Nayantara Biswas on Demand- and Supply-Side Interventions in India's Maternal Health Policy

SHRUTI RAJAGOPALAN: Welcome to Ideas of India, a podcast where we examine academic ideas that can propel India forward. My name is Shruti Rajagopalan, and this is the 2025 job market series, where I speak with young scholars entering the academic job market about their latest research on India. 

Our sixth scholar in the series is Nayantara Biswas is a postdoctoral research fellow at the Beth Israel Deaconess Medical Center. She received her Ph.D. in economics from Clark University. Her research focuses on health equity impact evaluations of small-scale interventions and large-scale public policies. We spoke about dissertation titled, The Impact of Social Policies on Reproductive Health, Maternal Employment, and Child Health: Evidence from India. We talked about demand side versus supply side policy interventions in public health, India’s maternal health policy landscape, the ASHA workers program, variation across states in policy impact and much more. 

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, Nayantara. Welcome to the show. It’s such a pleasure to have you here.

NAYANTARA BISWAS: Hi, Shruti. I’m so excited to be here. As you know, I’m a big fan of this podcast, and I’m very, very happy to be on as one of the speakers.

Setting the Stage

RAJAGOPALAN: I was telling you just before we started recording how much I love talking to people on the job market. Your paper in particular looks at women’s reproductive health, child infant health, and all related outcomes through policy interventions. But specifically, you look at supply-side interventions.

You look at whether an increase in supply through a particular policy that the government has announced or implemented will actually impact the behavior of those who are on the receiving end or the people who use that particular policy, and therefore, how it impacts their health outcomes. 

In particular, maternal health is obviously a difficult thing to look at because we have very few numbers. Most women are pregnant in India apparently 2.2 times in their life, which is a strange way to phrase it, but you don’t have this large sample size of number of times a woman gets pregnant in her life. But there is a lot of other things associated with it, such as reproductive healthcare services, antenatal, postnatal care, contraception use and so on. There’s actually a lot to study when it comes to maternal health, and India performs very poorly when it comes to maternal mortality and things like that.

You look at a very nice policy intervention, which was the ASHA workers that were launched in India, and you look at how much an additional ASHA worker is associated with utilization of reproductive health services by women in India. And you look at this in an extraordinary way at the district level, which is complicated for various reasons that we can get into. You actually find that an additional ASHA worker per 1,000 population is associated with a 2.04% to 4.1% increase in the utilization of reproductive health services. Is this a good way to think about your paper? Then maybe you can tell us how you did all of this.

BISWAS: That was an excellent summary, Shruti. I thank you for that. I also wanted to mention that, right now as it stands, I was looking at the long-term effect of this healthcare policy intervention, which is why I do find such significant impacts. I will say that a lot of work has already been done by public health researchers. They don’t sometimes find these impacts, and that could be because they’re looking at immediate outcomes. Especially when you’re thinking about changing household behaviors, you do need to give a longer period of time, which is what I’ve been fortunate enough to exploit in my dissertation, in my job market paper.

RAJAGOPALAN: Can you walk us through what is the landscape of women’s health, maternal health and mortality, infant and child health policies in India? Especially because a lot of these are state subjects. A lot of them are implemented at the district or the panchayat level, but they’re announced in terms of outlays by union government schemes. It’s a very complicated thing. Can you just walk us through what that landscape looks like, and then we can talk about the intervention and the outcomes and what you measure and so on?

India’s Maternal–Child Health Policy Landscape

BISWAS: Absolutely. Very broadly, my motivation is coming from the fact that India, in general, has invested in a lot of maternal and child health policies. Karthik Muralidharan and others have recently released a working paper where they shared that cash transfers alone cost ₹2 trillion per annum. That’s 0.6% of the GDP. This is serving over 130 million women beneficiaries who are in the reproductive age.

If you’re looking at this as being a demand-side investment of just cash transfers being 0.6%, and you’re comparing this to India spending 3% to 4% of its GDP on healthcare, that’s a really huge investment on just demand-side interventions. However, in this context, we’re not fully understanding how do the supply-side interventions matter and how do they intersect with these demand-side policies. That is where I come in in thinking about this. I’m thinking, do more workers actually shift behavior, or is it that culture and social norms—are they more restrictive and are they binding, and they impede the utilization of these reproductive health services?

RAJAGOPALAN: There are two ways to think about it. Someone may be more likely to go to a clinic because they received a health voucher, or they received health insurance, or they received a direct cash transfer, and that changes how they demand a particular health or service which is in their village or their district, and so on.

