Dr. Miriam Laker is the Global Director of Research at GiveDirectly and a Senior Research Scientist and Epidemiologist with nearly two decades of experience conducting research. Amongst her extensive experience, she led the design of the evaluation plans for GiveDirectly’s recently launched Yemen Refugees program; the learning agenda for large cash for refugees in Rwanda, and the evaluation of cash transfers in a disaster (floods and landslides) response in Uganda. She was also involved in a recently concluded randomized controlled trial evaluation of the impacts of large lump sum cash transfers on refugee and host households in Uganda.
Episode Description
What is the best way to support people living in extreme poverty? Could unconditional cash transfers and universal basic income be viable options? How can we know if such programs will work? Today's episode of stats and stories focuses on addressing the needs of people living in extreme poverty with Miriam Laker.
+Full Transcript
John Bailer
What is the best way to support people living in extreme poverty? Could unconditional cash transfers and universal basic income be viable options? How can we know if such programs will work? Today's episode of Stats and Stories focuses on addressing the needs of people living in extreme poverty. I'm John Bailer. Stats and Stories is a production of Miami University's department of statistics and media journalism and film as well as the American Statistical Association. Joining me as a panelist is Rosemary Pennington, professor in the Department of media, journalism and film. Our guest today is Miriam Laker. Dr. Laker is the global director of research at give directly and a senior research scientist and epidemiologist with nearly two decades of experience conducting research. Among her extensive experience, she's led the design of the evaluation plan for give directly is recently launched Yemen refugees program, the learning agenda for large cash for refugees in Rwanda, and the evaluation of cash transfers in disasters, like floods and landslides, their response in Uganda. She was also involved in a recently concluded randomized control trial evaluation of the impacts of large lump sum cash transfers on refugee and host households in Uganda. Miriam, thank you so much for being here today.
Miriam Laker
You're welcome. Thank you for having me.
John Bailer
Well, to start our conversation, can you describe why cash transfers have been proposed for supporting people living in extreme poverty?
Miriam Laker
Thank you for asking that question. So the beauty about cash transfers, or I will take a step back and say, people living in poverty have a lot of problems, they're going through a lot of issues. It may be lack of housing, it may be lack of food, it may be, as we know, lots of problems. And it varies not only within the country, but across countries. The great thing about cash transfers is that it allows many different people to meet many different needs at the same time. I mean, how exciting is that? And also, cash is like a gift that keeps giving. Because when one person receives cash, the cash doesn't stay in their pocket, it also helps somebody else in their community, and they're more people in the wider community. And I think for me, that is why cash transfers really are an exciting topic.
Rosemary Pennington
Give Directly has been doing this for a while now. How do you decide what communities you're going to work with? And then how do you evaluate whether the cash transfers were successful in alleviating poverty and helping the community?
Miriam Laker
Thanks for that question. So Give Directly has been, yes, definitely doing this for a while working in multiple countries, up to 13 countries right now. Our focus is two groups. So one, we have a development focus, which is focusing on people living in poverty. And the second is focusing on people experiencing humanitarian crises. I'll talk mainly about our development program in answering your question. So usually what we do is we try to use a very objective source of information to identify whether people were communities living in poverty. An example of this is using government census data. Because government census data is not done, knowing that there's a possibility that someone is going to help a particular group of people and therefore tweaked to fit that. So we use, for instance, government census data to identify communities that are living in poverty. And then when we go to those communities in Africa. So in countries in Africa, when we go to those communities, we do not target individual households within the community. And this is something we learn from much earlier experimental studies that we did, where we identified households based on the quality of roofing that they had. And at the end of the day, we found that it led to a lot of conflict in the community. So for most of our models, we use what we call demographic saturation, meaning when we identify a poor community, everyone in that community is eligible for cash transfers. Another model that we use is called mobile aid. So in this system, we use people's detailed cell phone data usage, to categorize people based on their poverty level. So this is what we initially did. It took off with UC Berkeley, and found that detailed cell phone records can actually quite accurately categorize people based on their levels of poverty. So in cases like that, we use that information and are able to identify individuals who will receive cash, or sometimes people who are served by cell towers, where a lot of people are categorized using their cell phone, what's as living in poverty? Sometimes we ingest lists like when we're working with refugees, for instance, we get lists from like the UNHCR, and use those lists to identify the people that will give cash transfers to. So those are some of the ways that we do it.
