Received this image below from a friend over WhatsApp earlier today. It is a district-wise graphical representation of multidimensional poverty in Bihar, created by the good folks at India in Pixels. The raw data comes from the National Multidimensional Poverty Index (MPI): A Progress Review 2023 (based on NFHS-5), put together by the NITI Aayog.
Source: https://twitter.com/indiainpixels/status/1703472456844058658
What is multidimensional poverty?
This from the Executive Summary section of the NITI Aayog report: “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. It complements income poverty measurements because it measures and compares deprivations directly.”
According to B.V.R. Subrahmanyam, CEO, NITI Aayog, “India’s National Multidimensional Poverty Index (MPI) is the first-of-its-kind index which estimates multiple and simultaneous deprivations at a household level across the three macro dimensions of health, education and living standards. Accordingly, this index rigorously measures national and sub-national performance to facilitate policy actions.”
Is there no hope for Bihar?
‘Bihar’ and ‘poverty’ have become kind of synonymous. As the figure above shows, one in every three Bihari is multidimensionally poor. This is more than twice the number for average Indian, where less than one in six Indians are multidimensionally poor. But there may be a silver lining for Bihar that is hiding behind this aggregate snapshot.
The report is interesting in that it captures the changes in multidimensional poverty between the survey periods of NFHS-4 (2015-16) and NFHS-5 (2019-21). If one compares the changes in multidimensional poverty over the two survey periods, there may be some hope yet for Bihar. It shows that the percentage of multidimensionally poor people in each district has declined, some more so than others.
The two figures below from pages 78-79 of the NITI Aayog report shows the district-wise decline over the two NFHS survey rounds.
Here now is the district-wise decline.
Four of the bottom six districts in terms of least decline in poverty are from Mithila/Koshi region in the North-East of Bihar. These districts of Saharsa, Araria, Purnia, and Supaul, have shown least decline in poverty, and thereby continue to be the most multidimensionally poor districts.
One would assume that since these districts are so extremely poor, on the margin they should be able to show larger improvements. Instead, they continue to lag behind others. This tells me that something unusual is going on here.
Why are some districts able to show much higher improvements compared to others? All aspects of this trend needs further examination.