The gap in manufacturing sector GVA

Why in the News

An alternative estimate of India’s manufacturing output puts gross value added (GVA, the value a sector adds after the cost of the inputs it consumed is deducted) at Rs 27.4 lakh crore for 2023-24. The National Statistical Office (NSO), in the new National Accounts Statistics (NAS) series, puts the same figure at Rs 38.6 lakh crore. The official number is higher by 40.9 per cent. The alternative estimate is built by adding the Annual Survey of Industries (ASI), the annual production account of the registered factory sector, to the Annual Survey of Unincorporated Sector Enterprises (ASUSE), which covers informal units. The contested input is MCA-21, the Ministry of Corporate Affairs database of annual statutory filings by registered companies, which partially replaced the ASI in the official estimate from the 2011-12 base revision.

How is manufacturing GVA estimated?

1. The sector is measured in two parts: The organised part covers registered factories employing 10 or more workers with power, or 20 or more without power, including registered companies. The other part covers unincorporated workshops and household units outside the corporate and factory sector.
2. One survey covers each part: The ASI reports the production accounts of the factory sector. ASUSE covers the unincorporated sector.
3. The two surveys together are near complete: Their combined output represents almost the whole of manufacturing GVA, so their sum is a usable independent estimate.
4. Corporate filings partially replace the factory survey: The official series uses company balance sheet data from MCA-21 for organised manufacturing. The practice began with the 2011-12 base revision and continues in the latest revision with minor modifications.

Why is the gap traced to organised manufacturing?

1. The official estimate exceeds the survey based one by 40.9 per cent: Rs 38.6 lakh crore against Rs 27.4 lakh crore for 2023-24 at current prices. The official figure is 14.7 per cent of GDP.
2. The informal segment cannot explain the divergence: ASUSE is the source for the unincorporated sector in both estimates. That segment contributes 13.9 per cent of manufacturing GVA.
3. Only the corporate route is left: The divergence must therefore arise in the estimation of organised manufacturing output, where the balance sheet data replaces the survey.

Does the employment check close the gap?

1. A large body of workers is unaccounted for: The Periodic Labour Force Survey (PLFS, the official household survey that measures employment and unemployment) estimated 697.5 lakh manufacturing workers in 2023-24. The ASI and ASUSE datasets together captured 532.9 lakh.
2. The residual is 164.6 lakh workers: These workers produce output that neither survey records, and they are the first candidate for explaining the gap.
3. Companies outside the survey frame are added too: 2,72,534 MCA companies sit outside the 78,618 private companies captured in ASI data. Most of them are likely to be non factory private companies.
4. Their potential output is small: Applying technical ratios, meaning output per worker ratios derived from unit level ASI and ASUSE data, the residual workers and companies add Rs 3.6 lakh crore. The alternative estimate rises to Rs 31.0 lakh crore.
5. A fifth of the official figure stays unexplained: Rs 31.0 lakh crore is 24.5 per cent below the official estimate, at 80.3 per cent of it. Rs 7.6 lakh crore, or 19.7 per cent of official manufacturing GVA, remains unaccounted for.

Why is the official explanation contested?

1. The stated official defence: The ASI is establishment based, so it does not capture value addition that occurs inside an enterprise but outside factory premises, in head office, marketing and distribution, or research and development functions.
2. The evidence cited against it: A 2018 study in the Economic and Political Weekly found that the available evidence does not support that view, so the missing head office value addition cannot carry a gap of this size.
3. The alternative suspicion is the scaling method: The official procedure scales up sample estimates of active companies to the full universe of registered companies. The size and composition of that universe are unverified.

Challenges to the official manufacturing GVA estimate

1. The company universe is unverified: Scaling a sample of active filers onto the full corporate register counts companies that have stopped operating. Eg. The Ministry of Corporate Affairs struck off more than 2 lakh companies from the register in 2017 for failing to file returns.
   The Fix: Publish an annual active company frame reconciled against Goods and Services Tax filings before it is used for scaling.
2. The unit of measurement changes between sources: The ASI counts factories and MCA-21 counts companies, so one firm with several plants enters the two datasets on different terms. Eg. The 2011-12 base revision inserted the company based route into a series that until then rested on the factory based survey alone.
   The Fix: Publish a factory to company concordance so the two frames can be matched establishment by establishment.
3. The methodology is not open to outside checking: Neither the MCA data nor the scaling procedure is available for independent replication, so a disputed figure cannot be settled by evidence. Eg. The National Statistical Commission’s 2018 back series report was withdrawn from the public domain shortly after its release.
   The Fix: Release anonymised unit level MCA-21 data and the full estimation procedure to researchers on a fixed schedule.
4. Informal manufacturing is measured least well: ASUSE misses the smallest own account units, so the segment most exposed to shocks is estimated rather than enumerated. Eg. Output of unincorporated units after the 2016 demonetisation and the 2020 lockdown was inferred from indicators rather than counted.
   The Fix: Run ASUSE at a higher frequency and link it to the Udyam registration database for a live enterprise frame.

Conclusion

Whether the official figure is a fuller description of ground reality or an overestimate of output cannot be settled from outside the statistical system. The dispute has moved from arithmetic to access. Opening the corporate filings and the estimation procedure to independent verification is the only step that would close it. Every downstream number built on manufacturing GVA, from sectoral growth to the investment rate, carries the same doubt until that happens.

Matching Previous Year Question

“[2023, GS3, 10 marks] Faster economic growth requires increased share of the manufacturing sector in GDP, particularly of MSMEs. Comment on the present policies of the Government in this regard.”