In Retrospect

Partial abatement

Positive strides towards reducing multidimensional poverty, as indicated by recent NITI Aayog and UNDP reports, are reassuring, but concentration of a large number of poor persons in selected pockets could exacerbate regional imbalances

Partial abatement

On July 17, 2023, National Institution for Transforming India (NITI) Aayog, formed in 2015, in place of the erstwhile Planning Commission, published the ‘National Multidimensional Poverty Index: A Progress Review 2023’. It presents the second edition of the national multidimensional poverty index (MPI) and is a follow-up to the Baseline Report published in November 2021. The report provides multidimensional poverty estimates for India’s 36 States & Union Territories, along with 707 administrative districts across 12 indicators of the national MPI. These estimates have been computed using data from the 5th round of the National Family Health Survey (NFHS-5) conducted in 2019-21, employing the same methodology as the baseline report. This edition also presents the changes in multidimensional poverty between the survey periods of NFHS-4 (2015-16) and NFHS-5 (2019-21). The baseline report of India’s first-ever national MPI measure was based on the reference period of 2015-16 of the National Family Health Survey (NFHS).

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. It captures overlapping deprivations in health, education, and living standards, and complements income poverty measurements as it measures and compares deprivations directly.

The latest update of the Global Multidimensional Poverty Index (MPI) with estimates for 110 countries was released in July 2023 by the United Nations Development Programme (UNDP) and the Oxford Poverty and Human Development Initiative (OPHI) at the University of Oxford. The report demonstrates that poverty reduction is achievable. However, the lack of comprehensive data over the COVID-19 pandemic poses challenges in assessing immediate prospects.


Historically, poverty estimation has predominantly relied on income as the sole indicator. However, the Global Multidimensional Poverty Index (MPI), based on the Alkire-Foster (AF) methodology, captures overlapping deprivations in health, education, and living standards.

India’s national MPI measure uses the globally accepted methodology developed by the Oxford Poverty and Human Development Initiative (OPHI) and the United Nations Development Programme (UNDP), which have been key partners in ensuring the public policy utility and technical rigor of the Index. Importantly, as a measure of multidimensional poverty, it captures multiple and simultaneous deprivations faced by households.

The national MPI has been constructed by utilizing twelve key components that cover areas such as health and nutrition, education, and the standard of living. Like the global MPI, India’s national MPI has three equally weighted dimensions – Health, Education, and Standard of living – which are represented by 12 indicators: Refer to Table 1.

The indices of the national MPI comprise:

v Headcount ratio (H): How many are poor — proportion of multi-dimensionally poor in the population, which is arrived at by dividing the number of multi-dimensionally poor persons by the total population;

v Intensity of poverty (A): How poor are the poor - the average proportion of deprivations experienced by multi-dimensionally poor individuals.

MPI value is arrived at by multiplying the headcount ratio (H) and the intensity of poverty (A): MPI = HxA. An individual is considered MPI poor if their deprivation score (MPI) equals or exceeds the poverty cut-off of >= 0.3333 (33.33 per cent).

Few major findings of the Global Multidimensional Poverty Index (MPI)

v The report, while analysing the trends from 2000 to 2022 — focusing on 81 countries with comparable data over time — reveals that 25 countries successfully halved their global MPI values within 15 years. These include Cambodia, China, Congo, Honduras, India, Indonesia, Morocco, Serbia, and Vietnam.

v Despite these encouraging trends, the lack of

post-pandemic data for most of the 110 countries covered by the global MPI restricts researchers’ understanding of the pandemic’s effects on poverty.

v According to the 2023 release, 1.1 billion out of 6.1 billion people (just over 18 per cent) live in acute multidimensional poverty across 110 countries. Sub-Saharan Africa (534 million) and South Asia (389 million) are home to approximately five out of every six poor people.

v Nearly two-thirds of all poor people (730 million people) live in middle-income countries, making action in these countries vital for reducing global poverty. Although low-income countries constitute only 10 per cent of

the population included in

the MPI, these are where 35 per cent of all poor people reside.

v Children under 18 years old account for half of MPI-poor people (566 million). The poverty rate among children is 27.7 per cent, while among adults it is 13.4 per cent.

v Poverty predominantly affects rural areas, with 84 per cent of all poor people living in rural areas. Rural areas are poorer than urban areas across all regions of the world.

