Multidimensional Poverty Index was launched by the UNDP and the Oxford Poverty & Human Development Initiative (OPHI) in 2010.
MPI is a measure that takes into account the incidence of poverty and the extent of deprivation. Going beyond just monetary measures, the MPI takes into account several factors.
- Education: Years of schooling and child enrollment (1/6 weightage each, total 2/6);
- Health: Child mortality and nutrition (1/6 weightage each, total 2/6);
- Standard of living: Electricity, flooring, drinking water, sanitation, cooking fuel and assets (1/18 weightage each, total 2/6)
Positives of the Index :
- The MPI methodology shows aspects in which the poor are deprived and helps to reveal inter-connections among those deprivations. This enables policymakers to target resources and design policies more effectively. This is especially useful where the MPI reveals areas or groups characterized by severe deprivation.
- The multidimensional poverty approach can be adapted using indicators and weights that are more relevant to national context at the country level to create tailored national poverty measures.
- therefore, MPI can be useful as a guide to help governments tailor a poverty measure that reflects local indicators and data. In 2009, Mexico became the first country to adopt a measure of multidimensional poverty as an official national statistic.
- The MPI methodology can be, and often is, modified to generate national measures of Multidimensional Poverty that reflect local cultural, economic, climatic and other factors.
- Such national measures of Multidimensional Poverty may directly serve the purpose of monitoring SDG Indicator 1.2.2 (proportion of men, women and children of all ages living in poverty in all its dimensions according to national definitions).
- The global MPI was devised as an analytical tool to compare acute poverty across nations.
- The MPI reflects the multiple deprivations that people face at the same time. It is a measure of “acute” poverty because it reflects overlapping deprivation in basic needs and also to avoid confusion with the World Bank’s measure of “extreme” poverty that captures those living on less than $1.90 (in 2011 $PPP) a day.
- The MPI reflects both the incidence of multidimensional deprivation (a headcount of those in multidimensional poverty) and its intensity (the average deprivation score experienced by poor people).
- It can be used to create a comprehensive picture of people living in poverty, and permits comparisons both across countries, regions and the world and within countries by ethnic group, urban or rural location, as well as other key household and community characteristics.
- The MPI offers a valuable complement to income-based poverty measures.
Findings of Index :
The 2018 Statistical Update presents estimates for 105 developing countries with a combined population of 5.7 billion (77% of the world total). About 1.3 billion people in the countries covered—23.3% of their entire population—lived in multidimensional poverty between 2006 and 2016-17.
Data for India :
India has made momentous progress in reducing multidimensional poverty, according to estimates from the 2018 global Multidimensional Poverty Index (MPI). The incidence of multidimensional poverty has almost halved between 2005/6 and 2015/16, climbing down to 27.5 percent from 54.7 percent.
Among South Asian countries, only Maldives has a lower headcount ratio than India at 1.9 percent, with Nepal (35.3 percent), Bangladesh (41.1 percent), and Pakistan (43.9) having higher incidences of multidimensional poverty.
Though the traditionally disadvantaged groups – across states, castes, religions, and ages –are still the poorest, they have also experienced the biggest reductions in MPI through the decade, showing that they have been “catching up”.
Despite the massive gains made in reducing multidimensional poverty, 364 million Indians continue to experience acute deprivations in health, nutrition, schooling and sanitation. Just over one in four multi-dimensionally poor people in India are under ten years of age.
“Although the level of poverty – particularly in children – is staggering so is the progress that can be made in tackling it. In India alone some 271 million have escaped multidimensional poverty in just 10 years.
Over half of all multi-dimensionally poor in India live in the four poorest states
Pockets of poverty are found across India, but multidimensional poverty is particularly acute – and significant – in the four states of Bihar, Jharkhand, Uttar Pradesh and Madhya Pradesh. These accounted for 196 million MPI poor people – more than half of all MPI poor in India.
But there was also progress. Jharkhand made the biggest strides among all states in reducing multidimensional poverty, with Arunachal Pradesh, Bihar, Chhattisgarh, and Nagaland only slightly behind.
Across nearly every state, poor nutrition is the largest contributor to multidimensional poverty. Not having a household member with at least six years of education is the second largest contributor. Insufficient access to clean water and child mortality contribute least. Relatively fewer people living in poverty experience deprivations in school attendance – a significant gain.
- India’s MPI stood at 0.121 in 2016, half of what it was in 2006.
- States above the trend line have reduced poverty at a better rate than India’s average.
- Among districts, Alirajpur (0.402) and Jhabua (0.393) districts in Madhya Pradesh and Shrawasti (0.393) in Uttar Pradesh had the highest MPI. The worst 10 districts were in Madhya Pradesh, Uttar Pradesh and Bihar.
- The lowest MPI was in Kottayam district, Kerala — where the MPI stood at 0, indicating no deprivation. Thrissur and Ernakulam districts in Kerala had a marginal MPI of 0.001.
- In fact, the 10 districts with the lowest MPI were all in Kerala, except for Chennai in Mahe in Puducherry (0.001) and Chennai district in Tamil Nadu (0.05).
- The MPI has gone down across communities, but it is more than double among Scheduled Tribes compared to others.
Drawbacks of MPI :
The MPI has some drawbacks, due mainly to data constraints.
- First, the indicators may not reflect capabilities but instead reflect outputs (such as years of schooling) or inputs (such as cooking fuel).
- Second, the health data are relatively weak and overlook some groups’ deprivations, especially for nutrition, though the patterns that emerge are plausible and familiar.
- Third, in some cases careful judgments were needed to address missing data. But to be considered multi-dimensionally poor, households must be deprived in at least six standard of living indicators or in three standard of living indicators and one health or education indicator, or in two health or education indicators. This requirement makes the MPI less sensitive to minor inaccuracies.
- Fourth, intra-household inequalities may be severe, but these could not be reflected.
- Fifth, while the MPI goes well beyond a headcount ratio to include the intensity of poverty, it does not measure inequality among the poor, although decompositions by groups can be used to reveal group-based inequalities.
- Finally, the estimates presented here are based on publicly available data and cover various years between 2006 and 2016-17, which limits direct cross-country comparability.
Global MPI 2018 is a contribution to the implementation and monitoring of Sustainable Development Goal 1 which aims to end poverty in all its forms everywhere, and to the achievement of the Agenda’s ambition and fundamental principle of “Leaving No One Behind”. In addition, national measures of Multidimensional Poverty may directly serve the purpose of monitoring SDG Indicator 1.2.2 (proportion of men, women and children of all ages living in poverty in all its dimensions according to national definitions).