This episode is the first installment of a series in which Shruti speaks with doctoral candidates and postdoctoral scholars about their research as they enter the job market and the world of academia. In this episode, Shruti talks with Nishant Vats about his job market paper (co-authored with Pulak Ghosh), “Safety Nets, Credit and Investment: Evidence from a Guaranteed Income Program for Small Entrepreneurs.” Vats is a Ph.D. candidate in finance at the Booth School of Business at the University of Chicago. His primary research interests are finance and development, financial intermediation and corporate finance, with a secondary interest in macroeconomics and political economy.
SHRUTI RAJAGOPALAN: Welcome to Ideas of India, where we examine the academic ideas that can propel India forward. My name is Shruti Rajagopalan, and I am a senior research fellow at the Mercatus Center at George Mason University. This is the 2022 job market series, where I speak with young scholars entering the academic job market about their latest research. I spoke with Nishant Vats, Ph.D. candidate in finance at the Booth School of Business, University of Chicago.
We discussed his job market paper, co-authored with Pulak Ghosh, “Safety Nets, Credit and Investment: Evidence from a Guaranteed Income Program for Small Entrepreneurs.” We talked about the Pradhan Mantri Kisan Samman Nidhi and its impact on landowning farmers, especially credit, and his work on political power-sharing, firm entry and economic growth.
For a full transcript of this conversation, including helpful links of all the references mentioned, click the link in the show notes or visit mercatus.org/podcasts.
Hi, Nishant. Thank you so much for being here. This is such a pleasure.
NISHANT VATS: Thank you, Shruti, for having me here. I’m really excited to talk to you about my research.
Does Guaranteed Income Increase Productivity?
RAJAGOPALAN: You’re looking at unconditional, recurring, guaranteed transfers to farmers in India, the Pradhan Mantri Kisan Samman Nidhi. They give a guaranteed unconditional transfer, which is recurring, of about 6,000 rupees to all the landowning farmers in India.
This is what you’re studying, and what you find is that the guaranteed income, or the increase in income in this case, actually leads to an increase in farm income too, because they’re using this increased guaranteed transfer to increase their productivity on other margins of what is actually their day job. Can you walk us through this? Because this is a slightly surprising result.
VATS: Yes. Thank you so much for describing the research so nicely, but let me try to frame it in a bigger context. The key question that we are asking in this paper is how do safety nets affect productive activity and the key role that the credit markets play in this effect. As the title of the paper says, we are looking at a very specific safety net which resembles their guaranteed income program.
Before I go into my result—just to fix ideas—what do we mean when we say the word guaranteed income? Primarily we are thinking about an unconditional and a perpetual stream of cash flows or cash transfers which are given to people regardless of their income, regardless of their effort, regardless of whatever productivity they have, regardless of their preferences.
Basically, it’s like everybody gets the money in a well-defined community. Of course, when the well-defined community is the entire country, it becomes a universal basic income. When the well-defined community is a citizen, it becomes a citizen income. Basically, this is the question that we are trying to answer in this particular paper. And over the last 10 years, there has been a lot of discussion about guaranteed income programs, more specifically universal basic income programs. There is a lot of debate as to how exactly these universal basic income programs will affect economic activity.
We do not have any systematic direct evidence from such a program. And Hoynes and Rothstein in their review article, as well as Banerjee and co-author in their review article, talk about how we do not really have clear evidence on how these cash transfers would affect people and their economic activity. In this paper, I basically try to target this question or try to inform this question. I do not see this paper as settling the debate but as informing the debate on a different dimension.
What I do is basically start with theory. As you rightly pointed out, one of the most obvious things that comes to mind is if you give people free money, they’re going to work less. What exactly is happening in my paper? Theoretically, what we know is that classical macroeconomic models say that if you give people free money, they will work less. But we also know that people often suffer from borrowing constraints because of which there’s underinvestment.
One can imagine that this money comes in as cash in hand, because of which they’re able to invest more. On the other hand, you could also think that because these transfers are a permanent income shock, where your period income permanently increases, it can actually result in credit market effects as well, either by stimulating credit supply, by increasing your creditworthiness or by increasing credit demand by increasing your financial resilience.
What we actually find in this paper is that a guaranteed income program increases income from work, or it actually generates additional income. Just because I’m in finance and I really like to talk about money, you can think about it like this: $1 of guaranteed income basically gives you an additional income of $1.70. So this $1 of guaranteed income actually becomes $2.70 at the end of the day. The way this happens is this $1 increases your investment by around $8 and increases your credit by around $12. The key mechanism that we find in this paper is that this is primarily driven by the financial resilience effect of these transfers, which basically increases their credit demand.
