How to Measure India's Inequality

The Wire

22-07-2025

Economy
The World Bank's assessment is testament to the fact that any study of inequality in India requires a multi-dimensional and inter-sectional approach.
By now, the World Bank report which has claimed a drastic reduction in the state of inequality in India between 2011 and 2022 – first shared by the Press Information Bureau – has been shared widely. Headlines have been splashed across mainstream news platforms without much by way of due diligence.
Meanwhile, the Ministry of Statistics and Programme Implementation (MoSPI) also released the Sustainable Development Goals (SDG) National Indicator Framework Progress Report 2025, which tracks India's progress across 17 SDGs using 284 indicators. This report presents time-series data from various line ministries and offers a macro-level diagnostic lens into the country's trajectory toward Agenda 2030, a United Nations plan adopted in 2015 to guide global development efforts.
While it is a valuable tool for aligning India's metrics with global targets, the report predominantly emphasises administrative progress and aggregated outcomes, often missing ground-level disparities in access, affordability, and inclusion. This is, however, critical in shaping and measuring relative poverty and inequality for India.
There are serious issues with the larger interpretation of the World Bank assessment where consumption-based inequality is mapped with income-inequality scales across countries – an effort which is like comparing apples with oranges.
But instead of diving deeper into the methodological nuances of this concern, which most credible development economists studying inequality and poverty debate in India would agree on, the nature of our understanding of inequality itself merits a deeper, more multidimensional discussion.
The Access (In)Equality Index (AEI) 2025, developed by the Centre for New Economic Studies (CNES), can serve as a critical component to this debate. It draws largely from the same official data sources, but reorganises indicators through a disaggregated, intersectional lens grounded in the 4A framework: availability, affordability, approachability, and appropriateness.
It then evaluates these across five measurable pillars – access to basic amenities, access to healthcare, access to education, access to socio-economic security, and access to legal recourse – thereby capturing the often overlooked distributive aspects of the income-wealth based criteria on which most 'inequality' and 'poverty' measurement studies are based on. These aspects are also overlooked in the SDG-NIF analytical framework.
Creating a more multidimensional approach allows us not only to contextualise SDG progress more meaningfully but also to identify which populations, regions or services might be excluded or underserved despite aggregate improvements in their performative assessments. What on average may present an 'improvement' in nominal data may reflect deeper and more paradoxical realities.
Basic amenities: Presence versus functionality
The World Bank brief misses several points in the debate on inequality measurement and in studying inclusive prosperity from income or wealth-based criteria. The SDG-NIF framework, which is far more comprehensive and wider in scope offers a useful normative space but merits greater analytical coherence of the inequality scenario. The AEI tries to offer this coherence.
Within the pillar of basic amenities, for example, the AEI correlates with SDG-NIF indicators. These include SDGs to do with piped water supply, improved sanitation/toilet facilities, use of clean cooking fuel or electricity and access to affordable, safe housing under schemes like PMAY-U.
The SDG-NIF Progress Report 2025 presents encouraging trends. For example, piped water coverage increased from 21.33% in 2019-20 to 80.22% in 2024-25. Access to clean cooking fuel is reported to have exceeded 100% coverage in some years, suggesting robust reach. Similarly, school sanitation indicators show consistent achievement, with over 97% of schools having separate toilets for girls by 2023-24. Housing quality is also tracked through the share of pucca houses, which has improved modestly over the years.
Yet, when these figures are mapped against Access Inequality Index data for states across India, a more layered picture emerges. The Index ranks states based not only on the presence of infrastructure but also on functionality, usability and inclusion.
Goa, for instance, scores the highest on AEI's Basic Amenities pillar (0.97), while Jharkhand (0.31), Bihar (0.38) and Odisha (0.39) lag significantly. Although national indicators show increased infrastructure rollout, AEI findings suggest disparities in actual access especially among rural, tribal and low-income populations due to location constraints, affordability and irregular supply.
Piped water access provides a clear example of this layered assessment. According to the Access Inequality Index Report, while Goa reports 91.9% piped water coverage, Assam remains at 5.8%.
Similarly, although the SDG-NIF shows progress in bringing water 'within premises,' AEI notes that only 25% of states have piped water coverage above 50%, implying that in many states, most households still fetch water from outside their homes a burden disproportionately carried by women.
Clean cooking fuel is another area where outputs and access may diverge. While the SDG-NIF reports over 99% LPG access nationally, AEI data highlights that in 50% of states, functional coverage remains below 25%. The discrepancy may be due to inability to get refills, affordability constraints or supply chain limitations in remote regions. These nuances are essential, especially considering the implications of indoor air pollution on women's health and the undeniable time burden.
Housing and sanitation indicators, similarly, reveal alignment. But these also come with caveats. For example, although national data shows high latrine coverage with Telangana achieving 100%, AEI reveals that in half the states, coverage remains below 95%. Questions of regular usage, privacy and access for persons with disabilities are rarely addressed. While the SDG Target 11.1 focuses on providing safe, affordable housing by 2030, the AEI data shows that in more than half of Indian states, fewer than 75% of households live in pucca homes, highlighting the precarity surrounding structural housing.