Few major findings of the National Multidimensional Poverty Index (MPI)

Within six days of the release of the global report, the Indian government released the national MDPI.

v The MPI estimates highlight a near-halving of India’s national MPI value and a decline in the proportion of the population in multidimensional poverty from 24.85 per cent to 14.96 per cent between 2015-16 and 2019-21. This reduction of 9.89 percentage points in multidimensional poverty indicates that, at the level of the projected population in 2021, about 135.5 million persons have exited poverty between 2015-16 and 2019-21. Refer to Table 2.

v A nearly 15 per cent headcount ratio indicates that nearly 210 million citizens of India were multi-dimensionally poor and they live in acute multidimensional deprivation of basic necessities of their living. This huge number (210 million) of poor people in India roughly equals the total numbers of citizens of Germany (83.4 million), the UK (67.4 million), and France (65.6 million) put together.

v Disparities in multidimensional poverty still exist between rural and urban areas, with the proportion of multidimensional poor in 2019-21 being 19.28 per cent in rural areas compared to 5.27 per cent in urban areas.

v Table 2 also reveals that rural areas saw a faster reduction in their MPI value, compared to urban areas. The incidence of poverty fell

from 32.59 per cent to 19.28 per cent in rural areas, compared to a decline from 8.65 per cent to 5.27 per cent in urban areas between 2015-16 and 2019-21

v Table 3 reveals that Bihar, the state with the highest MPI value in NFHS-4 (2015-16), saw the fastest reduction in MPI value in absolute terms, with the proportion of multidimensional poor reducing

from 51.89 per cent to 33.76 per cent in 2019-21. The next fastest reduction in the MPI value was seen in Madhya Pradesh and Uttar Pradesh. The proportion of multidimensional poor in Madhya Pradesh and Uttar Pradesh in NFHS-5 (2019-21) are 20.63 per cent and 22.93 per cent respectively.

v Table 3 also flags a very disturbing trend of acute MDP in a few specific regions of India. In the said table, 14 states still have over 10 per cent MDP people.

v Four out of fourteen states — namely, Bihar, Jharkhand, Odisha, and West Bengal — fall under the East zone as identified by the Reserve Bank of India, (refer to Table 4)

v Three states, namely UP, MP, and Chhattisgarh, come under the Central zone.

v Five northeastern states — Meghalaya, Assam, Tripura, Nagaland, and Arunachal Pradesh — fall under Northeastern circle

v Only one state, Gujarat, falls under the Western Circle.

v Most of the states which still suffer from high incidences of MDP (refer to Table 3), are concentrated only in three geographical circles — North eastern region, Eastern region, and central region.

v A cursory look at Table 4 reveals that the above three zones of India, where the incidence of MDP is very high, have very low credit-deposit ratios. Discrepancies in providing credit to these relatively poor states are very wide. It appears that the ‘vicious circle of poverty’ has not

been disturbed much – at least by infusing more banking capital into the backward regions. The major gainers of this systematic siphoning of local deposits of these three regions are the South, West, and North zone.


This year’s Global report has flagged a few positive initiatives in reducing the basic deprivation of millions of people in Africa, South Asia, and other regions of the country. However, the historically vulnerable regions have still remained poverty-stricken.

The Hindi belt of India, which for years has been suffering from a high incidence of poverty, still tops the list in Table 3

Higher concentration of MDP in a few zones where banks are reluctant to provide them with adequate Credit may have led to serious regional

imbalances. It appears that the deprived regions have become the internal colony of modern India.

Views expressed are personal

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