government forces and has lasted for 17 years until a recent peace treaty in 2020. The war caused tens of thousands of civilian casualties, and millions were forced to flee their homes due to the conflict and general economic instability due to years of fighting that inflated commodity prices. Moreover, much of Sudan is covered by desert and arid land, posing further difficulties as most people rely on agriculture for their livelihoods. Overuse of the land, droughts and flashfloods have contributed to displacement as people escape food insecurity and natural disasters. As of December 2019, there were 2.4 million IDPs in Sudan (IDMC 2020), around 5.6% of the total population (World Bank 2020a). Sudan also has one of the largest refugee populations in Africa, with many people from surrounding countries such as Ethiopia and South Sudan, and even as far as the Syrian Arab Republic and the Republic of Yemen, seeking safety from violence and conflict. As of 2014, 12.2% of the population was living on less than $1.90 a day (World Bank 2020b) and 52.3% were MPI poor in the same year (UNDP and OPHI 2020). Widespread displacement and poverty following decades of conflict has also contributed to gender-based violence, particularly against the most vulnerable population groups such as IDP girls and women. According to the UN Women database, the prevalence of child marriage in Sudan is 34%, while 87% of the population are subject to female genital mutilation.<sup>12</sup>

# **3. Methodology**

## **3.1 Alkire-Foster method**

The Multidimensional Poverty Index (MPI) constructed for this analysis is based on the AlkireFoster (AF) method of multidimensional poverty measurement (Alkire and Foster 2011). The AF method allows for the construction of individual- and household-level deprivation profiles that can then be used to identify multidimensionally poor people. There are three key statistics for any MPI: incidence or headcount ratio (H), which is the proportion of the population who are multidimensionally poor; intensity (A), which is the average share of weighted deprivations experienced by the poor; and the MPI or adjusted headcount ratio, which is the product of the incidence and intensity (MPI = H × A).

The AF method uses a dual-cutoff counting approach to poverty measurement. First, households (or individuals) are classified as deprived or non-deprived according to deprivation cut-offs, specific to each indicator. The deprivations for each individual are weighted and aggregated into a weighted deprivation score. Next, a cross-dimensional poverty cut-off _k_ is used to identify people with a deprivation score equal to or greater than the threshold as multidimensionally poor.

The MPI can be broken down by indicator to show the composition of multidimensional poverty, a feature of dimensional detail that brings added policy relevance to the analysis. The censored headcount ratio is the percentage of the population that is both poor and deprived in a given indicator. The MPI can be calculated by adding up the weighted censored headcount ratios of each indicator: MPI = sum [ (h )] for all , where add up to 1. The percentage contribution of a given indicator to the MPI is calculated as the indicator’s censored headcount jj jj jj ratio, multiplied by its weight, and divided by the MPI. ww jj ww In addition, the MPI can be disaggregated by different population groups, such as urban or rural areas, age groups, subnational regions or, in the case of this work, host communities and

> 12 - - <u>https://evaw global database.unwomen.org/fr/countries/africa/sudan</u>

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