To capture poverty beyond mere income thresholds, alternative frameworks such as the Multidimensional Poverty Index (MPI) are often used.
Created by the Oxford Poverty and Human Development Initiative (OPHI) and the United Nations Development Programme (UNDP), it offers a broader understanding of poverty by assessing it across three dimensions: health, education, and living standards.
The MPI uses ten indicators within these dimensions to assess both the incidence of poverty (how many people are affected) and its intensity (the average number of deprivations faced by the poor). For example, in the health dimension, it considers child mortality and nutrition. In education, it evaluates school attendance and years of schooling. For living standards, it includes indicators such as access to clean water, sanitation, electricity, and adequate housing. Each indicator is assessed using a structured framework to determine if a household meets the criteria for being multidimensionally poor. This framework enables policymakers and researchers alike to pinpoint where deprivations are most severe, guiding targeted interventions.
MPI adds to our understanding of poverty by extending the measure beyond a simple consumption-income metric to various dimensions along which life can experience deprivations. The idea builds on Amartya Sen’s philosophy of the ‘Capability Approach,’ which views poverty as more than just lack of income – it is about the deprivation of essential capabilities.
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These capabilities represent the substantive freedoms individuals have to achieve for the kind of lives that they value. This includes being healthy, having access to quality education, and engaging meaningfully in community and economic activities.
By focusing on what people can ‘do’ and ‘be’, rather than focusing solely on material resources, the Capability Approach prioritises what people can achieve (their functionings) and the opportunities they have to achieve these goals (their capabilities).
The Niti Aayog approach
Coming to India, the Niti Aayog, has adopted a version of the MPI to highlight progress in poverty alleviation under the incumbent government. They retained the original indicators and added two more: bank account ownership and maternal health.
Their report revealed a significant decline in poverty across India, with the proportion of multidimensionally poor individuals reducing from 24.85% in 2015-16 to 14.96% in 2019-21. This decline was presented as evidence of the Union government’s effective efforts in addressing poverty.
However, this method has faced significant criticism regarding its choice of indicators, thresholds and methodology. Adding to this, we aim to argue that when countries adopt this metric, they should tailor it according to the realities of their country and there should be a particular focus on including measures that capture their access to positive freedoms – indicators that will help build their capabilities rather than just focusing on final outcomes.
Based on this, we argue that access to health insurance and internet access paired with smartphone ownership should be included in MPI.
Life on the teetering edge
An increasing prevalence of non-communicable diseases has rendered health spending catastrophic for a significant portion of the population in India.
Out-of-pocket expenditure (OOPE), which stands for direct payments made by households for healthcare services without reimbursement from any insurance or government programmes, constitute a staggering 49.8% of total health expenditures in India.
A study by Nanda et al., analysing the latest round of the National Sample Survey (2017-18), reveals that 49% of households requiring hospitalisation or outpatient care incurred medical expenses that significantly exceeded their financial capacity to bear these costs. Due to these expenses, about 15% of 113,823 households surveyed were pushed below the poverty line. The study also noted that the poverty headcount ratio was notably higher among households seeking care from private facilities compared to public ones.
Indian households rely heavily on their income or savings as a means to financing OOPE incurred, with around 83-85% covering hospitalisation or outpatient care costs through these means. Other resources used include borrowings, selling physical assets (what is termed as distress selling) and leveraging personal connections (Figure 1).
This heavy reliance on alternative means to raise healthcare funds underscores the financial vulnerability of low-income households. This burden not only limits their access to healthcare but also forces difficult trade-offs, like cutting down on nutrition, foregoing children’s education, or even sacrificing long-term investments like spending on fertilisers and migration for better livelihoods, leading to conditions of deprivation.
This encapsulates the dynamic nature of poverty: that of vulnerability. Heath shocks can naturally occur to any household independent of them being poor or rich, beneficiary or non-beneficiary of any targeted government policies. Hence, it’s just a matter of the occurrence of a disease or an accident that can drag households, otherwise showing marginal improvements in poverty indicators at the time of surveys, into severe economic impoverishment thereafter.
Figure 1: Financing the OOPE, the share of various sources of financing. Photo: Health Policy and Planning
In light of the above, we need an indicator or a kind of measurement present in most public survey data to quantify the levels of household economic vulnerability to such health shocks. Access to a health insurance programme can be one such indicator that offers the necessary padding against a health situation.
