Examine the significance of leveraging administrative data (GST, etc.) for economic statistics compilation in India.

Administrative data — records generated as a by-product of governance, such as GST returns, railway and aviation traffic, and banking or insurance filings — is emerging as a second pillar of India's statistical system alongside sample surveys. Its potential is best illustrated by MoSPI's Index of Services Production (ISP), base year 2024-25, which relies primarily on aggregated GST data for market-based services [2].

Filling critical data gaps

• Unlike industry, which the IIP tracks monthly, the services sector had no high-frequency output indicator, creating a gap in assessing overall economic performance [1].
• Services form the largest share of GVA; the ISP proposes to cover sub-sectors from trade and transport to banking, telecom, real estate and professional services [1].

Timeliness and policy responsiveness

• Administrative records arrive monthly and near-real-time, enabling nowcasting of GDP and sharper inputs for monetary and fiscal decisions.
• The first trial ISP for April 2026 covers 19 sub-sectors, about 60% of the services sector, with trial release on 14 July 2026 [3].

Cost, coverage and respondent burden

• Reusing existing tax and administrative datasets avoids costly fresh primary surveys and reduces compliance burden on firms.
• GST's near-universal formal-sector coverage offers a census-like base, unlike sample surveys prone to sampling error.

Concerns the approach must address

• Administrative data captures the formal sector only, leaving India's large informal services economy unmeasured — health and education are to be folded in only later [1].
• Tax data reflects turnover, not volume, requiring careful deflation; a Laspeyres volume index with GVA weights is proposed to address this [3].
• Confidentiality risks are real; MoSPI has clarified it will use only aggregated, not unit-level, GST data [1].
• Definitional mismatch between tax and statistical classifications demands continuous validation.

Administrative data therefore strengthens, rather than replaces, India's survey architecture. The prudent path is the phased, trial-first rollout the Technical Advisory Committee recommended — validating methodology against quarterly and annual datasets before regular publication [3]. Coupled with statutory safeguards on data privacy and gradual extension to informal segments, such data convergence can build a statistical system that is timely, credible and evidence-driven.