Deconstructing the World Bank’s New Poverty and Inequality Numbers - Part 1

 Part 1: The Recalibration of India: Deconstructing the World Bank’s New Poverty and Inequality Numbers

When the World Bank releases a major update to its Poverty and Inequality Platform (PIP), it’s a significant event for global development watchers. But when that update involves India, a country home to one-sixth of humanity, the implications are monumental. The "June 2025 Update" is just such an event. At first glance, the numbers are startling, suggesting a dramatic and rapid decline in both poverty and, most strikingly, inequality in India. It’s a narrative that aligns with a story of broad-based progress. Yet, as I began to delve into the accompanying technical note, a far more complex and layered picture emerged. The story of India's improved metrics is not a simple tale of policy triumph; it is an intricate interplay of genuine progress, profound methodological shifts, and critical data omissions. This update is less a photograph of India and more a recalibration of the camera itself. Understanding the nature of this recalibration is the most important task for anyone seeking to grasp the reality of poverty and inequality in India today.

The significance of this update lies not just in the new numbers it presents, but in the fundamental break it creates with all previously published data. To comprehend the shift, we must first understand the machinery. The Gini index, our primary metric for inequality, measures the distribution of a resource—in this case, consumption—across a population. A score of 0 represents perfect equality (everyone has the same), while a score of 100 represents perfect inequality (one person has everything). For years, India’s Gini hovered in the mid-to-high 30s, a figure that, while not extreme, pointed to significant disparities. The new report, however, presents a Gini of just 28.8 for 2011, plummeting to 25.5 by 2022. This is a seismic shift. To put it in perspective, the previous World Bank vintage, published just months earlier in September 2024, had reported a Gini of 35.4 for the very same year, 2011. How can a country’s inequality metric for a year in the past fall by nearly 7 points overnight? The answer has nothing to do with history and everything to do with methodology. The Bank has, in essence, re-engineered its entire approach to measuring Indian consumption, and this re-engineering accounts for the lion’s share of the “improvement.”

Let's break down the four key factors driving this change.

-        The single most dominant factor, which the report’s own analysis suggests accounts for a staggering 80% of the reduction in inequality, is the shift in the survey's recall period. Previously, India’s surveys used a Uniform Reference Period (URP), asking households to recall all their expenditures over the last 30 days. The new methodology, applied retroactively to 2011, uses a Modified Mixed Reference Period (MMRP). Under MMRP, families report frequent purchases like food and groceries over a short period (7 or 30 days) but recall infrequent, lumpy expenditures like clothing, footwear, or small appliances over a full year (365 days). The impact of this is profound. A low-income family might not buy a new sari or a pair of school shoes every month, so a 30-day survey could easily miss this expenditure, understating their annual consumption. A 365-day recall for these items captures this spending far more accurately. This systematically lifts the measured consumption of lower and middle-income households, who spend a larger portion of their non-food budget on such lumpy items. It has a powerful compressive effect on the entire distribution, closing the gap between the bottom and the top and, consequently, causing the Gini index to fall dramatically.

-        The second factor is the construction of a new welfare aggregate. This is not one change but a collection of crucial adjustments that collectively lift the bottom of the distribution while lowering the top. To lift the bottom, the Bank now imputes a market-equivalent price for goods received through the Public Distribution System (PDS). For decades, a poor family’s consumption was valued at the one or two rupees they paid for subsidized grain, or zero if it was free. This was a massive understatement of their real welfare. By valuing that 35kg of grain at its market price, the new methodology correctly captures the enormous impact of India’s food security net, boosting the measured welfare of millions. Simultaneously, the methodology lowers the top by excluding certain types of expenditure. Purchases of durable goods, jewelry, and even wristwatches are no longer counted. The justification is that these are often stores of value, not pure consumption. Furthermore, and critically, the value of housing services has been completely excluded for both renters and homeowners due to challenges in consistent data capture. Since wealthier, urban households spend disproportionately more on high-value items and housing, excluding these components clips the top of the consumption distribution, further compressing the Gini index.

-        The third and fourth factors, the revision of price deflators and the adoption of new 2021 Purchasing Power Parities (PPPs), are more technical but important. Using more granular state-specific price indices instead of simple urban-rural ones makes the data far more accurate in a country as diverse as India. However, its impact on the Gini index is minimal compared to the MMRP and welfare aggregate changes. The new PPPs, meanwhile, primarily affect the international poverty headcount—for instance, changing the extreme poverty line from $2.15 to $3.00 per day. They have no direct impact on the Gini index, which is calculated on the domestic currency distribution before any international conversion. Together, these four changes create the "structural break." The India of 2011 in this report is a statistically different entity from the India of 2011 in all previous reports. The fall in inequality from 35.4 to 28.8 for that year is not a reflection of a newly discovered reality, but the result of applying a new measurement ruler. The subsequent, more modest decline from 28.8 in 2011 to 25.5 in 2022 is the trend we are now invited to analyze, a trend that is itself shaped by these new methodological choices.

What this new, re-engineered camera fails to capture, however, is as important as what it now brings into focus. The report, based on the Household Consumption Expenditure Survey (HCES), is silent on the crucial questions of income and wealth. It tells us what households spend, but not how they earn. There are no metrics here on access to better jobs, rising wages, or entrepreneurial income. Has inequality of opportunity in the labor market improved? We cannot say from this data. The improved consumption at the bottom could be from better wages, or it could be, as the methodology itself suggests, overwhelmingly from government transfers. The report shows a population that is better supported, but not necessarily one that is more empowered through income generation. The omission of wealth is even more stark. The methodology explicitly excludes the primary channels of wealth creation and accumulation for ordinary families: the purchase of durables, the value of housing, and other assets. In a period where India has seen a booming stock market and significant real estate activity, this is a colossal blind spot. We are being shown a picture of declining consumption inequality while being left completely in the dark about what might be a very different, and potentially diverging, trend in wealth inequality. The report cannot tell us if the bottom 40% are accumulating assets or falling further behind in the race for wealth.

In conclusion, the World Bank’s June 2025 update is a landmark revision that must be handled with extreme care. The good is that the new methodology is undeniably more robust. It is far better at capturing the real-world impact of India’s massive social safety net, particularly the PDS, providing a more accurate measure of the consumption floor in the country. This is a welcome and long-overdue improvement. The bad, however, is the high potential for misinterpretation. The headline-grabbing drop in the Gini index is primarily a statistical artifact of this methodological change, not a simple continuation of a past trend. Comparing the new Gini of 25.5 to the old figures in the mid-30s is a comparison of apples and oranges. The most significant shortcoming, however, lies in its omissions. By focusing exclusively on a narrow definition of consumption and actively excluding proxies for wealth, the report presents a partial and potentially sanitised view of inequality. For policymakers, this is perilous. It risks fostering complacency by highlighting success in consumption support while masking potential failures in promoting equitable income opportunities and preventing the concentration of wealth. The public, in turn, may be led to believe that the challenge of inequality is far smaller than it actually is. This update has given us a better tool to measure one part of the elephant, but we must not forget that it leaves the other, perhaps larger, parts entirely in the dark.