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Amy Castro On Early Results From Guaranteed Income Programs

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المحتوى المقدم من Judith Siers-Poisson and Institute for Research on Poverty. يتم تحميل جميع محتويات البودكاست بما في ذلك الحلقات والرسومات وأوصاف البودكاست وتقديمها مباشرة بواسطة Judith Siers-Poisson and Institute for Research on Poverty أو شريك منصة البودكاست الخاص بهم. إذا كنت تعتقد أن شخصًا ما يستخدم عملك المحمي بحقوق الطبع والنشر دون إذنك، فيمكنك اتباع العملية الموضحة هنا https://ar.player.fm/legal.
For this episode of the Poverty Research and Policy Podcast, we hear from Professor Amy Castro about the concept of Basic Income, and what she and her team are learning from data coming in from pilot projects around the country. Professor Castro is Founding Director of the Center for Guaranteed Income Research and an Assistant Professor of Social Policy and Practice at the University of Pennsylvania.

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Transcript:

Judith Siers-Poisson: Hello, and thanks for joining us for the poverty research and policy podcast from the Institute for research on poverty at the university of Wisconsin-Madison. I'm Judith Siers-Poisson.

For this episode we are going to be talking with Professor Amy Castro about the concept of Basic Income, and what she and her team are learning from data coming in from pilot projects around the country. Professor Castro is Founding Director of the Center for Guaranteed Income Research and an Assistant Professor of Social Policy and Practice at the University of Pennsylvania. Professor Castro, Thanks for joining us today.

Amy Castro: Thanks for having me.

Siers-Poisson: What do we mean when we talk about a guaranteed income? What is it and what is it not?

Castro: Yeah, it's a great question because there's a lot of terms that are floating out there in the public imagination that also in the literature. So, there's three basic terms that pertain to this body of work. First is UBI or Universal Basic Income, and that's the one that people are probably the most familiar with given Andrew Yang's presidential run. UBI is exactly what it sounds like. It's universal. It's an unconditional amount of cash that goes to every single person in a city, a state, a town, a county, whatever that jurisdiction may be. We actually have not had a UBI experiment here in the United States because obviously universality know would apply to everybody. We have not had that yet. Second is basic income. Basic income is again an unconditional amount of cash that is given to a group of people, and it's enough to cover your basic needs. The third category, which is primarily what I study, is guaranteed income. It's not enough money to cover your basic needs but is a fixed amount of cash that's recurring, so you can rely on that money coming each month each week, whatever that cadence may be. And I think that's key about all three of these categories. A characteristic that carries across all is the unconditional nature of it, meaning you receive that cash because you're human, you don't receive that cash because you fit a means test criteria or because you are doing something like participating in a workforce force training program or a financial literacy program. You receive that cash because you are because you exist. And that's really the ethos behind guaranteed income or basic income.

Siers-Poisson: And it seems like that point is what distinguishes it from, say, what people used to lump under the umbrella of welfare in the past.

Castro: Exactly. And I think that that's why, you know, on the one hand, people are so excited about this idea. And then on the other hand, why there is so much backlash, right, is that we truly are talking about giving away money, no strings attached. And traditionally here in the United States, when we talk about the provision of cash or goods to people who are struggling to make ends meet, we layer it with all sorts of restrictions as to how that money can be spent and who can have access to it. And what's attached to those restrictions are social constructions ideas that are not rooted in reality, they’re rooted in ideology most of the time around race, class, gender, marital status. And they're used as ways to shame and blame people who access these programs. And it really serves as a social deterrent for people to access them.

In contrast, basic income or guaranteed income functions completely differently. If you're enrolled in one of these programs or pilots, you receive it because you're human. And the idea is that people know best what they need and what their households need. And secondly, if we think about need, right? So like financial scarcity or financial need, needs fluctuate from month to month and cash is the only benefit that's flexible. So if needs are flexible, we want to have something that's dynamic to match it. And cash is really the only thing that does that in comparison to something like food stamps or SNAP, which can only be used for restricted items such as food that fits a pre-set list that's set by a bureaucrat.

Siers-Poisson: So you just explained that this goes to people because they're people, not because they qualify in some way, but then who was targeted for these guaranteed income programs?

Castro: Yeah, it's a great question. So, you know, it's a fancy way of saying it would be what is the recruitment criteria, right? Because we're running experiments scientifically. So we are designing and studying these programs to see what happens when you provide people the money. So one of the big questions that we get any time we're running a new pilot—and right now we're running or at various stages of running twenty-eight pilots across the US at my center—is who gets the money right? And so that's a complicated process that for us happens across three different sets of stakeholders.

First, we have our community-based stakeholders, which is what the community wants to set as far as eligibility criteria. Second, you know, elected officials who may or may not be working with us and that are really spearheading the program and helping to kind of get it off the ground. And then third, those of us within the research space trying to determine how do we best leverage this project to answer research questions so that we are informing policy with data. So that recruitment criteria really varies for us from state to state and from location to location. I would say the majority of the projects we're working on right now are focused on people who are struggling to make ends meet. Oftentimes, they have children in the household, and oftentimes there are people who have had some type of a pandemic-related incident with their work: their hours being cut, something to that effect. But that's a general statement of each pilot is slightly different.

Siers-Poisson: I want to get into the nuts and bolts of how this works, but first, I want to touch on something that you just said and that's getting feedback from the communities that you are in. And I think that especially the communities that we're talking about are communities that have maybe historically been treated with less respect in the ways that they are given support or help, if they are at all. When you also layer on things like systemic racism and the history of understandable distrust of systems, how do you go in and build those relationships that are necessary to have any hope of being successful?

Castro: That’s such a great question. You know, first I’ll own, before I say how, and sort of jump to say how we resolve that problem, or we try to resolve that problem, because I'm by no means saying that we fix it. The first thing I just want to own is that, you know, as a scientist and as somebody who has social work training, this is the hardest part of my job. You know, it's really easy as a scientist to stay in a position of control. And that's how we're trained, is that you hold your research design so tightly. You are the expert, you know, best it needs to happen. You determine the hypotheses, you determine the design and it is in your hands. And it is very comforting, right? You can lean back into your methods training, lean back into your degree, lean back into your institution or your brand, and label yourself as the expert and that feels very safe. But the more you involve the community in your design, the more you are letting go of really being in control.

