India’s progress against multidimensional poverty

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n Francine Pickup
There’s been some good news for India over the last month. Three different robust, credible measures of poverty have recorded a dramatic reduction in the incidence of poverty in India. The most straightforward of these, the World Bank’s estimate of the number of people living on less than $1.90 per day on a purchasing power parity basis (the international poverty line), found that poverty declined from 21.6% to an estimated 13.4% between 2011 and 2015. The 2018 update to the United Nations Development Programme’s (UNDP’s) human development index (HDI) said that between 1990 and 2017, India’s HDI value has increased by nearly 50%—emblematic of the country’s remarkable achievement in lifting millions out of poverty. And, according to perhaps the most comprehensive measure of poverty, the multidimensional poverty index (MPI) released by UNDP and the Oxford Poverty and Human Development Initiative (OPHI), India has lifted 271 million people out of multi-dimensional poverty in the 10 years between 2005-06 and 2015-16. Even though traditionally marginalized population groups such as rural populations, scheduled castes and tribes, Muslims, and young children remained the poorest in 2015-16, they were also “catching up”—that is, they also showed the largest reduction in MPI.
This is, of course, extremely encouraging news, not just for India but also the rest of the world. India’s success is pivotal for the realization of the ambitious sustainable development goals (SDGs) that aim to leave no one behind. These reports are a sure sign that India is heading in the right direction, even if there is still some way to go before poverty is eliminated from the country.
India’s performance on the MPI is truly remarkable because, unlike the World Bank’s $1.90 numbers, the MPI is not limited to an income-based measure of poverty. Instead, the MPI complements income measures of poverty and captures the multiple, overlapping disadvantages poor people can face—such as poor sanitation, malnutrition, poor quality of housing and lack of education. This is important because overlapping deprivations undermine people’s capacity to pursue a life trajectory of their choosing and chart a course out of poverty. To use an example, the MPI identifies Sylhet as Bangladesh’s poorest region, with 62% of its population multidimensionally poor. But Sylhet ranks as one of the least poor regions, with 16% poor, using monetary measures. The reason is that in Sylhet, households receive high remittances, boosting incomes—but these remittances do not translate into better schooling or healthcare. So, while multidimensional and income measures of poverty capture different and sometimes divergent experiences, using them in a complementary manner provides a more complete view of poverty and better insights for policy action.
For India, the MPI used data from the third and fourth rounds of the National Family Health Survey (NFHS) to measure multidimensional poverty across 640 districts. It is the first large-scale index disaggregated to both state and district levels, by rural and urban areas, age groups, scheduled castes and tribes, and religious groups. This means that for the first time, granular information about who is poor and where they live is available to policymakers. The fifth NFHS, planned for 2018-19, would add a further data point and offer district-level trend analysis. Much has changed in the decade between 2005-06 and 2015-16. Trends from more updated data could reveal an even more encouraging present. But there are other reasons why officials should factor the MPI into their decision-making. When the poverty problem is framed simply in monetary terms, so will the solutions. During the launch of the 2018 global MPI report, Nobel laureate Angus Deaton pointed out that, “In the real world, deprivations in different areas are positively correlated with one another. It’s often—perhaps usually—the same people who lack resources who also lack education, or the sanitation and clean water that protects them against infectious disease…we have to have data that allow us to look at all of the dimensions for each and every person at the same time.” These intersections of deprivation, or, as the report calls it, the “coupling” of disadvantages between different sources of deprivation, add critically important dimensions to understanding poverty, and in directing public policy to tackle it.
In that sense, the MPI is a powerful tool in our arsenal to combat poverty and achieve the SDGs. Its depth of insight can help policymakers make evidence-based decisions by identifying trends and intervention hotspots, which means officials will be able to direct public resources more effectively.
Francine Pickup is country director, UNDP India. Views expressed are personal.

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