John Bailer
Yeah, I'm intrigued with this idea of conducting the equivalence of a quote, a clinical trial with in the context of of this as an assessment of a plan, such as you've described, so if we were to kind of break down that trial that you're conducting, can you tell us first a little bit about the treatment, no treatment conditions? You told us a little bit about identifying, you know, candidates for treatment just now. But what exactly is the treatment, and then what would be the control to which that treatment was compared?
Miriam Laker
Very exciting. And you know, one of the things that made me excited about the work you've directly done is exactly that experimental studies, which are like clinical trials, really. So the way we identify the controls is really the same way that we identify the treatment group. Because, as you may be familiar with experimental studies, what you're trying to do is almost create a time machine where you have like the same person, give them an intervention, follow them up into the future, and then rewind time and not give them the intervention and follow them up. But because we still don't have a time machine, we try the best that we can. And in this case, we identify communities that are similar. And we do what we call a baseline evaluation based on the outcome we're interested in. So if, for instance, our outcome of interest is nutrition, we do baseline questionnaires to find out how many times the last few days did you not eat? Did you get what you wanted to get? And then we assigned the intervention, I'll give a very basic example, the intervention or treatment in this case would be cash. And so we're trying to study whether giving cash will improve people's nutritional outcomes. And so then we give cash transfers to randomly selected group of people out of that group, and the other group does not get cash, and then follow them up for a predetermined amount of time, at the end of that time, as the very same questions that we asked at baseline, or do the very same measurements, and any difference that we find between those that receive the treatment, which is causing this case, and those that did not receive the treatment is then say to be as a result of the intervention, which was cash. So that's a very basic explanation of a cash transfer trial.
Rosemary Pennington
I know that with Give Directly, the cash you receive as is given, I mean, you give out, is unconditional. There's no strings attached. Why? Why unconditional cash transfers, and what have you found people use the funds for?
Miriam Laker
Our first value is “recipients first” and foremost that people in poverty are not dumb. They know what they need; they know when they need it. And that is why we give the cash unconditionally. And also it goes back to what I said in the beginning that people in poverty have different needs, at different times. And so we give the cash unconditionally, to give people agency to make decisions that are right for them as individuals, and that are right for their households, and sometimes that are also right for their communities. So that is why we do our cash transfers as unconditional cash transfers.
John Bailer
I thought that that was an interesting issue that you're thinking about, facilitating autonomy. And you know, this sort of, as you say, the agency of individuals to determine who best knows your need but you? And that seems very empowering in that regard. So you've talked a little bit about the outcome, one being nutrition. You also mentioned in the exam that there's a certain period of follow up. So in reading about some of the examples, in one of the studies, you're giving this cash over two months, and actually the amount of the cash that was given might be equivalent to that in that two month period what a family would receive in a year. So it was quite an infusion into the lives of folks. What is the timeframe over which you're going to evaluate change in the communities?
Miriam Laker
So this varies. It depends on the outcome that we are looking at. So in other words, how much time do we think it will take for cash to lead to that change? But also it depends on: are we trying to look at sustainability? So we have studies where we have followed up for one year, we have our cities where we followed up for two years, some three years, some will still follow up for a longer time. There is one that we actually have in Kenya. It's the largest universal basic income run nobody's control trial in the wild right now, where the follow up period is up to 12 years. So it really depends on the outcome that we're looking at and the sustainability impacts of cash that we are trying to study as well.
Rosemary Pennington
That actually leads to the question I've been thinking about in regards to sustainability, is that you're giving people this infusion of cash, which seems to mostly be kind of a one time infusion, even though it's over a period of time. But the structures and the systems that sort of help perpetuate poverty are still in place. So I wonder, how does the organization view the way it fits into this fight against poverty, which is a systemic problem? But you're sort of going in, like in this episodic moment to help? And then how do you feel like you fit into that larger picture?