Healthcare: Equity beyond outcomes
In the domain of healthcare, the AEI aligns closely with SDGs concerning good health and well-being, particularly through shared indicators such as institutional delivery rates, immunisation coverage, out-of-pocket expenditure on health, and the doctor-to-population ratio.
The SDG-NIF highlights a steady improvement in neonatal mortality, which declined from 25 per 1,000 live births in 2015 to 19 in 2021, signalling national progress in early child health outcomes. Similarly, institutional births have risen markedly from 78.9% in 2015–16 to 90.6% in 2019–21 indicating expanded facility-based maternal care.
Yet, the AEI allows for a more nuanced assessment by disaggregating access across geography and affordability. For instance, while Goa (93%) and Tamil Nadu (89.9%) report high levels of adequate antenatal care, reflecting well-developed state health systems, Nagaland records just 20.7%, pointing to critical gaps in preventive maternal healthcare in northeastern and hilly regions.
When it comes to OOPE, a core AEI metric evaluating the economic burden of accessing healthcare Haryana (Rs 1,666) and Madhya Pradesh (Rs 1,619) emerge as the most affordable states for institutional deliveries.
In stark contrast, Manipur reports an average OOPE of ₹14,518, suggesting inadequate financial protection and limited access to free or subsidised services. While Kerala (99.8%) and Goa (99.7%) lead in institutional deliveries, ensuring nearly universal facility-based births, states like Nagaland (45.7%) reveal persistent service gaps, highlighting the need to go beyond national averages in evaluating maternal health outcomes.
Additionally, AEI considers structural access indicators often absent in the SDG framework, such as the average radial distance covered by sub-centres and the average rural population per sub-centre.
These reflect how far rural communities must travel to receive basic care. In this regard, Goa and Mizoram perform well, with sub-centres catering to rural populations of just 1,781 and 1,850 respectively, figures that demonstrate both proximity and effective outreach. These indicators provide a critical lens to understand not just the presence of health infrastructure, but its accessibility, reach and affordability dimensions that remain under-explored in conventional SDG reporting.
Socio-economic security: Outputs versus usability
In the realm of socio-economic security, the SDG-NIF and AEI both engage with overlapping indicators of poverty, gender equality, decent work and economic growth, and reduced inequalities. On each of these fronts, the SDG data presents steady national-level progress.
For instance, the labour force participation rate (LFPR) among individuals aged 15-59 increased from 61.6% in 2022-23 to 64.3% in 2023-24. Similarly, the number of banking outlets per 100,000 people rose from 59.9 in 2015-16 to a peak of 267.5 in 2021-22, before stabilising at 144.3 in 2023-24. The expansion of ATM networks has been slower, rising marginally from 16.5 in 2015-16 to 18.5 in 2023-24. While these improvements signal institutional expansion, they say little about who has access to these services, under what conditions and how evenly these gains are distributed.
The AEI 2025 contextualises these outcomes through a nuanced lens of usability and reach. It highlights state-level disparities in employment access, financial infrastructure and income equity.
For example, Andhra Pradesh ranks highest in the AEI's socio-economic security pillar with a score of 0.70, followed by Goa (0.60). In contrast, Bihar (0.18), Assam, and Manipur (both around 0.21) emerge as the lowest performers. Strikingly, the top eight performers in AEI's socio-economic security pillar include all five southern states, while many northeastern states consistently rank at the bottom. This geographic clustering reflects both policy prioritisation and institutional gaps.
AEI's granular focus reveals infrastructure deficits and access inequalities that the SDG framework tends to mask. For instance, 51% of states have automated teller machines (ATMs) or customer relationship management or white label ATM coverage below 25%. Bihar, the worst performer, has just 10.7% availability, while Goa leads with 67.3%, revealing deep regional disparities in financial infrastructure. Furthermore, workforce participation trends, while captured at a macro level in SDG-NIF, gain depth through AEI's lens. The AEI notes that approximately 21.6% of states have workforce participation rates below 50%.
Moreover, although the budgetary allocation to northeastern states has remained relatively stable, rising from 1.66% in 2015-16 to 2.10% in 2023-24, this has not yet translated into commensurate improvements in socio-economic access for the region.
The differences in focus between the two frameworks become evident in their handling of gendered economic vulnerability. While SDG 5 includes participation in SHGs as a proxy for empowerment, AEI interrogates the broader ecosystem of gendered access to employment, income-generating programs and grievance redressal.
Additionally, rising rates of crimes against women, which increased from 54.2 per 100,000 in 2015 to 66.4 in 2022, further contextualise the precariousness of women's public participation, something that the AEI captures through indicators on institutional trust and safety, often excluded from SDG metrics.