So when we think about the posture of science and the posture of how we engage with community stakeholders, it's crucial that we sort of hold our integrity as a scientist in one hand while on the other hand, being willing to relinquish control to some degree to involve community voice in the process. And when we look back through social science, we see, you know, decades of places where we've been unwilling to do this and we start measuring things, designing programs and policies, without the community input. And then we wonder why it doesn't work. This happened with TANF, or Welfare to Work as we designed this program, assuming it would work without bothering to think, “Hey, what happens if you expect the mom to work and take three busses to get to the other side of a city?” That literally makes absolutely no sense, right? So I will say that at the outset, it's the most rewarding part of what I do. It's also the most terrifying because it means I’m not in a position of control. As far as how we resolve it, there's no way to do it that’s going to make everyone happy. I’ll own that from the start. But a couple key steps. First is making certain that we are involving ourselves from the very beginning of a project with community-based stakeholders and organizations who know their community well. So this means doing that legwork of meeting with CBOs, nonprofits, and also the constituents themselves and the people who receive benefits from those programs to understand best how a program ought to be designed. So in some cases, we involve people in giving us feedback on how we design that recruitment criteria, or another way of putting it who gets the money, and getting that feedback. And then crucially, another way that we involve community stakeholders is in release of findings. So in Stockton, for instance, all of that data that's been released on spending that people can see, that is seen by a group of focus groups of community stakeholders that are not elected officials, that are not people in power. They're regular humans who get to see that data first and work with us to think about how we display this data to the public.

Siers-Poisson: So let's get down to those nuts and bolts of how these programs work. First of all, how is the amount decided on? You did say that guaranteed income is not supposed to provide for all expenses, but even given that, it seems like the cost of living in different parts of the country or even parts of a state would need to be taken into consideration. So how do you find that that amount that is going to give you some kind of results that mean something?

Castro: That's a great question, and it's one of our most vexing open research questions. So first, Stockton was set at $500 a month. The rationale behind that $500 a month is that the question of whether or not you can absorb a $400 unexpected shock or financial emergency is a standard question or threshold within economic mobility research and something that's standard in a lot of our large datasets. So it sort of made sense to start there. A lot of other cities who have built on the Stockton model have kind of just lifted that amount of money because that's what Stockton did. We have very limited control as to deciding the disbursement amount. And of course, those things are also restricted by the amount of funds that are available to a given pilot. However, some of our larger places and bigger cities with higher cost of living like, for instance, the L.A. area, we're talking about $1,000 a month. So it's really an open question for research and for policy as to how should we adjust unconditional cash based on cost of living. It's not something we have a good answer to yet, and I'm hoping that we will within the next three or four years because, yeah, cost of living is different from one state to the next, from one city to the next. And that's absolutely something that needs to be taken into consideration when we're talking about moving from pilot to policy.

Siers-Poisson: So Stockton, which is the Stockton Economic Empowerment Demonstration, or SEED, I believe, as you said, that was the first pilot of this specific type of guaranteed income program. How did it come about? Why Stockton?

Castro: So it's incredibly interesting. So first, Mayor Michael Tubbs really spearheaded the launch of that project in partnership with Economic Security Project. So Economic Security Project or ESP, which is headed up by Chris Hughes, former cofounder of Facebook, and Natalie Foster, they had been sort of looking for a city that was interested in potentially testing this idea. Now everyone is kind of running to try find a basic income pilot but go back to 2017, 2018, people are like “you are crazy. You're going to give people money? No strings attached? That's absolutely nuts.” And here's Mayor Tubbs, who you know is, I believe the youngest, if not one of the youngest, who's 26 years old, elected as mayor in Stockton. You know, Stockton had nowhere to go but up. They had experienced the worst that capitalism has to offer. They were once the foreclosure capital of the United States, while also absorbing the cost of housing from the bay area. So it made it sort of an ideal spot to test this idea because one, you had a mayor who was interested and willing to try anything right, willing to take the risk. But second, it really is a bellwether location. And when we think about sort of the way that risky lending has really dismantled the middle class and resulted in tremendous losses in wealth, particularly for, you know, Black and Brown households, Stockton was an ideal place to test policy proof of concept because it really kind of fit that Venn diagram of all these, these different forces that are really contributed to the loss of wealth, the United States.

Siers-Poisson: So you had, I think it's fair to say, a visionary young mayor who was interested in trying this. So where did the money come from?

Castro: The money came from two kind of different categories. So first, you have the disbursement money, so the money that actually goes to the people. That funding came primarily from the Economic Security Project, along with a number of other philanthropists who donated, smaller family foundations, and also some individual donors. And then the science—this is crucial because this is a model that we, we maintain across all the things that we're working on—the funding for the science came from the Robert Wood Johnson Foundation. And so we really like to keep a strong firewall between those two sides. So there's not coercion. So, RWJF, you know, really to their credit, specifically, the evidence for action arm of RWJ, really took a chance on our project and funded the research side. So the evaluation dollars were coming from sort of that traditional form of funding.

Siers-Poisson: And so how many people were enrolled, and do you think of them as people or as households?

Castro: Oh, great question. Yeah. So we tend to talk about sort of the findings at a household level simply because that's how people live, right? They live in networks, they live in households, but the money is not going to specific household, it's going to a specific individual in the household. So we had 125 people in the treatment group, which is another way of saying the people who got the $500. And then we also had a control group who were taking all the same surveys, participating in the same interviews as the treatment group, but not getting the cash so we could compare one group to the other.

Siers-Poisson: When did it start and how far along are you now?

Castro: So the research ran for two years. Our last payment was in February of this year. So we had one full year of pre-pandemic data or disbursements and then one year of payments during the pandemic or after. We've only released the first-year findings. The second-year findings, that is the total findings, will be released to the public in late spring of 2022.

Siers-Poisson: What were the key findings from that first year in Stockton?

Castro: So we really saw changes in three key areas. First was income volatility. One of our driving research questions is can guaranteed income disrupt income volatility, which is your money going up and down each month, which really locks people out of financial instruments and being able to plan for the future. We saw less income volatility in those who were in the treatment group in comparison to control after one year. We saw that that sort of stabilization in family finances allowed families to plan for the future. So in the treatment group, after one year, we saw that monthly income volatility really dropped. And one of the ways that we look at that is asking this question: “Can you pay for unexpected $400 emergency expense with cash?” At the beginning of the experiment, in the treatment group, only 25% said that they could do that, along with the control. And after one year, those receiving the cash, 52% of them said they could absorb a $400 unexpected shock, while only 28% of those in control said that.

Now this finding is really important because on the face of it sort of obvious, right? If you give people more money, they're going to have more money. But what's key to understand about this is two things. First, that liquidity in the household allowed people to both plan while also absorb the unexpected things that happen to all of us: the flat tire, the missed shift at work, the unexpected copay, which then tends to spill over in a household and cause strain elsewhere in the budget. Second, that liquidity was really pooled across fragile family networks, such that stabilizing those resources in one household actually had a spillover effect into other families where they normally would borrow money and food for those households, which is really key and interesting.

