Assessing Human Development in India: Challenges and Insights

India is home to 1.4 billion people spread across 28 states and 8 union territories, each with vastly different levels of development. Measuring how well this population is doing – in terms of health, education, and standard of living – is not a simple task. The Human Development Index (HDI), developed by the United Nations Development Programme (UNDP), provides a standard framework for this assessment. But applying it to a country as large and diverse as India requires navigating complex statistical challenges, multiple data sources, and significant regional disparities. Understanding how India’s human development is measured, and what that measurement reveals, is key to understanding the country’s development story.

What the HDI measures and where India stands 🔗

The HDI is a composite index that captures three core dimensions of human development: a long and healthy life (measured by life expectancy), access to knowledge (measured by expected and mean years of schooling), and a decent standard of living (measured by Gross National Income per capita). Each dimension is given equal weight, and the final score ranges from 0 to 1, with higher values indicating greater human development.

According to UNDP’s 2025 Human Development Report, India’s HDI value increased from 0.676 in 2022 to 0.685 in 2023, placing the country at rank 130 out of 193 countries – still within the medium human development category, but inching closer to the threshold for high human development (HDI ≥ 0.700). Since 1990, India’s HDI value has grown by over 53%, outpacing both global and South Asian averages. Life expectancy rose from 58.6 years in 1990 to 72 years in 2023, the highest since the index began. Children are now expected to stay in school for 13 years on average, compared to just 8.2 years in 1990. GNI per capita climbed from $2,167 to $9,047 over the same period.

These are meaningful gains. But the aggregate national figure masks deep inequalities and methodological complications that make measuring India’s human development a challenge in its own right.

The statistical challenges of measuring human development in India 🔗

India’s sheer scale makes data collection inherently difficult. Accurate measurement depends on reliable, up-to-date statistics – and India faces structural gaps in its data ecosystem that complicate a clear picture of human development.

Delayed census and data gaps 🔗

One of the most significant obstacles is the absence of a recent national census. India’s last census was conducted in 2011. The census scheduled for 2021 was postponed due to the COVID-19 pandemic and has still not been conducted as of 2025. As analysts have noted, this leaves policymakers, researchers, and planners without reliable data on a wide range of demographic and socioeconomic indicators – from population distribution to literacy rates – that are essential for human development assessments. In the absence of census data, estimates are built from surveys, which carry their own limitations in terms of sample size, coverage, and representativeness.

Inconsistencies across survey data 🔗

India relies on several large-scale surveys to track human development indicators, and these often produce results that do not entirely align with each other. The National Family Health Survey (NFHS), conducted by the International Institute for Population Sciences (IIPS) under the Ministry of Health and Family Welfare, is among the most widely used. The NFHS is one of the world’s largest household surveys, tracking fertility, child and maternal health, nutrition, and gender indicators at the national, state, and district levels. Five rounds have been conducted since 1992-93, with NFHS-5 completed in 2019-21.

However, the NFHS is not without limitations. Research has shown that NFHS data on sex ratios are inconsistent with population projections from the Registrar General of India and with National Sample Survey (NSS) data, requiring caution when interpreting some of its findings. Similarly, immunisation coverage figures across rounds and states have shown unexplained fluctuations that appear to reflect data quality issues rather than actual changes in health delivery. These inconsistencies illustrate a core challenge: when different surveys yield different numbers for the same indicator, it becomes difficult to confidently assess where a state or district actually stands.

The income measurement problem 🔗

Measuring income for HDI purposes presents another methodological difficulty. The HDI uses Gross National Income (GNI) per capita as a proxy for standard of living, but GNI captures only the formal economy. In a country like India, where a large share of economic activity is informal – from agricultural labour to petty trade – GNI per capita can significantly understate the real economic conditions of the population. Comparisons of poverty rates across surveys also reflect this problem: the India Human Development Survey (IHDS) estimated a poverty rate of 25.7%, close to the NSS estimate of 27.5%, but other variables showed notable divergences, underscoring that the choice of survey and methodology materially affects what the data shows.

Key surveys and reports that inform India’s human development picture 🔗

Despite these challenges, a combination of national surveys and reports provides the evidence base for understanding human development in India.

National Family Health Survey (NFHS) 🔗

The NFHS is the primary source for health and demographic indicators. Each successive round has expanded its scope: NFHS-4 (2015-16) added district-level estimates by nearly fivefold expanding its sample size, while NFHS-5 (2019-21) introduced new questions on disability, death registration, and preschool education. NFHS-5 provides information for India and each state, union territory, and 707 districts, making it one of the most granular sources of health and development data at the sub-national level.