How Guaranteed Income Increases Credit
RAJAGOPALAN: As you pointed out, a large part of your mechanism works through credit. I believe the credit multiplier that you find is 0.65. So a 100-rupee increase in income to the farmer means a 65-rupee bump in credit. That’s basically what you guys are finding.
How does this exactly work? Is it because of the increase in income the farmers are now more creditworthy—a supply-side response to the increased income? Or is it because the farmers are now more willing to take risk in the credit market? They’re more willing to borrow because now they have this guaranteed stream of income, which would be a demand-side response if we had to make this distinction. What is exactly going on to get you the additional 65-rupee effect for each increase in 100 rupees?
VATS: That’s a very important question and something that we delve into very deeply into the paper. You’re right. Theoretically, because it’s a permanent income shock, your creditworthiness can increase, which can basically trigger supply-side response. On the other hand, it could trigger a demand-side response because now you are much more well protected against risk. You’re much more willing to take risk and finance risky economic activity using credit demand.
What we actually find in this paper is that this particular money does not really raise creditworthiness in the short run. It actually operates via the credit demand channel. We really need to distinguish about the short run and the long run.
For example, say if you go to a banker and say, “Hey, I want a mortgage loan.” I actually tried this experiment. I actually went to my banker and asked them, “Okay. See, I’m at Booth. I’m a grad student right now. My stipend is meager, but after a year what will happen is I’ll go into the market, and by the historical records I will at least earn $150,000 a year. Is it possible for you to basically give me a loan against my future income?” He laughed. He said, “No, it’s not possible.” What happens is when you go to a bank, they will ask for your credit score, which again is based on your historical data; the amount of income that you’re generating, which is again based on your historical data; and if you have any collateral, which again is based on historical data.
In the short run, it’s very difficult for credit market to actually respond to these shocks because of these institutional frictions. In the short run, it doesn’t respond. Of course, in the long run, you will have a feedback effect. For example, now because of your demand effect, you’re able to increase your income, and as a result of your income, your creditworthiness goes up much more. However, we need to realize that there’s a causal chain. First your demand increases, and that triggers a supply-side response.
In the short run, there’s only a demand-side response. In fact, just as a caveat of my paper, because the policy was launched in 2019, and in March of 2020 we were hit by COVID, I actually try to restrict my analysis to normal time. I only basically have one year of post-policy data. In that data, I’m basically trying to do the short-run analysis, and that’s how I’m able to basically distinguish between credit supply and credit demand.
RAJAGOPALAN: Now that we know that this is coming from the demand side, what is a way to think about this income from the point of view of the farmer? Do they view it as a form of insurance? Do they view themselves as now having a higher amount of liquidity, and that’s why they are more able to take more risk and demand credit? How do the farmers view this sudden increase in income?
VATS: Absolutely. That’s a great question. I don’t really distinguish so much between liquidity and insurance because, of course, if you have liquidity, you also have insurance. The answer is that they actually think of this as insurance. Right now, I’m conducting a field survey where I’m collecting primary data from these farmers in India. Over there, it seems to me from their responses, they’re saying that their concern to meet basic needs in bad times really decreases. By basic needs, I’m really talking about food, clothing and shelter—really small things.
Basically, you can think about a farmer. She has some medical emergency, or there’s a drought in the area because of which she’s concerned about meeting her basic needs. This policy is really helping her out in terms of mitigating those concerns. In a way, you have this safety net. Basically, the way I think about this entire policy is this: You can think about a small entrepreneur trying to walk between two tall buildings on a very tight rope, and the safety net is like a cushion which is there. If you fall, it’s there to catch you and you don’t die.
RAJAGOPALAN: That makes sense. Because the amounts are so small, that makes sense that this is the insurance against having to go without medicine or having to go without basic food, clothing and so on.
Addressing the Theoretical Incentives
RAJAGOPALAN: I want to go back to one of the bigger results that you find which is very surprising. Normally, all the discussions about any kind of universal basic income or income guarantee is that it’s going to make people lazy and unambitious. It’s going to reduce the labor hours, it’s going to reduce initiative and productivity, which is one of the big effects. You don’t find that at all in your study.
Now, two questions related to that. Is it because the amount is so small? We are basically talking about an additional 500 rupees a month. While that is very important when it comes to a cushion or increasing liquidity and so on, it’s not exactly something that a household can live off. The substitution effect, understandably, is quite small. That is one way of thinking about it.