And then the second area that we saw big shifts was in our second research question, which was ‘How do changes in income volatility impact health and well-being?” And what we found was that people receiving the cash were less anxious and depressed, both over time and compared to the control group. They reported improved emotional health and well-being, energy over fatigue, again, both over time compared to the control group. Now key, Judith, it's still staggering for me to even think that this is one of research findings is that at the beginning of the experiment, almost everyone in treatment control met the clinical criteria for either anxiety or depression, as measured by some pretty standard measures that we all use at the doctor's office. Most of us have taken these. And so what we saw was that after one year, we saw that treatment group move from meeting that clinical criteria for mild mental health disorder into the category of likely to be well, and that did not happen in the control group. And all we did was provide people with unconditional cash, which is fairly extraordinary.

Then finally, our last question was “How is guaranteed income generate agency over one's future? Are we seeing people have greater control and self-determination?” And the biggest finding that we had here was around employment. So, you know, we've talked a lot about assumptions around poverty, and those are certainly very politically driven. And one of the criticisms we often get is “well if you give people cash, they’re going to stop working and they'll just quit their jobs en masse,” which is kind of silly if you think about it, because you can't live off of $500 a month anywhere, let alone California. And what we saw in the treatment group was that at baseline, 28% of people in the treatment group were fully employed and after one year, 40% were fully employed, and we did not see that same shift in the control group. Literally the opposite of what politically we're told will happen if you give people cash. And again, when we leaned into our mixed methods design and followed up with qualitative data to understand, OK, how did this happen and why?

It was really interesting. Two things that happened first was that the cash removed material barriers to seeking employment that people could not address prior. So in many instances, people who moved from knitting together multiple part-time jobs to one full-time job literally couldn't take a shift off of work to even apply for another job, and the cash allowed them to do that. So it removed some material barriers: cost of transportation, being able to skip work. So if you think about it, it takes time to apply for full-time jobs and you're not guaranteed that you're going to get it. And there's also that protracted period of going through H.R., resigning one position and starting another. If you're living paycheck to paycheck, you literally don't have time to do that because financial scarcity generates time scarcity. And so really, removing those material barriers allowed people to apply for positions that they knew they were eligible for and just couldn't didn't have the time to do.

Second was an increased capacity for risk taking. So what we saw was several months into that first year of treatment, as people's anxiety dropped, as their scarcity dropped, they had more bandwidth to breathe and really plan for the future. So being able to set certain goals for themselves and take risks knowing that they had the cash to fall back on. So those are both a material thing, you know, as well as a cognitive capacity thing and really sort of being able to reimagine what they wanted for their future.

Siers-Poisson: You were able to see how people were using the money by tracking the purchases. And actually, we should say people received the funds on a monthly basis and a debit card, right?

Castro: Correct. So in Stockton, the $500 was disbursed each month on a prepaid debit card. So that debit card was reloaded each month right in the middle of the month, and we chose that date. I think it’s a crucial thing that gets lost oftentimes in kind of the excitement around guaranteed income is the timing of the money. So most social safety net programs, specifically SNAP benefits or food stamps, they run out by the second or third week of the month. And so what you see is food security at the front of the end of the month and by the end of the month, families are really scraping to get by and having to borrow from friends and family simply to feed their kids. So we intentionally chose the middle of the month, you know, we're really looking to disrupt income volatility, your finances going up and down consistently within the home. So that was kind of chosen to smooth that piece over.

Siers-Poisson: So what have you learned from the format of this, that on a debit card, you can see exactly where money was being spent and how much? What are you seeing?

Castro: First, I'll say, what's happening with the spending data or how people are using the money, is not one of our primary research questions. We don't really care. I have to be totally honest with you. I mean, how people spend the money is not a research focus of ours. We're far more interested in how spending the money impacts people's lives and impacts their health and well-being. However, again, we echo back to what I said prior. The community is certainly interested in how the money is spent. And when we talked with those focus groups, specifically a group of housing activists who live in Section 8 housing, they were insistent. I mean, absolutely insistent that we were release spending data. And when we asked them why, rather than saying it was because they thought it should be monitored, it was because they had such faith in how people who looked like them would spend it. They said, “No, we want the world to see exactly what it's like to struggle to make ends meet. And we know exactly how low-income moms and dads are going to spend this money,” which is why we took that step.

So, you know, the thing around on the spending data first, you know, most of the money went to food. So approximately 40% of the money that's tracked each month on that debit card went directly toward food purchases. And then the next category after that, I believe, was big box stores. And we're talking about things like utilities. Now key, a large portion of the money was transferred off of the card each month into cash or into other bank accounts. And this is the beauty of a mixed-methods design is you can follow up with families to determine why they did that. So when we followed up with people to sort of figure out like, “Hey, what's this about transferring the money into cash,” it was really interesting. Several things first, like I said before, Stockton experienced the worst the capitalism has to offer. They were targeted consistently for risky lending schemes. They still are. Scams are really prevalent in the community, so they had no reason to trust us whatsoever. So the community is sitting there like “I'm constantly targeted with risky things. Why would I trust you?” So people would quickly move the money off the card into an account that they know and that they trust where it felt safer. And then also, you know, a lot of folks are still conducting their everyday lives in cash. So spreading cash around family networks, paying babysitters, things to that effect.

Siers-Poisson: I wanted to go back to that focus group being adamant about releasing those results because I'm guessing that they, and other people who are living similar lives to theirs, are very aware of those critics. The people who say, you know, they can't be trusted, they're going to spend it on alcohol and drugs. Do you think that was part of it too? Not just that they were confident that their cohort was going to spend it responsibly, but they wanted to be able to show people like, “Look, this is who we are, not who you think we are.”

Castro: Yeah, that's a beautiful way of putting it. I mean, without question, is that they really wanted people to see, you know, so less than 1% of the money on the card that's tracked each month, meaning sort of those merchant codes, these are the same codes that we all have on a normal debit card, you know, went to alcohol and cigarettes. Now, is it possible that people pulled the money out in cash and actually spent some money? Yeah, I'm sure they did. You know, like I bought wine last night, like, don't we all do this? This is a whole kind of point of giving money—that they can be human. But yeah, like they were adamant that they wanted people to see what it was like and they were really clear. And saying, “there are these stereotypes that people have about families who are struggling to make ends meet, and this is a chance for us to show the world really that what it's like to be me.” And I have to say, that group was not just that group, but there are several that we worked with. The challenge of relinquishing control and giving them a true voice in the process has been one of the best decisions we ever could have made as a research team because I wouldn't have chosen to do that. I'd have just chosen to leave it be, not talk about it, not step out into that space. And they really have the confidence and the boldness to say that that we had an ethical obligation to do so. And I think they were right.

Siers-Poisson: Have you seen any negative effects in in the data? Have there been any unintended consequences that you, you wish hadn't happened?

