Discuss the potential and challenges of using GST data for official statistics in India, with reference to the Index of Services Production.

Services make up nearly 53% of India's GVA [1], but until 2026 there was no monthly measure of their output. The trial Index of Services Production (ISP), released by NSO-MoSPI from July 2026, uses GST data for statistical purposes for the first time [2]. This is a major reform in data governance, but its value depends on fixing some clear gaps in what the data can show.

Potential of GST data

• High frequency, short lag: GST returns are filed every month, so ISP can be released about 60 days after the month it covers. Services are consumed as they are produced, so sales closely track output [2].
• Wide coverage: GST data feeds 15 of the 19 trial sub-sectors, including trade, telecom, real estate and IT [2].
• No extra cost to firms, privacy protected: the data is already collected for tax, so businesses report nothing new. MoSPI receives only aggregated data, never firm-level data [1].
• Universe approach: the index counts all GST filers, not a fixed panel of firms, so it picks up firms opening and closing [4].
• Useful policy signals: in July 2026, retail trade grew 18.5% while air transport fell 8.4% [3]. Breakdowns like this help the RBI and ministries, and feed into GDP estimates.

Challenges

• Formal-sector bias: firms with turnover below ₹20 lakh (₹10 lakh in some North-Eastern states) do not have to register [4]. So the informal sector is left out [2].
• Partial coverage: the excluded sub-sectors make up nearly one-third of services GVA [4]. GST-exempt services such as health, education and most of railways need other data sources [1].
• Formalisation mistaken for growth: under the universe approach, a firm newly registering for GST enters the index as if it were new production [4].
• Weak price correction: GST gives only money values, not real volumes. Service producer price indices (SPPIs) exist for only five sub-sectors, and only every quarter, so general CPI measures are used instead [2][4]. CPI prices include GST, so a change in the GST rate distorts measured real output [4].
• Weights and volatility: the temporary turnover-based weights give too much importance to high-sales, low-margin trade, and some GST categories are "very volatile" [4].

GST has turned a tax system into a statistical asset and given India's largest sector its first monthly measure. The trial phase should be used to fix the known weak points: monthly SPPIs from DPIIT, monthly reporting by line ministries, and ASISSE/ASUSE survey coverage of health, education and informal units [4]. This would bring ISP in line with OECD practice and support the aim of timely, reliable data under SDG target 17.18.