Measuring manufacturing growth afresh: Three questions

Why in the News

The new Gross Domestic Product (GDP) series of the Ministry of Statistics and Programme Implementation (MoSPI) shows the manufacturing Gross Value Added (GVA) deflator recording negative growth for nine consecutive quarters between 2023 and 2025. The same series places the level of real manufacturing GVA in 2025-26 at no less than 15 percentage points above the Index of Industrial Production (IIP) for manufacturing. When the new series was announced, the Chief Economic Advisor and the Secretary, MoSPI stated that the estimates rested on a new methodology. That methodology was said to have solved the measurement problems that had bedevilled the old series, including in manufacturing. MoSPI has not yet released the detailed standard document explaining the new calculations. Three specific anomalies in the manufacturing numbers therefore cannot be tested against the stated method, and the plausibility of the series has to be assessed from the numbers themselves.

What is the manufacturing Gross Value Added deflator?

1. Gross Value Added, defined: GVA for a sector is the value of its output minus the value of its intermediate inputs. It measures what producers in that sector actually added, before taxes on products are added and subsidies subtracted.
2. What the deflator does: The sector deflator is the price index that converts nominal GVA at current prices into real GVA at base year prices. Real GVA equals nominal GVA divided by that deflator.
3. What its movement signals: A deflator growing negatively means the sector’s own price level is falling. Real growth then runs ahead of nominal growth by the size of that fall.

Why does confidence in manufacturing data matter now?

1. The China Squeeze: The Chinese manufacturing export machine has again moved across world markets and threatens lower-skill manufacturing in poorer countries. The pressure this creates on Indian producers is what the data is being asked to measure.
2. Two decades of stated ambition: The Union government set major ambitions for the sector, beginning with the flagship Make in India programme in 2014. The production-linked incentive (PLI) scheme followed several years later.
3. The PLI’s dual purpose: The scheme was in part a response to the opportunities opened by the China-plus-one shift in global sourcing. It was also a response to the challenge of aggressive Chinese competition.
4. Conflicting signals elsewhere: The wider economy is sending contradictory signals at present. Understanding manufacturing performance is the route to lifting some of that confusion.
5. A recognised prior problem: Problems in manufacturing sector data under the previous series were widely recognised. MoSPI made strenuous efforts to address them in the new series.

Why has the manufacturing deflator shown falling prices for nine straight quarters?

1. The anomaly itself: The manufacturing GVA deflator records negative growth, meaning falling price levels, for nine consecutive quarters between 2023 and 2025. No comparable stretch of deflation appears anywhere else in the price data for that period.
2. The core inflation test: The core Consumer Price Index (CPI), which excludes food and energy-related products, shows no sign of deflation across those quarters. Core CPI through December 2025 rests on the 2011-12 series and the March 2026 reading on the 2024 series.
3. The wholesale price defence, and its limit: The wholesale price index (WPI) was negative for some of this period. It was not negative for nine consecutive quarters.
4. Why WPI is the wrong benchmark anyway: The GVA deflator should not move in line with the WPI. The WPI is overly driven by input prices, and a value added deflator must reflect output prices net of inputs.

Why is real GVA growth almost twice IIP growth?

1. The size of the gap: In 2025-26 the level of real manufacturing GVA exceeded the IIP by no less than 15 percentage points. Both series are measured on the 2022-23 base.
2. The growth gap it implies: Annual average real growth of manufacturing between 2022-23 and 2025-26 measured by GVA is about twice that measured by the IIP. The two figures are about 11 per cent against about 6 per cent.
3. The informal sector explanation, and why it fails: Real GVA includes the informal sector and the IIP excludes it, so faster informal growth could in principle open a gap. For the most recent two years informal sector performance has been proxied by formal sector data, which makes the explanation mechanically impossible.
4. The volumes versus value added explanation: The IIP measures output volumes rather than value added. A widely held perception holds that real GVA can grow faster than real output when input prices fall.
5. Why that perception is wrong: Real GVA is calculated at constant prices, not at changing prices, so falling input prices cannot lift it. Real value added can grow faster than output volumes only where productivity improves, that is where firms become more efficient in using intermediate inputs.

Why has the link between the two series broken down?

1. The pre-2011 benchmark: Before the 2011-12 methodology changes, GVA and IIP moved closely together. The correlation between their growth rates over June 2005 to that break was 0.8.
2. The post-2011 divergence: The two series diverged after the 2011-12 methodology changes. That divergence has been exacerbated in the new series rather than corrected by it.
3. The recent segment: Since September 2022 the two series move very differently. The comparison excludes the Covid quarters from June 2020 to March 2022.
4. The character of the difference: The real GVA series bounces around a great deal across quarters. The IIP series over the same stretch is fairly stable.

What do the three questions together say about the new series?

1. None is individually decisive: No one of the three issues is dispositive about the quality of the new series. Each is an unexplained pattern rather than a demonstrated error.
2. The missing document is the binding constraint: The detailed standard document explaining the new calculations has not been released. Independent researchers therefore cannot check the anomalies against the method that produced them.
3. The methodology claim raises the bar, it does not lower it: The new series was presented as the fix for exactly the manufacturing measurement problems of the old series. Anomalies concentrated in manufacturing are the hardest place for that claim to sit unexplained.
4. What plausible explanations would buy: Explanations would engender confidence in the new GDP figures. They would also allow an assessment of the state of Indian manufacturing and of the impact of recent government actions to revive it.