Castro: That's a great question. Some of that we’ll be talking about more as we release the full report. I'd say the number one sort of unintended consequence that would definitely have a negative impact has been interaction with benefits. So this is not just been true in Stockton, this has been true across all the other pilots that we're working with is that within the United States, our social safety net is very punitive. We have something called a benefits cliff, which means that for every dollar that somebody receives, we pull back some of their benefits. So families constantly are in this horrific calculation. “If I take this, you know, I want to take this extra shift at work because I need the cash and because I don't want to lose my job. But if I do that, I might lose my benefits.” And so you're constantly making this calculation, which leaves over less cognitive capacity for other things like goal setting and well-being. That's one issue. But second, it means that families are constantly trapped or penalizing them for working more.

So what this meant in Stockton and across all these unconditional cash experiments is that we sometimes have to tailor our recruitment criteria and design to make sure that people aren't losing benefits. So we in many instances where people were randomized into the treatment group to receive the $500 they showed up for the onboarding. They went through the informed consent process and realized, “I’m at way too high of a risk for losing my health insurance, or my housing voucher or my SSI,” and just felt like “I'm too vulnerable. I can't take the risk.” So that is an unintended consequence that we haven't resolved yet. We do our best, but it's one that we're consistently contending with, and it's incredibly frustrating. And what ends up happening is that all of our data is about the people who are willing to take that risk or who were able to take that risk versus those who were forced because of the benefits flip issue to not enroll in these experiments in the first place.

Siers-Poisson: I have to say on a human level that I would assume that would be crushing to someone who thinks that they're going to be able to take part in this and then realize it's too much of a risk. Did you get any feedback on it?

Castro: Oh man. Yeah. Yes and no. I mean, on one hand, yes, there's times it's crushing and right now my center is embarking on a huge clinical trial with low income cancer patients, and it's a far more vexing issue in that experiment than the other ones. So, yeah, like at times, it is totally crushing. I think what's even more sobering was that people weren't surprised. You know, those who had to decline or who didn't bother were like, “well, of course, the systems turned again. Why would this work in my favor? The world's not set up for me. I don't matter. Government doesn't see me.” It was like, “yeah, of course. Of course it went that way.” And so we had a little bit of both.

Siers-Poisson: One of the things that I was thinking about, especially when you said that the Stockton experiment dispersed its last round of funding earlier this year. Do we know what happens when a program ends and those people who for a couple of years have that regular influx of cash no longer has it?

Castro: Yeah, it's a great question. You know, it's something that we're still sort of obviously collecting data on for all the experiments that we run, we collect data for six months after and then in some cases, there's administrative data that goes on for many years. So I can't give sort of an empirical answer to that quite yet. What I will say is, from a values perspective, this was something that we had to resolve as a team when we were building out Stockton early on, and there really wasn't anything to go on and asking ourselves the question like, “what does it mean to extend hope to somebody and then pull it away?” Like, “How dare you?” Is that even just, is that ethical?” And when I felt caught on that and my team felt caught on that, we went to our Associate Dean of Research, Dr. Solomon, who's a brilliant social work researcher. And she kind of got in my face a little bit, honestly. And she said, “Amy, you are a social worker. What is wrong with you? If you trust people to spend the cash, and to be able to enroll in the experiment, programs are closing on folks all the time. You don't trust them to weather the end?” And it was one of the most profound things of mentorship that I could receive at that moment in time, because she really challenged my biases. Like, I had this bias like people couldn't handle it. And that's not to say that there's not harm that's caused when something ends. But, you know, what Dr. Solomon pointed out, was the poor constantly having things pulled out from underneath them. There's tremendous resilience there. How dare you assume that they'd be worse off? Why don't you wait and see what happens? So right now, we're waiting to see what happens.

Siers-Poisson: You talked earlier about how much of a paradigm shift this is of giving people money, trusting them to spend it as they need. And to me, there's definitely an element of trying to restore some dignity to life for people who have, in many cases, had that taken away from them and respecting them and their choices. How do you see efforts like this working to change the narrative about people living in poverty?

Castro: Oh, I mean, it's crucial. Right, so here's the thing scientists tell terrible stories, we're bad at it. If we were better at communicating with the public, people would be vaccinated and COVID would be a little less right now. Right. We're bad at telling stories, we're good at staying in our ivory towers and measuring things. To me, it is without question crucial that we that we deal with narrative. So when we look back throughout U.S. history, we know that when policy windows open and we design new poverty alleviation methods, or we design new policies that really move the needle, we have two things that happen. One, we have consensus on data. So we actually know how to design a good program based on what's happening. And that's colleague to colleague, data to data, right? But then second, we see a shift in public mood. And if you do not tackle that public narrative around deservedness, around shame, around blame and you don't deal with public mood, all you do is migrate shame, blame, and assumptions about race and class from one social program to the other. So one of my driving concerns right now, as guaranteed income programs and conversations take off across the country, is making certain that we are keeping our eye on that narrative change work and not assume that this is some sort of silver bullet that's going to get rid of hundreds of years of racism in the United States, because it's not going to. If we don't do that narrative change work, we're just going to migrate the myth of the welfare queen off of TANF and onto guaranteed income. How do we do that? We're still working on it. But what we do know is that privileging voice, privileging community voice in the process, definitely helps us with this, along with dealing with a lot of things like discourse analysis and leading into narratives and putting people's stories out there in the press and in measured ways where, you know, if you want to change the narrative, change the narrator. It doesn't need to be me being the one who's in front of the mic all the time telling those stories.

Siers-Poisson: You said earlier that Stockton was the first pilot project, and there are so many more going on right now that you have a hard time keeping track of how many. So what does success look like as these programs are kind of mushrooming around the country?

Castro: I mean, everybody sort of defines that a little bit differently. For us within the center, we define success as first of all, were we able to design and experiment with integrity? So were we able to answer the research questions that we set out to answer with the design that we implemented? That's first and foremost, success. Second, to answer on a values perspective, really, we're pretty clear about what we're trying to do. We want to see policies on unconditional cash. Now again, that is not a silver bullet. But what I think success would look like to us as a center is having policies and unconditional cash that are informed by science, informed by data, and not just informed by somebody's good idea. So for us, we really want to see this movement from pilot to policy, but that those policies are evidence based and that they're rooted in science and rooted in real people's lives.

Siers-Poisson: Professor Castro, thanks so much for sharing your work with us, and we'll definitely be looking forward to talking about the results from that second year of Stockton.

Castro: Yeah, happy to. Thanks for having me.

Siers-Poisson: Thanks so much to Professor Amy Castro, Founding Director of the Center for Guaranteed Income Research and an Assistant Professor of Social Policy and Practice at the University of Pennsylvania. If you would like to learn more about pilot programs around the country, check out the website for Mayors for a Guaranteed Income. That's at mayors for A-G-I dot org. The production of this podcast was supported in part by funding from the U.S. Department of Health and Human Services Office of the Assistant Secretary for Planning and Evaluation, but its contents don’t necessarily represent the opinions or policies of that office, any other agency of the federal government, or the Institute for Research on Poverty. Music for the episode is by Poi Dog Pondering. Thanks for listening.