Is the other way of thinking about it that they’re not yet used to this? Both the program was introduced so recently and your study looks at the immediate short-run effect—that if this went on in the longer run, then you might find some effect on labor productivity? What is a good way to think about your result?
VATS: That’s a very important question. I agree with your analysis to an extent. Let’s try to take a step back and try to think about where this entire idea of people becoming lazy comes from. It comes from the classical macroeconomic models where we say that if you give people free money, they want to work less. That basically assumes that this money does not change their marginal productivity. In fact, Benjamin, in his 1992 seminal work, talks about this. He basically talks about this assumption, and it’s a very crucial assumption to generate this result.
Recently we do have some work from Dean Karlan and Abhijit Banerjee and co-authors, which tries to investigate a very similar thing in Kenya, where they see that actually, these transfers can have an effect on your physical stress, can have an effect on your nutrition, because of which they can actually affect marginal productivity of labor. Basically, think about it like this: Say, if I haven’t eaten in a day and you want me to go and do physical work, or if I’m stressed about paying the education fees of my daughter, I might not be able to work so much. There’s some kind of psychological and physiological productivity effect of cash transfers.
Having said that, I think from the results that we know about from lottery winning—there’s some evidence on lottery winnings and the labor supply response in Sweden, this work by Matt Noto[widigdo]. Then there’s some other work in the U.S. by Mikhail Golosov and co-authors. And they basically show that people who win lotteries tend to work less and tend to earn little. I agree. If you make somebody a trust fund child, they probably may not work so much.
Again, we need to come back to the reality of the policy over here. When we think about policymakers and academics really talking about this kind of guaranteed income, they’re not really thinking of making them trust fund kids. They’re really thinking about giving them a basic amount of money. You’re right. If the money is very large, I think it’d be very hard to basically motivate people in terms of making them work. But if the money is small, there could be different channels through which it could work and actually increase.
Going back to your point that I basically show that it does not make people lazy, I would say that my result rejects that hypothesis in a weak sense. In my survey, I do find that 8% of the people do say that they actually reduced working. Again, that’s a very, very small fraction of the entire effect that I’m talking about.
Substitution and Scaling
RAJAGOPALAN: I have a broader question. This is very much about the Indian farm policy context or agricultural context. In previous economic surveys, for instance, one of the ideas that was floated was that for farmers, it is probably a good move to go into some form of universal basic income or quasi-universal basic income. This can be funded by rolling back all the other subsidies. Now I’m thinking just about farmers.
Now, what impact will this have? Because the interesting thing about the Pradhan Mantri Kisan Samman Nidhi is that it doesn’t change any of the other subsidies, and this is an additional transfer that’s given. It’s also very small. On the other hand, if this is extended or if it is made larger, then it’s a huge cost to the exchequer. It’s not exactly sustainable. Agricultural subsidies in India are already about 2.25% of the GDP if I’m not wrong. What is a good way to think about a basic income guarantee for farmers and scaling the kind of policy that you studied? Is that feasible? Is that unfeasible? Can your paper inform us about this question at all?
VATS: There are two parts of this question. Let me try to talk about the first part first, which is about substitution. Let’s take a step back again and try to think about where this idea of substitution comes from. We don’t want to tell people, “Go and take education,” “Go to hospitals.” We give them money and let them choose optimally among themselves that, “I want education,” “I want hospitals.” That’s a very good hypothesis to have, a very good null to have if you’re really dealing in markets which are well developed.
However, when you’re thinking about developing countries, where you may not have a lot of private players in the education sector, in the health sector, it might be actually a very dangerous policy when you think about the substitution. Because while you’re giving people money to spend on health, they might not actually have healthcare centers, or they might not have enough private vendors to buy seeds or fertilizers or pesticides from. The substitution is a tricky argument, especially in the context of emerging markets where the private markets are not well developed enough to fill that supply gap. We have to be a bit careful when we are thinking about that substitution.
In terms of scaling, that’s, again, a tricky argument and relates back to your previous questions of how large do we want to go. To an extent, that’s a quantitative exercise. Right now, I’m actually also working on a model, which is not a part of this paper but something that I will release as future work. What I’m trying to think about is, what is the basic amount of money that you should give to people so that it basically increases your marginal productivity and acts as a safety net, but it does not trigger that negative income effect that you have from increasing money?
