Why in news?

The National Statistical Office (NSO) recently released new National Accounts Statistics (NAS), showing manufacturing sector's Gross Value Added (GVA) at ₹38.6 lakh crore for 2023-24 — 14.7% of GDP.

But when researchers cross-checked, this figure using other official data sources, they found a much lower number, raising questions about the reliability of the official estimate.

What’s in Today’s Article?

• Understanding Manufacturing's Two Parts
• The Gap: A 41% Difference
• Where Does the Official Data Come From?
• Checking the Numbers Using Employment Data
• Possible Explanations — And Why They Fall Short

Understanding Manufacturing's Two Parts

• India's manufacturing sector is made up of two segments:
  • The organised sector — registered factories and companies, tracked by the Annual Survey of Industries (ASI).
  • The unorganised sector — small, informal workshops and household units, tracked by the Annual Survey of Unincorporated Sector Enterprises (ASUSE).
• Together, these two surveys should capture almost all of India's manufacturing output.
• So, researchers added up the GVA from both surveys to create an "Alternative Estimate" and compared it with the official figure.

The Gap: A 41% Difference

• The Alternative Estimate, based on ASI and ASUSE data, works out to just ₹27.4 lakh crore — significantly lower than the official ₹38.6 lakh crore.
• That's a difference of nearly 41%, far too large to be explained by minor definitional or methodological differences between surveys.
• Since the unincorporated sector uses the same ASUSE data in both calculations, it cannot explain this gap.
• The unorganised sector, in any case, contributes only about 14% of total manufacturing GVA.
• This means the real mismatch lies somewhere in how the organised (company) sector's output is being calculated.

Where Does the Official Data Come From?

• For the organised sector, the NAS doesn't rely only on ASI data.
• Instead, since the last major revision (base year 2011-12), it has increasingly used company balance-sheet data from the Ministry of Corporate Affairs' database, known as MCA-21.
• This database is built from annual statutory filings that registered companies are legally required to submit — and this practice continues in the latest revision too.

Checking the Numbers Using Employment Data

• One way to sanity-check GVA figures is to look at how many workers are actually employed and estimate what they could realistically produce.
• This is where an interesting discrepancy shows up:
  • The Periodic Labour Force Survey (PLFS) estimates 697.5 lakh workers in manufacturing for 2023-24.
  • But ASI and ASUSE data together account for only 532.9 lakh workers.
  • This leaves 164.6 lakh "residual workers" unaccounted for — likely employed in smaller non-factory companies or informal units too small to be captured by ASUSE
• Using standard production ratios, researchers estimated that these residual workers could plausibly add about ₹3.6 lakh crore in GVA.
• Adding this to the earlier Alternative Estimate of ₹27.4 lakh crore brings the potential total to ₹31.0 lakh crore.
• The Unexplained Gap Still Remains
  • Even after this adjustment, the potential estimate of ₹31.0 lakh crore is still 24.5% short of the official ₹38.6 lakh crore figure.
  • In other words, all identifiable workers — in both companies and informal units — can only account for about 80% of the official GVA estimate.
  • That leaves roughly ₹7.6 lakh crore worth of manufacturing output that remains genuinely unexplained.

Possible Explanations — And Why This Matters?

• The NSO has suggested that ASI, being a factory-based survey, may miss value addition happening outside the factory floor — such as at head offices, in marketing, distribution, or R&D activities.
• However, researchers point out that available evidence does not really support this explanation.
• An alternative possibility is that the NSO's method of scaling up sample data — extrapolating from a sample of companies to represent the entire universe of registered companies — may be inflating the estimate, especially since the true size and composition of India's vast company universe remains unclear and largely unverified.
• Manufacturing GVA is a key input for calculating India's overall GDP.
• Inflated or unreliable estimates can distort our understanding of the economy's real structure and health — affecting policy decisions on industrial growth, employment planning, and sectoral targeting.

Conclusion

The significant, unexplained gap between the official manufacturing GVA and independently verified estimates raises serious questions about India's statistical methodology, especially the use of scaled-up corporate filings.

Resolving this puzzle requires the NSO to make its MCA data and estimation methods public for independent scrutiny — essential for maintaining confidence in India's economic statistics.