Deconstructing the World Bank’s New Poverty and Inequality Numbers - Part 2

 Beyond the Metrics – The Policies, the People, and the Great Wealth Blind Spot

In the first part of this analysis, I deconstructed the "what" and "how" of the World Bank's recent, transformative update on Indian poverty and inequality. We established that the dramatic fall in the Gini index was overwhelmingly driven by a methodological recalibration, creating a new, lower baseline from which to measure progress. Now, I want to move beyond the statistical machinery and explore the "why." What does this new, albeit partial, picture tell us about the real-world policies that have shaped the lives of over a billion people? And, more importantly, what does its great blind spot—the complete absence of wealth data—mean for our understanding of India's economic trajectory? To do this, I will examine the report's implications through the four critical lenses of economic well-being: 1) access to income, 2) the policies that shape it, 3) access to wealth, and 4. the policies intended to foster it.

1.     Let's begin with the most fundamental element: access to income generation. A sustainable reduction in poverty and inequality is built on the foundation of empowering people to earn a decent living. When I look for evidence of this in the report, I find an unsettling silence. The data, rooted in consumption, does not track wages, employment types, or business creation. It cannot tell us if the decline in poverty is due to a structural shift from low-paying agriculture to better-paying manufacturing or services, or if real wages have outpaced inflation. The report shows that the poorest households have more resources, but the origin of those resources remains ambiguous. This is where we must read between the lines. The primary evidence of improved household resources is the stunning drop in extreme poverty, which, by the new metric ($3.00/day), fell from 27.1% in 2011 to a mere 5.25% in 2022. A change of this magnitude is not trivial; it means tens of millions of families crossed a critical threshold of consumption. But was this because they were earning more or receiving more? The report’s own methodology, with its careful valuation of welfare transfers, points heavily towards the latter. The explicit accounting for PDS rations and other in-kind benefits as a form of non-cash income provides a clear, quantifiable source for this improved consumption. While real-world initiatives like the 'Make in India' campaign, the formalization of the economy post-GST, and various skilling missions are all aimed at boosting generated income, this report offers no data to measure their direct impact on household earnings. My conclusion, based strictly on the evidence presented, is that the report paints a picture of a population that is better supported by the state, rather than one that is necessarily more empowered in the labor market. The story of income generation remains largely an unwritten chapter.

 

2.     This leads directly to the second, and perhaps most compelling, aspect of the update: its ability to illuminate the power of policies that directly target consumption inequality. It is here that the new methodology truly shines, acting as a lens that brings the impact of India's social safety net into sharp focus. The most significant of these is the Public Distribution System (PDS), fortified by the National Food Security Act (NFSA) of 2013. For decades, the true value of this massive food transfer program was statistically invisible in welfare calculations. By now imputing the market value of this subsidized food, the World Bank isn't just making a technical tweak; it is statistically validating the role of food security as a cornerstone of India's poverty reduction and inequality compression. During the COVID-19 pandemic, this was amplified by the Pradhan Mantri Garib Kalyan Anna Yojana (PMGKAY), which provided additional free rations. This policy didn't just prevent a humanitarian crisis; it actively propped up the consumption floor, and the new methodology allows us to see that effect in the numbers.

Beyond food, the report hints at the impact of other policies. The mention of valuing "free school uniforms and footwear" points to the quiet but steady work of schemes under the Samagra Shiksha Abhiyan, which reduce the out-of-pocket expenditure for poor families, freeing up scarce cash for nutrition or other needs. Furthermore, while not named, the fingerprints of the Direct Benefit Transfer (DBT) system are all over these results. Since 2013, India has progressively shifted from inefficient in-kind subsidies to direct cash transfers for everything from LPG cylinders (PAHAL scheme) to farmer support (PM-KISAN). By plugging leaks and ensuring money reaches intended beneficiaries, DBT has likely been a powerful engine for boosting real consumption among the poor, an effect that is captured in the aggregate consumption data of the HCES. So, when we look at the 3.3-point decline in the Gini index between 2011 and 2022 under the new series, it is plausible to attribute a significant portion of it to the scaling-up and improved efficiency of these very policies. The new data doesn't just show a fall in inequality; it helps explain why, pointing directly to the success of a consumption-support model of governance.

3.     However, as we turn from consumption to wealth, the picture goes from high-definition to a complete blackout. This is the report’s great, and in my view, dangerous, blind spot. Access to wealth—owning a home, having savings, building a small business, possessing land—is the bedrock of intergenerational mobility and economic security. It is what separates a household that is one bad harvest away from poverty from one that has a buffer to withstand shocks. Yet, the report is methodologically designed to be blind to it. The exclusion of durable goods purchases removes a key indicator of asset accumulation. The exclusion of housing values removes the single largest asset for most families from the equation. The result is a paradox: we are analyzing inequality using a tool that ignores the most unequal and most critical component of a family's economic life.

This is not a trivial omission; it is a fundamental flaw in using this dataset alone to understand Indian inequality. The period from 2011 to 2022 was not just one of expanding welfare; it was also a period of explosive wealth creation at the top. The Indian stock market has seen historic booms, a new class of "unicorn" startups has emerged, and real estate values in major cities have soared. This creation of financial and physical wealth is, by its nature, highly concentrated. It is therefore entirely possible, and I would argue highly probable, that while consumption inequality was modestly declining (due to the welfare floor rising), wealth inequality was simultaneously increasing, perhaps significantly. The report offers us a comforting story about one trend while being structurally incapable of telling us the potentially alarming story of the other. For a policymaker, this is like flying a plane with the altimeter working but the radar turned off. You know your current altitude, but you have no idea if you are flying towards a mountain.

4.     This brings me to the final area of analysis: policies designed to reduce wealth inequality. Here, the report’s silence is deafening, as it offers no way to evaluate the success or failure of the government's own flagship programs. Consider the Pradhan Mantri Awas Yojana (PMAY), a massive mission to provide "Housing for All." Has it succeeded in creating housing assets for the poor and reducing the housing gap? Or has its implementation been uneven? We cannot know from this report. Think of the Pradhan Mantri Jan Dhan Yojana (PMJDY), which brought over 500 million people into the formal banking system. Has this financial inclusion translated into actual savings and wealth creation for the poor, or are many of these accounts dormant? The report offers no clue. What about the MUDRA Yojana for micro-enterprise loans, or state-level efforts to grant land titles? These are all policies explicitly aimed at building an asset base for the economically vulnerable. Their impact is arguably more important for long-term security than annual consumption support. Yet, the primary tool used by the World Bank to monitor India's progress cannot say a single word about whether they are working. This is a critical failure of the data ecosystem. It means that trillions of rupees are being spent on wealth-creation policies with no corresponding metric in this global benchmark to track their distributional impact.

In my final analysis, the World Bank’s June 2025 update is a profound and necessary revision that nonetheless comes with a heavy burden of responsibility for anyone who uses it. It is an invaluable tool for understanding the success of India's consumption-support model. It provides, for the first time, a statistical validation of the immense role that food security and welfare transfers have played in lifting millions from abject poverty and compressing consumption gaps. We should celebrate this clarity. However, we must resist the temptation to accept this partial picture as the whole truth. The report’s silence on income generation and its structural blindness to wealth inequality are not minor details; they are gaping holes in the narrative. The risk is that we celebrate a battle won on consumption support while ignoring a potential war being lost on wealth concentration and opportunity. The true challenge for India, and for those of us who analyze it, is to build upon this new baseline: to continue strengthening the safety net it so clearly validates, while urgently developing and using better tools to measure and address the deeper, structural inequalities of income and wealth that it currently leaves shrouded in darkness.