Ladies and gentlemen, with this may I please now invite Dr Shamika Ravi, Member, Economic Advisory Council to the Prime Minister, to kindly share her views, thoughts, and perspective on the narrative for Viksit Bharat. Ladies and gentlemen, we have the very valuable presence of Dr Shamika Ravi, Member, Economic Advisory Council to the Prime Minister, among us. I request her to kindly share her ideas and her thoughts on the narrative for Viksit Bharat.

Ladies and gentlemen, previously Dr Ravi was Director of Research at Brookings India, Vice President of Economic Policy at the Observer Research Foundation, and a Non-Resident Senior Fellow of the Governance Studies Program at the Brookings Institution. Her research focuses on the economics of development, including areas of finance, healthcare, urbanization, gender equality, welfare, and poverty. Ma’am, we welcome you. Welcome, ma’am.

Namaskar. Good morning everyone. First of all, thank you, Samir, for putting together thoughtful gatherings on issues which I think are very critical and which not only require sensitization amongst the scholar community, the researcher community, and industry bodies, but to a large extent also within policymakers.

One thing to recognize is that while we are setting narratives for Viksit Bharat, there are narratives and narratives. The only way to counter narratives, first of all, is by using what is seemingly more objective, which is data. Otherwise, when you tell a story—whether India is improving or India is deteriorating—stories have to be founded on something objective. Otherwise, it is your feeling versus my feeling. These are anecdotes, and I think powerful anecdotes do go a long way, but in no way are they a substitute for careful, scientific, rigorous studies and assessments.

So I think first and foremost we must recognize that data—people will tell you data is the new oil, you have heard that cliché millions of times—but data is more like crude oil. It is not of very much value unless you process it, unless you analyze it. And I think that is where our key constraint comes. We have more data than ever historically, not just because of Digital India and the transformation that the government and layers of government across the country are going through, but private bodies too—everything is getting digitized very rapidly.

So we have a lot of data, but it will only get transformed into knowledge and information if you put analytics and data science behind it. Otherwise, it is noise—potentially dangerous noise. And that is why I think it becomes important, of course, to talk about governance matters on data and data responsibility, etc.—very critical areas. I am here to basically pitch for making data-based recommendations for all kinds of policies that the country needs.

I will start by sensitizing you to something which was one of the first studies that I did when I got into government, into the EAC. You know the narrative we often hear—that India is a majoritarian country, India is getting more and more majoritarian, democratic backsliding, etc. Some of the indices which are often cited are based on highly subjective, hypothetical questionnaires.

Now, as an economist and as an empiricist, which means I only deal with data, most of the time you are taking that data to certain theories and testing—are these things true? In today’s polarized world, if you tell me the identity of the expert you are talking to, I can to a large extent, with a high degree of accuracy, tell you what they will say about the situation in India. That means subjective measures of whether the situation is improving or deteriorating are very well explained by the identity of the person.

So a lot of what passes off for drawing-room conversations is projected as evidence. That is dangerous. And as people who work with data, who work with large databases, we have to put that down.

One of the first studies that I did was looking at secular democracy in practice. In India, there is politics, and politics is loud, noisy, and emotional. But what does the data tell you about the nature of Indian administration? Does the government or the administration discriminate in any way?

One thing is to ask the government itself, but that becomes a conflict of interest. I know what each department will tell me—100% electrification, piped drinking water, education. That is the government’s point of view, because government departments and administrative data will tell you one story.

The second is to ask households directly, through surveys—electricity is there, but how reliable is the availability? Each of these amenities can be measured. And the beauty of India’s data systems is that we actually have a very large number of surveys which have been done regularly.

One myth that you often hear in the media is that this government puts out very little data. Ten years back, we used to wait every five years to get estimates of employment from NSS surveys—the thick rounds. Now you have PLFS, the Periodic Labour Force Survey. It was a conscious decision to improve data collection and put it out regularly. That is why it is periodic. We have had it for the last seven to eight years now.

If you look at the National Family Health Survey—health status, biomarkers, maternal mortality, infant mortality—these large metrics of social importance are also directly linked with the SDGs. After all, we are a responsible democracy which has signed and ratified the Sustainable Development Goals as a metric of development beyond GDP growth.

Earlier, NFHS was done every ten years. Now it is happening every five years, and the frequency has improved further. So today, availability is not the problem. We have shifted the goalpost—we are now saying quality.

If I ask this room a very simple question: how urban is India? Most of you will reflexively say 35%. We were 35% urban as per Census 2011. But do you realize what twelve years can do to a dynamic, young, rapidly urbanizing country like India? When we use nightlights data and satellite imagery, India is anywhere between 65% and 67% urban. We are an urban nation.

This has two implications. One is directly on policymaking. We still think rural because of the old Gandhian philosophy that India lives in its villages. That is no longer true. India has already moved to a very large extent. Policy design must change accordingly.

There is dissonance between the real economy, which is moving very fast, and what administration captures. Millennial cities are being governed through panchayats. So policymaking and administration have to catch up.

We are gathering a lot of data, but we also have to strengthen data governance, legal architecture, and consent architecture. People have to be empowered. Laws have to be modern and progressive, but people also need awareness. Digital public campaigns are needed, just like health and education campaigns.

There are real dangers—a gender digital divide. We studied this during G20. Access of women to digital infrastructure is a major issue. But India’s growth story is unique. JAM—Jan Dhan, Aadhaar, Mobile—forms the core digital architecture.

During the pandemic, people received cash directly when stepping off buses and trains. That is efficient, targeted welfare. The government talks about efficiency gains and fiscal savings, but there is a bigger story—the innovation and private sector story.

This digital architecture has fueled startups—agritech, healthtech, edtech—some of the fastest-growing sectors today. The smartest students today are building startups. Incubators are everywhere. This is fueled by digital infrastructure.

Globally, over 60 countries have expressed interest in adopting India’s digital public infrastructure—Aadhaar, UPI, and others. This interest comes not only from developing countries but also advanced economies because India’s solutions are cost-effective.

Now, coming back to data quality: more data is not necessarily better than no data. If your sampling is wrong, you become precisely wrong. Quality matters more than quantity.

We must also look beyond traditional surveys. Nightlights data was useful earlier, but LED lighting has changed that. Now we use daytime satellite data—10m by 10m resolution—to measure construction, crop loss, insurance claims, and policymaking inputs.

Household surveys are in crisis globally. This is not an India-specific problem. Even in the US, surveys failed to predict major political outcomes. Sampling bias, non-response bias—these affect all systems.

Every ministry today has chief statisticians and economists. We need to improve methodological rigor and move towards genuine evidence-based policymaking, not policy-based evidence-making.

A lot of backend plumbing work is happening in India—brick-and-mortar changes in data systems. It may not be exciting for the media, but it is critical. We should use public data more actively to improve policymaking in this digital age.

Thank you very much for the opportunity. Namaskar.

Participants at the Indices for Viksit Bharat