Affiliate Spotlight: Seema Jayachandran on deforestation, corruption, and the roots of gender inequality

Posted on:
Douglas Clement
Anjali Nair
Seema Jayachandrani sits on a wooden bench outside and smiles at the camera.
Photo: Brittany Hosea-Small
Featuring research by Seema Jayachandran.

Northwestern University economist discusses wide-ranging research in the developing world and insights gained into gender parity, economic growth, and pandemic impact in poor nations

This interview was originally posted on the Federal Reserve Bank of Minneapolis website on February 12, 2021.

Seema Jayachandran planned a career in theoretical physics when she graduated from MIT in electrical engineering and finished her master’s in physics and philosophy at Oxford University. Harvard offered her a spot in its selective doctoral physics program. But coffee conversations with an acquaintance changed her life.

“What he was doing was really cool,” she recalls. His discipline, economics, offered an irresistible blend of high theory and hardheaded fieldwork. It was “quantitatively analytical,” like physics, “but with more of an application to society.” She applied to Harvard’s economics doctoral program. “I didn’t have much economics when I transferred,” she admits. “But it was a perfect fit.”

Indeed. Jayachandran, now a professor at Northwestern University, is a leading authority in development economics, with particular focus on women. Much of her research involves randomized, controlled trials to evaluate program interventions aimed at improving well-being. Many of her field experiments are in India, but she’s worked throughout the world, from Mexico to Burkina Faso to Zambia.

Today, she is co-director of the Development Economics Program at the National Bureau of Economic Research. She also sits on the board of the Abdul Latif Jameel Poverty Action Lab (J-PAL) and chairs its Gender Sector.

One of J-PAL’s founders is Sendhil Mullainathan, the economist Jayachandran shared coffee with years ago. “One of the most useful things I’ve done for the economics profession is help Seema transition from physics to economics,” he now jokes. “She’s pushing the field to integrate the best of economics reasoning and modeling with the best of the causal inference revolution.”

Looking back at her career transition, Jayachandran differentiates her roles as producer and consumer. “I still love consuming physics. There’s just such a beauty in it,” she says. “But a choice of a career is really about producing knowledge. For me, economics was the obvious choice.”

Interview conducted on October 9, 2020

Gender inequality in developing nations

You’ve done so much important work, especially about women in developing nations. We’d like to start by focusing on your research on the roots of gender inequality in the developing world.

You wrote a 2015 paper documenting that gender inequality is larger in poor countries while also discussing reasons gender gaps might diminish as nations develop.

Could you review some of that for us? In what ways is there more inequality across genders in poor countries than in richer? And how might the process of development help diminish gender inequality?

There are lots of aspects of people’s well-being, and for many of those measures of well-being, the gender gaps favoring men are larger in developing countries.

It’s true in terms of educational attainment, for example, although I should note that in rich countries like the U.S., that gap has now reversed. Women here go to college more than men.

But if you look at how that pattern varies with countries’ GDP per capita, you’re more likely to see in poorer countries that girls are lagging behind boys in schooling. You also see it in access to health care and life expectancy.

And you see it in softer measures. In surveys where people are asked about how much freedom of choice they have in their lives, women are more likely to report having less freedom of choice than men. That gap is more common, and larger, in poorer countries.

There’s a famous U-shaped relationship in the data between economic development and female labor force participation. Let me insert a piece of logic here. Economists have focused on female labor force participation because often if you could boost women’s earning capacity, then some of the other measures of well-being might improve. Women would have more autonomy if they could earn more money. Parents would send their daughters to school if they expected them to be entering the labor market. Things like that.

Historically, in richer countries, you’ve seen this U-shape where, initially, there are a lot of women working when most jobs are on the family farm. Then as jobs move to factories, women draw out of the labor force. Claudia Goldin has done the seminal work on this in developed countries.

But then there’s an uptick where women start to enter the labor market more and not just enter the labor market, but earn more money.

There are several reasons why we think that will happen.

One is structural transformation, meaning the economy moves away from jobs that require physical strength like in agriculture or mining towards jobs that require using brains. Women have a relative advantage in such jobs. By that I mean that while for jobs that rely on physical strength, men are more productive than women, in jobs that draw on our cognitive or interpersonal skills, women are on equal footing with men. They might even be advantaged, or at least any disadvantage is smaller than in strength-based jobs. That means that women are going to be better positioned to be successful in the labor market as the economy naturally evolves.

