India’s new GDP methodology a welcome development: IMF

Washington : The International Monetary Fund (IMF) on Thursday endorsed India's updated gross domestic product (GDP) calculation methodology, describing the base revision as a "welcome development" consistent with its advice.

Krishna Srinivasan, Director of the IMF's Asia and Pacific Department, said the revisions aligned with recommendations from the Fund's statistics department.

"These revisions to the methodology are entirely consistent with what the advice we've been giving them, including from our statistics department," he said.

Srinivasan noted that India had also issued an explanatory note on the changes. While there was room for further improvement, he acknowledged the work done by the Ministry of Statistics and Programme Implementation (MoSPI) to improve GDP statistics.

The IMF official also said India had faced the energy shock with strong economic fundamentals and responded well. Pressure on the rupee should not be interpreted as a sign of economic failure, he said, attributing exchange-rate movements to global interest rates, investor risk appetite and oil prices.

The IMF's Regional Economic Outlook for Asia and the Pacific, released on Thursday, identified India among emerging economies whose currencies came under pressure following the energy shock. It said the pressure had partly eased in recent months and noted that India was among countries that intervened in foreign exchange markets.

The endorsement comes amid a political controversy over India's reported GDP growth of 7.8 per cent in the June quarter. Former Finance Secretary S C Garg had questioned the figures, alleging that growth was artificially boosted by compressing the previous year's data. Opposition parties also questioned the credibility of the statistics.

Chief Economic Advisor V Anantha Nageswaran dismissed Garg's approach as "cherry-picking" data. He said the latest figures used the financial year ending March 2023 as the new base year, with methodological changes leading to revisions in the previous year's quarterly data.

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