Underutilised data: GST transactions are a rich mine for policymakers

In the seven years since goods and services tax (GST) was introduced, an enormous number of transactions have been recorded by the GST Network, or GSTN. The question is whether this data can be put to use in multiple spheres. The GSTN has been understandably reluctant to be particularly open with this data because of privacy and security concerns. But, properly anonymised, there is much that could be done with this data to inform not just policymakers but also the markets and the broader public. The GST Council needs to be proactive in directing the GSTN to better inform the public and policymakers.

One possible use for the GST data that has been suggested is by the Union government’s statisticians, who report to the Union Ministry of Statistics and Programme Implementation (Mospi). It has been reported that India’s official estimates of output could soon incorporate the GST data as their next improvement once statisticians have finalised the mechanism for shifting the base year against which gross domestic product (GDP) is calculated. There have been several criticisms levelled against the current ways of estimating economic activity used for India’s national accounts. One major concern has been the use of company balance sheets reported to the Union Ministry of Corporate Affairs (MCA). Basing private-sector value added on corporate earnings in the MCA database runs the risk of biasing the estimates towards large, formal enterprises. Especially given that, at present, the differential and unequal impacts of policies across large and small enterprises are being widely discussed, such a bias in official statistics is a serious problem.

While GST by its very definition is constructed out of formal-sector payments, it will nevertheless have access to a far wider and more heterogeneous domain of transactions out of which better estimates might be designed. GST data is not only more granular, but also more regular than company reports, which are submitted once a quarter as compared to a monthly tabulation of GST data. There are of course multiple other ways in which individual and aggregated GST data might be used. At the level of the individual taxpayer, for example, it must be examined whether it can be used to inform the planned Unified Lending Interface, which is being incubated by the Reserve Bank of India innovation hub. With the proper security and privacy guardrails of the sort that are common in India’s digital public infrastructure, it could vastly improve the quality of information made available to lenders about possible borrowers, increasing welfare all round.

Aggregate data must be properly anonymised and then publicly released. Data on which items and which slabs provide how much revenue is an essential input into discussions of how to reform GST, raise more revenue, while also simplifying procedures. Such data will inform a lot about the functioning of the Indian economy and enable suitable changes in business models. It is imperative to move GST towards fewer slabs, as many entrepreneurs and small business owners have been consistently arguing. But to make this argument effectively to the government, the exact amount raised per slab must be made available, so that calculations ensure any changes are revenue-enhancing or at least revenue-neutral. The GSTN’s concerns about privacy and security are important and must be respected, but they are not insurmountable.