Multidimensional Poverty Index (MPI)

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 developed by Alkire and Foster (2011). The global MPI was developed in 2010 by Alkire and Santos (2014, 2010) in collaboration with the UNDP’s Human Development Report Office (HDRO). Since its inception, the global MPI has used information from 10 indicators, which are 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.

In 2018, the first major revision of the global MPI was undertaken, considering improvements in survey microdata and better align to the 2030 development agenda insofar as possible (Alkire and Jahan, 2018; OPHI, 2018). The revision consisted of adjustments in the definition of five out of the ten indicators, namely child mortality, nutrition, years of schooling, housing and assets. Alkire, Kanagaratnam, Nogales and Suppa (2022) provide a comprehensive analysis of the consequences of the 2018 revision. 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). The revision of assets indicator is detailed in Vollmer and Alkire (2022).

The global MPI begins by establishing a deprivation profile for each person, showing which of the 10 indicators they are deprived in. Each person is identified as deprived or non-deprived in each indicator based on a deprivation cutoff. In the case of health and education, each household member may be identified as deprived or not deprived according to available information 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 normalised indicator weight structure of the global MPI means that the living standard 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 or 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 the person’s deprivation score is equal to or higher than the poverty cutoff of 33.33 percent. 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 percentage of weighted deprivations experienced by the poor. We then compute the adjusted poverty headcount ratio (M0) or MPI by combining H and A in a multiplicative form (MPI = H x A).

Both the incidence and the intensity of these deprivations are highly relevant pieces of information for poverty measurement. The incidence of poverty is intuitive and understandable by anyone. People always want to know how many poor people there are in a society as a proportion of the whole population. Media tend to pick up on the incidence of poverty easily. Yet, the proportion of poor people as the 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 close to the one-third threshold, that is, if they are deprived in 20 to 33.32 percent of weighted indicators. The tables also apply a higher poverty cutoff to identify those in severe poverty, meaning those deprived in 50 percent or more of the dimensions.

The AF methodology 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 each indicator. This is known as the censored headcount ratio of an indicator. The weighted sum of censored headcount ratios of all MPI indicators is equal to the MPI value.

The censored headcount ratio shows the extent of deprivations among the poor 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, because 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.