Challenges to the new GDP series’ manufacturing estimates

1. Deflator choice drives the real number: Real GDP requires choosing a deflator, and the production side deflator is heavily influenced by the WPI. Eg. In FY23 a global commodity price surge pushed the WPI into double digits, and the high deflator suppressed measured real growth. Fix. Complete the WPI base revision so the deflator basket reflects the current price structure.
2. No producer price index exists: India deflates goods sectors with a wholesale index built for trade flows rather than for producer output. Eg. Services sectors are deflated using CPI components because no dedicated producer price series covers them. Fix. Introduce a Producer Price Index on the model used across advanced statistical systems and retire WPI-based deflation.
3. Transparency lags the release: The estimates reach the public well before the sources and methods behind them. Eg. The new series arrived with a stated methodology claim and without the standard explanatory document. Fix. Publish the sources and methods volume alongside the series so verification is concurrent with release.
4. Informal output is still partly extrapolated: Informal sector performance for recent years is proxied from formal sector data, which cannot capture divergence between the two. Eg. The old series extrapolated large-company filings to the whole informal economy and stayed blind to the sharper hit small firms took after demonetisation. Fix. Shorten the lag on the Annual Survey of Unincorporated Sector Enterprises so proxying is not required for two full years.
5. Statistical independence has been questioned: Resignations from the National Statistical Commission and withheld survey results have raised concerns about the autonomy of official statistics. Eg. Two members of the Commission resigned in 2019 over the handling of employment data. Fix. Constitute an independent statistical commission with a statutory mandate, as recommended by the Rangarajan Commission in 2001.

Conclusion

The new GDP series was presented as the answer to the manufacturing measurement problems of the old one, and its manufacturing numbers now carry three patterns that the stated methodology does not obviously produce. A deflator falling for nine quarters, a 15 percentage point level gap against the IIP and a correlation that has weakened since 2005-2012 are each testable claims that cannot be tested without the sources and methods document. Releasing that document is the precondition for confidence in the figures. Whether and how Indian manufacturing has stood up to Chinese competition is a question only reliable data can answer.

What is National Income Accounting?

1. About: National Income Accounting is the set of methods used to measure economic activity in a national economy as a whole. It yields the headline indicators of GDP, Gross National Product and National Income.
2. Rationale: Governments rely on national accounts to design fiscal and monetary policy and to allocate resources across sectors. Per-capita income drawn from these accounts is the standard gauge of living standards.
3. The three methods it rests on: The income method sums factor incomes of rent, wages, interest, profit, mixed income and net income from abroad. The expenditure method totals consumption, investment, government spending and net exports.
4. The third method, and the one manufacturing uses: The production method sums value added at each stage across agriculture, industry and services. It is the route through which sector deflators enter the calculation.

Government Initiatives in Statistical Measurement

1. The 2022-23 base revision: The GDP base year was revised from 2011-12 to 2022-23, with the new series released on 27 February 2026. The CPI base was updated to 2024 and the IIP base to 2022-23 alongside it.
2. Administrative data replacing proxies: Goods and Services Tax data is now used more widely across sectors and the Public Financial Management System covers central government accounts. E-Vahan estimates transport spending in place of an indicator-based estimate.
3. Supply and Use Tables: The Supply and Use Table framework balances production against consumption across the accounts. It exists to minimise statistical discrepancies between the two sides of the estimate.
4. Direct State estimates and new coverage: States now measure their own activity instead of relying on national-level splits. Intermediary platforms and gig workers are captured systematically beyond the corporate sector.

Challenges in National Income Accounting

1. Data accuracy in the unorganised sector: Reliable collection is hardest in the large informal and unorganised segments of the economy. Eg. Small shops, roadside vendors and repair workshops sit outside formal registration entirely. Fix. Institutionalise the Annual Survey of Unincorporated Sector Enterprises on an annual cycle with a fixed release calendar.
2. Double counting of intermediate goods: Distinguishing final goods from intermediate goods is difficult at the point of collection. Eg. Flour bought by a bakery is an intermediate input and the same flour bought by a household is a final good. Fix. Extend Supply and Use Table reconciliation to more sectors so intermediate flows are netted out systematically.
3. The black money gap: Parallel economies and undisclosed incomes are kept off the record and produce systematic under-reporting. Eg. Cash-intensive trade in real estate and gold routinely escapes the transaction trail national accounts rely on. Fix. Integrate real-time payment data from the Unified Payments Interface, the Government e Marketplace and FASTag into the accounts.
4. Environmental depletion is not counted: GDP counts resource extraction as income and records no charge for the depletion of natural capital. Eg. Groundwater drawdown in Punjab raises measured agricultural output and never appears as a cost. Fix. Publish a Green GDP series that subtracts resource depletion and pollution costs from the headline figure.
5. Non-market activity is excluded: Subsistence farming, barter, volunteer work and the care economy go uncounted, understating true output. Eg. Unpaid domestic and caregiving work performed overwhelmingly by women enters no national account. Fix. Build a satellite account for unpaid work off the Time Use Survey and publish it alongside the annual estimates.

Matching Previous Year Question

“[2021, GS3, 10 marks] Explain the difference between computing methodology of India’s Gross Domestic Product(GDP) before the year 2015 and after the year 2015.”