For example, the percentage of the economy in services is higher in the U.S. compared to Chad, and service jobs are going to advantage women. So that’s one reason that economic development helps women in the labor market.

The second reason is improvement in household production. Women do the lion’s share of household chores and, as nations develop, they adopt technology that reduces the necessary amount of labor. Chores like cooking and cleaning now use a lot more capital. We use machines like vacuum cleaners, washing machines, or electric stoves rather than having to go fetch wood and cook on a cookstove. This labor-saving technology frees up a lot of women’s time because those chores happen to be disproportionately women’s labor.

Some of those technological advances are in infrastructure. Piped water, for instance, where we’re relying on the government or others to build that public good infrastructure. And some is within households; once piped water is available, households invest in a washing machine.

The third reason is fertility. When countries grow richer, women tend to have fewer kids and have the ability to space their fertility. For example, both the smaller family size and the ability to choose when you have children allows women to finish college before having children. Or at a critical point when continuity in the labor force is important, she might delay having another child.

Less on the radar is that childbearing has also gotten a lot safer over time. There’s some research on the U.S. by Stefania Albanesi and Claudia Olivetti suggesting that reduction in the complications from childbirth are important in thinking about the rise in female labor force participation.

All of these forces are reasons why promoting economic development can improve women’s earnings and their participation in the labor market. It’s an optimistic story—a lot of this problem might get solved if we figure out how to make poor countries grow. Another reaction might be that we can take a laissez-faire approach if we think economic forces are going to solve a lot of the problem of gender inequality.

But it doesn’t mean we shouldn’t use policy to expedite change. Moreover, there are also some thorny exceptions to the rule of inevitable progress, where it just doesn’t seem that even if we were willing to be patient for decades or centuries, we would see great improvements for women. Some inequality will persist because of society-specific cultural norms that favor males unless we tackle those problems head-on.

“Missing women”

That’s perhaps a good transition to research you’ve done on gender imbalance, particularly your 2017 “Fertility Decline and Missing Women” paper. You were looking at Haryana state in India where the ratio of boys to girls is 1.2. And Haryana also has a very low fertility rate. You showed that falling fertility explains roughly a third to a half of India’s sex ratio increase over the past 30 years.

Could you tell us more about this work? In particular, what is the mechanism that links declining fertility to the rise in gender imbalance?

For me, this is one of the sharpest examples where what we usually think of as progress is actually making an aspect of gender equality worse, rather than better. It’s not just that it’s not improving; it’s making it worse.

There’s a strong desire to have sons in India. This is true in some other societies, too, but certainly not all of them. It tends to be present in patriarchal societies where sons play a role in taking care of their parents and parents pass down land to the eldest son. One thing that’s important about the preference or desire for a son is that it’s really about the central role played by an oldest son. So having one son is really important.

For me, this is one of the sharpest examples where what we usually think of as progress is actually making an aspect of gender equality worse, rather than better. It’s not just that it’s not improving; it’s making it worse.

There’s a strong desire to have sons in India. This is true in some other societies, too, but certainly not all of them. It tends to be present in patriarchal societies where sons play a role in taking care of their parents and parents pass down land to the eldest son. One thing that’s important about the preference or desire for a son is that it’s really about the central role played by an oldest son. So having one son is really important.

When women get more education, it does erode a little bit of this importance of having a son for them. But it doesn’t make a big dent in that. It’s still important in the culture to have an eldest son. So that’s a little bit of progress on that one desire. But it has also led women to want to have fewer kids. When you put those two effects together, improving women’s education could have this ironic effect of actually increasing sex-selective abortions.

Changing gender attitudes

Perhaps with that in mind, you’ve also studied a number of interventions that seek to change gender attitudes. We’d like to ask about a recent project, also in India’s Haryana state, that involved classroom discussions about gender equality. It was a large study, 14,000 students in over 300 secondary schools, for two-and-a-half years.

Can you briefly describe the study? What did you find, and is there potential for expanding it beyond the 300 schools?

That project very directly comes out of the work we just talked about where normal economic forces—things like women getting more education or more availability of jobs that give women an advantage—those alone aren’t necessarily going to address the sex ratio. And so then how do you fix that humanitarian or human rights problem?