That’s a very important question, and honestly, we do not know the answer to that question. It’s something we need to do more research on, and I’m trying to work on that question as well.
RAJAGOPALAN: I think the way you’re approaching both big-picture questions I asked, I can see where you’re going with this. I look forward to reading that paper.
Landowners vs. Tenants
RAJAGOPALAN: Going back to your study, this particular intervention was only for landowning farmers. It was not for tenant farmers. Does that itself bias the study in any way? I’m asking for the following reason: Is the fact that the person who’s receiving the income guarantee or this additional source of money—is the fact that they are landowning a large part of the result coming through the credit markets? Is there something inherent about landowners as a group, that they are more likely to become creditworthy, or they’re already more creditworthy?
Does it have to do with their social standing? Does it have to do with the fact that everyone in the village or town may know that this person is landowning, so they’re a safer bet to give credit to? Is it that they are more risk-taking given that now they have the land and they have the insurance money?
This could also be driven by other social indicators like caste and so on. Typically, landowning castes are different from tenant castes. Typically, they tend to be upper caste—not always, but tends to be so. What is a good way to think about the fact that this particular intervention only targeted the landowning farmers?
VATS: That’s a very excellent question, and you’re right. One of the obvious systematic differences between my treatment and my control group is land ownership. If you go to credit markets and you have a collateral, you’re more likely to get a better loan. However, we need to think about what exactly this policy really changed. Basically, this policy did not change the amount of land. They could go to the bank before, they could go to the bank after.
We need to distinguish between credit supply being a necessary condition or a sufficient condition. This necessary condition, which is ownership of land—so you have a collateral to give to the bank—was always there. However, this treatment group was still not accessing those markets out of their own will. And that was because they were scared to take risk because they didn’t know what would happen to them during bad times.
This policy basically just removes that particular friction, so you’re right. In a way, this result is being generated because they have a borrowing capacity. But the point that I’m trying to say is that they have this unused borrowing capacity, and now they’re actually utilizing it, which is exactly what we would want.
Again, there could be other differences—caste or other social network differences—but are these immutable characteristics really changing because of this policy? I doubt if somebody changes their religion or caste because of this policy. In fact, one thing to note, if you’re thinking about, say, upper-caste people being landowners so they have a strong network, in this case they would actually be more willing to provide informal insurance to each of them before the policy. If anything, you should not find the result for them.
RAJAGOPALAN: I was asking more from the point of view of the difference between the control and the treatment group. I’m persuaded by what you’re saying in the sense that these people always had a latent capacity to raise credit because they are landowning. They could have gone to the bank and given it as collateral, unlike your forthcoming Ph.D. One can’t do that exactly. But I’m asking more from the point of view of, if we extended this program to tenant farmers, would you expect to find the same effect? Not to say that what you find is not legitimate; more that once you include the control group in the treatment group, are we going to find a similar effect?
That to me seems less plausible, given your explanation, right? Maybe they don’t go to credit markets; maybe they treat it as something else. Maybe they actually reduce the number of labor hours because they’re already at the max point of the productivity that they could get to through tenant farming. They don’t want to make greater improvements to their land because they don’t own it. What is a good way of thinking about that?
VATS: Usually the way I think about credit supply and demand is through the example of a thirsty horse. Say you have a thirsty horse, and as a policymaker, you want to basically quench the thirst of the horse. Basically, the way I think about credit supply is taking the well to the horse. The way I think about credit demand is the horse going to the well and drinking water.
In the case of landowning farmers, there was always a well, and the problem that I noticed is that they were not drinking from the well. Maybe the horse was scared that if he drinks water, he’ll get malaria or some other disease or something else. This policy removes that fear. With landowning farmers, you may not have water in the well, which might be another problem.
RAJAGOPALAN: With tenant farmers?
RAJAGOPALAN: With tenant farmers, you’re saying there may be no water, there may be no well—
RAJAGOPALAN: —so that question doesn’t even arise?
VATS: Yes, and actually there’s one interesting test that I actually do in my sample of landowning farmers. Basically, in credit markets, if you have had a prior history of default, you can get excluded from the credit markets. You can think of them as a horse with no well and no water. I actually find with them, there is literally no effect. The effect basically comes from people who have access to the credit supply. You have to think about the credit supply—and it’s a necessary condition. You need water in the well to quench your thirst, but you really want to go over there and drink water.
