The global MPI is a measure of acute poverty covering over 100 countries in the developing regions of the world. This measure is based on the dual cutoff counting approach to poverty measurement developed by Alkire and Foster (2011). The global MPI was developed in 2010 by Alkire and Santos (2010; 2014) in collaboration with the United Nations Development Programme’s (UNDP) Human Development Report Office (HDRO). Since its inception, the global MPI has used information from 10 indicators, grouped into three equally weighted dimensions: health, education and living standards. These dimensions are the same as those used in the UNDP’s Human Development Index.

The first major revision of the global MPI was undertaken in 2018, considering improvements in survey microdata and to better align with the 2030 Agenda for Sustainable Development insofar as possible (Alkire and Jahan, 2018; OPHI, 2018; Alkire and Kanagaratnam, 2021). The revision adjusted the definitions of five of the ten indicators: child mortality, nutrition, years of schooling, housing and assets. The normative and empirical decisions that underlie the revision of the global MPI, and adjustments related to the child mortality, nutrition, years of schooling and housing indicators, are discussed in Alkire and Kanagaratnam (2021). Alkire et al. (2022) provide a comprehensive analysis of the consequences of the 2018 revision. The revision of the assets indicator is detailed in Vollmer and Alkire (2022).

The global MPI begins by establishing a deprivation profile for each person, showing in which of the 10 indicators they are deprived. Each person is identified as deprived or non-deprived in each indicator based on its respective deprivation cutoff. In the case of health and education, each household member may be identified as deprived or not deprived according to the information available for other household members. For example, if any household member for whom data exist is undernourished, each person in that household is considered deprived in nutrition. Taking this approach – which was required by the data – does not reveal intrahousehold disparities, but is intuitive and assumes shared positive (or negative) effects of achieving (or not achieving) certain outcomes. Next, looking across indicators, each person’s deprivation score is constructed by adding up the weights of the indicators in which they are deprived. The indicators use a nested weight structure: equal weights across dimensions and an equal weight for each indicator within a dimension. The indicator weight structure of the global MPI means that the living standards indicators receive lower weight than health and education-related indicators because, from a policy perspective, each of the three dimensions is of roughly equal normative importance.

In the global MPI, a person is identified as multidimensionally poor (MPI poor) if they are deprived in at least one-third of the weighted MPI indicators. In other words, a person is MPI poor if their deprivation score is equal to or higher than the poverty cutoff of 33.33%. After the poverty identification step, we aggregate across individuals to obtain the incidence of poverty, or headcount ratio (H), which represents the percentage of poor people in the population. We then compute the intensity of poverty (A), representing the average deprivation score, or the average percentage of weighted deprivations, experienced by poor people. We compute the adjusted poverty headcount ratio (M0) or the MPI by multiplying together H and A (MPI = H x A).

Both the incidence and the intensity of multidimensional poverty are highly relevant pieces of information for poverty measurement. The incidence of poverty is intuitive and understandable by anyone. People want to know how many poor people there are in a society as a proportion of the whole population, and the media tend to pick up on the incidence of poverty. Yet, the proportion of poor people as a headline figure is not enough (Alkire, Oldiges and Kanagaratnam, 2021).

A headcount ratio is also estimated using two other poverty cutoffs. The global MPI identifies individuals as vulnerable to poverty if they are not poor but are close to the poverty threshold; that is, if they are deprived in 20% to 33.32% of weighted indicators. The method also applies a higher poverty cutoff to identify individuals in severe poverty, meaning those deprived in 50% or more of the dimensions.

The Alkire-Foster method has a property that makes the global MPI even more useful – dimensional breakdown. This property makes it possible to consistently compute the percentage of the population who are multidimensionally poor and simultaneously deprived in an indicator. This is known as the censored headcount ratio of an indicator. While above we described MPI to be the product of H x A, the MPI can equivalently be computed as the weighted sum of the censored headcount ratios of all MPI indicators.

The censored headcount ratio shows the extent of deprivations among poor people but does not reflect the weights or relative values of the indicators. Two indicators may have the same censored headcount ratios but different contributions to overall poverty, as the contribution depends both on the censored headcount ratio and on the weight assigned to each indicator. As such, a complementary analysis to the censored headcount ratio is the percentage contribution of each indicator to overall multidimensional poverty.