In that project, we said, “Let’s try to see if we can get to the root of the problem and try to shift these attitudes that individuals hold.” And then, if it can be scaled up, it can change the whole norm within the community.

This was a nice example of collaboration between government and a nonprofit and researchers. The project came out of the government of Haryana approaching J-PAL and saying they’re interested in trying to address sex ratios specifically. It then broadened to several aspects of gender equality. I’m not sure the sex ratio was really the focus ultimately, but the genesis was about the sex ratio. And if you think about it, while governments hopefully care about the human rights aspect of it, there are also just very practical reasons to not want a society where there are 10 million extra young men compared to women. That seems like a recipe for unrest. Just from a pragmatic point of view, governments want to try to reduce sex selection.

They actually have some policies in Indian states, conditional cash transfers, where parents are paid if they have daughters and then become sterilized. I find it a highly fraught policy, in terms of my personal reaction to the ethics. A government mandate to adopt those fertility patterns would clearly be viewed as unacceptable. With a voluntary transfer program, poor people are probably more likely to accept it, which to my mind opens up some of the same ethical issues.

But even leaving aside the ethics of the matter, it’s not clear that paying people is a long-run solution. You can even imagine that it starts to erode intrinsic appreciation of daughters if people are getting paid by the government to have daughters.

In those conversations with government officials, we said, “Can we try a different approach of trying to change attitudes?” And we decided to focus on kids, for a couple of reasons.

One is that kids aren’t as set in their ways. Think about, say, climate change or gun control in the U.S.; young people are often the ones leading those movements. So let’s focus on young people.

But, also, because kids are in schools. If you’re trying to change attitudes like promoting a human rights idea in a society, schools are a really powerful way for a government to do that because you have kids in classrooms.

Breakthrough, an NGO in India that works on gender and human rights, designed an intervention which is really focused around kids thinking through these issues and discussing them in class. It was a very discussion-based intervention.

How old were the kids? What grades did this involve?

They’re in grade seven to 10. So, on average, they’re about 12 years old at the beginning of the intervention, and 15 at the end. Breakthrough developed the curriculum and, for this pilot, Breakthrough staff would come into classrooms, with government approval, and lead these sessions. The regular teacher participated sometimes, and sometimes he or she just took a break while the Breakthrough person led the session, walking kids through issues and questions about gender roles.

The particular discussion session that resonates most for me is on household chores. The kids break into groups and talk about who does different household chores like cooking and cleaning. And then they come back together and share their answers.

It turned out that they all said women and girls do all the chores. And they then talked about, “Is that fair? Why is that?”

If they said it’s because women are better cooks than men, then the Breakthrough facilitator would say, “Well, in that case, wouldn’t it make sense for women to be able to cook in restaurants?”

It’s a combination of a moral argument and also the economic argument that discrimination is leaving money on the table. If women are amazing cooks, it would be good for the world if their talents could be shared with more people.

What did you find, in general? Did these discussions, about chores and other issues, change attitudes?

Yes, we found that it had a large effect on kids’ attitudes. Our best measure is what they believe is right or wrong. That’s tricky to measure because students might just provide what they know is the “right answer.” So we took a lot of extra steps to try to rule out reporting bias.

It does seem that kids genuinely started to change their views on whether it’s wrong for women to work outside the home, for instance, or whether boys should get more resources for school than girls do.

We saw big changes. Of the attitudes people initially held that didn’t support gender equality, about 16 percent were converted by the program. So it doesn’t solve the entire problem, but I don’t think any intervention could. Moreover, you can imagine running this intervention for longer than two years.

I was encouraged by seeing these big effects a few months after the program. But the really exciting thing about the project is that when we followed up with the kids two years later, we saw those effects had persisted.

It makes me less worried that this is reporting bias—kids telling us what they think we want to hear. But, also, I’m excited that this really stuck with kids, and it might stick with them in the future. They were about 17 years old when we last surveyed them. But soon they’ll be marrying and maybe becoming parents themselves. And the boys in the program will make decisions or weigh in on whether their wives can work.

One interesting pattern was that we saw similar changes in attitudes for boys and girls. Girls start out more supportive of gender equality, but both boys and girls become even more supportive than they initially were.

