Updated GDP Series

On 31 August 2026, the updated series of annual and quarterly GDP estimates with 2022-23 as the base year was released. The estimates incorporate the new Output Producer Price Index and Banking Services Price Index, both based on 2022-23, along with updated administrative data.

Two concepts are important in the latest GDP series: revision of the base year and adoption of double deflation for manufacturing.

. The base year in National Accounts Statistics provides the reference prices used to calculate real growth.  It is revised periodically to reflect structural changes and ensure relative prices remain representative of current economic conditions.

. The updated GDP series reflects an improved and more robust methodology.   The double deflation method is adopted for various industries under the manufacturing sector. Under this, output and intermediate consumption are deflated separately to derive GVA at constant prices.  

IMF describes double deflation as the preferred method for calculating GDP in volume terms.

To read more about India’s GDP Performance in Q1 2026-27, please refer to: India’s GDP Performance

To read more on India’s National Accounts Statistics revisions, please refer to: Counting What Counts: Strengthening India’s National Accounts and Core Economic Statistics

Deflation Methodology

1. How can the manufacturing sector record a negative inflation in GVA implicit deflator of “-1.5%” in Q1, 2026-27 despite increase in both manufacturing output and input prices while the agricultural sector recorded a positive inflation rate of 3.9%?

Understanding Double Deflation: Under the double-deflation approach, output and intermediate consumption of the manufacturing sector are deflated separately. The real GVA is obtained as real output minus real intermediate consumption. Therefore, when input prices increase faster than output prices, the relative price movement can result in nominal GVA growing more slowly than real GVA.

Consequently, the implicit GVA deflator, which is derived by comparing nominal GVA with real GVA, can show negative inflation even though both output and input prices are rising.

Importantly, a negative GVA deflator does not mechanically imply lower real growth. Real GVA growth depends on the relative movements in real output and real intermediate consumption.

A negative inflation in implicit deflator in manufacturing does not mean that manufacturing prices have fallen. It is important to distinguish between the price deflators of output and inputs and the implicit Gross Value Added (GVA) deflator.

An illustration to understand the above scenario is given below:

	Year 1	Year 2	Growth Rate
Gross Value of Output	1,000 Cr	1,200 Cr	20.0%
Intermediate Consumption	800 Cr	976 Cr	22.0%
Nominal Gross Value Added (Current)	200 Cr	224 Cr	12.0%
PPI Output Index	100	110	10.0%
PPI Input Index	100	114	14.0%
Deflated Output (Constant)	1,000 Cr	1,091 Cr	9.1%
Deflated Inputs (Constant)	800 Cr	856 Cr	7.0%
Real Value Added (Constant)	200 Cr	235 Cr	17.5%
Current Price Growth Rate (%)	12.0%
Constant Price Growth Rate (%)	17.5%

As per illustration, nominal GVA grows by 12%, while real GVA grows by 17.5%, resulting in a negative implicit GVA deflator. It reflects the relative movement of output and input prices under double deflation.

In Q1, 2026-27 manufacturing GVA is compiled using the double-deflation approach, under which output and intermediate consumption are separately deflated. During this period input prices increased faster relative to output prices. As a result, nominal GVA growth for this sector was relatively lower at 7.7%, while real GVA growth was 9.2%. The resulting difference between nominal and real GVA growth produced a negative implicit GVA deflator of 1.5%.

For example, some of the activities where the growth of input prices was found more than that of output prices are manufacturing of textile and cotton ginning, manufacturing of basic metals, manufacturing of rubber and plastic products, etc.

OECD Research Papers highlight that countries using double deflation frequently experience volatile or negative implicit deflators in manufacturing during global energy and raw material shocks. Advanced economies that depend heavily on imported raw materials regularly experience negative manufacturing deflators when international supply chains fluctuate.

At Quarterly level, Agriculture GVA is compiled at constant price first using the production estimates. Current Price estimates of Agriculture GVA is then derived by inflating the Constant Price estimates using the relevant Producer Price Index.

During Q1, 2026-27, the output Producer Price Index for Agriculture, Forestry and Fishing group rose by approximately 5%. Since the output prices rose and agricultural nominal GVA is heavily driven by these output prices, its implied inflation remained positive at 3.9%.