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المحتوى المقدم من Judith Siers-Poisson and Institute for Research on Poverty. يتم تحميل جميع محتويات البودكاست بما في ذلك الحلقات والرسومات وأوصاف البودكاست وتقديمها مباشرة بواسطة Judith Siers-Poisson and Institute for Research on Poverty أو شريك منصة البودكاست الخاص بهم. إذا كنت تعتقد أن شخصًا ما يستخدم عملك المحمي بحقوق الطبع والنشر دون إذنك، فيمكنك اتباع العملية الموضحة هنا https://ar.player.fm/legal.
For this episode of the Poverty Research and Policy Podcast, we hear from Professor Amy Castro about the concept of Basic Income, and what she and her team are learning from data coming in from pilot projects around the country. Professor Castro is Founding Director of the Center for Guaranteed Income Research and an Assistant Professor of Social Policy and Practice at the University of Pennsylvania.

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Transcript:

Judith Siers-Poisson: Hello, and thanks for joining us for the poverty research and policy podcast from the Institute for research on poverty at the university of Wisconsin-Madison. I'm Judith Siers-Poisson.

For this episode we are going to be talking with Professor Amy Castro about the concept of Basic Income, and what she and her team are learning from data coming in from pilot projects around the country. Professor Castro is Founding Director of the Center for Guaranteed Income Research and an Assistant Professor of Social Policy and Practice at the University of Pennsylvania. Professor Castro, Thanks for joining us today.

Amy Castro: Thanks for having me.

Siers-Poisson: What do we mean when we talk about a guaranteed income? What is it and what is it not?

Castro: Yeah, it's a great question because there's a lot of terms that are floating out there in the public imagination that also in the literature. So, there's three basic terms that pertain to this body of work. First is UBI or Universal Basic Income, and that's the one that people are probably the most familiar with given Andrew Yang's presidential run. UBI is exactly what it sounds like. It's universal. It's an unconditional amount of cash that goes to every single person in a city, a state, a town, a county, whatever that jurisdiction may be. We actually have not had a UBI experiment here in the United States because obviously universality know would apply to everybody. We have not had that yet. Second is basic income. Basic income is again an unconditional amount of cash that is given to a group of people, and it's enough to cover your basic needs. The third category, which is primarily what I study, is guaranteed income. It's not enough money to cover your basic needs but is a fixed amount of cash that's recurring, so you can rely on that money coming each month each week, whatever that cadence may be. And I think that's key about all three of these categories. A characteristic that carries across all is the unconditional nature of it, meaning you receive that cash because you're human, you don't receive that cash because you fit a means test criteria or because you are doing something like participating in a workforce force training program or a financial literacy program. You receive that cash because you are because you exist. And that's really the ethos behind guaranteed income or basic income.

Siers-Poisson: And it seems like that point is what distinguishes it from, say, what people used to lump under the umbrella of welfare in the past.

Castro: Exactly. And I think that that's why, you know, on the one hand, people are so excited about this idea. And then on the other hand, why there is so much backlash, right, is that we truly are talking about giving away money, no strings attached. And traditionally here in the United States, when we talk about the provision of cash or goods to people who are struggling to make ends meet, we layer it with all sorts of restrictions as to how that money can be spent and who can have access to it. And what's attached to those restrictions are social constructions ideas that are not rooted in reality, they’re rooted in ideology most of the time around race, class, gender, marital status. And they're used as ways to shame and blame people who access these programs. And it really serves as a social deterrent for people to access them.

In contrast, basic income or guaranteed income functions completely differently. If you're enrolled in one of these programs or pilots, you receive it because you're human. And the idea is that people know best what they need and what their households need. And secondly, if we think about need, right? So like financial scarcity or financial need, needs fluctuate from month to month and cash is the only benefit that's flexible. So if needs are flexible, we want to have something that's dynamic to match it. And cash is really the only thing that does that in comparison to something like food stamps or SNAP, which can only be used for restricted items such as food that fits a pre-set list that's set by a bureaucrat.

Siers-Poisson: So you just explained that this goes to people because they're people, not because they qualify in some way, but then who was targeted for these guaranteed income programs?

Castro: Yeah, it's a great question. So, you know, it's a fancy way of saying it would be what is the recruitment criteria, right? Because we're running experiments scientifically. So we are designing and studying these programs to see what happens when you provide people the money. So one of the big questions that we get any time we're running a new pilot—and right now we're running or at various stages of running twenty-eight pilots across the US at my center—is who gets the money right? And so that's a complicated process that for us happens across three different sets of stakeholders.

First, we have our community-based stakeholders, which is what the community wants to set as far as eligibility criteria. Second, you know, elected officials who may or may not be working with us and that are really spearheading the program and helping to kind of get it off the ground. And then third, those of us within the research space trying to determine how do we best leverage this project to answer research questions so that we are informing policy with data. So that recruitment criteria really varies for us from state to state and from location to location. I would say the majority of the projects we're working on right now are focused on people who are struggling to make ends meet. Oftentimes, they have children in the household, and oftentimes there are people who have had some type of a pandemic-related incident with their work: their hours being cut, something to that effect. But that's a general statement of each pilot is slightly different.

Siers-Poisson: I want to get into the nuts and bolts of how this works, but first, I want to touch on something that you just said and that's getting feedback from the communities that you are in. And I think that especially the communities that we're talking about are communities that have maybe historically been treated with less respect in the ways that they are given support or help, if they are at all. When you also layer on things like systemic racism and the history of understandable distrust of systems, how do you go in and build those relationships that are necessary to have any hope of being successful?

Castro: That’s such a great question. You know, first I’ll own, before I say how, and sort of jump to say how we resolve that problem, or we try to resolve that problem, because I'm by no means saying that we fix it. The first thing I just want to own is that, you know, as a scientist and as somebody who has social work training, this is the hardest part of my job. You know, it's really easy as a scientist to stay in a position of control. And that's how we're trained, is that you hold your research design so tightly. You are the expert, you know, best it needs to happen. You determine the hypotheses, you determine the design and it is in your hands. And it is very comforting, right? You can lean back into your methods training, lean back into your degree, lean back into your institution or your brand, and label yourself as the expert and that feels very safe. But the more you involve the community in your design, the more you are letting go of really being in control.

