Large digital databases like the GST Network can give granular insight, create predictive models; this can lead to more grounded interventions
A lot has been said about the current economic slowdown. Econometricians have opined on whether the fall in growth rate is structural or cyclical; economists have wondered whether the response has to be from the supply side or whether demand needs a boost; politicians have traded barbs on whether the issue is the mismanagement of the local economy or the impact of the global trade wars and suchlike; industry and stock market participants have loudly called for succour, fiscal prudence be damned, as their profits and positions suffer even as bureaucrats and government think-tanks continue to talk of India becoming a $5 trillion economy. Since the macro-economy affects all participants, it is natural for all of them to have an opinion and voice it out clearly.
As they perceive the current slowdown from their own vantage points and perspective, the diagnosis, prognosis and solutions depend either on the tools of trade available to them, or on their own reasonable self-interest. Any macro-economic change creates a unique Tower of Babel—too many people talking about too many things and, in many cases, talking past each other, or with deep contradictions.
In the current case, the epicentre seems to be the automotive sector, though, now, many other sectors are beginning to report slower growth numbers. As is usual in a large and complex economy, not all sectors behave in unison—there are some sectors (say, aviation, paints, etc) where growth continues to remain high. Depending on which side of the table one is on, data points can be brandished at will. The challenge for policymakers is to absorb all this crosstalk and to convince most, if not all, of them that their interests will eventually be taken care of.
If one looks at the commentary, a significant amount of time and effort is invested in trying to identify the causes of slowdown. Most economy watchers have created their own Le Keqiang index of their favourite high-frequency data points: a former CEA used some indicators to come up with a measure of India’s economic growth while a data reporting company uses its chosen eight indicators monthly. The creation of collections of such sub-indicators only adds to the cacophony of the commentary; these indicators may neither be completely representative nor adequately comprehensive to capture the complexity of the economy.
What is the way out?
One way in which the Tower of Babel can be made less confused is if everyone agrees on some fundamental axioms. This can happen when what is being commented upon is based on facts that are universally acknowledged and agreed upon, rather than on data points that are selectively available. Generation and dissemination of data is a trust-based public good that is entrusted to a monopoly: the government. India has recently gone through a rough phase, where its macro-economic data has been questioned. Questions and suspicions can quickly corrode trust—reinstating and rebuilding trust requires a long-term, patient approach.
The formal sector of the economy, which is currently suffering from a slowdown, is now largely digitally connected with the government. With the roll-out of the GST network and the digital interface of the direct taxes, there is a large data exhaust that is now available to the government. With the expected collection of `14 trillion of GST at an average rate of, say, 14%, the GST network now gets an insight into `100 trillion of value-addition. This represents around half of the `200 trillion Indian economy.
The GST network has valuable data, the analysis of which can shed light on a wide variety of questions: which sectors are hurting, how are the upstream and downstream ecosystems coping, are there stress signs in adjacent or different sectors, which states seem to be facing bigger issues and which are holding up, etc. There can be deep analysis of size, scale, networks, complexity, etc. The need for privacy of an individual entity is well-recognised and, indeed, is upheld in law as a fundamental right. However, meta-analysis of consolidated, anonymised data can throw up meaningful, actionable insights.
The GST system has stabilised over the last couple of years. India should use this ‘crisis’, as every commentator who loves to paraphrase Rahm Emanuel would attest, to create a framework for data sharing. Once a constant and consistent stream of data is available, a large self-interested community of analysts, both in the private and public sector, will begin to dig deeper and build sophisticated tools to help not only identify where the current slowdown is hurting but also what and where to look to identify the next downturn or exuberance.
Given (1) how important data is as a public good, (2) the importance of developing evidence-based policies, and (3) the public funding of various digital networks of the government, opening of anonymised, consolidated data to the public should not pose any legal or technical challenge. A five-star framework of Open Data policies, developed by Tim Berners-Lee, the inventor of the world wide web, sets out a framework for authorities globally. India should harness its available data to come to more grounded conclusions, solutions and interventions.
(The writer is the author of The Making of India. Views are personal)