Mahapatro et al. provide empirical evidence in their paper showing households with health insurance – whether government or private – incur lower OOPE compared to uninsured households (Figure 2). Not surprisingly, insurance coverage was only limited to 9.55% of the BPL population for the reference study.
Therefore, access to health insurance in any form is a critical indicator for understanding the impact of OOPE financial deprivation on households. It acts as an enabler of freedom – offering households the capacity to pursue more stable lives. By integrating health insurance into the MPI, we can capture these overlapping deprivations, which emphasises the systemic barriers that impede both the health and financial security of households.
Figure 2: Depicts that among the poorest households (Q1), the mean OOPE was Rs. 674 for those with government insurance, Rs. 684 for those with private insurance, and Rs. 766 for the uninsured. This pattern persists across other economic groups. Photo: Science Direct
However, enrollment in such schemes comes with substantial limitations. For instance, government-backed programmes like the Ayushman Bharat Scheme primarily cover inpatient treatments, excluding outpatient care, which constitutes 40-80% of healthcare expenditures in India. Additionally, many individuals lack access to quality empanelled hospitals, and even hospitals themselves report delayed reimbursements under these schemes.
Digital access
Access to the internet has become a fundamental necessity in today’s interconnected world, enabling individuals to participate in digital education, economic activities, and healthcare services.
Studies have highlighted that increased internet penetration significantly reduces poverty by empowering individuals with tools for economic and social mobility by looking at data from 86 countries collected between 2005 and 2020.
These studies have pointed out that internet access enabled individuals to have access to jobs in the gig economy and other freelancing opportunities, hence pushing people out of agriculture and contributing to structural transformation.
However, internet access alone is insufficient if people lack the devices to use it, such as mobile phones or computers. Assets like these, combined with internet connectivity, expand essential capabilities, allowing individuals to engage with digital economies, pursue educational opportunities, and access telemedicine services.
Incorporating an indicator that captures both internet access and compatible devices into the MPI goes with Sen’s Capabilities Approach, where the core focus is to improve access to tools which people use to live a fulfilling life. Without these assets, individuals are deprived of meaningful connectivity, limiting their ability to achieve higher living standards. It accords individuals with ‘positive freedom’ allowing them to exercise their agency effectively.
Therefore, it’s essential to incorporate internet access into the MPI, due to the underlying inequalities that persist despite impressive absolute numbers. According to government data, there are 954.4 million internet subscribers in India as of March 2024, with nearly 400 million of them residing in rural areas.
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However, a deeper dive into these numbers shows the gap between internet usage on the lines of gender, caste, residence etc. According to Oxfam India Inequality Report 2022, women are 33% less likely to use mobile internet services compared to men, highlighting a significant digital gender gap. Along with this, only 31% of the rural population uses the internet, compared to 67% in urban areas, illustrating the stark regional disparity. Such disparities highlight why including digital access to MPI for India will help in improving understanding of the nature of poverty in India.
India has seen a sharp decline in extreme poverty based on consumption-based measures, with the poverty rate falling from 37% in 2004-05 to an estimated 10% in 2019, as per the World Bank.
It has become the world’s fifth-largest economy with GDP growing from $1.22 trillion in 2009 to $3.73 trillion in 2023. These achievements reflect progress in reducing material deprivation and improving access to essential infrastructure such as roads, electricity, and sanitation – critical aspects of what economists term negative freedom, or the absence of constraints that hinder basic survival. However, it continues to lag in positive freedom that enables individuals to fully realise their potential to lead stable and fulfilling lives.
Digital access and health insurance are critical determinants of wealth yet large sections of India remain deprived. Including these metrics in the MPI would help policymakers more effectively identify and address poverty hotspots.
For instance, analysing state-level variations in health insurance coverage could guide better allocation of resources to strengthen public health infrastructure. We need to ensure that the indicators we use to fight poverty shine a light not on the fights that we have won, but on the fights that we need to win.
Ayush Rawat is an economics student at Ashoka University with interests in public policy, economic research, and international relations. Rishit Roy is a third year economics student at Ashoka University with interests in developmental studies and public policy.
