Multidimensional Poverty Index

The Global MPI uses three standard dimensions: Health; Education; Standard of Living. These mirror the Human Development Index.

Multidimensional Poverty Indices used for purposes other than global comparison have sometimes used different dimensions, including income and consumption.

The Global MPI uses the following ten indicators with the following cutoffs.[8][9]

The indicators selected for other MPI oriented studies vary according to availability of data and the context,[11] as well as the theoretical considerations of the researchers.[12]

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).

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).

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 methodology 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.

Country X consists of persons A, B and C. The following table shows the deprivation on each of the 10 indicators for persons A, B and C.

"0%" indicates no deprivation in that indicator, while "100%" indicates deprivation in that indicator.

Factor H for country X is:

${\displaystyle {\frac {1+1+0}{3}}=0.667}$

Factor A for country X is:

${\displaystyle {\frac {33.33\%+50.00\%}{2}}=0.417}$

Thus, the MPI for country X is:

${\displaystyle 0.667\times 0.417=0.278}$

HDI, the Human Development Index, was developed by Mahbub ul Haq and Amartya Sen, in 1990, and was also developed by the UNDP. It is calculated as the geometric mean of the normalized indices of the three dimensions of human development it takes into account: health, education and standard of living. The UNDP is trying to improve on the HDI formula by introducing the IHDI (Inequality affected HDI).

While both HDI and MPI use the 3 broad dimensions health, education and standard of living, HDI uses only single indicators for each dimension of poverty while MPI uses more than one indicator for each one. This, amongst other reasons, has led to the MPI only being calculated for just over 100 countries, where data is available for all these diverse indicators, while HDI is calculated for almost all countries.

However, though HDI is thus more universally applicable, its relative sparsity of indicators also makes it more susceptible to bias. Indeed, some studies have found it to be somewhat biased towards GDP per capita, as demonstrated by a high correlation between HDI and the log of GDPpc. Hence, HDI has been criticized for ignoring other development parameters.

Both HDI and MPI have been criticized by economists such as Ratan Lal Basu for not taking "moral/emotional/spiritual dimensions" of poverty into consideration. It has been attempted to capture these additional factors by the "Global Happiness Index".