force of reduced income inequality has been the fall in returns to education, which at the same time has been one of the important factors to constraining the period’s remarkable progress in poverty reduction and expansion of the middle class.

This paper compares two alternative methods for measuring multidimensional poverty. This question has become extremely important in recent years, both in the scientific literature and in social policy. We propose to use latent class analysis to evaluate poverty in Spain. We make use of the “fuzzy set” approach, and compare the results achieved from these two methodologies.

Children in Malaysia, just as children in many other countries, are vulnerable to poverty. They are exposed to different forms of deprivation and the COVID-19 pandemic exacerbated their predicament. Concerns have been raised about the impact of the pandemic on children’s well-being, as this health crisis had intensified the educational and economic disparities among children in Malaysia, and for some children the impact will be lifelong. It is important to recognise the multidimensionality of poverty in regard to deprivation among poor children; however, such concerns are less pronounced in public policy discussions. Demands for greater policy attention intensified following the increasing number of unemployed parents and bereaved children who lost their parents due to the pandemic. The scope of poverty alleviation policies failed to consider the varying poverty gaps between recipients and the various forms of deprivation experienced by children in poor and larger sized households. As a result, the allocation of funds for the improvement of children’s well-being has been insignificant. The aim of this chapter is to provide a thorough overview of child poverty in developed and developing countries and how child poverty has changed in Malaysia. The analysis in this chapter seeks to provide deep insights on the development of policies that address poverty among children in Malaysia. An analysis on budget appropriations reveals that efforts to address other dimensions of child development were steadily improved, but policy commitments for such purposes need to be intensified in the post-pandemic era when hundreds of thousands of families and children have been plunged into poverty. It is timely for policymakers to acknowledge the need for separate policy considerations for children since they experience poverty differently from adults. The fulfilment of their needs should be prioritised, and the recognition of this fact would produce desirable plans of action for children living in poverty.

Post reform India has generated high economic growth, yet progress in income poverty and many other key development outcomes has been modest. This chapter primarily examines how inclusive economic growth has been in India between 2005–2006 and 2015–2016 in reducing multidimensional poverty captured by the global multidimensional poverty index (MPI). The authors employ a constellation of elasticity and semi-elasticity measures to examine vertical, horizontal as well as dimensional inclusiveness of economic growth. Nationally, the authors estimate that a 1% annual economic growth in India during their study period is associated with an annual reduction in MPI of 1.34%. The association of the national growth to state poverty reduction (horizontal inclusiveness) is, however, not uniform. Some states have been successful in reducing poverty faster than the national average despite slower economic growth between 2005–2005 and 2015–2016; whereas, other states have been less successful to do so despite faster economic growth during the same period. The authors’ analyses and findings show how these tools may be used in practical applications to measure inclusive growth and inform policy.