On the other hand, people may also be more likely to use a particular service if it is easier to use because of the supply, that is, there’s actually a clinic within walking distance. The clinic is actually staffed. It has a midwife, it has an ASHA worker, it has enough people within my neighborhood going there that I feel comfortable going there. That might change my behavior. As you rightly point out, demand-side and supply-side interventions can typically be extremely expensive. As policymakers, when we think about something, we need to look at both the cost and the benefits. There’s this excellent paper by Karthik Muralidharan and his coauthors on the demand side, and now you are really looking at the supply side and how that changes women’s behavior.

BISWAS: Exactly. That is precisely what I’m trying to do. I think that, exactly how you said it, is that unless you have the access to a certain facility or a clinic, then it’s really hard. Even if I want to seek reproductive healthcare services, I want to give birth in an institution, but if I don’t have the access, like you said, or if I even don’t have the information access—that is also a form of access—then I will not be able to take up that service. India has made remarkable progress in maternal health as well as child health. Maternal mortality has actually fallen by more than 80% since the 1990s to currently, which is a huge progress. It’s from 560 deaths, which was quoted in NFHS for 1998-99 ..

RAJAGOPALAN: Per 100,000.

BISWAS: … per 100,000, of course—to less than 100 per 100,000 births. Now, infant mortality has also dropped pretty significantly, but the progress, like you mentioned, is very uneven. The district-level variation really exists, and that is the basis of using this district-level policy measure for my paper. For instance, states like Kerala and Tamil Nadu, they have outcomes which are comparable to middle- to high-income countries, whereas you have other states like Bihar and Uttar Pradesh who are lagging behind by a huge margin, sometimes. Even within the states, there is district-level variation. The variation is part of the reason of why studying in India is so interesting and so important because it shows what is possible, but it also shows where the gaps remain.

Uneven Progress: State Differences, Culture, and Measurement Challenges

RAJAGOPALAN: Now that we’ve talked about the variation, I guess a good question here is, Indian states are very different. There’s a linguistic factor. There’s also the GDP per capita, like Kerala and Tamil Nadu are very rich states. Bihar and UP are technically at sub-Saharan levels of GDP per capita. There’s an income issue. There are also culture issues, cultural practices.

Kerala is very famously a matriarchal society, which is about as far removed as you get from Bihar and Uttar Pradesh and so on. When you look at behavior of women when it comes to taking up or using more reproductive services or healthcare services, how do you manage to separate the existence or the supply of a particular service from the cultural practices or the norms or whatever exists in that society? I guess that’s a good place where you can start us off, and it’ll set us up well for the rest of your paper. 

Who Are the ASHA Workers?

BISWAS: Okay. The ASHA program, very broadly—first of all, let’s start with what the ASHAs are. The ASHA worker stands for Accredited Social Health Activist. These are community health workers. They are designed in such a way that these are local women chosen from their villages or their towns, and they’re trained to link households to the healthcare system. Many researchers actually refer to ASHAs as link workers for this very reason. 

Now they’re tasked with a variety of things. They initially entered the landscape as maternal and child healthcare workers, but now they are essentially population health workers. We saw that, particularly during COVID, they were pivotal. ASHAs were particularly pivotal in disseminating vaccines as well as the importance of vaccination. Because again, if you don’t have education around vaccines, would you really be taking up that vaccination?

ASHAs were pivotal because they provided both the information and the access, and that is so unique about them. A little bit more about this particular policy is that they were paid on a piece-rate basis. This is a very unique part of the community health worker system in this particular context, because before ASHAs existed in 1975, the Anganwadi workers were also introduced.

They were a little bit different from ASHAs because they were in charge of these Anganwadi centers, and they were giving out a lot of different benefits, even though it was more to do with maternal and child health. Similarly, in 1956, you had the auxiliary nurses and midwives, but these were very trained healthcare workers. Now, when you’re thinking about ASHAs, they are not as trained. These are middle school graduates; they’re 25 to 40 years old. They were very mobile workers. 

One of the very interesting requirements was that they had to be a married resident of the village. A lot of people ask me, “Why is that?” Well, that’s because India follows a patrilocal system. You want somebody in the village who you can refer to even during later years of your reproductive health. This is a very known person in the village who understands the culture, who understands all of these shared practices.