Miriam Laker
Great, Rosemary, thank you for that question. And I think this is a question that you could ask to anyone who is doing work in the development sector, because there are a number of systemic things that need to be changed for poverty to be completely eradicated. But what we say right now is that if you think about all the development interventions, we feel that at the moment, cash is the best, because it addresses multiple needs for multiple people at different times. And also, it is probably the most cost effective, because I don't know how familiar you are with our work. But efficiency is in the range of 85% to about 91%, meaning every dollar that we receive, about 90 cents of that goes to the recipients. So what we are saying is, at the moment, based on the multiple studies that have been done, it is the best way to do it. Can we do it until something better comes up down the road? Then we are happy to move to that. However, that being said, we don't work independently of the systems that are supposed to be improving the systems that perpetuate poverty. So we do work with governments. We actually call the countries where we work, have a government relationship person, and we let them know about the work that we're doing. And in some cases, we have interest from the government to support the work we're doing by improving the infrastructure that exists in those areas, as well. But also interestingly, we found that cost transpires sometimes, on their own are able to improve some infrastructures, for instance, markets without any external input from the government, just having more money in the community, we have seen, in some places, has been able to improve the markets in those areas. So to answer your question, there is no silver bullet. We're doing the best with what we know right now. But also we are working with governments to hopefully improve the infrastructure that needs to be improved.
John Bailer
You know, one thing that you mentioned was that some of the follow up periods for looking at the intervention have gone over 12 years. And the example that was the universal basic income, which I assume was also something that was continuing for that 12 year window of time, too. So that treatment was also continuing as well as the monitoring. Can you describe the kind of big, big outcome changes that have been observed or things that you've seen as part of these interventions?
Miriam Laker
Absolutely amazing. I just had, with the most basic what, for many people, are the common sense differences of consumption. So one of the things we've seen is as soon as people receive cash transfers, the food security is improved, and the quality of food that people eat goes up immediately. Children are able to go to school with child labor reduced because now families have enough money to not have their children working instead of going to school. Health outcomes improve. I mean, we've seen a lot of improvement in mental health. Intimate partner violence goes down because women now are empowered because they have access to money. People are not only expanding businesses, but also investing in new businesses. And people are brave enough to do it because they have either a large amount of cash that is immediately available to them, or they are assured that on a monthly basis or on a defined basis. They're always going to be repeatedly receiving cash transparents. The other thing we've seen is investment in assets. It may be livestock, so a family has access to milk on a regular basis, or bowls to plow their land, investment in land improvement in the quality of houses. I mean, there's just multiple things that people are able to do with their cash transfers. It's just amazing to see it. And sometimes it's interesting. People spend their money on things that make you wonder whether it was the right decision. I'll give an example, or two examples if you have the time. One of them was in Kenya. The first time we saw what happened was in Kenya. When people receive their cash transfers, they immediately rewrote their houses from grass touch to timesheets, and we've seen that repeated in many countries. So the concept initially was, how are these people using their money for the right thing. And the recipient said, you know, when I put 10 sheets on my house, then I no longer have the cost of having to re-roof my house, I have access to clean drinking water, because I'm harvesting rainwater. My children are not going to get malaria because we no longer have breeding places for mosquitoes on our roof. And also my children are sleeping well. So mental health improves. One other example was a gentleman who his whole community was buying livestock. And he went out and he bought music instruments, and he started a band. And so when our team went out and asked him, “why are you spending money on the band?” His answer was not everyone wants a coat. I mean, the interesting thing that we've seen.
John Bailer
You're listening to Stats and Stories. Our guest today is Miriam Laker, global director of research.
Rosemary Pennington
That brings me to another question I wanted to ask, Miriam. So I know that sometimes development projects can get critiqued because they can often be shaped by people coming into a community without really sort of working with the committee community to figure out what the needs are. How does Give Directly work with communities or interfacing communities as you're sort of figuring out, you know, what you're doing for them?