Education: From enrolment to access and equity
In the domain of education, both the SDG-NIF and AEI focus on similar foundational indicators aligned with the SDG of quality education.
Time-series data from the SDG-NIF illustrates gradual improvement in several areas: the GER at the higher secondary level rose from 48.3% in 2015–16 to a peak of 57.6% in 2021-22, though it slightly declined to 56.2% in 2023-24. Net enrolment in primary and upper primary education, however, has been more erratic, with figures for upper primary education dropping from 74.1% in 2020-21 to 66.0% in 2023-24, highlighting recent setbacks in sustained school attendance, possibly exacerbated by the digital divide during and after the pandemic.
A key SDG 4 target is universal access to early childhood and pre-primary education, and while the SDG-NIF tracks improvements in infrastructure indicators, the AEI reveals significant disparities in actual access and educational quality.
For example, while the proportion of secondary and higher secondary schools with internet access increased from 46.3% in 2015-16 to 78.5% in 2023-24, AEI data shows that more than half of Indian states still have less than 50% of schools with functional computers, and only 25% of states exceed 75% coverage. In terms of digital readiness, only Kerala and Gujarat surpass 60% school-level internet coverage, raising concerns about the preparedness of most states to deliver 21st-century learning.
These findings correspond to SDG indicators but provide a deeper look at structural exclusion. For instance, the standard deviation of AEI education scores is 0.12, with a median score of 0.47, reflecting broad inter-state disparity. Interestingly, in most states, AEI education scores are lower than their scores for basic amenities highlighting a critical lag in social infrastructure despite gains in physical provisioning.
Dropout rates further illuminate these gaps. According to AEI data, Odisha records the highest dropout rate at 27.3%, with Meghalaya, Bihar, and Assam also exceeding 20%. The median dropout rate is 11.2%, which implies that in half the country, over one in 10 children leave school annually. These figures challenge the optimistic narrative often inferred from enrolment data alone.
The pupil-teacher ratio, an important determinant of learning outcomes, also varies significantly. The SDG-NIF sets a national target of 30:1, but states like Bihar report a ratio of 47, suggesting overcrowded classrooms and limited attention per child. The AEI thus offers a vital corrective to purely outcome-based SDG indicators by foregrounding issues of accessibility, institutional capacity, and digital inequality. It highlights that education access is not merely a matter of enrolment but of sustained participation, quality delivery, and equity.
Legal access: Institutional presence versus user-centric access
The access to legal recourse pillar, aligned with SDGs on peace, justice, and strong Institutions aims to evaluate the functionality and inclusiveness of justice delivery systems. The SDG-NIF data presents a modest institutional picture. The number of courts per lakh population has shown a slow upward trend from 1.82 in 2016 to 1.93 in 2024. Similarly, the number of judges per lakh population has increased from 1.33 in 2016 to 1.55 in 2024, reflecting incremental capacity building in the judiciary. However, these indicators, while useful in capturing administrative density, say little about the accessibility or effectiveness of legal recourse.
The AEI framework adds vital context to these institutional indicators by assessing actual access, trust, and institutional responsiveness. Surprisingly, Nagaland, often classified as an 'aspirant' in other development areas, ranks highest in this pillar with an AEI score of 0.67.
This indicates that despite overall development challenges, some states may have functionally accessible legal systems. At the other end of the spectrum, Bihar ranks lowest with a score of 0.36, reinforcing long-standing concerns regarding judicial inaccessibility and delayed justice in certain states.
AEI indicators also include gender-disaggregated data on the representation of women in legal institutions, which provides a crucial equity lens missing in the SDG-NIF. For instance, Sikkim leads with 33.3% of judges being women, reflecting significant strides in gender representation.
In stark contrast, several states including Bihar, Uttarakhand, Manipur, Meghalaya, and Tripura record 0% women judges, underscoring persistent gender exclusion in judicial appointments. Furthermore, the SDG-NIF notes that 1.2% of women aged 18–29 reported experiencing sexual violence before the age of 18 (2019–21) a figure that likely underestimates the real extent due to underreporting and cultural stigma.
While both the SDG-NIF and AEI aim to assess developmental progress, they differ significantly in approach and scope. The SDG-NIF uses a top-down, outcome-based model relying on aggregated administrative data, often focused on infrastructure coverage. In contrast, the AEI employs a bottom-up, access-oriented lens, emphasising disaggregated data across gender, caste and region. While SDG-NIF measures delivery, it often fails to capture whether services are functional or equitably accessed.
There is a need to acknowledge these critical gaps by foregrounding core distribution issues of access, equity, social identity, and functionality across essential services and public goods. It is these which are directly responsible for shaping and enabling well-being for citizens, independent of their income or wealth status.
Deepanshu Mohan is professor of economics, and director of the Centre for New Economics Studies (CNES) at the O.P. Jindal School of Liberal Arts and Humanities.
Ankur Singh and Aditi Desai contributed to this article as research analysts with CNES.
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