RAJAGOPALAN: I think that’s a fair way of thinking about this. Now, coming back to the control group, what’s a way to think about that if we did extend it to them—I know that’s not in the paper—but what does your hunch say? How would it go? We know that it need not go through the credit mechanism, right? What would you expect to find? Would you actually expect to find the typical result, that they do reduce their labor hours? Would you expect that they are more risk-taking on a different margin, which is changing their profession or starting their own business or something else which is unrelated to land and increases in farm productivity? Which way do you think that trajectory will go?
VATS: One, as you rightly pointed out, it will depend on how much access they have to credit. Let’s assume, as a baseline, they don’t have any access to credit in order to answer this hypothetical question. We could also have the marginal productivity of labor effect where these farmers have this extra amount of money, so they have better nutrition, they have lower stress, which could basically have a positive effect on their marginal productivity. Is there a risk that this money might get wasted on things that we, as a society, might not think is right? Probably, yes. Honestly, I don’t know an exact answer to that question.
Political Power-Sharing and Economic Activity
RAJAGOPALAN: To switch gears, what are some of the other projects that you’re working on?
VATS: One of the other projects that I’m working on examines how political power-sharing affects economic activity [co-authored with Harsha Dutta, Pulak Ghosh and Arkodipta Sarkar]. In that paper, we exploit this haphazard overlap of administrative block boundaries and the assembly boundaries. And what we see is that changing the number of politicians governing a block has an effect on economic activity and firm entry.
Specifically, we find that when you increase the number of politicians, firm entry, as well as economic activity, goes up. And the primary mechanism through which it happens is when you have multiple people working together, they tend to exert checks and balances on each other because of which there is an improvement in economic activity.
RAJAGOPALAN: Let me take a step back. What you’re basically studying is our electoral boundaries of the state assembly seats, and our administrative unit or ward units are not identical. Sometimes what happens is all the wards will be assimilated within one electoral constituency, and sometimes a ward may fall in two electoral constituencies, which means that that administrative ward will actually have two representatives depending on where you are in that particular ward. Is that right?
VATS: Yes. Absolutely. That’s exactly the right characterization of our experiment.
RAJAGOPALAN: Now what you find is that if there’s only one elected MLA [member of legislative assembly] per ward, there is a different result when it comes to firm entry and economic outcomes and economic growth relative to when a ward actually has two different elected officials. That’s the starting point of the experiment. What is driving this result? Is it the fact that ward sizes in India and, in general, electoral sizes in India, constituency sizes are just so large that it’s very difficult to pay attention at the granular level?
When we are talking about these contested wards—there’s a ward that’s not completely within your purview where there is more contestation because there is another elected official who’s also governing a part of that ward—they are basically in a political competition, so the politician decides to devote more of their resources and attention to that ward because the competition is very evident? Someone else could be doing better than you. Or is it that now there are two elected officials, so they can monitor each other and they can check each other, and therefore no one is going to throw in useless roadblocks and demand bribes and so on? What is driving this particular result?
VATS: In terms of what’s driving our results, what we say is that it’s actually the latter, which is the checks and balances story. Say you have multiple cooks cooking the same broth, so the classical story has been that if multiple cooks are cooking the same broth, it’s going to get spoiled. On the other hand, you could also say that one cook is trying to add extra oregano or extra chili, and the other one will go and say, “Hey, don’t do this. You will not get a right dish,” which is like checks and balances story. That’s exactly what we find that, there’s a checks and balances story.
One important test that we do in our particular paper is basically look at the heterogeneity among these multiple politicians. For example, when these multiple politicians belong to separate castes, in that case, it might be difficult for them to collude or act like a single unit. What we do find is that the effect is higher when your multiple politicians belong to different castes or they actually belong to different political parties, in which case also, we again find that there is a higher effect.
It seems to be coming from the checks and balances story that when you have multiple people—especially people who, because of their historical background, have different traits—they might want to check each other and balance out the negatives in each other.
RAJAGOPALAN: How do we know that this is not going to just increase the amount of economic activity, but simultaneously also increase corruption? This is one of those—“I had to bribe one politician; now I know I have to bribe two.” There is clarity. There’s certainty on who are the political actors that need to be bribed in order for the firm to enter. At the same time, this particular case, while the firm can enter, they’re also paying higher amounts of bribes. Is there a way to measure this? Is there a way to think about this or look at this?
VATS: Yes. There’s this very interesting paper by Raymond Fisman, Florian Schulz and Vikrant Vig where they try to estimate the tip of the corruption iceberg by examining winner’s premium. What exactly is winner’s premium? You can think about two elections, and there’s a person who won in the previous election and a person who just lost the previous election. At the start of each election, they have to report their assets.