Particularly here, I would want to refer to S. Anukriti’s and others’ paper called “Curse of the Mummy-ji,” where they very clearly showed that reproductive health decisions are not borne by women alone. 

RAJAGOPALAN: It’s a family decision.

Trust, Access, and the Information Channel

BISWAS: It’s a family decision. It’s usually in-laws and such who will come in and will say, “Okay, you get to seek this healthcare services” versus “You don’t.” It’s not just about educating the mother; it’s also about educating the entire household. That is why ASHAs serve as this liaison between the community or the household, as well as the healthcare system. This is particularly important, I want to highlight, in the Indian context because—and this is from a Times of India article, where they surveyed Indians and they showed that Indians have over a 90% institutional distrust.

Meaning that Indians just do not trust public or private healthcare systems. We can think about this from many different angles, but if you do not have trust in a particular service, you are not going to be seeking help in that formal institution. Again, that is where ASHAs are coming in as this informal gap that they are bridging.

RAJAGOPALAN: The other part of it is, Indians also spend a lot on healthcare, private healthcare, out of pocket. You simultaneously have this question of distrust because most women, when they interface with the healthcare system, have had some unfortunate experience. When I talk to my friends, even the rich elite friends, and the kind of experiences they’ve had during childbirth, I’m frankly astonished anyone goes to a doctor in India sometimes.

There are so many layers to this. The first part, I guess, is the healthcare service actually needs to be forthcoming. It needs to exist in that particular village or that particular district. Then the next part of it is, now we need to encourage people to come there. The demand-side intervention that we discussed could be health insurance or cash transfers, or things like that.

Now, to motivate people to show up, there is going to be more information and more access, and this is basically provided through the ASHA worker. It’s a supply-side intervention in that they’re strengthening the district-level health center as a supplier, but it’s also a demand-side partial intervention in that they’re actually going and talking to the women and telling them the buffet of options that they can use at these centers, which of the services are free, which of the services need to be paid for, and so on and so forth.

What are the things that their children can benefit from, and not just them? Is that a good way now to think about ASHA workers, and do they operate the same way in every state and every district?

Pay, Hours, and Unionization: Why Conditions Vary by State

BISWAS: That’s an excellent way to think about ASHA workers in general. However, in terms of how do they operate in different states and different districts, that is where the variation is coming in. This is actually quite unfortunate, because when I’m thinking about the current unionization—there’s a lot of media articles surrounding the unionization of these workers, particularly after COVID, because they were seen to be very vital workers in the healthcare system.

RAJAGOPALAN: Overworked and underpaid, and they’re not part of the government infrastructure in terms of benefits and status and all the other important things.

BISWAS: Precisely. That is where they deviate from the other community health workers in the Indian context. All that they are fighting for is equal rights, that “we are healthcare workers, so please respect us like healthcare workers.” What is happening across the Indian context is that you have states like Odisha as well as in Bengal where they are being paid an honorarium, like how Anganwadi workers are being paid, of a per-month wage of ₹2,000, which is still pretty limited, especially when you consider the huge impacts that they’re having on population health.

In other states, like say in Tamil Nadu and Kerala, they’re now getting paid 7,000. As you can imagine, this huge deviation in terms of their remuneration is also not very clear, first of all, because the state government is the one who’s making these decisions, but the money is coming from the central government for the ASHA deployment. It’s very hard for the state government to really determine, “Okay, how much am I going to pay the ASHAs, and how much am I going to pay the healthcare institutions?” because these are both supply-side incentives.

Like you said, India is very much—particularly at the district level, it’s very much decided by how much is the income at that district. When you are thinking about a lot of these districts which have poor health outcomes, they also have really low socioeconomic and demographic statuses. Their income levels are low; their literacy levels are low.

It is a huge political challenge for these governments to really determine how much can we pay these workers. I’m sure it’s not really coming from a sense that, “Okay, let’s see how to undercut these workers.” It’s really coming from a fiscal or a budgetary challenge of how to really allocate these funds in a way that is justifiable.

How Incentives Are Structured

For instance, because ASHAs are being paid on a piece-rate basis, let’s look at some of the incentives that they are receiving, at least when the policy was being implemented. When you are talking about something like institutional deliveries and how they’re facilitating it, they were being offered from ₹200 to ₹600. It was based on the fact of whether or not the mother was located in a rural versus an urban center.