But there was a gender difference in terms of translating that into behavior. These kids didn’t have a lot of autonomy because they were still living with their parents. But of the decisions they were making, we saw that boys were translating that attitude change into behavior change more than girls were.

Is that because boys had more decision-making power than girls?

Yes, exactly. Part and parcel of the problem that girls don’t have power in society is that when they believe in something, they can’t necessarily translate it into action. That doesn’t mean you shouldn’t work with both boys and girls. But it really makes it hit home that you want to involve boys in these programs because the very nature of the problem is that they might be able to effect change more easily.

What do I expect to find in three years or five years? What I’m most optimistic about seeing is that the wives of the boys who were in the program are going to be more likely to be working. Those boys might get some pushback from parents, of course. “Why are you not being masculine enough? Why are you letting your wife earn money?” But for a boy, pushing back on parents seems easier compared to what a girl who was in the program will have to do. She’ll have to convince her husband. She’ll have to convince her in-laws. And there’s that power differential.

I’m hoping we’ll still see changes in that at some point, but I think the first change we’ll see is with the wives of the boys.

I should add that India’s female employment rate is one of the lowest in the world, around 20 to 25 percent, so enabling more women to work is an important goal.

Are you optimistic about expanding this program, changing attitudes on a wider scale?

There are conversations right now between Breakthrough, J-PAL India, and a couple of state governments to try to scale this up. We’ve had some promising conversations, but I think everything’s on hold during the pandemic.

One state was interested in just scaling it up right away with government teachers. That’s the cost-effective way to do so. Another state wanted to try something small. This is often how randomized trials translate into policy. This state wants Breakthrough to run it initially with government teachers shadowing them. And then the next year, there’d be a small-scale pilot where the government teachers would do it. And then the state would scale it up.

So one state is gung-ho and ready to go full-force forward, whereas the other wants to try it out at a small scale, which perhaps is more sensible.

We’re hopeful that one or both of those efforts will allow the program to reach a state in India. I don’t know what the population is, but probably 30 or 40 million. So millions of kids.

Female entrepreneurship

Continuing on the topic of women in the labor force, we’re curious about your 2016 India study in which you showed that women attending business trainings with a friend were able to expand their businesses and even increase household earnings by 12 percent.

Could you share your insights regarding constraints in female employment, but also ways to further engage women in entrepreneurship?

Sure. Two reasons women are not able to be as successful in entrepreneurship is that they don’t have access to capital and they don’t have access to as much education. Some of the most common interventions are therefore centered around microcredit or business-skills training.

In our research in Gujarat, we saw that social norms and constraints on women’s freedom were also a barrier. Women can’t move around as freely in their villages, their communities, or their cities. That means they can’t necessarily find the low-cost supplier or travel to different neighborhoods to find potential customers. Another aspect of that simply seems to be having people to bounce ideas off of or who give you some encouragement.

So when we had people attend a business training with a friend of their choosing, we saw much bigger impacts than when they attended the business training alone.

We then tried to understand why it mattered to come with a friend. Was that making you pay attention more and learn the material? It didn’t seem to be that. It really seemed to be about ambition. Women set more ambitious goals, and they achieved those goals.

We all rely on other people to push us or boost us up when we’re discouraged. One of the downsides of all the restrictions on women is they don’t have as much of that. Having a support network is important psychologically. It’s important per se. But it also has this knock-on effect on how successful they are as entrepreneurs.

When economists and policymakers think about active labor market policies or programs to improve skills and success in the labor market, we usually think of policies around adding human capital and giving access to credit.

But my takeaway from this research is that for women, at least in some societies, there’s a whole other set of policies related to addressing these restrictive social norms that should be an important part of the portfolio of labor market policies.

Deforestation in Uganda

You’ve also done very important work on economics of the environment. We wanted to ask about a study in western Uganda involving payments to landowners to prevent deforestation.

The intervention compared outcomes in about 120 villages, where landowners in half the villages were paid about $28 per hectare per year to not cut down their trees, roughly what they would have earned were they to sell lumber from that land. It was a fascinating piece of research.

Could you describe that study—a bit about how you carried it out, what you found, and what the policy implications might be?

In short, we found that paying landowners to keep their forests intact led to a big increase in forest cover and was a cost-effective way to reduce carbon emissions.

