India’s GDP Debate, Right Questions, Wrong Numbers – A Response to Claims of Overestimation
How accurately does India’s Gross Domestic Product (GDP) capture what is actually happening in the economy? This question has been the subject of serious debate among economists and policymakers for some years. It is a legitimate and important question. An accurate measurement of national income is not merely an academic exercise; it is the foundation upon which governments allocate resources, central banks set interest rates, and investors make decisions about the future. If the numbers are wrong, the policies built on them are built on sand. A recent paper that claims India’s GDP has been significantly overestimated has reignited this debate, raising serious questions about the country’s official economic statistics. The paper’s authors argue that the national accounts have been overstating growth by a substantial margin, a claim that, if true, would have profound implications for India’s economic narrative. However, a detailed response from India’s Chief Economic Adviser and the Secretary of the Ministry of Statistics and Programme Implementation argues that while the paper asks the right questions, it arrives at the wrong conclusions by relying on flawed methodology, outdated assumptions, and a fundamental misunderstanding of India’s rapidly transforming economy.
The February 27 revision to the national accounts methodology, developed through what even the paper’s authors describe as “commendable consultations,” represents the most substantive effort to improve GDP estimation in years. This revision addressed critical issues such as deflator choices, the treatment of inflation, and other technical factors. The authors of the paper argue that this revision was necessary to account for the impact of the pandemic and other structural changes. However, the paper’s core methodological critiques—that India used Wholesale Price Index (WPI)-based deflators tracking commodity and oil prices rather than prices of actual production, and that it used formal-sector corporate data as a proxy for informal-sector activity—are not new. These critiques have been present in the academic literature since at least 2016, including in the earlier work of one of the paper’s authors. The critical point, which the paper glosses over, is that these methodological choices were not made out of analytical oversight or incompetence. They were driven by structural data limitations that have plagued Indian statistics for decades. In the absence of regular, high-frequency annual data on informal-sector output and a comprehensive Producer Price Index (PPI), the use of WPI-based deflators and formal-sector corporate data was a pragmatic, and arguably the most viable, option available to statisticians working with the tools at hand.
The paper’s assertion that the WPI is an inappropriate deflator and that the Consumer Price Index (CPI) is a better alternative is, the response argues, fundamentally misplaced. India’s WPI is conceptually close to a Producer Price Index (PPI), which is precisely what international statistical recommendations prescribe for deflating output in the production account. The CPI, by contrast, reflects price movements relevant to private consumption. It is the right tool for measuring inflation as experienced by households, but it is the wrong tool for deflating the output of industrial and service sectors. Goods and services such as steel, cement, minerals, chemicals, IT services, trade, and professional services are produced primarily for industrial use and rarely appear in the CPI basket. Using the CPI to deflate these would introduce a different, and potentially larger, set of errors. The paper’s insistence on the CPI as the superior deflator reveals a misunderstanding of the purpose of different price indices.
The paper’s most dramatic claim is that India’s GDP has been overestimated by as much as 22 per cent. This staggering figure, if true, would represent one of the largest statistical errors in modern economic history. But the response argues that this claim is built on a foundation of questionable assumptions that do not hold up under scrutiny. A central pillar of the paper’s argument is the importance of the informal sector. It uses data from unincorporated enterprises surveyed during the COVID-19 lockdown to estimate the extent of informal employment, arguing that the informal sector is crucial because it provides a source of income for many households. However, the paper provides no evidence that the informal sector has grown significantly over time, nor does it adequately account for the rapid and well-documented formalisation of the Indian economy that has occurred over the past decade.
This is where the paper’s argument runs into its most damaging contradiction. Subramanian, one of the paper’s authors, was himself the principal author of the Economic Survey of India 2017-18. Chapter 2 of that Survey, using early data from the Goods and Services Tax (GST), found that purely informal firms—those outside both GST and social security coverage—accounted for only about 7 per cent of total economic turnover, even though they represented 87 per cent of firms by number. Firms within the GST net accounted for nearly 80 per cent of total turnover. The Survey documented a rapid, self-reinforcing process of formalisation, as small firms registered voluntarily to access input tax credits from larger buyers. The 2026 paper’s mismeasurement argument rests on the claim that the informal sector accounts for roughly 44 per cent of Gross Value Added (GVA) and that the formal and informal sectors diverged so sharply after 2015 that using formal data as a proxy led to sustained overestimation. But if 80 per cent of turnover was already in the formal economy by late 2017, and formalisation was accelerating, the informal sector’s weight would have shrunk further still in the years that followed. The 2026 paper makes no attempt to reconcile its baseline assumption with the evidence it itself produced. The informal sector’s contribution to GDP, even if substantial, is not the 44 per cent the paper assumes. Weaken that assumption, and the entire quantitative edifice of the paper collapses.