2. How does the mechanism of double deflation apply to Private Final Consumption Expenditure (PFCE), and does it enter PFCE calculations directly?

The mechanism of double deflation does not directly enter the calculation of PFCE.

Double deflation is a production-side technique used to estimate the GVA of an industry at constant prices by deflating gross output and intermediate consumption separately. Because PFCE is a measure of final demand (expenditure on goods and services for final use), it has no intermediate consumption to subtract.

At the quarterly level, PFCE is estimated at a detailed item/item-group level. For various goods such as food and manufactured products, constant-price estimates are compiled first using appropriate volume indicators, and current-price estimates are subsequently derived using relevant Consumer Price Indices.

For several services items under PFCE, such as education, health, restaurants and accommodation services, current-price estimates are compiled using relevant output indicators and the corresponding constant-price estimates are derived using appropriate price indices.

Thus, double deflation is relevant to the estimation of production-side GVA and is not a method used directly for estimating PFCE.

Understanding Nominal and Real Estimates

1. How do we reconcile a 2.5% implied GDP inflation rate when consumer inflation (CPI) was 3.9% and wholesale inflation (WPI) was over 9%?

This price divergence is reconciled by understanding that the GDP deflator is an implied price of net value added, not a direct measure of transaction prices. There is no inconsistency because the GDP deflator, CPI and WPI measure different aspects of the economy and have different coverage and weights.

The baskets of goods used to measure these economic indicators vary according to their purposes:

CPI (Consumer Price Index): Reflects price changes of only a specific basket of household consumption of goods and services at the final consumer’s end.

WPI (Wholesale Price Index): Reflects price changes of bulk commodities, raw materials, and manufactured goods excluding services at the wholesaler’s level.

Implicit GDP Deflator: It is the ratio of GDP at current prices and GDP at constant prices and it covers the entire economy, including government spending, corporate investments, exports, and financial and non-financial services (like banking, IT, and real estate). Since raw material prices were very high and certain service sector inflation is very low, it diluted the high inflation seen in the consumer or wholesale commodity sectors.

The implicit GDP deflator need not move in line with either CPI or WPI. Differences in coverage, weights, price concepts and the relative performance of different sectors of the economy can result in the GDP deflator being significantly different from consumer or wholesale inflation.

Note: Deflation of individual item/group of items is done using the relevant price indices for that item/item-group. The implicit GDP deflator is only a derived number reflecting the price impact of more than 300 individual price deflators used at the item/item-group level.

2. Why there is massive gap between Nominal GVA and Real GVA estimates of Mining sector?

In the Quarterly GDP compilation, the constant price estimates of the Mining & Quarrying sector are compiled using the relevant Index of Industrial Production (IIP) as the volume indicator. During Q1 (April-June) 2026-27, the IIP growth for Mining & Quarrying was -3.8% in April, -1.4% in May and 1.6% in June.

Table-1: Growth Rate in IIP
Description	April-26	May-26	June-26
Mining & Quarrying	-3.8	-1.4	1.6
(a) Fuel Minerals	-5.6	-6.1	-1.8
(b) Metallic Minerals incl. Rare Earth Mineral	12.4	18.3	39.4
(c) Non-Metallic Minerals incl. Minor Mineral	-10.3	-6.1	-11.7

This is broadly consistent with the -2.4% growth in real GVA of the Mining & Quarrying sector during Q1 2026-27.

The nominal estimates are derived by applying the relevant Producer Price Indices (PPI) to the corresponding real estimates for different mineral groups.

The PPI data for Q1 2026-27 indicate significant price increases in the Mining & Quarrying sector. In particular, prices of Crude Petroleum and Natural Gas increased by 69.5% in April, 72.2% in May and 33.7% in June, while Mining of Metal Ores recorded inflation of 27.6%, 25.2% and 23.5%, respectively.

Table-2: Inflation based on PPI
Commodity Name	April-26	May-26	June-26
Mining & Quarrying	22.0	21.2	15.5
(A) Mining of Metal Ores	27.6	25.2	23.5
(B) Mining of Coal and Lignite	-1.6	-2.3	-1.6
(C) Other Mining and Quarrying	6.9	6.5	8.7
(D) Extraction of Crude Petroleum and Natural Gas	69.5	72.2	33.7

The nominal GVA growth of the Mining & Quarrying sector accordingly stood at 22.3% in Q1 2026-27.