The idea of trying to address deforestation in poor countries has long been considered low-hanging fruit for addressing climate change. It comes down to the economics of what people have to sacrifice to reduce their carbon emissions.

In many developing countries, people are clearing forests to grow some cassava or other crop to feed their family. Obviously, that’s really important to them. You wouldn’t want to ban them from doing that. They’d go hungry!

But if we think about it in absolute terms and global terms, the income people are generating by clearing forests is small. If we can encourage them to protect the forest and compensate them for the lost income, then protecting the forest actually makes them better off than clearing it. And because the income they’re forgoing is small in global terms, that could cost a lot less than other ways of reducing carbon emissions.

Climate change is quite unique in that it’s really global. Sitting here in the United States, I benefit as much from carbon reductions in Uganda as from carbon reductions in the U.S. Rich countries are responsible for most of the carbon in the atmosphere, and they also have the resources to address it. From both standpoints, they should therefore bear a lot of the cost of reducing climate change.

If you then look around the world and ask where and what are the low-cost ways to reduce carbon emissions, reducing deforestation in poor countries makes sense.

I’m struck by the fact that, for the time being, you’re living with your parents in California after helping them evacuate from forest fires presumably related to climate change.

Yes, exactly. Being in California this August and September really makes concrete how climate change is affecting our lives right now.

Ten years ago, researchers and other people who strongly believed in climate change were thinking about and framing climate change as in the future. But now, for many people, climate change is something they’re feeling in the here and now.

One of the remarkable things about this study was how you were able to analyze tree cover. Can you describe the technology involved?

This is a truly interdisciplinary project. One of my collaborators is a specialist in remote sensing, which is analyzing satellite data to measure land use and forests. It’s similar to the machine learning that economists use often. But here we use high-resolution satellite imagery, where a single pixel covers 2.4 meters by 2.4 meters of surface area.

If I showed you one of our images, you could spot every tree with your eye. Of course, there are 300 million pixels in the area we have imagery for, so you don’t want to go and hand-classify all those trees. But we have the algorithms and the techniques to classify all of those pixels into whether there’s a tree or not.

We have this imagery for both the control villages where the program wasn’t in place and the treatment villages where it was, where landowners were paid to not cut their trees. So we could see before-and-after images of what happened in both control and treatment villages.

By doing that, we could see that in the control villages over this two-year period, 9 percent of the tree cover that existed at the beginning was gone. That’s a really rapid rate of deforestation. If you’re losing 9 percent of your trees in two years, you can play that forward, and it won’t be long before there’s essentially no forest in this area.

By comparison, in the villages with this program, the rate of tree loss was cut in half, closer to 4 to 5 percent. There’s still tree loss—not everybody wanted to participate in the program—but the program made a pretty big dent in the problem.

Another thing the high-resolution imagery shows is the pattern of tree-cutting, and that showed that we’ve been underestimating the rate of deforestation in poor countries. On relatively low-resolution satellite imagery, we could see clear-cutting of acres and acres of land. That is an important problem. But recent estimates suggest that, especially in Africa, half of the deforestation is smaller landholders who are cutting four or five trees in a year to pay for a hospital bill, say. That adds up.

So the finer-resolution satellite imagery could distinguish between selective cutting and clear-cutting, and showed substantial selective cutting that hadn’t been identified before.


Corruption and economic growth

Let’s jump to your 2017 study in Vietnam about firm growth and corruption. You investigated the relationship by looking at 10,000 firms throughout the country. And, in a nutshell, you propose that regional competition for firms helps explain why bribery rates decline as firms grow.

Can you tell us a bit about that research and how that relates to the well-documented inverse relationship between a nation’s wealth and its level of corruption?

As you say, there’s a well-known negative correlation between corruption and the economic development of a country. What’s been studied most often is the idea that corruption can dampen economic growth. It’s basically a tax on firms and creates uncertainty, and that’s not good for growth.

We were interested in the opposite. And Vietnam is a good place to study whether growth drives out corruption. Our data sets tell you something special about Vietnam’s business development strategy. They were originally collected so the government could create something called the “provincial competitiveness index.” It rates the business climate of different provincial governments. The idea is that shining a light on whether there was a lot of red tape in different provinces would enable firms to choose where to locate, and that would give provinces an incentive to be less corrupt and have less red tape.