Why did this happen in the first place? This happened, first of all, in low-focus states. The government of India came in 2005; they implemented this really huge policy called the National Health Mission, and that is when the ASHA workers were implemented. Then they make this decision that in these very, very high-priority states, I am going to be deploying these ASHAs at both the urban and the rural level.

At the rural level, I’m going to be paying them ₹600 for every institutional birth, and at the urban areas, I’m going to be paying them a little bit less, just because of the fact that rural areas are much harder to access than urban areas.

RAJAGOPALAN: Yes, they’re underserved.

BISWAS: Exactly. Exactly. This is why the incentive was more. Now, ASHAs were not just hired to be bringing about changes in institutional deliveries. They were also being brought in to increase, say, immunizations for the children that were being born to these women.

Now, when you think about institutional deliveries, though, the incentive that is being offered to the ASHA in the same setting was around ₹250. That’s already so much less. Then, when you’re thinking about family planning, the ASHAs were not being remunerated at all for providing this kind of information access, but they were being given, say, ₹1 to distribute condoms and birth control pills.

There was a huge variation in the incentives. If you think about it from a standpoint of a worker who’s going in and they have’ limited hours. The deal is that when ASHAs were introduced, they were only allowed to really work two to four hours a day and for four days a week, which of course is not the case today, but that is how they came in. Now imagine if you have . . .

RAJAGOPALAN: Also, like, the idea that someone thought two to four hours a day, you can squeeze in the labor of a pregnant woman into two to four hours. The whole thing is laughable when we design some of this stuff.

BISWAS: Exactly.

RAJAGOPALAN: I hope it’s on average.

BISWAS: It goes to show what happens when it is men deciding these kinds of policies, reproductive health policies for women. You don’t really recognize how long on the labor and delivery floor. I work in an OBGYN department right now, and at the L&D floor, it can take up to like 48 hours sometimes. It’s a little insane to me [chuckles] that people would think that “Okay, this is going to be enough.”

No wonder these workers today are working sometimes 80 hours a week. That is why they are so overworked. Now, obviously, you can think about a situation like this. If you are a worker and you are now getting incentivized more for a delivery versus for family planning, then would you not want to substitute more deliveries for family planning? Of course you would, because that is where your incentive lies.

Multiple researchers have shown in low middle-income countries that incentives really drive the performance of the workers. It’s in particular not just social recognition and other incentives. It is pecuniary or monetary incentives. This has been shown time and time again that this is good. This is Econ 101. If you pay me more, I perform better.

That is exactly where this incentive design is coming from, but it doesn’t seem to be designed as something which could be working out in the long term unless there is a revision. That is exactly what my paper is trying to make people think about: that along those lines, that on the national landscape, there has been this policy which has been wildly successful. Why don’t we think about remunerating the people who have made these policies successful?

RAJAGOPALAN: Now you’ve laid this out so well for us, but as an economist, now I’m thinking about the nightmare of measuring this. How do you actually measure this kind of supply-side intervention? Because, as you just said, it has so many moving parts. One, you just literally have to count up the number of workers and associate them with districts. The districts are complicated because they have become too big, and our districts have split up, and all those sorts of issues. Also, all the other kinds of services they offer, the difference in rates. Can you walk us through how you’ve actually measured this and constructed your dataset?

From Design to Data: Building the District-Level Panel

BISWAS: Yes. Here is how I created a novel dataset using administrative data from the health management information systems, which was collected by the Ministry of Health and Family Welfare. Essentially, I created this district-level monthly panel dataset. I used the number of ASHAs who are receiving a performance incentive across public as well as private institutions. I normalize that—in other words, I just divide that by the population using the census of 2011.

Here, this is my rationale. Now, because ASHAs are being allocated on a 1:1,000 rule—the rule by the National Health Mission on the Government of India was that there must be one ASHA per 1,000 population. I exploited this, and I use this as my supply-side policy variation. Using my now treatment variable of the number of ASHAs per 1,000 population, I am able to link it to my household surveys. The pre-survey that I use is the district-level household and facility survey, which is collected before the implementation of the National Health Mission. I used the fourth round of the National Family Health Survey. Both are being collected by the IIPS [International Institute of Population Studies] in Mumbai.

Using this, I’m able to compare the long-term outcomes, such as antenatal care, institutional deliveries, and family planning, before and after the policy rollout across temporal variation, which is the policy rollout as well as this patient variation, which is coming from the placement of the ASHAs at the district level.

I find that for each additional ASHA per 1,000 population, there is an increase between 2% to 4% in the utilization of reproductive health.

