The Covid-19 pandemic, which pushed many countries to bring their economies to a grinding halt, has had a deep impact on the Indian economy. According to the International Labour Organisation (ILO) in 2020, 400 million workers in India’s informal economy are at risk of falling deeper into poverty due to the pandemic. With a share of almost 90 percent of people working in the informal economy in India, it is integral to enable paths to prosperity for those most vulnerable to economic shocks, especially in the midst of a global downturn and rising inequality.

Sustainable Development Goal (SDG) 1 aims to end poverty in all its forms everywhere. With a decade to go before the 2030 deadline for its achievement, it becomes important to assess where India stands, and the ways in which the Covid-19 pandemic may have affected our trajectory towards this ambitious agenda.

Figure: Sustainable Development Goal 1, United Nations Development Programme. Image sourced from

Measuring Poverty: Global Experience and Indian Context

In order to enable long term and sustainable paths to prosperity for the country’s poor, we need to redefine measurement. Countries’ poverty estimates can be absolute or relative in nature, or both. Most developing countries measure their poverty using an absolute threshold, within which a daily minimum expenditure is calculated for sustenance. The World Bank’s international day poverty rate of $1.90 per day (in 2020) helps measure trends across time and enable cross country comparisons.

Most developed countries have seen a shift from absolute to relative estimates with increases in prosperity stemming from the understanding that the experience of poverty has a social dimension. As a result, countries in western Europe and other rich countries, including the UK estimate a relative poverty line. Here, poverty is treated as a proportion, 50-60% of the median per capita yearly income.

India’s experience in the measurement and alleviation of poverty has been shaped by the informal nature of work and calorie requirements in rural and urban areas.  At present, levels of poverty are estimated on the basis of the Tendulkar Committee’s methodology within which the poverty line is expressed in terms of Monthly Per Capita Expenditure (MPCE) based on a Mixed Reference Period. The data for this is based on consumer expenditure surveys conducted by the National Statistical Office (NSO) on a quinquennial basis.

India has a plethora of pro-poor schemes ranging from food distribution, public works and employment guarantees, health insurance, social security, education, skill development and housing. The extent to which these schemes come together to alleviate poverty in the short and long term remains unclear, and the impact they exercise on India’s poorest amidst the pandemic era is a challenge we must face with urgency. There are several steps we can take in order to optimise the gains of the past, and set the stage for an inclusive India.

Fostering Innovations in Poverty Measurement

While an absolute headcount remains essential to tracking overall progress over time, real time progress could also be better augmented when schemes know which populations are deprived of one or overlapping needs. A significant step taken in this direction, in line with the first SDG, has been the recent decision of the government to measure country progress on 21 global indices, of which the Multidimensional Poverty Index (MPI) published by the UNDP and the Oxford Poverty and Human Development Initiative (OPHI) since 2010  is particularly relevant for the future of India’s welfare programs.

The NITI Aayog is responsible for leveraging monitoring mechanisms related to the MPI in order to drive reforms for poverty reduction, improve last-mile delivery of government schemes, and therefore enable the long-term localization of SDGs at the district and block level. This new development has the potential to change India’s human development story.

The MPI aims to measure the lived reality of peoples’ experiences and the forms of deprivations they face. Each person’s deprivations are measured across ten indicators, which are spread out across the equally weighted sectors of Health, Education and Standard of Living. It complements the international monetary poverty rate by showing the nature and extent of overlapping deprivations for each person. People identified to be multidimensionally poor are often deprived in more than one SDG and in 2020, 1.3 billion people across the world were multidimensionally poor (out of 5.9 billion covered), out of these 98.8% are deprived in at least three indicators simultaneously.

The MPI could help allow us to identify pockets with the greatest distance from government outreach across programmes, with district level implications on targeted outreach for inclusion. For example, districts with a high proportion of households with compounded deprivations can be identified as priority districts for poverty alleviation efforts. For example, districts with a high percentage of households with malnutrition, unsafe drinking water and absence of electrification could be flagged.

In addition to focusing on the material aspects of poverty, it is also important to acknowledge the cognitive burden of poverty. A study by Princeton published in Science magazine suggests that being poor can keep people from concentrating on the very avenues that lead them out of poverty. In a series of experiments conducted across geographies, it concludes that a person preoccupied with money problems can exhibit a drop in cognitive function similar to a 13-point dip in IQ, or the loss of an entire night’s sleep. This has implications on how pro poor policies can be designed to remove the red tape of access and be more forgiving of errors such as absences or delays.

Localising Data for Evidence-Based Outreach

Creating a culture of data based governance at the district and block level would achieve long term solutions for prosperity . Drawing on the national SDG dashboard, a national dashboard measuring disaggregated monetary and multidimensional poverty would help isolate geographical pockets at the level of administrative units that require targeted intervention in the domains of health, education, standard of living or combinations of deprivations. Formulating policies for inclusion on the basis of existing gaps in key areas would empower district administrations with the correct evidence for outreach efforts. An important accompaniment to data driven policy would be capacity development of block and district level officers to on-board them as interested and driven stakeholders in the process.

National Coalition on What Works & How.

In addition to a culture of localised and bottom-up data-based outreach, creating a central pool of evidence on ‘what works’ to aid long term prosperity could help local governments learn from each other. Best practices can be shared and uploaded on repositories like the India Knowledge Hub and Vikaspedia maintained by the government. In addition to local best practices, national-level strategies could also be informed by critical evidence generated through the years and by building partnerships with NGOs, academics, and civil society. Capitalising on the things we know remains important, in addition to creating evidence on what may work through pilots. There is bludgeoning evidence from Kenya, Madhya Pradesh, Alaska, Iran , Brazil, and other parts of the world on the case for cash transfers or a universal basic income to help people make critical decisions that enable them to stand on their own feet in the long term, with positive externalities on health, education, and employment. In response to the pandemic, Spain also began the largest experiment on a UBI for 850,000 households in 2020. Clubbing data on what works, and starting scalable pilots from the bottom up would help create local and long term paths to change.

The time to foster a critical enquiry into the measurement of poverty and sustainable paths to prosperity is now. This will have implications on India’s human development story, and the extent to which we are able to do justice to our demographic dividend in the wake of the pandemic.

Anmol Narain

Anmol provides policy research inputs at Niti Aayog and the Cabinet Secretariat, Government of India. She is a young professional with four years of experience in the development sector, and interest in multidimensional poverty, shared prosperity, impact evaluation, and behavioural science.

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