So when we think about the posture of science and the posture of how we engage with community stakeholders, it's crucial that we sort of hold our integrity as a scientist in one hand while on the other hand, being willing to relinquish control to some degree to involve community voice in the process. And when we look back through social science, we see, you know, decades of places where we've been unwilling to do this and we start measuring things, designing programs and policies, without the community input. And then we wonder why it doesn't work. This happened with TANF, or Welfare to Work as we designed this program, assuming it would work without bothering to think, “Hey, what happens if you expect the mom to work and take three busses to get to the other side of a city?” That literally makes absolutely no sense, right? So I will say that at the outset, it's the most rewarding part of what I do. It's also the most terrifying because it means I’m not in a position of control. As far as how we resolve it, there's no way to do it that’s going to make everyone happy. I’ll own that from the start. But a couple key steps. First is making certain that we are involving ourselves from the very beginning of a project with community-based stakeholders and organizations who know their community well. So this means doing that legwork of meeting with CBOs, nonprofits, and also the constituents themselves and the people who receive benefits from those programs to understand best how a program ought to be designed. So in some cases, we involve people in giving us feedback on how we design that recruitment criteria, or another way of putting it who gets the money, and getting that feedback. And then crucially, another way that we involve community stakeholders is in release of findings. So in Stockton, for instance, all of that data that's been released on spending that people can see, that is seen by a group of focus groups of community stakeholders that are not elected officials, that are not people in power. They're regular humans who get to see that data first and work with us to think about how we display this data to the public.

Siers-Poisson: So let's get down to those nuts and bolts of how these programs work. First of all, how is the amount decided on? You did say that guaranteed income is not supposed to provide for all expenses, but even given that, it seems like the cost of living in different parts of the country or even parts of a state would need to be taken into consideration. So how do you find that that amount that is going to give you some kind of results that mean something?

Castro: That's a great question, and it's one of our most vexing open research questions. So first, Stockton was set at $500 a month. The rationale behind that $500 a month is that the question of whether or not you can absorb a $400 unexpected shock or financial emergency is a standard question or threshold within economic mobility research and something that's standard in a lot of our large datasets. So it sort of made sense to start there. A lot of other cities who have built on the Stockton model have kind of just lifted that amount of money because that's what Stockton did. We have very limited control as to deciding the disbursement amount. And of course, those things are also restricted by the amount of funds that are available to a given pilot. However, some of our larger places and bigger cities with higher cost of living like, for instance, the L.A. area, we're talking about $1,000 a month. So it's really an open question for research and for policy as to how should we adjust unconditional cash based on cost of living. It's not something we have a good answer to yet, and I'm hoping that we will within the next three or four years because, yeah, cost of living is different from one state to the next, from one city to the next. And that's absolutely something that needs to be taken into consideration when we're talking about moving from pilot to policy.

Siers-Poisson: So Stockton, which is the Stockton Economic Empowerment Demonstration, or SEED, I believe, as you said, that was the first pilot of this specific type of guaranteed income program. How did it come about? Why Stockton?

Castro: So it's incredibly interesting. So first, Mayor Michael Tubbs really spearheaded the launch of that project in partnership with Economic Security Project. So Economic Security Project or ESP, which is headed up by Chris Hughes, former cofounder of Facebook, and Natalie Foster, they had been sort of looking for a city that was interested in potentially testing this idea. Now everyone is kind of running to try find a basic income pilot but go back to 2017, 2018, people are like “you are crazy. You're going to give people money? No strings attached? That's absolutely nuts.” And here's Mayor Tubbs, who you know is, I believe the youngest, if not one of the youngest, who's 26 years old, elected as mayor in Stockton. You know, Stockton had nowhere to go but up. They had experienced the worst that capitalism has to offer. They were once the foreclosure capital of the United States, while also absorbing the cost of housing from the bay area. So it made it sort of an ideal spot to test this idea because one, you had a mayor who was interested and willing to try anything right, willing to take the risk. But second, it really is a bellwether location. And when we think about sort of the way that risky lending has really dismantled the middle class and resulted in tremendous losses in wealth, particularly for, you know, Black and Brown households, Stockton was an ideal place to test policy proof of concept because it really kind of fit that Venn diagram of all these, these different forces that are really contributed to the loss of wealth, the United States.

Siers-Poisson: So you had, I think it's fair to say, a visionary young mayor who was interested in trying this. So where did the money come from?

Castro: The money came from two kind of different categories. So first, you have the disbursement money, so the money that actually goes to the people. That funding came primarily from the Economic Security Project, along with a number of other philanthropists who donated, smaller family foundations, and also some individual donors. And then the science—this is crucial because this is a model that we, we maintain across all the things that we're working on—the funding for the science came from the Robert Wood Johnson Foundation. And so we really like to keep a strong firewall between those two sides. So there's not coercion. So, RWJF, you know, really to their credit, specifically, the evidence for action arm of RWJ, really took a chance on our project and funded the research side. So the evaluation dollars were coming from sort of that traditional form of funding.

Siers-Poisson: And so how many people were enrolled, and do you think of them as people or as households?

Castro: Oh, great question. Yeah. So we tend to talk about sort of the findings at a household level simply because that's how people live, right? They live in networks, they live in households, but the money is not going to specific household, it's going to a specific individual in the household. So we had 125 people in the treatment group, which is another way of saying the people who got the $500. And then we also had a control group who were taking all the same surveys, participating in the same interviews as the treatment group, but not getting the cash so we could compare one group to the other.

Siers-Poisson: When did it start and how far along are you now?

Castro: So the research ran for two years. Our last payment was in February of this year. So we had one full year of pre-pandemic data or disbursements and then one year of payments during the pandemic or after. We've only released the first-year findings. The second-year findings, that is the total findings, will be released to the public in late spring of 2022.

Siers-Poisson: What were the key findings from that first year in Stockton?

Castro: So we really saw changes in three key areas. First was income volatility. One of our driving research questions is can guaranteed income disrupt income volatility, which is your money going up and down each month, which really locks people out of financial instruments and being able to plan for the future. We saw less income volatility in those who were in the treatment group in comparison to control after one year. We saw that that sort of stabilization in family finances allowed families to plan for the future. So in the treatment group, after one year, we saw that monthly income volatility really dropped. And one of the ways that we look at that is asking this question: “Can you pay for unexpected $400 emergency expense with cash?” At the beginning of the experiment, in the treatment group, only 25% said that they could do that, along with the control. And after one year, those receiving the cash, 52% of them said they could absorb a $400 unexpected shock, while only 28% of those in control said that.

Now this finding is really important because on the face of it sort of obvious, right? If you give people more money, they're going to have more money. But what's key to understand about this is two things. First, that liquidity in the household allowed people to both plan while also absorb the unexpected things that happen to all of us: the flat tire, the missed shift at work, the unexpected copay, which then tends to spill over in a household and cause strain elsewhere in the budget. Second, that liquidity was really pooled across fragile family networks, such that stabilizing those resources in one household actually had a spillover effect into other families where they normally would borrow money and food for those households, which is really key and interesting.

