The Future of Multidimensional Poverty
‘To end poverty in all its forms everywhere by 2030’, declares the first Sustainable Development Goal mightily, inviting global participation in making this goal a reality. As discussed in the first part of this two-part article series, the world has developed multiple tools over these years to measure poverty in an increasingly nuanced manner so that we can combat it efficiently and effectively.
The question remains: are we there yet? Do we have the tools required to achieve this SDG, nearing 2023 rapidly as we are currently?
To measure and explore poverty around the world, the global MPI is annually updated to create an internationally comparable index of acute multidimensional poverty for over 100 countries in developing contexts. Their report for the year 2023 reveals that, over time, 25 countries have successfully halved their global MPI values, indicating that rapid progress is attainable, even at a large scale.
However, there are countries with national MPIs to measure their contextual poverty levels, and India is one of them.
India has developed its National Multidimensional Poverty Index (MPI) to estimate multiple and simultaneous deprivations at a household level across the macro dimensions of health, education, and living standards.
If the dimensions are the same, why should a national MPI exist?
Even when the dimensions and indicators are the same, state-level data will differentiate based on their context. For example, some Indian states with low groundwater levels may have a higher MPI on the dimension of living standards. This necessitates an area-specific intervention that helps them get access to water for drinking purposes. Such a policy emerges from the availability of state-level data, thereby necessitating a national MPI.
Despite India’s list of dimensions being similar to the global MPI index, there is a difference in the indicators for two of its dimensions, i.e., Health and Standard of Living. NITI Aayog released a progress review report in 2023, showing that the national MPI adds two indicators, namely Maternal Health and Bank accounts, in line with national priorities.
These MPI values have been computed using data from the 5th round of NFHS conducted in 2019-21, thereby reflecting the changes in MDP between the survey periods of NFHS-4 (2015-16) and NFHS-5 (2019-21).
India’s MPI value has more than halved over the period between these two health surveys, indicative of millions of people having moved out of extreme multidimensional poverty.
The numbers are encouraging, the progress is promising. However, the collected data reflects figures from before the COVID-19 pandemic hit the world. Data from the World Bank reveals that as of March 2023, 11 million more people live in extreme poverty. These numbers primarily reflect in regions from South Asia, the Middle East, and North Africa.
This raises an interesting question.
Even when MDI measures contextual poverty, is it a sustainable model that can accommodate so many new contexts that global emergencies create? While expansive, the list of indicators for the MDI also needs to be revisited frequently to keep up with the constantly evolving state of existence in this world.
Furthermore, measuring multidimensional poverty is heavily dependent on data availability, which is commonly seen as difficult for developing countries to acquire. For this model to truly reflect the many dimensions of poverty, robust data systems need to be strengthened and implemented to capture real-time situations. Only then can we answer questions about the validity and applicability of models such as these and determine the next best step to achieve the goal we are collectively working towards—to end poverty in all its form everywhere.
Aishwarya Bhatia, Sambodhi
