Ending Poverty: An Assessment of NITI Aayog’s Multidimensional Poverty Index

“The test of our progress is not whether we add more to the abundance of those who have much; it is whether we provide enough for those who have too little’’ is the quote by Franklin D. Roosevelt which rightly shows the direction of efforts that depicts the right path of poverty eradication. Poverty is not just about how much we have as an individual but how much we possess as a society. Hence, poverty should be seen as a multidimensional issue that shows the gap between efficacy and sufficiency of our economic growth. 

The Resolution of the United Nations General Assembly on 25 September 2015 established the 17 Sustainable Development Goals (SDG). SDG 1 in its entirety – “End poverty in all its forms everywhere”- is multidimensional in nature and definition. The Multidimensional Poverty Index (MPI) has been used by the United Nations Development Programme in its flagship Human Development Report since 2010 and is the most widely employed non-monetary poverty index in the world (Godinot & Walker, 2020). It captures overlapping deprivations in health, education and living standards.

Multidimensional Poverty Index: Genesis & Evolution

The theoretical underpinnings of a non-monetary approach towards poverty and instead, as a multidimensional phenomenon is drawn from the capability approach (Sen 1979, 1987, 1999). The capability approach suggests that functionings and capabilities are two integral parts of a person’s quality of life and wellbeing where functionings are the “beings and doings” that they value and have reason to value –such as being healthy and nourished; and capabilities reflect the freedom that they have in achieving valuable functionings. Therefore, to arrive at the conclusion that a household or individual is deprived of basic capabilities, it is pertinent to examine and consider multiple dimensions of wellbeing. This is of significance to policy formulation and targeted interventions in the context of intra-country or intra-region heterogeneity in development. the Multidimensional Poverty Index, based on the Alkire-Foster method, employs an adjusted headcount ratio (MPI score) which is arrived at by multiplying the headcount ratio with the average deprivation among the MPI poor (Alkire & Foster, Counting and Multidimensional Poverty Measurement, 2011). In 2010, this measure of multidimensional poverty replaced the Human Poverty Index (HPI) in UNDP’s Human Development Report. It draws from the capability approach by including multiple dimensions of poverty across the dimensions of health, education and living standards, and examines the “fundamental objective features” which affect the poor. 

Poverty Eradication in India: Past & Present

The history of poverty estimation in India dates back to as early as 1901 when Dadabhai Naoroji estimated poverty in the country based on the cost of a subsistence diet. In 1938, the National Planning Committee suggested a poverty line estimation based on living standards followed by the authors of the Bombay Plan in 1944. Addressing and ending poverty has been part of the national agenda since independence. Various committees, working groups and scholars including the working group of 1962, Dandekar and Rath in 1971 and the Y.K. Alagh taskforce in 1979 were engaged in estimating the headline statistic of poverty to inform public policy. Similarly, the Expert Groups under Lakdawala (1993) and Tendulkar (2009) and the Rangarajan Committee (2014) undertook the exercise of estimating monetary poverty.

The recent national MPI statistic developed by NITI Aayog is tailored to the national priorities and therefore, they have chosen their own set of dimensions, indicators, weights, and cut-offs. National MPIs are disaggregated by subnational regions, urban or rural areas, age, and other factors. They are also always reported with the indicator-wise deconstruction and breakdown. These details can guide and monitor national policies such as budget allocation, targeting specific interventions, and policy coordination across sectors. 

Within the larger framework of MPI as Alkire – Foster method, NITI Aayog has come out with an illustrative plan to measure multidimensionally poor people in India. This method contains two distinct parts: a) Identification & b) Aggregation. 

The steps of identification are as follows: 

  1. Determine the set of indicators to be used in the MPI and group thematically similar indicators into dimensions.
  2. Set the deprivation cut-offs for each indicator, i.e., the level of achievement considered normatively sufficient in order for an individual to be considered not deprived in an indicator. E.g., the individual has completed at least six years of schooling.
  3. Apply the cut-off and determine whether the individual is deprived in each indicator.
  4. Select weights to be applied to each indicator such that the sum of the weights for all indicators adds up to 1. Optionally, the weights of the indicators could be such that the weight attributable to each dimension (i.e., the sum of the weights of the indicators in that dimension) is the same.
  5. Calculate the weighted sum of deprivations for each individual. This is known as their deprivation score.
  6. Apply the second order cut-off, i.e., the proportion of weighted deprivations that an individual needs to experience to be identified as multidimensionally poor. India’s national MPI follows the second order cut-off of 33.33 percent used in the global MPI measure.

While the aggregation steps are:

  1. Determine the proportion of individuals identified as multidimensionally poor in the population. This is known as the headcount ratio (H) of the MPI or the incidence of poverty. The headcount ratio broadly explains ‘how many are poor’.
  2. Determine the average share of weighted indicators in which multidimensionally poor individuals are deprived i.e., add the deprivation scores of the poor and divide it by the total number of poor individuals. This is known as the intensity of poverty (A) in the MPI or the breadth of poverty, which broadly explains ‘how poor are the poor’.
  3. Compute the MPI score (M0) as the product of the partial indices of Headcount Ratio and Intensity.

Based on this methodology, NITI Aayog has computed MPI for all States and UTs in India by using the database of National Family Health Survey, 2015-16. This computation gives the following elaborative picture of Multidimensional Poverty in India: 

The colour represents the MPI score of a State/UT. The colour moves from green, through yellow, to red as the MPI score increases. Green represents areas with the lowest MPI scores while red represents areas with the highest MPI scores.

The decision to conduct subsequent National Family Health Surveys once in every three years will increase the frequency of MPI revisions and reduce the lag in the reflection of development outcomes in poverty estimates. A higher frequency of NFHS will also address the issue of stagnation of India’s global rankings in MPI and reflect the improvements adequately.

To sum up, the recent action plan devised by NITI Aayog is comprehensive and it adopts a bottom to top approach in defining national priorities for economic growth. It strives to ensure that the prime motto of our economic development ‘no one is left behind’ or ‘Antyodaya’ is served.  People’s participation at all levels of development will be the key in changing the landscape of poverty eradication in India. National MPI computation will play a key role in this. 

References:

  1. https://www.niti.gov.in/sites/default/files/2021-11/National_MPI_India-11242021.pdf
  2. Explainer Note on National Multidimensional Poverty Index, National Multidimensional Poverty Index: Baseline Report based on NFHS-4 (2015-16)

https://pib.gov.in/PressReleasePage.aspx?PRID=1775489

  1. MPI in India: A Case Study, Global MPI 2018, OPHI. 

Author’s Information:

Ms. Aparna Kulkarni

Asst. Professor, Department of Economics,

St. Xavier’s college, Mumbai. 

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