Miriam Laker
So like I said, our first value is “recipients first.” And we try as much as possible to model our programs in a way that suits the recipients personally, not just because we're giving them cash transfers, and therefore agency, but we also think about other components as well. So for instance, we have what we call the “recipient advocacy team.” We have a group that is firewalled from tokenization. So this group of people, while they're part of Give Directly, they essentially work undercover. And they go out to the communities to find out what do the recipients want? How are our programs affecting the recipients? Is there fraud going on? So we have that constant interaction with our recipients. Right now, we are in the process of coming up with a research project that is asking recipients whether the model that we're using is what they want. So right now, we think our model is really great. But we're like, is that what the recipients think? So initially the question was, if you tell someone that they're going to receive $1,000, they're all going to want to receive it immediately. And so based on that, we like to do a focus group discussion in three countries, Liberia, Malawi, and Kenya. And what was surprising is that people wanted different modalities, even when the money was immediately available to them. And so we're now rolling out a bigger research project to understand recipient needs, and then based on that, we will be able to model our projects or our programs to fit their needs.
John Bailer
So I'm now intrigued about this undercover team. So you have this separate group that's going to embed themselves in the same communities where you're implementing these cash awards for action. Has there been anything surprising that's come out of the work that these teams have done?
Miriam Laker
Yes. So I think what is surprising is, when you're doing a cash program, especially in a lot of the low and middle income countries, one of the things that people are worried about is corruption, someone is going to take this money, this money is not going to get to the recipients. And so that is one of the things that our recipient advocacy team does. And trying to like, make sure there is no fraud either by our staff or other people in the community. And what has surprised me is that the amount of cash that we have lost as a result of our projects is really small. So for instance, out of over 100 million in cash transfers, we lost less than $200,000. And so, for me, that was surprising. So the amount of loss that we have as a result of fraud and the like is really, really miniscule. So, for me, that absolutely was surprising. And it makes me say we need to have these undercover teams working all the time.
Rosemary Pennington
You mentioned earlier how improvements to markets are something you've seen as far as an impact in the community at large. You know, these cash payments obviously are going to individuals and to families. What other ways are you tracking the impact of these cash transfers on the community at large? Like how are you figuring out how that is helping the community appointed to study?
Miriam Laker
So one of them is the large refugee RCT that we did in Uganda. And now going forward, all our randomized control trials embed alliterative components in that. And by that, I mean, in addition to getting our quantitative numbers, we also talk to the recipients and ask them how the cash affected them and their neighbors and their communities. Another example, which I think is the biggest one, is what we call a general equilibrium study. So this was a randomized control trial that was done in Kenya. The follow up actually is still going on five years down the road, to look at the impact of the cash transfers beyond the household. What happens is their inflation, or what happens in the community. And what we have seen with that I mentioned earlier is the multiplayer in multiplayer. First of all, there was no inflation. There was zero inflation in places that were well connected to the market. And in the more rural settings that had poor connections, the market inflation was less than 1%. And even then it was just for immovable goods, things like land. But in addition to that, what we saw was communities that were up to two kilometers away from the communities that have received cash transfers, had the exact same level of consumption as the communities that had received cash transparency. So the spillover effect, even two kilometers down the road, was completely amazing. And then the multiplier impact as well. So we're bringing cash into our household, but it multiplies itself in the entire community. And so we're seeing a lot of that happening in the projects that we're doing, and not just Give Directly studies. I mean, this cuts across all costs, transplant programs.
John Bailer
You know, when you talk about these RCTs, that you're randomizing something, so you're randomizing the treatment, and you're doing it to communities? So you're taking similar communities and then assigning one the intervention, as in the other is the control? I mean, are you blocked? I'm sorry, this is inside the baseball park of showing the terms of the methods you do. Are you blocking on communities, similar communities before you randomize? And how many communities are receiving treatments? And how many are the controls?