RAJAGOPALAN: What does that mean, really? Can you unpack that up for us a little bit?

BISWAS: How do I put these results into perspective? Here is where I also bring in this different treatment intensity. Just in case we didn’t want to think about looking at the ASHA placement, and we might have thought that just because there are ASHAs, perhaps people are not using that service? I also create this other intensity measure where I look at the utilization of ASHA workers.

This could be utilization along any measure. It could be you coming into contact with an ASHA worker during your antenatal care. It could be you going to an ASHA when your child is sick. It could also be you going to an ASHA for family planning workshops or the distribution of sanitary napkins, et cetera. All of these factors are going to be playing a huge part in terms of your uptake of the services.

I find that from the National Family Health Survey in 2015/’16, that there were 334 women per 1,000 women in that particular survey who were using this service. If I’m now trying to put that into context, I’m actually finding numbers which are close to 17% to 20% of an increase.

Obviously, as we know, these numbers could be biased because of selection issues. These are actually the numbers. If you’re actually thinking of 100% utilization of these services, that is how large these numbers could be. It could be the order of 20%. It’s only because I only measure the access that I’m finding these smaller numbers.

We Are Measuring ASHAs—and Something Else

RAJAGOPALAN: Now, how do we know that this is not because of other factors? It’s not an information factor, or they heard about it on Facebook or WhatsApp, or something else. How do you actually identify that the causal effect is because of the policy intervention?

BISWAS: That’s a great question. One way that I try to assess this—particularly because we know that in the literature on information diffusion, it has been shown that information is also shared by your neighbors. It could be, like you said, a WhatsApp group is being created, and my neighbor is like, “Hey, there’s this new policy—why don’t you use it?” How do I know that it’s driven by ASHA? I test for this by looking at the different social groups that are in that particular neighborhood.

Controlling for, say, Hindus versus non-Hindus in the religious factor, or if I’m looking at caste groups, I don’t really see any changes in their uptake of these reproductive health services, which is driven by social groups. Meaning that it is the community health worker intervention that is driving this uptake of reproductive health services and not just the fact that my neighbor, who is in my community or in my social group, who is sharing this information, and therefore I am taking up these services.

The way that I measure my identification strategy is using a difference in differences design. The key is in how I’m measuring exposure.

DiD Simplified: How the Causal Claim Works

A difference-in-differences design is, like the name suggests, a double difference strategy. As I mentioned previously that I’m looking at a spatial variation of the ASHAs, which is the ASHA placement at the district. That’s my first difference. The second difference is coming from the timing of the policy, so the before and after. Since I’m looking at the long-term effect of this policy, I look at the ASHAs who are placed obviously after the policy was universalized, so post 2009, which is when I have my data available for ASHA placement. Before that policy, I just assume that there are no ASHAs in any of these districts, so they just get assigned a treatment of zero.

The only limitation to this is that, of course, there are other community health workers who are existing during this time. Later, I do try to use a placebo treatment where I’m trying to see, do these other community health workers—are they able to change this policy, or are they able to increase the utilization? But I don’t really find effects in that either. It is the ASHAs who are driving this effect.

In terms of thinking through this whole difference-in-differences strategy that I now construct is that, rather than relying on whether or not an individual mother has reported using NHM [National Health Mission] benefits—which, like we said, is subjected to a lot of selection biases—I’m using a very objective district-level measure. The district-level measure, it’s being shown in the literature to have a much more of a lower bound of effects, which is why I am underestimating, if anything, the effect of this policy.

RAJAGOPALAN: What is the district-level measure that you use?

BISWAS: The district-level measure here is the placement of the ASHA worker. The number of ASHA workers who are being paid the incentive—the performance incentive—when a birth of a child is being recorded in an institution, whether private or public. I also supplement this by using another treatment, which is the utilization of the ASHA workers. Both from access and from use, I find very positive and significant effects of this policy on use of these reproductive health services.

RAJAGOPALAN: Now, this is interesting. In some sense, what you’re telling me is that the policy intervention itself lends itself to measurement. Because these people are paid a piecemeal rate per service that’s provided, then you get a pretty granular view of how much their service is being used, as opposed to in a regular survey. Some of it could be memory issues, some of it could just be people . . .

