What if we could track the economy in near real time, with the same speed and detail that financial markets track stock prices? The data already exists; the goods and services tax (GST) system is a gold mine. It's time to tap this opportunity.

From tax collection to economic nowcasting: When GST was rolled out in 2017, it replaced a maze of central and state levies with a unified, multi-stage, destination-based tax system. This also created one of the richest data-sets in the country.

Also Read: Mint Quick Edit | Market buoyancy: Thank GST expectancy

Each registered business has a GST identification number linked to its Permanent Account Number (PAN). For companies in the organized sector, PAN can be matched to the registration database of the ministry of corporate affairs (MCA) with the Corporate Identification Number (CIN) and National Industrial Classification (NIC) code, making it possible to connect GST data with a company's industry classification.

For the non-corporate sector, the GST system does not capture NIC codes directly; it only records the Harmonized System of Nomenclature (HSN) codes for goods and Services Accounting Code (SAC) for services. Unless a one-to-one mapping between NIC and HSN/SAC is established, industry classification for this segment will remain an approximation. GST returns, however, still record sales and purchases down to the invoice level, providing detailed product- and service-level data.

This covers most of India's non-agricultural economy—from small traders to large firms—across states and districts. Its strength lies not just in its breadth, but in its frequency: collections are published monthly, making GST India's only high-frequency administrative data-set covering the bulk of its economy. Yet, it is treated mainly as a fiscal tool for tax mobilization. That is like using a satellite only to measure rainfall, when it could also track deforestation, urban growth or climate change.

Also Read: GST 2.0: A tax reform that could deliver a more competitive India

The evidence is compelling: Our analysis of quarterly GDP and GST collections shows GST growth moving in lockstep with non-agricultural GDP growth. This held true during the pandemic's shock and the rebound later, making GST a natural 'early warning system' on the economy's health.

Its predictive power is even more compelling if we look at recent data. In the first quarter of 2025-26, GST collections grew 16% year-on-year. Based on historical correlations, that level of GST growth points to a predicted non-agricultural nominal GDP growth rate of about 12%. Policymakers can see this signal months before the official quarterly GDP data is released, which makes it a valuable head-start in adjusting policy levers.

More than just topline growth: GST data can revolutionize economic monitoring in multiple ways:

Sectoral/sub-sectoral performance: Linking GST's HSN/SAC codes to the NIC can provide monthly industry-specific trends.

Consumption mapping: As a destination-based tax, GST reveals where demand is strongest. Normalizing the data by population would help identify per capita consumption gaps across states and track shifts over time.

Also Read: Scrapping GST on insurance premiums: A remedy worse than the disease?

Informal sector visibility: With the GST regime's turnover thresholds of ₹40 lakh for goods and ₹20 lakh for services, it captures a significant slice of the unincorporated sector. Combined with the Annual Survey of Unincorporated Sector Enterprises (ASUSE), it can provide quarterly visibility into a segment otherwise captured only annually.

Why isn't this already happening? India has the digital infrastructure. The barriers are institutional and procedural:

Privacy: Taxpayer data is sensitive and must be protected.

Classification mismatches: HSN/SAC codes don't map neatly onto NIC codes.

Compliance gaps: Late or incomplete filings can distort aggregates.

Institutional silos: We have limited coordination among the ministries of statistics and finance, the Central Board of Indirect Taxes and Customs (CBIC), the GST network and state directorates of economics and statistics (i.e., DES offices).

Other countries have overcome such hurdles. Brazil uses electronic invoice data for regional GDP estimates. Estonia integrates tax and statistics platforms for real-time indicators. With political will and institutional alignment, we can do so too.

Also Read: Mint Quick Edit | GST 2.0: Reform at long last

A few targeted steps can unlock GST's promise.

An inter-agency task force: Bring together the Department of Economic Affairs, CBIC, GSTN,  statistics ministry and state governments to align classifications, validate data and map HSN/SAC codes onto NIC and Central Product Classification.

Automated updating: Integrate NIC-2008 codes into GST filings, with annual updates from the  corporate affairs ministry's filings for registered companies.

Data sharing protocols: Build secure frameworks to balance privacy with policymaking utility.

As India prepares for major GST reforms—including tax slab and exemption changes—headline collections will inevitably fluctuate. While revenues rise or fall with tax rates, business turnover reported in GST returns does not. That turnover, published monthly or quarterly, would give policymakers and the public a transparent, rate-neutral proxy for real economic activity. If made public, it would allow governments to spot slowdowns or surges early, businesses to plan with confidence and citizens to track growth without waiting months for GDP data. 

Imagine the finance ministry adjusting spending in response to a visible overall or industry-specific slowdown in GST collections, weeks before GDP data confirms it. Imagine various state governments spotting a surge in consumption and responding to it through various policy interventions. And imagine businesses, investors and industry bodies acting early on the basis of credible signals of economic turning points. 

GST data offers these possibilities, but only if we treat it as more than a tax ledger.

The authors are, respectively, former director general, ministry of statistics and programme implementation, and distinguished fellow, Pahle India Foundation; and fellow, Pahle India Foundation