Miriam Laker
That's a good question. So first of all, just taking a step back, when we're doing experimental evaluation of our studies, of our projects, we don't evaluate them ourselves. We work with external evaluators. They may be academics. They may be research organizations. And this is really just to make sure we avoid conflict of interest, since really, we are the intervention initially. And also in countries like the US where people don't live in communities, per se, we do what we call “individual randomized control trials,” where the household next door may be receiving cash and the one that still does not receive a cough. But in Africa, we found that it leads to a lot of conflict in the community. And so what we do is we identify similar communities, and then we try to get the smallest administrative unit, usually they are broken down into villages. And so the treatment villages, we try to make sure they're geographically very distant from the control villages, so that we do not have the skill of happening.
John Bailer
So how many villages are in each group? How many villages would receive the cash advance? And how many would be their “parents”, their controls?
Miriam Laker
So it usually really varies, and it depends. What is normally done in the beginning is what we call “power calculations.” In other words, the researchers work out what the minimum number of clusters are needed for us to be able to detect a small difference, if there was one. And now the number of villages also varies depending on how large the villages are for RCTs. We try to get as small an ability as possible, because the way Give Directly works is, we need to saturate the entire village. And so we make sure the clusters we get are small enough, so one might be enough to meet the research objective, but small enough to make sure that we saturate the entire village. So it varies from one research project to another.
John Bailer
I was wondering if there was some kind of cluster randomization. It sounds exactly like what you might be doing. So what would you say is an important difference to detect when you say you're designing these to detect certain differences? How large of a change would you look for in something like nutrition? Or would you hope to see based on the interventions you're doing?
Miriam Laker
That's a hard one. So I guess at the end of the day, let's say for nutrition, you may be interested in food security, the variety of food people have access to. Or you may be interested in actual physical changes. And so what is important is to determine if this change is not just numerically significant, but actually, economically, let's say significant, so we have to make that decision as well. And then we say based on the amount of cash that we are giving, what is the smallest possible change that could happen as a result of the cash? And so we use that to power the RCTs that we're doing. But of course, it varies from outcome to outcome. And we're thinking about meaningful changes. Yeah.
John Bailer
I'm curious, what's next? So you've been doing this for a while. You've been learning about different patterns in which intervention may occur, whether it's a large installment over two months, or continuous monthly installments, and given what you've learned, what's the next direction for this type of intervention that you think is most promising?
Miriam Laker
I think that life is a number, but I will mention two of them. One of them is a concept that is now more and more being called “cash purists.” And by cashpass, it means, is it possible to add another intervention on top of cash to get a much bigger impact than you would get with cash alone? Or would that intervention alone? Right now, the evidence shows that cash plus has no impact. So it's just useless to give a cash plus another intervention. And the other thing is that those interpreter interventions are usually very expensive. We've done some randomized control trials called “benchmarking studies” with USA ID, where they compare the per dollar impact of their intervention from an intervention to cash equivalent interventions. But we're saying is it possible that we're not seeing any impact? Because people, or the site agencies, are deciding on the class that should be given to a community. And right now, we're working with a team called the Behavioural Insights Team. We've created a cost plus lab. And what we want to do is to go out into communities and find out from the people living in poverty, one: if they actually do want any classes, and if they do, what are the kinds of classes that they want. And two: use that information to design a class that is being requested by a community. Then also thinking about things like timing, for instance, we did an RCT in Rwanda, with USA ID, where we compare cash unknown to an intervention, which was skilled for entrepreneurship. And we found that cash did better. And the question was, is it because of the way the cash was timed? Because cash and the intervention were given at the same time? The question is, should we have given it before? Should we have given it at the end? So those are questions that need to be answered. And then the other one is, what would happen if we gave cash transfers to everyone living in poverty in a country? What would happen? What would happen to poverty? What would happen to macroeconomics? And so that is something else that we are seeking to actually be able to do and, hopefully, to answer as well.
John Bailer
But I'm afraid that's all the time we have for this episode of Stats and Stories. Thank you so much for joining us today.
Miriam Laker
You're welcome. And thank you for having me.
Rosemary Pennington
It's great having you here.