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Using Feedback Loops For Policy-making – IMPRI Impact And Policy Research Institute

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Using Feedback Loops for Policy-making

Session Report
Tripta Behera

Contours of the Public Policy in India in the Amrit Kaal is an An Online International Autumn School Program, A One-Month Immersive Online Intermediate Certificate Training Course held in September, 2023 by IMPRI. The Keynote Speech was given by Dr Sanjeev Sanyal, Member, Economic Advisory Council of the Prime Minister (EAC-PM), and Secretary to the Government of India (GoI). Former Principal Economic Adviser, Ministry of Finance on “Using Feedback Loops for Policy-making. Dr Sanyal initiated the session by briefing the participants about Decision Theory and the use of Feedback Loops in making policy decisions. 

Decisions in the midst of Uncertainty in Policy-making

Dr Sanyal started by making an important and fundamental difference between risk and uncertainty. Risk pertains to events that we know are a possibility, ones we can apply a probability to. But when it comes to real decision making, a lot of it relates to events that are uncertain. Uncertainty implies that it isn’t possible to calculate all the possible outcomes, and it is also not possible to attach a probability to such outcomes. 

A prime example of this, as Dr Sanyal stated, was the event of the COVID-19 pandemic in India and across the world. India had a different response to COVID as compared to virtually every other country. The information that we had at the brink of the pandemic, in the beginning of 2020, there was little to no information about the virus, or the exact cause of so many deaths. In such a situation of complete uncertainty, there were a myriad of possibilities put forth by experts, ranging from some calling the virus a harmless flu, to some predicting millions of deaths by July. 

Faced with this range of possibilities, China went with a Zero Covid, complete shutdown policy; Sweden went with a completely open Swedolicyish policy; the UK went for herd immunity, and later switched to a complete lockdown. India followed a barbell strategy, derived from the derivatives strategy used in the financial markets.

It prescribes that when you are faced with utter uncertainty, you combine two opposite strategies. India decided that on one side it would iterate and try to do bayesian updating, to try to deal with the level of uncertainty; and on the other side, it would create handrails and safety nets to avoid the worst possible outcomes. In the first round of this iterative process, with no information, India decided to impose a full lockdown so that some time could pass and more information could be collected inturn. 

This was followed by opening up of the economy through an iterative process.

Supply Shut-Down from COVID-19

The economic downturn due to the pandemic, required a series of measures that would bring the economy out of a slump. Dr Sanyal mentions that instead of using resources to do a Keynesian style demand expansion, the policy makers took the view that this was a supply side shock. People wanted to spend money, but they couldn’t as markets, malls, cinemas, everything was shut. Sso this presented a supply side problem, rather than a demand side one. So India decided against following other countries in providing stimulus cheques to boost demand, albeit criticised for doing so. 

Policy makers did not attempt to revive the economy by pumping demand, but created safety nets of various kinds. The JAM (short for Jan Dhan-Aadhaar-Mobile) Trinity was used to make sure that the poorest of the poor were given money for sustenance. There was also a fear that a cascade of defaults would lead to a crash. So India decided to guarantee 80% of the defaults, which in turn nudged most agents not to default. 

Agile software development in IT

In his concluding remarks, Dr Sanyal mentioned that the lockdown was not imposed during the DELTA wave due to the feedback loop based system. This is similar to what is followed in the software sector. The agile strategy refers to the introduction of a software that is 80% done, and having introduced it, they fix the bugs retrospectively through a process of iteration. It allows them to fast forward and introduce changes as compared to the exante fixing of bugs prevailing in the system. 

Dr Sanyal highlighted that this was also how the GST was introduced. It was introduced, and the problems that arose were fixed on the way. It caused a disruption, but it was finally in place. Even now there are a huge number of  policy reforms based on this feedback loop. This is fundamentally different from how policies were made in the past. The iterative mechanism enables policies to fit evolving organic complex systems. To quote Dr Sanyal, nothing works, it has to be made to work. 

Acknowledgement: Tripti Behera is a research intern at IMPRI.

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