The paper also criticises the use of Ministry of Corporate Affairs (MCA) data, arguing that it may lead to overestimation. But the MCA database provides comprehensive coverage based on actual reported data from companies, not survey-derived estimates like the Annual Survey of Industries (ASI). Corrections that rely solely on ASI data for organised manufacturing are therefore incomplete and potentially misleading. More fundamentally, the paper never confronts the reality that India’s economy underwent a profound structural transformation after 2015. The rapid expansion of the digital economy, strong growth in financial services and insurance, the emergence of India as a major hub for Global Capability Centres (GCCs), and deliberate policy-driven formalisation have all reshaped the economic landscape. These are precisely the activities that do not show up in traditional indicators like energy consumption, trade volumes, or bank credit data—the very indicators the paper treats as reliable proxies for aggregate output. Some weakening of correlation with these selected variables is therefore not unexpected. It is not evidence of statistical error; it is evidence of structural change.
The strongest empirical check on the paper’s claims is the official February 2026 revision itself. The authors of the paper describe the revision as “problematic but nevertheless positive.” But the revision, produced by professional statisticians working with full access to administrative data and without the methodological shortcuts the paper employs, produced a substantially more modest adjustment than the paper’s estimates imply. If the true overestimation were really 22 per cent of GDP, the official revision would look nothing like it does. That gap between the paper’s dramatic claims and the modest official outcome is not a detail to be explained away. It is a fundamental refutation of the paper’s central thesis.
The debate over India’s GDP is important. It forces statisticians and policymakers to constantly question their methods and strive for greater accuracy. But knowing where to stop is part of the discipline of empirical work. The paper asks the right questions about measurement, but it arrives at the wrong numbers by relying on outdated assumptions, ignoring structural changes, and failing to reconcile its claims with the overwhelming evidence of formalisation and with the actual outcome of the official statistical revision. A healthy debate about measurement is essential. A debate based on flawed numbers is a distraction.
Questions and Answers
Q1: What is the central claim of the paper that this article is responding to?
A1: The central claim of the paper is that India’s GDP has been significantly overestimated, possibly by as much as 22 per cent. The paper argues that this overestimation resulted from methodological choices, including the use of WPI-based deflators and formal-sector corporate data as a proxy for informal-sector activity.
Q2: According to the response, what is the main problem with using the CPI as a deflator instead of the WPI?
A2: The response argues that the WPI is conceptually close to a Producer Price Index (PPI), which is the correct tool for deflating output in the production account. The CPI, by contrast, reflects prices relevant to private consumption. Using it to deflate industrial goods and services (like steel, cement, IT services) would be inappropriate and would introduce a different set of errors.
Q3: What evidence from the Economic Survey 2017-18 is used to counter the paper’s claims about the informal sector?
A3: The 2017-18 Economic Survey, co-authored by one of the paper’s authors, found that purely informal firms accounted for only about 7 per cent of total economic turnover, even though they represented 87 per cent of firms. Firms within the GST net accounted for nearly 80 per cent of turnover, and the Survey documented a rapid process of formalisation. This directly contradicts the paper’s assumption that the informal sector accounts for roughly 44 per cent of GVA.
Q4: What structural changes in the Indian economy after 2015 does the response cite to explain why traditional indicators might not correlate perfectly with GDP?
A4: The response cites several structural changes:
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Rapid expansion of the digital economy
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Strong growth in financial services and insurance
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Emergence of India as a major hub for Global Capability Centres (GCCs)
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Deliberate policy-driven formalisation
These activities do not show up in traditional indicators like energy consumption or bank credit, explaining the weakening correlation.
Q5: What does the response point to as the “strongest empirical check” on the paper’s claims?
A5: The response points to the official February 2026 revision to the national accounts methodology as the strongest empirical check. If the true overestimation were as large as the paper claims (22 per cent), the official revision would have been much larger. The modest adjustment produced by professional statisticians with full data access fundamentally refutes the paper’s central thesis.