We took that idea and asked, What happens when there’s economic growth? Does that lead to a reduction in corruption? We found that essentially what’s happening is that when industries are growing, it becomes more attractive to keep them in place. There are also reasons to attract new firms: They’ll create jobs, and provincial governments get more tax revenue. Economic growth therefore means that the risk of losing these firms is bigger.

So how do you reduce your likelihood of losing firms? By cutting back on the bribes that are demanded of them.

Lowering the cost of doing business.

Yes. Vietnam’s overall strategy was to decentralize a lot of the interaction with businesses to the provincial level and then create some competition among the provinces.

Part of the strategy is that firms need to be mobile. They need to be able to move to another province to take advantage of that competition. But if you can create the mobility, you can have a race to the top among these provinces. So firm growth leads to less corruption.

Odious debt

Some of your earliest work was on “odious debt,” a paper published in 2006 that you wrote with Michael Kremer, now a Nobel laureate.

Would you briefly explain the concept of odious debt? Why does your research suggest that loan sanctions limiting a government’s ability to borrow internationally are more effective, and more just, than trade sanctions?

Odious debt is a term that originates in international legal doctrine. It refers to sovereign debt, meaning government debt, incurred in the name of a country but not used for the benefit of the country’s citizens. It may be looted by the country’s leader and sent to a Swiss bank account.

Even worse, it may be used to oppress the people. Think of the apartheid government in South Africa taking out debt and using that money to oppress the Black population, for example. Then, at the end of apartheid, South Africa as a continuous sovereign nation now owes all of this money. That’s a clear moral injustice.

The question is, How do we prevent that? Again, South Africa is a good example because there was a movement after the end of apartheid to have the commercial banks and bilateral lenders forgive those loans as unfair loans.

One worry is that there’s a slippery slope, that for every South Africa, post-apartheid, where it’s a clear-cut case that that loan was immoral, there are going to be many cases of gray areas, where lenders will worry that after they make a loan, the world might say it needs to forgive this debt.

That could make lenders more reluctant to lend in the first place, or it could drive up interest rates on foreign lending. There’s clearly a lot of benefit to clearing up this uncertainty from the get-go.

The idea we had, and formalized in our model, is that it would be valuable at the time to have a public pronouncement—even if it wasn’t through some formal court process, but, say, from the U.N. Security Council or even just the U.S., Britain, and France—that collectively said, “We do not think that the current government in South Africa represents the people, so if there’s any debt afterwards, we will not consider it valid. If the future South African government wants to renege on that, we won’t count it as a blemish on their credit rating; we’ll continue to lend to them.”

Once a commercial bank knows that there’s going to be no penalty for South Africa to default on this, they’ll be very reluctant to lend to them. It nips the problem in the bud. Not only do you not have this slippery slope, but you prevent that loan from taking place in the first place.

This is also a type of economic sanction. The fear of not being able to borrow might make governments moderate their actions. One of the big advantages of this compared to trade sanctions is that, here, the sanction has bite even if it’s imposed by just, say, the UK, the U.S., and France, as long that coalition has deep enough pockets that it can be a country’s sole creditors. Even if no other country in the world was on board with the sanction and they all thought post-apartheid South Africa would be wrong to default on apartheid debt, South Africa would be fine economically if it just went ahead and defaulted.

What’s key here is that lenders in those other countries can see how this will play out, realize post-apartheid South Africa will default, and never make the loans in the first place. They’ll avoid lending to apartheid South Africa purely for dollars-and-cents reasons.

That’s a big difference from trade sanctions where you really need close to 100 percent of countries to be in agreement to not have leakage and have wholly ineffective trade sanctions. What matters for a loan sanction is having a coalition with enough strength, [but it needn’t be global consensus]. It’s hard to get a 100 percent coalition of governments to all agree to any sanction.

Like many things, it’s a double-edged sword. A foreign policy tool like this could be used trilaterally among three Western countries and doesn’t require Russia and China to be in agreement. That might be a concern. But at other times, that’s an advantage.

A related advantage is that loan sanctions are less fragile than trade sanctions because they’re self-enforcing. Potential creditors, like private banks, will tend to abide by them because any credit issued to a sanctioned government probably won’t be repaid.