You can look at their asset growth and compute how much extra asset growth happened for the winner, compared to the person who just lost the election. What we do find is that this winner’s premium tends to be actually lower for politicians whose constituency covers a greater extent of multiply governed administrative units.
RAJAGOPALAN: That’s very interesting. Basically it’s not an increase in corruption story, but now there’s a question of are they reducing their bribes because of competition or because of checks and balances, right?
VATS: Yes. What we do find, again—and I would appeal again to the previous result that I mentioned, which is about the effect being higher when politicians belong to different political parties or when politicians belong to different caste groups. In those cases, we actually find that the effect is higher, which is more likely to come from checks and balances rather than political competition. Because you can think about two politicians belonging to two different caste groups, so their vote bank is different. There’s not much political competition, but more of a checks and balances story.
RAJAGOPALAN: When I said competition, I meant politicians—they’re competing on different margins. One, they’re competing for votes, but they have already won the election and that’s not what you’re measuring. I’m talking about competition for bribes and rents. Basically, now there’s greater competition, so you reduce the bribe that you would’ve normally demanded, or you waive the bribe because you know that the party could go to the other side. That’s what I mean by is this a competition story or a checks and balances story.
VATS: I don’t think those two stories are entirely different from each other.
RAJAGOPALAN: Yes. One interpretation is political competition is the check and balance, right?
RAJAGOPALAN: Political competition can also often lead to more rent-seeking because now, two people are fiercely competing, and therefore the amount that a firm entrant needs to pay—actually, the bribes go up because there are many grabbing hands, as you pointed out. It’s an interesting thing. I completely understand what your result is. I’m just more curious about what the mechanism is that is driving that result.
VATS: One of the interesting things that we do in the paper is we were able to get survey data from the government of Kerala, which solicits opinions and beliefs of management done by politicians to whom these local bureaucrats are directly reporting. What we do find is that, for bureaucrats operating in multiple-politician-governed areas, they actually say that their management is much better. Again, that doesn’t really help distinguish between the stories of political competition and checks and balance so much, but I actually think of them as—
VATS: Yes, exactly. Not exactly something like fighting against each other.
RAJAGOPALAN: Yes, and need not be. They may or they may not. In this case, they are not. Another interesting way to test for that is by looking at—if within a ward that falls in two different electoral constituencies, also look at whether the member of parliament—and also, at the local level, the Pradhan in the Panchayati Raj election—are they from the same party? Are they from different parties? Because then you know that they are competing only against the MLA, but you can have checks and balances from leaders of different castes and different political parties who are at a level of government above you and below you. There may be an interesting way of teasing that out. I know that’s not the purpose of the paper, but that’s just something that you could think of in the future.
VATS: Actually, what you said is a very interesting point and something that I’ve been thinking about, which is exactly the industrial organization of corruption. How exactly does corruption happen? Is it a trickle-up effect? You give some amount of money to the local bureaucrat, and the local bureaucrat passes it up and up. That is the story. If that is the industrial organization of it, then there is no political competition in terms of getting more bribes.
However, if the story is that you have to actually go and knock on multiple windows, then there is indeed the story. I think the second interesting topic to study is what exactly is the industrial organization, and does that have an implication on how we think about corruption or how exactly corruption will happen in certain avenues?
RAJAGOPALAN: I think it’s fascinating, and maybe the topic for your next paper.
RAJAGOPALAN: You’ve done most of your doctoral work through the pandemic. What have you been up to? Has it gotten in the way of research? Have you spent it baking and binge-watching like the rest of us? What’s been happening?
VATS: The pandemic was difficult for me because I was in a foreign country by myself. I had no family anywhere over here, and all my friends started to migrate from Chicago to their home cities in the U.S., so I was left all by myself in Chicago. One good thing that happened to me after the pandemic ended was, I was able to talk to people in person and have in-person conversations with my adviser.
In terms of binge-watching, I feel Netflix and Hulu and all other things were very bad for me during the pandemic because all I did was binge-watch. Most recently, I’ve been watching this show called “The Sandman.” I love that show.
RAJAGOPALAN: I will put it as one of your recommendations, and I will make sure I watch it. I’ve heard very good things about “Sandman.”
VATS: Oh, absolutely.
RAJAGOPALAN: I think I’ll be interested in watching that. Thank you so much for doing this. This was such a pleasure, Nishant.
VATS: Same here. Thank you so much, Shruti.