The press release issued on 31 August 2026 places India’s first quarter 2026-27 GDP in current prices at Rs 88.27 trillion. The same press release estimates India’s first quarter 2025-26 GDP in current prices at Rs 80.00 trillion. This yields growth of 10.3 percent.

The first quarter GDP for 2024-25 has been estimated at Rs 74.03 trillion, making the Q1-2026 growth of GDP in current prices 8.1 percent. The Q1-2027 GDP growth at 10.3 percent is certainly higher than growth of 8.1 percent in Q1-2026, given higher inflation in the current year.

Government growth estimates/claims go for a toss drastically the moment you compare this year’s GDP (in current prices) with that of GDP (in current prices) for the same quarter announced last year. The GDP of Rs 88.27 trillion in Q1-2027 is only 2.6 percent higher than the GDP of Rs 86.05 trillion in Q1-2026. Yes, only 2.6 percent.

That lowly growth shows an awfully poor GDP performance in the Q1-2027 in current prices. If you take even a 2 to 2.5 percent inflation/deflator factor in the 2026-27 first quarter over the same quarter last year, the real GDP growth completely disappears, reducing it to zero (not 7.8 percent as claimed).

The government has been using this toolkit for the last few years, of over-projecting GDP in the concerned current year by showing high GDP growth in current prices and low or no inflation. In 2024-25 also, the Q1 GDP in current prices, which was announced at Rs 70.25 trillion in the press release of August 2024, has been reduced to Rs 66.81 trillion. 

It may be recalled that the government had revised down the 2023-24 GDP (current prices) by as much as Rs 11.4 trillion (from Rs 301.23 trillion to Rs 289.73 trillion) when the new series of GDP was issued earlier this year. 

The method is simple. Revise down the GDP of the year gone by to show the present year’s performance in much better colours. No one cares to see this revision of last year’s numbers, is the time tested belief. Don’t be surprised if the 2026-27 first quarter GDP is revised down next year (in August 2027) to show the 2027-28 Q1 performance better. 

If one were to compare the Q1-2027 performance for the eight GVA sectors against their claimed GVAs last year, a messy and horrifying picture emerges. 

Agriculture, mining, and electricity sector GVA growth shoots up sharply (much higher than what the MoSPI press release says). Agriculture had GVA of Rs 12.00 trillion in Q1-2026. It has grown to Rs 14.00 trillion in Q1-2027, giving a year-on-year (YoY) growth of 16.7 percent. Mining GVA grew from Rs 1.36 trillion to Rs 1.78 trillion, generating growth of 31 percent. Electricity GVA went up from Rs 2.04 trillion to Rs 2.29 trillion, yielding a growth of 12.2 percent.

The worst performance is in:

  • Manufacturing

  • Trade, hotels, transport, communications, services groups

  • Public administration sectors

The downward revision of their GVA in Q1-2026 from Rs 10.92 trillion to Rs 9.61 trillion, from Rs 12.28 trillion to Rs 10.53 trillion and from Rs 12.17 trillion to Rs 9.96 trillion respectively has led to improvement in their GVA growth from -5.2, -2.2 percent and -9.2 percent (actual) respectively to a high of 7.7 percent, 14.0 percent and 11 percent (as claimed in the 31 August press release) respectively.

On the expenditure side, the major downward adjustment has been made to private consumption (PFCE). It has been revised for Q1-2026 from Rs 51.87 trillion to Rs 44.66 trillion, resulting in a negative consumption growth of as much as -5.4 percent in relation to the PFCE of Rs 49.08 trillion. That perhaps explains why the pain of weak consumption felt in real life has got hidden in these restated numbers.

The gross capital formation expenditure (GFCE), having been revised down marginally, would have still yielded impressive growth of 15.5 percent as against 20.4 percent claimed by MoSPI.

Why did MoSPI decide to revise down the sectoral GVA for Q1-2026 so sharply and violently? The current GDP/GVA numbers are not supposed to vary so widely as these are sourced from the actual corporate and other government data. Did the selective application of double digit deflator do the trick or there were some other motivations at work?