When a serious person shows up at your door and they ask you, “Did you go to the health clinic nearby?” you’re likely to say, “Yes, I did.” Nobody wants to admit to going to a quack, necessarily, or not using services that are provided. You want to sound sensible and sophisticated when a government person shows up at your door. To that extent, it makes much more sense not to just use survey data, but also use these data, which is literally how much of a particular service was deployed and supplied. Presumably, there’s someone in the rural mission looking into not paying people if they didn’t do the service. There are multiple levels of checks at some level.

BISWAS: Precisely. Like you said, there’s always this social desirability bias that occurs when you’re collecting survey data. That is the concern when you’re using just survey data to assess policy impacts. That is exactly why I use this combination of administrative as well as survey data to answer my research question in a much more holistic way.

RAJAGOPALAN: The other thing about survey data—I also learned this from a couple of papers I was reading—it’s not the women who are of reproductive age who are always giving the answers. Usually, there’s someone else in the household who’s answering on their behalf. “Yes, yes, we took them to the clinic.” One is, of course, social desirability bias, but there’s also a whole number of issues on who’s actually answering the surveys themselves.

In some sense, having all these other ways to triangulate how much of a service is being provided is pretty helpful. In this case, the supply side can also tell you how much is being used just because of the way the intervention has been designed. Now, how does one think about the buffet of services? When you talk about a birth in an institutional setting as opposed to having a midwife come home, that’s one kind of service that’s being used. But, like we talked about, most women don’t use that service too many times in their life.

There are a number of health checkups, which may happen multiple times a year. It may be contraception, which is maybe you need to be prescribed once a quarter. It could be sanitary pad use, which is literally every month. What is a good way of thinking about all of these different things, especially given the fact that you told us previously that ASHA workers were more likely to supply or adjust their health services to the births, versus some of these other questions?

BISWAS: If I understand your question correctly, Shruti, and please correct me if I’m wrong, you’re asking how did the ASHA workers . . . what sort of competing interests they had in terms of saying that “This is the service that I’m going to offer,” versus another? No.

RAJAGOPALAN: I think the service you’re measuring pretty well, but I’m saying, do we have a good way of thinking about what else the women start using? They’re not going often enough to give birth, no birth. They’re doing only twice in their life.

BISWAS: Yes. That’s right. That’s right.

RAJAGOPALAN: You mentioned that ASHA women have this incentive to do more births than they have to do other things, right?

BISWAS: That’s right. This is where this whole information channel and social norms and things like that play a very, very big role in deciding what is it that will not just impact women’s health and reproductive health, but also other forms of healthcare access and utilization.

A recent paper that I’m working on in this context is on gender-based violence. We all know that gender-based violence is a global health concern. However, we don’t really know enough about what can change these sorts of decisions that are being made. It’s been shown that because of this information channel that ASHAs are being able to provide to households, not just to women, and also this role model effect, which is very unique. It’s coming in from the ASHAs being women and these role models for the community.

This really affects women’s empowerment in general. That also has interplay not just in women’s mobility and financial as well as other forms of autonomy, it also definitely affects their utilization of all types of healthcare services, and it also does affect their labor outcomes.

Policy Implications: Where to Invest and How to Train

RAJAGOPALAN: Here, I guess, we’ve talked about the policy intervention. What are some of the policy implications of what you’re telling us? In some sense, the ASHA worker policy, as you said, is pretty successful. It’s been rolled out all over India. We have more than a million ASHA workers. In that sense, this is a massive intervention that’s been made, which is vastly successful.

If I had to pick up from everything else that you’re saying, you’re basically saying, we need to invest more in this. Is the policy implication that we need more ASHA workers in every district? Is it that we need to pay them better? Is it that we need to train them better? What is a good way to think about the policy implication of this particular service? Now, again, I imagine you’re going to tell me there are differences at the state level.

BISWAS: Absolutely. You’ve exactly predicted what I’m going to say. However, I will start by saying yes to all. Yes to there being more workers, yes to paying them more, and also yes to having a better-designed incentive system. However, I know that every single person, whether at the micro or at the macro level, are all doing constrained optimization, and so is the Indian government.

Unfortunately, while more is better, and we want to move to the right-hand side of the indifference curve, it’s not always possible because of the budget constraints. Here, what I like to say is that we should definitely invest more, but it’s not just in more workers. I think that the answer is in designing a much, much better policy that incentivizes whatever it is that the Indian government is now choosing.

At the time that the policy was implemented, this was for a safe motherhood initiative. It was to complement the Janani Suraksha Yojana. However, what’s happened right now is that we’ve unfortunately had this whole thing where Indian fertility level has fallen below the replacement rate. It’s not just enough to say that “Okay, I’ve now provided safe births.” I think that that’s great on the extensive margin, but on the intensive margin, it’s also the quality of care that matters.

