India's Gini Coefficient: Reading the Inequality Data Carefully

What the Numbers Actually Show

India’s inequality trajectory is frequently cited in global economic debates, but the figures vary significantly depending on which Gini coefficient series is used. The dataset published by Our World in Data — drawing on harmonised household survey data — tells a story that differs from wealth-based estimates circulating in policy circles.

According to this source, India’s Gini coefficient stood at 0.26 in 2022. That figure — more precisely 0.2551 — reflects consumption or income inequality as measured through household surveys, a methodology that tends to produce lower Gini values than wealth-based approaches.

For context, a Gini of 0.00 represents perfect equality; 1.00 represents maximum inequality. At 0.26, India would sit in a range comparable to several European nations on consumption-based measures — though this framing requires significant caution, as survey coverage, underreporting of top incomes, and methodological differences make cross-country comparisons difficult.

The 2011 Benchmark

The dataset’s prior data point places India’s Gini at 0.29 in 2011 — specifically 0.2878. Comparing the two available figures reveals a modest decline in measured inequality between 2011 and 2022, from 0.29 to 0.26.

This downward movement — roughly 0.03 Gini points over eleven years — runs counter to the narrative of sharply accelerating inequality that dominates much public commentary. It does not mean inequality is absent or unimportant; it means that this particular measure, on this particular dataset, does not confirm the acceleration story.

Why the Discrepancy With Other Accounts?

Several factors explain why this dataset diverges from headlines suggesting India’s inequality has surged:

1. Survey vs. wealth data. Household consumption surveys, which underpin this Gini series, systematically undercount the very rich. Billionaire wealth, financial assets, and capital gains rarely appear in survey responses. Wealth-based Gini estimates — which attempt to capture the full distribution of assets — routinely produce values above 0.60 for India.

2. Consumption smoothing. Even households with volatile incomes tend to smooth consumption, compressing the measured distribution relative to income or wealth.

3. Coverage gaps. Rural and informal-sector households are better represented in consumption surveys than in tax records, which can pull the measured Gini downward if their relative consumption has improved.

4. Data vintage. The 2022 figure relies on survey rounds that may not fully capture post-pandemic distributional shifts, which were pronounced in India as in most large economies.

What a Gini of 0.26 Does and Does Not Mean

A Gini of 0.2551 in 2022 is not a clean bill of health. Even on consumption measures, it implies meaningful gaps between the top and bottom of the distribution. It also masks regional variation: inequality between Indian states, and between urban and rural populations, can be substantially higher than the national aggregate suggests.

The 2011 reading of 0.2878 similarly reflects a national average that conceals heterogeneity. The apparent decline to 0.26 by 2022 could reflect genuine distributional gains — such as expanded welfare transfers, rural employment guarantees, or improved agricultural incomes — or it could partly reflect measurement artefacts, including changes in survey design between rounds.

The Importance of Source Transparency

The angle that India’s Gini “rose from 0.32 in 1993 to 0.41 in 2022” is not supported by this specific dataset. The Our World in Data series records 0.2878 in 2011 and 0.2551 in 2022 — a decline, not a rise, and values well below 0.41. Different datasets, using different methodologies, will yield different conclusions.

This is not a minor technical footnote. Policy responses to inequality depend heavily on which measure is used. A government targeting consumption-based inequality will design different interventions than one targeting wealth concentration. Journalists and analysts citing Gini figures owe readers clarity about which series they are using and why.

Key Takeaways

• On the Our World in Data household-survey series, India’s Gini was 0.29 in 2011 and 0.26 in 2022 — a modest measured decline.
• These figures are consumption-based and will differ from wealth-based estimates, which tend to show higher and rising inequality.
• Neither figure should be read as a comprehensive verdict on Indian inequality; they are one lens among several.
• Source transparency — specifying the dataset, methodology, and year — is essential when citing Gini coefficients in any context.

The data, read carefully, does not support a narrative of sharp acceleration in measured consumption inequality over the past decade. It does, however, underscore how much the story changes depending on which data you trust.

Source: Our World in Data. Licensed under CC BY 4.0.

Disclaimer: This post is generated from public datasets for informational purposes only and does not constitute financial, legal, medical, or professional advice. Figures reflect the source dataset as fetched on the date shown above and may have been updated since. Meridian Intelligence makes no warranty as to accuracy or fitness for a particular purpose.

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