By: Soumya Kanti Ghosh and Falguni Sinha
The recent decline in India’s consumption-based Gini coefficient—from 28.8 in 2011–12 to 25.5 in 2022–23, as reported by the World Bank—has prompted considerable scrutiny, particularly when juxtaposed with income-based estimates from the World Inequality Database (WID), which peg India’s Gini at an ostensibly alarming 62 in 2023. Reconciling this apparent dissonance necessitates a closer interrogation of the underlying metrics, data sources, and conceptual frameworks. What follows is a reasoned engagement with the criticism—one that distinguishes methodological incompatibilities from substantive economic realities, and highlights the perils of conflating fundamentally distinct measures of inequality.
At the core of this divergence is a critical conceptual distinction: the difference between consumption inequality and income inequality. In a country like India—characterised by a large informal workforce, extensive in-kind transfers, and a rapidly expanding welfare architecture—income is often volatile, underreported, or difficult to capture comprehensively. Consumption, by contrast, tends to be smoother over time and more reflective of actual living standards. The World Bank’s Poverty and Inequality Platform (PIP) adopts this logic, using either disposable income or consumption expenditure depending on national context.
Firstly, It is worth pointing out that the World Bank in its paper titled “The World Bank’s New Inequality Indicator” gives a way of converting consumption gini to income gini and vice versa. The Bank estimated that the average ratio of income-to-consumption Gini coefficients across 84 country-years where data was available for both is 1.13. Applying this directly to India’s consumption-based Gini of25.5 yields an approximate income Gini of 28.8. This still places India at 12th, even under income-equivalent assumptions. This simple approximation gives a way of comparing welfare types within PIP database. This raises a pertinent question: why has this not been more widely acknowledged? The answer perhaps lies in the tendency to selectively emphasise outlier estimates. When the simple approximation given is used for comparison across nations, India’s inequality even when measured in income terms is significantly lower than United States and UK. Among the 48 nations where welfare approach is consumption based, India ranks 3rd. India’s consumption-based Gini coefficient of 25.5 in PIP database is also internationally striking. China’s consumption Gini, for instance, stands at 35.7, according to the same database and using the same welfare concept. This 10-point difference is significant.
Secondly, Why is the impact of large-scale social welfare schemes conspicuously absent from the criticism?”In a country like India, where large-scale social welfare programmes—such as subsidized food, LPG, housing, rural employment, health insurance, and direct cash transfers—have significantly boosted the living standards of the poor, consumption will inevitably be higher and more equitably distributed than income. These forms of public provisioning raise welfare especially in rural and informal segments. In BE 2025, the Union Government’s spending on beneficiary schemes amounts to ₹7.1 lakh crore, and states together add another ₹7.4 lakh crore. This totals nearly ₹14.5 lakh crore. According to PLFS data, the average monthly earning by regular salaried worker is approx. Rs 21000 and approx. Rs 14000 for self-employed. The average earning per day by casual labourer is Rs 433. Using these approximations and accounting for dependency assuming a family of four, this translates to an income of Rs 65000 per capita. Assuming 80% of the total beneficiary schemes reaches bottom 50%, this translates into Rs 15000 per year/per person accounting for leakages and overlaps through direct and indirect benefits. This uplift of approx. 20% in effective resources translates into consumption. Thus, even under these conservative assumptions, this significantly compresses effective inequality.These interventions have also led to a dramatic fall in poverty, with the extreme poverty rate dropping from 16.2% in 2011–12 to 2.3% in 2022–23. At the lower-middle-income line of $3.65/day, poverty fell from 61.8% to 28.1%.
Before accepting WID’s estimates at face value, shouldn’t we ask what exactly they are measuring? Coming onto the WID database, their benchmark income concept is:”Pre-tax, post-replacement national income” — that is, before taxes and transfers, except for social insurance components like pensions and unemployment benefits. This means they exclude most non-contributory welfare transfers — like India’s Direct Benefit Transfers (DBT), food subsidies, LPG schemes, Ayushman Bharat, rural housing, and more.
India’s social protection system relies much more heavily on non-contributory transfers than contributory insurance. These are not counted in the WID’s income concept, even though they materially raise real income and purchasing power.
This creates a systematic downward bias when WID measures inequality in India by ignoring the redistributive effect of these targeted schemes and Inflating the apparent concentration of national income at the top. So, under WID’s income inequality framework, we are essentially saying that major upliftment scheme in India — have zero impact on measured inequality.
Secondly, WID relies heavily on tax records to compile its database. Now, even if we look at Tax records, Gini coefficient estimated using ITR data of taxable income of individuals shows that individual income inequality has decreased from AY15 ( FY14) to AY23 (FY22) from 0.472 to 0.402. 43.6% Individual ITR filers belonging to Income group of less than Rs 4 lakhs in AY15 (FY14) have left the lowest income group and shifted upwards.
A comparison of disparity in income during FY14 and FY23 shows that there is a clear rightward shift in the income distribution curve signifying people in lower income brackets are increasing their income to converge towards their share in population. The bell shaped curve for AY24 speaks more!! In FY14, share of top1% in total income was 1.64% which has fallen to 0.77% in FY21. Furthermore, tax buoyancy of 1.1 alongside falling cost of collection actually shows better compliance and hence must not be misread as rising inequality.
If India’s official tax data shows improving progressivity, and large-scale consumption surveys indicate a sustained reduction in inequality, then it is worth asking why WID estimates tell such a different story.
To argue that India remains deeply unequal based solely on selectively elevated income estimates is much like claiming the country lacks water because Rajasthan faces water scarcity. Inequality, like deprivation, is not monolithic—it varies across dimensions, regions, and measurement tools but that does not invalidate the broader progress being made. Any evaluation that ignores these dynamics in favour of a narrow, partial view risks obscuring the very progress it seeks to critique.
As we move forward, two takeaways are critical.
First, improved reporting is not the same as increased disparity—and we must resist reacting to shadows cast by better data.
Second, and most importantly, welfare economics must always return to its core question: what improves the lived experience of the bottom half? In that, India’s story over the past decade is less about divergence at the top and more about convergence at the base—quiet, broad, and measurable in the resources people actually use.
Courtesy PIB Srinagar
(The authors are Member 16th Finance Commission and Group Chief Economic Advisor, State Bank of India and Economist, State Bank of India. Views are personal)