Therefore, training the ASHAs is very, very integral here. But training will cost more resources. Redesigning these training programs and rethinking the incentives that are being offered to ASHAs so that they can meet the policy that is being proposed by the Indian government is really pivotal at this turning point.

RAJAGOPALAN: You said something really important right now, which is we don’t just pick and choose policies based on what’s desirable. It’s based on what is possible, and beyond possible, what makes sense when we do the cost-benefit analysis. If we say, “Let’s invest another ₹100 in an ASHA worker,” the question is: Relative to what? I guess here I will ask you, do you find evidence that supply-side interventions are actually more cost-effective than the demand-side interventions? Because that would be a simple way to start to look at this problem, right?

Cost-Effectiveness: Supply vs. Demand

BISWAS: This is actually a very interesting point because, yes, in my case, for instance, when I’m trying to do a cost-effective analysis, I do think about the value of a statistical life, and then I do this whole comparison. I do find that, very much so, that even if you’re staffing 1 ASHA per 1,000 people, as the guidelines are suggesting, the cost is coming to about $70 to $100. This is taken from the ₹600 that you’re giving to the ASHA worker at the 2015 [level].

The ratio of the benefits to cost is enormous because the value of a maternal life lost is about $288,000 at this level. You can just imagine that this really goes to show that a supply-side incentive like this is really, really going to be improving outcomes much more than a demand-side, because at the demand-side, you are actually paying each woman an X amount of money to be delivering at the birth center. Here, instead, you’re employing a cohort of community health workers, and this cohort of community health workers can support each other, they can pass along this information and train each other, and they can go out there and they can not just facilitate one birth but multiple births.

You’re thinking about the same policy but from a supply side. It’s like having a multiplicative effect, as opposed to on the demand side, where you are just aiming one person at a time.

RAJAGOPALAN: Yes and no, right? Because the demand-side effect also means that if I have a greater uptick in terms of demand of going to these health service clinics and so on, then I’ll take people along with me. Most women never go anywhere alone; you spread the word and say you had a good experience. Even demand can start clustering in certain places.

I understand what you’re saying, that there’s a difference between paying each woman versus paying a particular worker who services a particular community. I still think I would disagree with you on the—I don’t think the impact on the demand-side intervention is just each woman, because at the end of the day, it means more uptick for the supply.

BISWAS: Yes, absolutely. What you pointed out is very, very crucial here. It’s the information channel. Whether it’s the ASHA who is informing the mother that, “Hey, giving birth in a healthcare center is going to be safer for you,” or if it’s the mother informing their friends or their sister or their sister-in-law, it’s still the information channel. And it boils down to that access concern, because information, to me, is a more supply-side mechanism.

Unless you have that information—and I think of the ASHAs as that focal point. They are giving this information; they are also facilitating the access. They’re combining these two very important measures. Like you said, without the demand, there’s no point of having a bunch of ASHA workers when people don’t really want to take up this service. I think that it has to coexist. Both are important and very, very necessary for the reproductive as well as population health landscape in India.

Why Supply-Side Effects Take Time

BISWAS: The argument that I’m trying to make in my paper is that supply-side incentives and supply-side measures in particular are understudied. That’s also because they don’t have such a high obvious and immediate effect, whereas demand-side, you can measure immediately that this was the impact of the policy.

That is why it makes supply-side incentives a little bit trickier to design and to advocate for. That’s why I try my best to push hard as much as I can to show that supply-side measures really do have this kind of an effect. Sometimes it’s this understudied effect because of this multiplicative nature that it will have only once you give the policy time to reap its benefits.

RAJAGOPALAN: Now, luckily, we have time, and we’ve also seen a pandemic, and we’ve seen their impact on nonreproductive services, on child services, on vaccinations. The broader point of what I really loved about your paper is, it’s hidden in every section that you write about, which is, you see in every state and in every district this building of state capacity when it comes to healthcare services, which was previously missing.

Some of that state capacity is missing because of personnel issues. It’s too costly. We never rolled this out. Some of that state capacity is missing because no one wants to show up at the clinic, so that no one develops the clinic further. It’s just being used as a storage facility or some other nonsense.

