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Alkire Foster method

OPHI’s method for multidimensional measurement

The Alkire Foster (AF) method is a way of measuring multidimensional poverty developed by OPHI’s Sabina Alkire and James Foster. Building on the Foster-Greer-Thorbecke poverty measures, it involves counting the different types of deprivation that individuals experience at the same time, such as a lack of education or employment, or poor health or living standards. These deprivation profiles are analysed to identify who is poor, and then used to construct a multidimensional index of poverty (MPI). For free online video guides on how to use the AF method, see OPHI’s online training portal.

Identifying who is poor

To identify the poor, the AF method counts the overlapping or simultaneous deprivations that a person or household experiences in different indicators of poverty. The indicators may be equally weighted or take different weights. People are identified as multidimensionally poor if the weighted sum of their deprivations is greater than or equal to a poverty cut off – such as 20%, 30% or 50% of all deprivations.

It is a flexible approach which can be tailored to a variety of situations by selecting different dimensions (e.g. education), indicators of poverty within each dimension (e.g. how many years schooling a person has) and poverty cut offs (e.g. a person with fewer than five years of education is considered deprived).

Constructing poverty measures

The most common way of measuring poverty is to calculate the percentage of the population who are poor, known as the headcount ratio (H). Having identified who is poor, the AF method generates a unique class of poverty measures (Mα) that goes beyond the simple headcount ratio. Three measures in this class are of high importance:

  • Adjusted headcount ratio (M0), otherwise known as the MPI: This measure reflects both the incidence of poverty (the percentage of the population who are poor) and the intensity of poverty (the percentage of deprivations suffered by each person or household on average). M0 is calculated by multiplying the incidence (H) by the intensity (A). M0 = H x A.
  • Adjusted Poverty Gap (M1): This measure reflects the incidence, intensity and depth of poverty. The depth of poverty is the average ‘gap’ (G) between the level of deprivation poor people experience and the poverty cut-off line. M1 = H x A x G.
  • Adjusted Squared Poverty Gap (M2): This measure reflects the incidence, intensity, and depth of poverty, as well as inequality among the poor (captured by the squared gap, S). M2 = H x A x S.

M0 can be calculated with ordinal as well as cardinal data, which is why it is most often used. Cardinal data are required to calculate M1 and M2.

The AF method is unique in that by measuring intensity it can distinguish between, for example, a group of poor people who suffer two deprivations on average and a group of poor people who suffer five deprivations on average at the same time.

Common uses of the AF method

  • Poverty measures: The AF method can be used to create national, regional or international measures of poverty or wellbeing by incorporating dimensions and indicators that are tailored to specific contexts.
  • Targeting of services or conditional cash transfers: The method can be used to target people who are deprived in multiple ways.
  • Monitoring and evaluation: It can be used to monitor the effectiveness of programmes over time.

Why is the AF method useful?

While the AF method provides a single headline measure of poverty, it can also be broken down and analysed in powerful ways to inform policy.

  • Decomposition by population group: It can be broken down by geographic area, ethnicity, or other sub-groups of a population, to show the composition of poverty within and among these groups.
  • Breakdown by dimension or indicator: It can be broken down to show which types of deprivation are contributing to poverty within groups.
  • Changes over time: The AF method can be used to monitor changes in poverty over time, using data collected at different periods. It reflects changes in particular dimensions and indicators of poverty directly and quickly, making it an effective monitoring tool.
  • Complements other metrics: The AF method can complement other measures, such as measures of income poverty.