And then the second area that we saw big shifts was in our second research question, which was ‘How do changes in income volatility impact health and well-being?” And what we found was that people receiving the cash were less anxious and depressed, both over time and compared to the control group. They reported improved emotional health and well-being, energy over fatigue, again, both over time compared to the control group. Now key, Judith, it's still staggering for me to even think that this is one of research findings is that at the beginning of the experiment, almost everyone in treatment control met the clinical criteria for either anxiety or depression, as measured by some pretty standard measures that we all use at the doctor's office. Most of us have taken these. And so what we saw was that after one year, we saw that treatment group move from meeting that clinical criteria for mild mental health disorder into the category of likely to be well, and that did not happen in the control group. And all we did was provide people with unconditional cash, which is fairly extraordinary.

Then finally, our last question was “How is guaranteed income generate agency over one's future? Are we seeing people have greater control and self-determination?” And the biggest finding that we had here was around employment. So, you know, we've talked a lot about assumptions around poverty, and those are certainly very politically driven. And one of the criticisms we often get is “well if you give people cash, they’re going to stop working and they'll just quit their jobs en masse,” which is kind of silly if you think about it, because you can't live off of $500 a month anywhere, let alone California. And what we saw in the treatment group was that at baseline, 28% of people in the treatment group were fully employed and after one year, 40% were fully employed, and we did not see that same shift in the control group. Literally the opposite of what politically we're told will happen if you give people cash. And again, when we leaned into our mixed methods design and followed up with qualitative data to understand, OK, how did this happen and why?

It was really interesting. Two things that happened first was that the cash removed material barriers to seeking employment that people could not address prior. So in many instances, people who moved from knitting together multiple part-time jobs to one full-time job literally couldn't take a shift off of work to even apply for another job, and the cash allowed them to do that. So it removed some material barriers: cost of transportation, being able to skip work. So if you think about it, it takes time to apply for full-time jobs and you're not guaranteed that you're going to get it. And there's also that protracted period of going through H.R., resigning one position and starting another. If you're living paycheck to paycheck, you literally don't have time to do that because financial scarcity generates time scarcity. And so really, removing those material barriers allowed people to apply for positions that they knew they were eligible for and just couldn't didn't have the time to do.

Second was an increased capacity for risk taking. So what we saw was several months into that first year of treatment, as people's anxiety dropped, as their scarcity dropped, they had more bandwidth to breathe and really plan for the future. So being able to set certain goals for themselves and take risks knowing that they had the cash to fall back on. So those are both a material thing, you know, as well as a cognitive capacity thing and really sort of being able to reimagine what they wanted for their future.

Siers-Poisson: You were able to see how people were using the money by tracking the purchases. And actually, we should say people received the funds on a monthly basis and a debit card, right?

Castro: Correct. So in Stockton, the $500 was disbursed each month on a prepaid debit card. So that debit card was reloaded each month right in the middle of the month, and we chose that date. I think it’s a crucial thing that gets lost oftentimes in kind of the excitement around guaranteed income is the timing of the money. So most social safety net programs, specifically SNAP benefits or food stamps, they run out by the second or third week of the month. And so what you see is food security at the front of the end of the month and by the end of the month, families are really scraping to get by and having to borrow from friends and family simply to feed their kids. So we intentionally chose the middle of the month, you know, we're really looking to disrupt income volatility, your finances going up and down consistently within the home. So that was kind of chosen to smooth that piece over.

Siers-Poisson: So what have you learned from the format of this, that on a debit card, you can see exactly where money was being spent and how much? What are you seeing?

Castro: First, I'll say, what's happening with the spending data or how people are using the money, is not one of our primary research questions. We don't really care. I have to be totally honest with you. I mean, how people spend the money is not a research focus of ours. We're far more interested in how spending the money impacts people's lives and impacts their health and well-being. However, again, we echo back to what I said prior. The community is certainly interested in how the money is spent. And when we talked with those focus groups, specifically a group of housing activists who live in Section 8 housing, they were insistent. I mean, absolutely insistent that we were release spending data. And when we asked them why, rather than saying it was because they thought it should be monitored, it was because they had such faith in how people who looked like them would spend it. They said, “No, we want the world to see exactly what it's like to struggle to make ends meet. And we know exactly how low-income moms and dads are going to spend this money,” which is why we took that step.

So, you know, the thing around on the spending data first, you know, most of the money went to food. So approximately 40% of the money that's tracked each month on that debit card went directly toward food purchases. And then the next category after that, I believe, was big box stores. And we're talking about things like utilities. Now key, a large portion of the money was transferred off of the card each month into cash or into other bank accounts. And this is the beauty of a mixed-methods design is you can follow up with families to determine why they did that. So when we followed up with people to sort of figure out like, “Hey, what's this about transferring the money into cash,” it was really interesting. Several things first, like I said before, Stockton experienced the worst the capitalism has to offer. They were targeted consistently for risky lending schemes. They still are. Scams are really prevalent in the community, so they had no reason to trust us whatsoever. So the community is sitting there like “I'm constantly targeted with risky things. Why would I trust you?” So people would quickly move the money off the card into an account that they know and that they trust where it felt safer. And then also, you know, a lot of folks are still conducting their everyday lives in cash. So spreading cash around family networks, paying babysitters, things to that effect.

Siers-Poisson: I wanted to go back to that focus group being adamant about releasing those results because I'm guessing that they, and other people who are living similar lives to theirs, are very aware of those critics. The people who say, you know, they can't be trusted, they're going to spend it on alcohol and drugs. Do you think that was part of it too? Not just that they were confident that their cohort was going to spend it responsibly, but they wanted to be able to show people like, “Look, this is who we are, not who you think we are.”

Castro: Yeah, that's a beautiful way of putting it. I mean, without question, is that they really wanted people to see, you know, so less than 1% of the money on the card that's tracked each month, meaning sort of those merchant codes, these are the same codes that we all have on a normal debit card, you know, went to alcohol and cigarettes. Now, is it possible that people pulled the money out in cash and actually spent some money? Yeah, I'm sure they did. You know, like I bought wine last night, like, don't we all do this? This is a whole kind of point of giving money—that they can be human. But yeah, like they were adamant that they wanted people to see what it was like and they were really clear. And saying, “there are these stereotypes that people have about families who are struggling to make ends meet, and this is a chance for us to show the world really that what it's like to be me.” And I have to say, that group was not just that group, but there are several that we worked with. The challenge of relinquishing control and giving them a true voice in the process has been one of the best decisions we ever could have made as a research team because I wouldn't have chosen to do that. I'd have just chosen to leave it be, not talk about it, not step out into that space. And they really have the confidence and the boldness to say that that we had an ethical obligation to do so. And I think they were right.

Siers-Poisson: Have you seen any negative effects in in the data? Have there been any unintended consequences that you, you wish hadn't happened?