National Sample Survey (NSS) and PLFS 🔗

The National Sample Survey Organisation (NSSO), now under the Ministry of Statistics and Programme Implementation (MoSPI), conducts periodic household surveys covering health, employment, consumer expenditure, and living conditions. The Periodic Labour Force Survey (PLFS), which replaced the older employment-unemployment survey, provides annual data on workforce participation – a key input for understanding the income dimension of human development. Together, NSS and PLFS data complement the NFHS and help cross-check indicators like poverty rates, health expenditure, and labour force participation.

Sample Registration System (SRS) 🔗

The Sample Registration System (SRS), in operation since 1970, provides annual estimates of fertility and mortality indicators including the Crude Birth Rate (CBR), Total Fertility Rate (TFR), Infant Mortality Rate (IMR), and Crude Death Rate (CDR). These are among the most reliable and continuously updated vital statistics in India, and serve as a key reference for tracking health dimension trends in human development reports.

National Human Development Reports 🔗

India’s Planning Commission released the first National Human Development Report (NHDR) in 2002, ranking states on 70 development indicators. The report revealed that per capita income alone did not determine development outcomes – Kerala ranked near the top despite not being among the highest-income states, while Punjab, with higher per capita income, ranked 19th. This insight anchored the case for multidimensional measurement in Indian policy thinking. Several states have since published their own State Human Development Reports (SHDRs), which adapt the HDI framework to local data and regional priorities.

State-level human development reports: indicators and insights 🔗

Because India’s federal structure means that health and education are largely state subjects, state-level human development reports are especially important. They are typically produced by state planning departments or by the UNDP in collaboration with state governments, and they use indicators tailored to state-specific data availability.

Indicators used in state HDRs 🔗

State Human Development Reports generally track the same three core dimensions as the global HDI – health, education, and income – but often incorporate additional indicators to reflect local realities. Health indicators typically include life expectancy, infant and child mortality rates, and institutional delivery rates drawn from NFHS or SRS data. Education indicators cover literacy rates, school enrolment, dropout rates, and – increasingly – learning outcomes drawn from assessments like ASER (Annual Status of Education Report) by PRATHAM. Income indicators use state domestic product or consumption expenditure data from NSS rounds. Some reports also include indicators on gender equity, access to safe drinking water, sanitation, and social protection coverage.

What state-level data reveals 🔗

The variation across Indian states in human development outcomes is stark. Subnational HDI analysis shows that the top-performing states – Delhi, Goa, Kerala, Sikkim, and Chandigarh – have HDI scores above 0.799, comparable to countries in Eastern Europe, while Bihar consistently scores the lowest. Kerala’s near-universal literacy (96.2%) stands in sharp contrast to Bihar’s substantially lower rate (70.9%), and infant mortality in Uttar Pradesh is roughly three times higher than in Kerala.

Importantly, high economic output does not guarantee high human development. States like Gujarat and Haryana rank relatively low on HDI despite high per capita GDP, showing that income growth is not automatically translating into better health and education outcomes. This decoupling is a central concern for Indian development policy and underscores why the multidimensional HDI framework – rather than GDP growth alone – is indispensable for evaluating state-level progress.

Inequality: the hidden cost in India’s HDI 🔗

The standard HDI reports average achievements, but averages can be misleading in a highly unequal country. The Inequality-Adjusted HDI (IHDI) corrects for this by discounting the HDI value based on the degree of inequality within each dimension. Inequality reduces India’s HDI by 30.7% – one of the highest losses in the South Asian region. The education dimension suffers the greatest inequality penalty, followed by health, and then income.

Gender inequality adds another layer. India’s Gender Inequality Index (GII) value is 0.437, reflecting significant gaps in reproductive health, political empowerment, and labour market participation. The labour force participation gap between women (below 25%) and men (above 76%) is one of the largest in the world. These inequalities mean that the national HDI figure, while useful for tracking long-term trends, can present a more optimistic picture than the lived reality of women, marginalised communities, and people in less developed states and districts.

The road ahead: improving measurement for better policy 🔗

Addressing India’s human development challenges begins with better measurement. Several improvements are necessary. Conducting the overdue decennial census is perhaps the most urgent – without current population data, all survey-based estimates carry a degree of uncertainty. Expanding district and block-level data collection, harmonising indicators across different surveys, and incorporating informal economy activity into income measures would all strengthen the evidence base. Greater granularity at the district and city level, including access to technology and informal work, would also improve the relevance of HDI calculations for policymakers operating below the state level.

State Human Development Reports, when produced regularly and with rigorous methodology, remain a powerful tool for identifying where development deficits are concentrated and for holding state governments accountable to measurable targets. The challenge is ensuring that these reports are produced consistently and that their findings feed directly into budget allocations and programme design.

What do you think? Given that India’s HDI score improves year on year yet inequality continues to reduce it significantly, should policy focus more on lifting the floor of the worst-performing states and districts rather than raising the national average? And does the absence of a recent census fundamentally limit how accurately India can assess its own human development progress?

References

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