The other rationale in favor of loan sanctions is about who’s hurt by trade sanctions. Trade sanctions are going to translate into higher food or medicine prices; the very people you’re trying to protect are often hurt by trade sanctions. But loans, because they’re going into the coffers of the government, are not affecting general markets directly; they’re affecting government revenue. And if that government revenue is being used to fund military police, then cutting that off is not doing the same humanitarian harm that trade sanctions can do.

Pandemic and progress

Let me ask about the effect of the pandemic. The Gates Foundation just put out its annual Goalkeepers Report. It’s usually pretty optimistic. This time, it seems the opposite.

It says that developing nations have regressed on the vast majority of sustainable development goals. And vaccine coverage, a good proxy for the health system, had been “set back about 25 years in about 25 weeks.”

Given your experience throughout the developing world, do you broadly share that bleak assessment? And how has the pandemic shaped your research agenda?

On so many metrics, there’s been steady progress over the years in reducing poverty and improving vaccination coverage, et cetera. When you study developing countries, you’re studying the problem areas, but if you take a step back, you can see progress. The data site out of Oxford University, Our World in Data, has been wonderful for reminding us of these big-picture improvements over centuries or even decades.

One of the many tragedies of the pandemic is that some of those metrics of hunger, poverty, and infant mortality are all going to be increasing. The optimism or pessimism is really going to be about how quickly we rebound.

I’m hopeful that once we’re past this pandemic, people will go back to getting prenatal care, will go back to getting vaccinations. For those future generations, it’s going to be a V-shaped recovery on some of these metrics.

But the challenge, as we know from social science research and public health research, is that there are critical times in child development, for example. If you have poor health in early childhood or you don’t have cognitive stimulation at critical ages, those can have lifetime effects. I’m optimistic that we haven’t done permanent damage to the immunizations of infants born in the future. But a year’s worth of one age cohort without access to health is a tragedy.

It’s going to require a lot more resources for the remedial health care and education for those cohorts that can’t rebound. Parents in the U.S. are struggling with Zoom teaching, but think about someone in a country where there isn’t internet service so they can’t get remote teaching. Parents themselves might not have enough education to be substitute teachers and help their kids keep up.

In terms of my own research, while some people have pivoted entirely towards working on COVID, I’ve mostly used this time as an opportunity to brainstorm some projects I want to work on post-pandemic and to finish up some older projects. So much of my research depends on surveying people, and that type of fieldwork was upended by the pandemic. So I have several projects that were in progress that are on pause for a while. In other cases, we scrambled and switched to phone surveys.

But I do want to add to what we know on COVID. I’m doing a project in India among people with diabetes and hypertension, which are risk factors for severe complications and mortality from COVID. Those people also rely on more regular interactions with health care systems. They face twofold risks. Because of restrictions, they might not be able to manage their disease as well, and not managing their disease puts them at especially high risk.

In this project in South India, we’re surveying people. From a previous study with a set of diabetics and hypertensives, we had good phone number information. We’ve been surveying them to see how this is all affecting them.

The simple question we ask is, “When you think about people your age who have diabetes, do you think you’re in the top half or the bottom half of people in terms of your risk of getting COVID, or dying from COVID if you get it?”

We’ve found that 90 percent of people say they’re in the lower risk half of people. People are pretty accurate about other people’s risk, but overly optimistic about themselves.

We’re trying a couple of things to try to debias people. One is simply pointing that fact out, that not everyone can be lower-risk. We tell them we surveyed a bunch of other people here in Coimbatore, and 90 percent say they’re a low risk. But really only 50 percent can be in the low-risk half.

I don’t know if it will make a difference, but we’ll see!

Another thing we do is based on the fact that people often think, “OK, I’m a 62-year-old with diabetes, but I’m really as healthy as a 52-year-old.” We’re just telling people, “OK, maybe the statistics for 62-year-olds aren’t relevant for you, but here’s some information on how risky it is for 52-year-olds.” That lets people live with some overconfidence about their health, but still points out that even then they shouldn’t be complacent.

Hopefully that project will provide some useful data on how diabetics are doing during this pandemic and help some of them take extra precautions that will help their health.

Authored By

  • Doug Clement Headshot

    Douglas Clement

    Managing Editor, Federal Reserve Bank of Minneapolis
  • J-PAL logo

    Anjali Nair

    Research Assistant, Federal Reserve Bank of Minneapolis