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What is Multidimensional Poverty?

  • IAS NEXT, Lucknow
  • 09, Dec 2021
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The Resolution of the United Nations General Assembly on 25 September 2015 established the 17 . SDG 1 in its entirety

(“End poverty in all its forms everywhere”) is multidimensional in nature and definition. While target 1.1 seeks to eradicate extreme poverty –measured as people living on less than $1.25 a day (subsequently increased to $1.90/day), target 1.2 aims at reducing multidimensional poverty, as defined by national definitions, by half.

In News: NITI Aayog has recently released the state-wise National Multidimensional Poverty Index or MPI in line with the global index released by the United Nations each year.

According to Global MPI 2021, India’s rank is 66 out of 109 countries. 

The Global MPI 

  • The Global MPI is part of the government’s decision to monitor the performance of the country on 29 select global indices.
  • It is an international measure of multidimensional poverty covering 107 developing countries. 
  • It was first developed in 2010 by Oxford Poverty and Human Development Initiative and United Nations Development Programme.
  • It is released at the High-Level Political Forum (HLPF) on Sustainable Development of the United Nations in July, every year.
  • The dimensions of poverty range from deprivations of health facilities, education and living standards.
  • It is computed by scoring each surveyed household on 10 parameters based on -nutrition, child mortality, years of schooling, school attendance, cooking fuel, sanitation, drinking water, electricity, housing and household assets.

National Multidimensional Poverty Index (MPI)

A national Multidimensional Poverty Index for India will 

  • Facilitate formulation of sectoral policies and targeted interventions which contribute towards ensuring that “no one is left behind”. 
  • This baseline National MPI Report and Dashboard is a landmark first step in bringing multidimensional poverty as a tool to the policy table at the national and subnational levels in India. 
  • Enable estimation of poverty not only at the level of the States but also for all the 700 plus districts (600 plus in 2015-16, 700 plus in 2019-20) across twelve indicators, capture simultaneous deprivations and indicator-wise contribution to poverty
  • It is expected that the report will play an instrumental role in sensitizing government, researchers, civil society, citizens, and other stakeholders on the need for and importance of MPI as a powerful policy instrument. 
  • At the higher levels, MPI could be used as an input to the design of development policies schemes, budget allocations, and target setting. 
  • At the lower levels, for instance, of that of district, MPI could decide priority of execution and delivery. With every revision of MPI based on new survey data, actions could be redesigned to shift focus to those who need it the most. 

NITI Aayog will play a key role in charting this path and supporting the stakeholders in their actions, through the following approaches.

  • The National MPI Project is the first attempt in years to define poverty measures and is aimed at deconstructing the Global MPI and creating a globally aligned and yet customised India MPI. 
  • The MPI is based on three dimensions — health, education, and standard of living — with each having a weighting of one-third in the index. 
  • The household micro data collected at the unit-level for the NFHS serves as the basis of the computation of National MPI. This unit level micro data collected in 2015-16 has been used in the current MPI report to derive an idea of baseline multidimensional poverty i.e. where the country was with respect to MPI before full-scale roll out of the above mentioned schemes. 
  • The MPI identifies 25.01 per cent of the population as multidimensionally poor. 
  • The progress of the country with respect to this baseline will be measured using the NFHS-5 data collected in 2019-20.

MPI Coordination Committee (MPICC): The inter-ministerial coordination committee constituted under NITI Aayog included Ministries and departments pertaining to areas such as health, education, nutrition, rural development, drinking water, sanitation, electricity, and urban development, among others. It also included experts from Ministry of Statistics and Programme Implementation and the publishing agencies – OPHI and UNDP.

Engagement with States: Building consensus on MPI at the subnational level State and Union Governments are pivotal stakeholders which make up the institutional bulwark of the country. 

  • With 36 States and Union Territories and over 700 districts –subnational entities represent the myriad socio-political, geographical and economic diversity in the country. 
  • For a public policy tool such as the national MPI to fully realise its potential, utilisation of its results and findings by State and UT governments is crucial. 
  • Simultaneously, the success of identification and implementation of reform areas and actions to improve the lives of households and individuals, would significantly be influenced by the level of adoption at the level of States. 
  • Therefore, building consensus on the need to create a national MPI and the model thereof, developing capacities, understanding and appetite for this novel policy tool, with our primary stakeholders, ie., the State governments and policy makers and implementers at the sub-national level, was felt to be imperative at the stage of MPI project design.

The Calculation: The MPI uses the globally accepted methodology developed by the Oxford Poverty and Human Development Initiative (OPHI) and the United Nations Development Programme (UNDP). The dimensions of the index have proven to help identify and achieve targeted policy interventions. The index is calculated by first setting the deprivation cut-offs for each indicator, i.e., the level of achievement considered normatively sufficient for an individual to be considered not deprived in an indicator. For example, the individual has completed at least six years of schooling. Such a cut off would be applied to determine whether the individual is deprived in each indicator. Weights are added to each indicator and a composite metric is then used to calculate the index.

Some results

  • Bihar has the highest proportion of people, at 51.91 per cent of the state’s population, who are multidimensionally poor, followed by Jharkhand at 42.16 per cent and Uttar Pradesh at 37.79 per cent.
  • Bihar also has the highest number of malnourished people followed by Jharkhand, Madhya Pradesh, Uttar Pradesh, and Chhattisgarh. 
  • Kerala, Goa, and Sikkim have the lowest percentage of population being multidimensionally poor at 0.71 per cent, 3.76 per cent and 3.82 per cent, respectively.
  • Among the Union Territories (UTs), Dadra and Nagar Haveli (27.36 per cent), Jammu & Kashmir, and Ladakh (12.58), Daman & Diu (6.82 per cent) and Chandigarh (5.97 per cent), have emerged as the poorest UTs in India.