Castro: That's a great question. Some of that we’ll be talking about more as we release the full report. I'd say the number one sort of unintended consequence that would definitely have a negative impact has been interaction with benefits. So this is not just been true in Stockton, this has been true across all the other pilots that we're working with is that within the United States, our social safety net is very punitive. We have something called a benefits cliff, which means that for every dollar that somebody receives, we pull back some of their benefits. So families constantly are in this horrific calculation. “If I take this, you know, I want to take this extra shift at work because I need the cash and because I don't want to lose my job. But if I do that, I might lose my benefits.” And so you're constantly making this calculation, which leaves over less cognitive capacity for other things like goal setting and well-being. That's one issue. But second, it means that families are constantly trapped or penalizing them for working more.

So what this meant in Stockton and across all these unconditional cash experiments is that we sometimes have to tailor our recruitment criteria and design to make sure that people aren't losing benefits. So we in many instances where people were randomized into the treatment group to receive the $500 they showed up for the onboarding. They went through the informed consent process and realized, “I’m at way too high of a risk for losing my health insurance, or my housing voucher or my SSI,” and just felt like “I'm too vulnerable. I can't take the risk.” So that is an unintended consequence that we haven't resolved yet. We do our best, but it's one that we're consistently contending with, and it's incredibly frustrating. And what ends up happening is that all of our data is about the people who are willing to take that risk or who were able to take that risk versus those who were forced because of the benefits flip issue to not enroll in these experiments in the first place.

Siers-Poisson: I have to say on a human level that I would assume that would be crushing to someone who thinks that they're going to be able to take part in this and then realize it's too much of a risk. Did you get any feedback on it?

Castro: Oh man. Yeah. Yes and no. I mean, on one hand, yes, there's times it's crushing and right now my center is embarking on a huge clinical trial with low income cancer patients, and it's a far more vexing issue in that experiment than the other ones. So, yeah, like at times, it is totally crushing. I think what's even more sobering was that people weren't surprised. You know, those who had to decline or who didn't bother were like, “well, of course, the systems turned again. Why would this work in my favor? The world's not set up for me. I don't matter. Government doesn't see me.” It was like, “yeah, of course. Of course it went that way.” And so we had a little bit of both.

Siers-Poisson: One of the things that I was thinking about, especially when you said that the Stockton experiment dispersed its last round of funding earlier this year. Do we know what happens when a program ends and those people who for a couple of years have that regular influx of cash no longer has it?

Castro: Yeah, it's a great question. You know, it's something that we're still sort of obviously collecting data on for all the experiments that we run, we collect data for six months after and then in some cases, there's administrative data that goes on for many years. So I can't give sort of an empirical answer to that quite yet. What I will say is, from a values perspective, this was something that we had to resolve as a team when we were building out Stockton early on, and there really wasn't anything to go on and asking ourselves the question like, “what does it mean to extend hope to somebody and then pull it away?” Like, “How dare you?” Is that even just, is that ethical?” And when I felt caught on that and my team felt caught on that, we went to our Associate Dean of Research, Dr. Solomon, who's a brilliant social work researcher. And she kind of got in my face a little bit, honestly. And she said, “Amy, you are a social worker. What is wrong with you? If you trust people to spend the cash, and to be able to enroll in the experiment, programs are closing on folks all the time. You don't trust them to weather the end?” And it was one of the most profound things of mentorship that I could receive at that moment in time, because she really challenged my biases. Like, I had this bias like people couldn't handle it. And that's not to say that there's not harm that's caused when something ends. But, you know, what Dr. Solomon pointed out, was the poor constantly having things pulled out from underneath them. There's tremendous resilience there. How dare you assume that they'd be worse off? Why don't you wait and see what happens? So right now, we're waiting to see what happens.

Siers-Poisson: You talked earlier about how much of a paradigm shift this is of giving people money, trusting them to spend it as they need. And to me, there's definitely an element of trying to restore some dignity to life for people who have, in many cases, had that taken away from them and respecting them and their choices. How do you see efforts like this working to change the narrative about people living in poverty?

Castro: Oh, I mean, it's crucial. Right, so here's the thing scientists tell terrible stories, we're bad at it. If we were better at communicating with the public, people would be vaccinated and COVID would be a little less right now. Right. We're bad at telling stories, we're good at staying in our ivory towers and measuring things. To me, it is without question crucial that we that we deal with narrative. So when we look back throughout U.S. history, we know that when policy windows open and we design new poverty alleviation methods, or we design new policies that really move the needle, we have two things that happen. One, we have consensus on data. So we actually know how to design a good program based on what's happening. And that's colleague to colleague, data to data, right? But then second, we see a shift in public mood. And if you do not tackle that public narrative around deservedness, around shame, around blame and you don't deal with public mood, all you do is migrate shame, blame, and assumptions about race and class from one social program to the other. So one of my driving concerns right now, as guaranteed income programs and conversations take off across the country, is making certain that we are keeping our eye on that narrative change work and not assume that this is some sort of silver bullet that's going to get rid of hundreds of years of racism in the United States, because it's not going to. If we don't do that narrative change work, we're just going to migrate the myth of the welfare queen off of TANF and onto guaranteed income. How do we do that? We're still working on it. But what we do know is that privileging voice, privileging community voice in the process, definitely helps us with this, along with dealing with a lot of things like discourse analysis and leading into narratives and putting people's stories out there in the press and in measured ways where, you know, if you want to change the narrative, change the narrator. It doesn't need to be me being the one who's in front of the mic all the time telling those stories.

Siers-Poisson: You said earlier that Stockton was the first pilot project, and there are so many more going on right now that you have a hard time keeping track of how many. So what does success look like as these programs are kind of mushrooming around the country?

Castro: I mean, everybody sort of defines that a little bit differently. For us within the center, we define success as first of all, were we able to design and experiment with integrity? So were we able to answer the research questions that we set out to answer with the design that we implemented? That's first and foremost, success. Second, to answer on a values perspective, really, we're pretty clear about what we're trying to do. We want to see policies on unconditional cash. Now again, that is not a silver bullet. But what I think success would look like to us as a center is having policies and unconditional cash that are informed by science, informed by data, and not just informed by somebody's good idea. So for us, we really want to see this movement from pilot to policy, but that those policies are evidence based and that they're rooted in science and rooted in real people's lives.

Siers-Poisson: Professor Castro, thanks so much for sharing your work with us, and we'll definitely be looking forward to talking about the results from that second year of Stockton.

Castro: Yeah, happy to. Thanks for having me.

Siers-Poisson: Thanks so much to Professor Amy Castro, Founding Director of the Center for Guaranteed Income Research and an Assistant Professor of Social Policy and Practice at the University of Pennsylvania. If you would like to learn more about pilot programs around the country, check out the website for Mayors for a Guaranteed Income. That's at mayors for A-G-I dot org. The production of this podcast was supported in part by funding from the U.S. Department of Health and Human Services Office of the Assistant Secretary for Planning and Evaluation, but its contents don’t necessarily represent the opinions or policies of that office, any other agency of the federal government, or the Institute for Research on Poverty. Music for the episode is by Poi Dog Pondering. Thanks for listening.

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