The Gap in Manufacturing Sector GVA

UPSC Syllabus: Gs Paper 3 – Indian economy

Introduction

India’s new National Accounts Statistics (NAS), with 2022-23 as the base year, estimates manufacturing GVA at ₹38.6 lakh crore in 2023-24. However, an alternative estimate using Annual Survey of Industries (ASI) and Annual Survey of Unincorporated Sector Enterprises (ASUSE) gives only ₹27.4 lakh crore, creating a 40.9% gap and raising questions about the official estimate.

How is Manufacturing GVA Estimated?

1. Two parts of manufacturing: Manufacturing includes the organised factory sector and unincorporated or informal units, such as small factories, workshops and household enterprises.
2. Factory-sector data through ASI: The Annual Survey of Industries (ASI) provides production, employment and value-added data for registered manufacturing factories.
3. Informal-sector data through ASUSE: The Annual Survey of Unincorporated Sector Enterprises (ASUSE) covers manufacturing units outside the corporate and factory sectors.
4. Combined coverage of ASI and ASUSE: Together, ASI and ASUSE capture almost the entire manufacturing sector, making their combined gross value addition(GVA) useful for checking official estimates.
5. MCA-21 as a major source: The NAS uses MCA-21 company balance-sheet data to estimate organised manufacturing GVA, replacing part of ASI-based estimation since the previous revision.
6. Changes in the 2022-23 base-year revision: The 2022-23 base-year series released in 2026 retains MCA-21, but fine-tunes the method through segregation of activities in multi-activity companies and uses ASUSE instead of earlier five-yearly NSS surveys.
7. Changes in price estimation: The new series uses double deflation where suitable, replacing single deflation to improve the measurement of manufacturing GVA at constant prices.

The Scale and Source of the GVA Gap

1. Official manufacturing GVA: The new NAS estimates manufacturing GVA at ₹38.6 lakh crore in 2023-24 at current prices, equal to about 14% of aggregate GVA.
2. Alternative estimate: The ASI and ASUSE datasets together produce an alternative estimate of ₹27.4 lakh crore, which is ₹11.2 lakh crore or 40.9% below the official figure.
3. Gap cannot be treated as minor: Such a large difference between estimates based on official datasets cannot be explained simply by small definitional or methodological variations.
4. Informal sector is not the main source: ASUSE is common to both estimates, while the unincorporated sector accounts for only 13.9% of total manufacturing GVA.
5. Organised sector creates the main difference: The major source of the gap therefore lies in organised manufacturing, where the NAS relies on MCA-21 company financial data.
6. Enterprise approach behind the shift: The 2011-12 base-year revision introduced the MCA-21-based enterprise approach to capture activities of manufacturing companies beyond individual factory establishments.
7. Continuation in the new series: The 2022-23 base-year revision of 2026 continues this MCA-21-based approach with limited methodological changes, making its treatment central to the present GVA debate.

Can Residual Workers and Companies Explain the Gap?

1. Employment-based validation: Potential manufacturing output can be estimated from employment by applying technical ratios derived from ASI and ASUSE data.
2. PLFS employment estimate: The Periodic Labour Force Survey (PLFS) 2023-24 estimates 697.5 lakh manufacturing workers, compared with 532.9 lakh workers represented in ASI and ASUSE.
3. Residual workers: PLFS estimates 697.5 lakh workers, while ASI and ASUSE account for 532.9 lakh, leaving 164.6 lakh residual workers, may therefore explain part of the GVA gap.
4. Employment data are not identical: PLFS, ASI and ASUSE use different employment definitions and collection methods, but PLFS still provides a useful reference for checking the official GVA.
5. Residual MCA-21 companies: MCA-21 has 3,51,152 active private non-financial manufacturing companies, while ASI covers 78,618 private companies, leaving 2,72,534 residual companies outside ASI coverage.
6. Uncertain operational status: A 2019 NSSO Technical Report found that 36% of MCA-21 companies in a services-sector exercise were closed, untraceable, unwilling to provide information or misclassified.
7. Estimated working residual companies: Since 36% of the 2,72,534 residual companies may be non-working, the remaining 64%, which is equal to 1,74,422 companies, are considered potentially working.
8. GVA of residual companies: The technical ratios for private non-factory companies, derived from unit-level ASI data, are applied to the 1,74,422 potentially working residual companies, giving 15.6 lakh workers and ₹1.9 lakh crore GVA.
9. GVA of remaining workers: The remaining 149.1 lakh residual workers are considered part of the unincorporated manufacturing sector; applying the GVA-per-worker ratio derived from ASUSE data gives ₹1.7 lakh crore GVA.
10. Total residual contribution: The ₹1.9 lakh crore GVA from residual companies and ₹1.7 lakh crore from the residual unincorporated sector together give ₹3.6 lakh crore.
11. Potential manufacturing GVA: Adding ₹3.6 lakh crore of potential GVA to the ₹27.4 lakh crore alternative estimategives ₹31.0 lakh crore.

The Unexplained Gap: Methodological Concerns

1. Large gap still remains: After adding ₹3.6 lakh crore to the ₹27.4 lakh crore alternative estimate, potential GVA reaches ₹31.0 lakh crore, which is ₹7.6 lakh crore below the official ₹38.6 lakh crore estimate; this difference is 24.5% of the potential GVA.
2. Unexplained GVA: The potential GVA of ₹31.0 lakh crore accounts for 80.3% of the official ₹38.6 lakh crore GVA, leaving ₹7.6 lakh crore, or 19.7%, unexplained.
3. NSO’s explanation: The NSO argues that ASI may miss value addition occurring outside factories, such as head-office, R&D, marketing and distribution activities, which MCA-21 may capture.
4. Evidence challenges the ASI explanation: Field-based evidence suggests ASI already captures employment, investment and value addition from activities outside factory premises when they belong to the enterprise.
5. Possible MCA scaling-up problem: Another explanation is that MCA-21 sample estimates may be scaled up to an uncertain universe of active companies, whose actual size and composition are unclear.

Way Forward

1. Open MCA-21 data: The Ministry of Corporate Affairs (MCA-21) data used for manufacturing GVA estimation should be made available for independent examination.
2. Disclose estimation methods: The NSO should provide detailed methods used to convert MCA-21 company data into manufacturing GVA estimates.
3. Enable independent validation: Researchers should be able to compare MCA-21, ASI, ASUSE and PLFS data to verify the official manufacturing GVA estimate.
4. Resolve the methodological dispute: Independent scrutiny can establish whether the higher MCA-21-based estimate reflects better production coverage or possible overestimation.
5. Restore confidence in official data: Greater transparency and independent verification can strengthen public confidence in GDP and sectoral GVA estimates.

Conclusion

The new 2022-23 base-year series gives manufacturing GVA of ₹38.6 lakh crore, but the ASI-ASUSE estimate gives only ₹27.4 lakh crore. Even after accounting for residual companies and workers, ₹7.6 lakh crore remains unexplained. The key issue is whether MCA-21 improves coverage or causes overestimation. Opening data and methods for independent verification is therefore essential to establish the estimate’s credibility.

Question for practice:

Examine the reliability of India’s manufacturing sector GVA estimates and the reasons behind the gap between official and alternative estimates.

Source: The Hindu