The substantial difference between real and nominal GVA growth doesn’t reflect an inconsistency between the real and nominal estimates. It is primarily a result of the strong increase in mineral prices, particularly crude petroleum and natural gas and metal ores.

Revisions and Statistical Reconciliation

1. Last year’s Current GDP has been revised down from Rs. 86 lakh crore to Rs. 80 lakh crore, to make current year’s GDP look better.  If last year’s number had not been revised, the growth would have been 2.6% in Current prices.

The comparison of the Q1 GDP estimates needs to be understood in the context of the revisions made to the GDP series. The change in the estimate of Q1 2025-26 does not represent a downward revision made to make the current year’s growth appear higher. It reflects successive methodological and data revisions to the GDP series.

Benchmark-indicator approach: The Quarterly GDP estimates are compiled using the benchmark-indicator approach, under which the movement in the quarterly estimates is guided by the movement in relevant high-frequency indicators.

A revision in the previous-year benchmark does not, by itself, create an artificial increase in the current year’s underlying economic activity or the indicators used for estimation.

In the quarterly series more than hundreds of volume or value indicators are used. To mention a few, some of the volume indicators used are, viz., growth in crop production, growth in cement production index, growth in finished steel consumption, growth in sales in commercial vehicles, etc.

• 29 August 2025: Q1 2025-26 GDP at current prices was estimated at ₹86.05 lakh crore under the then prevailing 2011-12 base-year series.
• February 2026: With the introduction of the 2022-23 base-year series, the estimate was revised to ₹80.32 lakh crore, reflecting updated data sources, improved methodologies, revised coverage and other relevant information.
• 5 June 2026: The Q1 2025-26estimate was further updated to ₹80.44 lakh crore with the release of the Provisional Estimates for 2025-26. Thus, reflecting the availability and updation of indicators and data.
• Subsequently: Incorporation of the new series of IIP and PPI series led to a further revision, taking Q1 2025-26 GDP at current prices to ₹80.00 lakh crore.

It is incorrect to interpret the difference as a deliberate downward revision of last year’s GDP to mechanically increase the current year’s growth rate. The movement from ₹86.05 lakh crore to ₹80.00 lakh crore is the result of successive revisions to the GDP series arising from the change in base year, incorporation of improved data sources and methodologies, and updation of available indicators.

Most importantly, the ₹86.05 lakh crore estimate from the old 2011-12 series cannot be directly compared with the current Q1 2026-27 estimate under the revised 2022-23 series. Rather, the growth rates are calculated using estimates from the same and latest comparable GDP series i.e., with base 2022-23.

Thus, the relevant comparison for Q1 2026-27 of Rs 88.27 lakh crore would have been with the earlier Q1 2025-26 estimate of ₹80.32 lakh crore, and not with the old ₹86.05 lakh crore estimate from the superseded series.

2. As the discrepancies are high in both current and constant price GDP estimates during Q1, 2026-27, does it mean the GDP estimates will be revised significantly in the next revision round when discrepancies get adjusted?

The Q1 2026-27 estimates are based on the information available at the current stage and are subject to revision as more comprehensive and updated source data become available. As additional information is incorporated, estimates under the different approaches may change and, consequently, the statistical discrepancy may also change.

The discrepancy is a statistical balancing item arising from the difference between the GDP estimates compiled through the production and expenditure approaches. Its movement should therefore not be interpreted, by itself, as evidence that the reported GDP is understated or overstated. Therefore, while the current discrepancy may change in subsequent revision rounds, it cannot be concluded in advance that GDP will necessarily be revised upward, or by a specific magnitude.

The direction and magnitude of any revision will depend on the revisions to the underlying production and expenditure-side estimates, rather than on a mechanical adjustment of the discrepancy alone.

At the time of release of final estimates at current prices, the discrepancies will be very insignificant or zero as was found in case of FY2022-23 and FY 2023-24.

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PIB Research

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