This constant building of healthcare capacity at every district, I think, might be one of the loveliest things about the ASHA worker program. Capacity is not just buildings and clinics. It’s actually people and their human capital. The fact that there are a million women in India who can actually do this and help other women is quite extraordinary.

BISWAS: No, I totally agree. I totally agree. It’s not just the fact of building a hospital, but it’s also who is running that hospital. It’s twofold.

Beyond Pregnancy: Anganwadi Daycare and Women’s Work

RAJAGOPALAN: A couple of questions. You sent me your whole dissertation, and I’ve read it, but I don’t think we have time to go into everything. I think of your dissertation very much as, like you mentioned, looking at supply-side interventions and can they work? We talked about this reproductive health and pregnancy situation. You also have a paper on when you look at supply-side interventions beyond a pregnancy situation. What happens once a child is born? Can you briefly walk us through that before I let you go?

BISWAS: Of course. Like you said, once a child is born, the constraint is going to be shifting from healthcare to childcare. In the second chapter of my dissertation, I look at the impact of the Anganwadi daycare system, which is a very unique policy in the Indian landscape as well, because the Anganwadi system is twofold. The Anganwadi center is both providing the supplementary nutrition, which has been studied by a lot of researchers, say, Saravana Ravindran. He’s shown that this policy has had a lot of very positive effects on child health outcomes, as well as maternal health outcomes. He doesn’t really find any effect on employment measure.

I dig a little bit deeper into this to see whether or not childcare can boost maternal employment. If so, what is the cost-effectiveness of such a policy? Affordable daycare, for instance, is a huge determinant when you’re thinking about when mothers of young children would be staying in the labor force. Particularly for them in the margin, would they be going into work?

RAJAGOPALAN: This is a nightmare in India. India has some of the lowest levels of female labor force participation. A lot of the labor force participation in rural areas doesn’t even get calculated well, because the farm is next to the household. Even with all of that, we still have this major problem. Thinking about local daycare and Anganwadi facilities for an infant or a child, for a young mother, seems like a really important question right now in India.

BISWAS: Precisely. You’ve actually hit the nail on the head because that is exactly where I find the impact of this policy. It is women who are working in the agricultural sector, as well as who are informally employed. They are the ones who see the huge benefits of this policy. You’re thinking about rural women as well, because if you’re in an urban setting, perhaps you have access to a bunch of other institutions. In this case, we’re also thinking about informal childcare institutions in the Indian context. You can think about an older sibling taking care, particularly older sisters, and also maternal grandmothers. That has been shown to be a huge factor.

In my paper, I don’t really find any effects of any other informal networks in the household. I’m able to show that it is the Anganwadi daycare that is being able to boost maternal employment. Particularly, the mechanism that I explore is that of child health. Like I mentioned, Anganwadi centers are providing the supplementary nutrition policies for pregnant as well as nursing mothers, as well as for their young children. This is only given from zero to two years of age.

I exploit the variation of that zero to two years age, using them as the control and using the three to five years of age as the treated cohort. Why? Because the three to five years of age, they get this very unique thing called the ECEI—the early childhood education initiatives. That is the preschool of the Anganwadi daycare system that I’m trying to use. I do find the effect is pretty large. For every one-standard-deviation increase in the daycare or Anganwadi daycare, I am finding an effect size of 8% increase in maternal employment.

RAJAGOPALAN: It’s huge.

BISWAS: It’s a huge increase.

RAJAGOPALAN: Especially given how low the base is in India. This would be fantastic.

BISWAS: Precisely. This impact is basically identical to the impact that a policy like MGNREGA is finding. It’s at a cost which is at a fraction of the MGNREGA policy. This is again going back to that whole demand-side incentive, which is costing the Indian government more, versus this supply-side incentive, which is a lot easier and is much more cost-effective.

RAJAGOPALAN: Presumably something the women actually want.

BISWAS: Yes, precisely. Because it’s been shown that there has been a boost in the maternal employment. Whereas paternal employment, very interestingly enough, of course, has not changed because, in my sample, almost there’s universal—men are all employed in the workforce. I don’t really find any effect there.

RAJAGOPALAN: [chuckles] Yes, that’s another charming side effect of the social desirability bias in rural household surveys where everyone is employed.

BISWAS: Precisely, yes. [laughs]

RAJAGOPALAN: No one is unemployed. No one is underemployed. This was fascinating. Thank you so much for sharing this work with us, Nayantara. It was a pleasure speaking with you.

BISWAS: No, it was a pleasure for me as well. Thank you so much, Shruti.