In the last month, opinion columns have been embroiled in a debate about India’s statistical systems. As valuable as National Sample Survey data is for the postmortem of policies made several years (or decades!) ago, focusing our attention on lacunae in the NSS risks missing the real data crisis in India — the complete lack of reliable high-frequency data that can support policymakers within the time frames they have available to them.

In sector after sector, administrators and policymakers are flying blind, especially for economic indicators at the state level. Overall GDP data comes with a large lag, and often needs significant correction. District GDP data, if available, are indicative at best. To make matters worse, much of the estimate is based on very old datasets, some last updated in 2014!

Employment, since 2017, is covered under the annual PLFS survey, data from which comes out ‘only’ a year later.

But a big, potentially game-changing data source on economic activity is now available, but we are not prepared to realise its potential — the Goods and Services Tax. With every business exceeding a turnover of ₹40 lakh required to file returns, the government now has access to a source of rich data on economic activity that is both high frequency — many businesses are required to file every quarter — and relatively reliable.

Even better, the data source comes built-in with incentives to keep it ‘honest’ and make it more reliable over time, on both government and business’ sides. All of these characteristics make the GSTN a very attractive source of data for decision-making.

But one big limitation is that it only captures formal sector activity. However, with more and more formalisation, this should correct itself.

Let’s take tourism as a case study to understand how GST data could be useful. The Tourism Ministry has prescribed a detailed methodology for the estimation of domestic and foreign visitors at a district level. But for States this is an expensive exercise.

So many states simply extrapolate footfall numbers based on whatever they can find or estimate.

If the State tourism department want to market a destination, how would they ever find out if they were making a difference?

GST data, however, captures returns filed by different services. Examining returns at an aggregated level for all hotels and restaurants in the district, or even sub-district, and comparing them with other areas/States can give a clear and reliable picture of effectiveness.

This picture can be filled out with other higher frequency data points like airport, train and road arrivals, low value, high volume UPI payments etc. Add in an occasional survey of informal sector tourist spend, and you can use correlations and high-frequency measures to generate reasonably good estimates of informal sector spending on an ongoing basis.

The roadblocks

So why is this not already happening? One important roadblock is that Tax Departments are extremely reluctant to share data, even with other government departments!

We are working with a State to implement a monitoring system that uses GST data, and it took months to get some data from the Tax Department. This roadblock can be done away with entirely.

Other reasons are structural, such as a lack of incentives to look at data and make good decisions. These will require us to set up better governance mechanisms and monitor them on their performance using GST data. Mechanisms like Destination Management Organisations or industrial region authorities that govern an entire region and use GST data to see if policy changes are making a difference.

Overall, there is a lot we can do a lot with GST data to monitor and improve economic activity, and we are barely scratching the surface.

The writer is Director, Foundation for Economic Development