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Podcast series from the MRC/CSO Social and Public Health Sciences Unit, University of Glasgow.
Ruth Dundas:
Welcome to 15 minutes on Health Inequalities and this is a podcast discussing results from a paper published in 2024 about using simulation modelling to estimate the impact of universal basic income policy on mental health inequalities. I'm Ruth Dundas from the MRC/CSO Social and Public Health Sciences Unit at the University of Glasgow.
Lia Demou:
Lia Demou. I'm a Senior Research Fellow, also at the MRC/CSO Social and Public Health Sciences Unit.
Ruth Dundas:
And today we are talking to...
Rachel Thomson:
I'm Rachel Thompson. I'm a Clinical Lecturer, also at the Social and Public Health Sciences Unit. But I'm also a Public Health Specialty Registrar, so a Public Health doctor at NHS Yorkshire and Arran.
Lia Demou:
Great to have you with us today, Rachel. We'll start off the podcast if you can tell us a little bit about your research into income and health inequalities?
Rachel Thomson:
So my research up until now was mostly focused on on what we call the economic determinants of health. So that's things like how much money you might earn, what job you do, how many hours you work, and then kind of wider economic things like the recessions for example. So thinking about how those influence health and mental health in particular. During my recent PhD, which I finished last year, much less papers from I focused on looking at how changes in income, so changes in how much money you have and changes in your work status can influence your mental health and how this might differ for different groups. So trying to get at the kind of what what we're calling the causal effect of income and what we like on health. So to do this, I brought together kind of existing papers in a big systematic review of evidence. And I also did in my own new research using data from the UK to try and get at those causal effects. And what I found or what we found in our team is that income changes do seem to be causally linked to mental health. That's probably not a shock for people who are particularly interested in public health, but we did seem to manage to, to kind of prove that and also the effects our much larger for moves in and out of poverty. So they seem to be kind of really important types of income changes in terms of the effects that they have on mental health. But another thing that we found was that actually when we compare the size of that effect to the size of the effect that might happen when you lose your job, that effect of kind of becoming unemployed is a much larger impact on mental health than just kind of moving in and out of poverty. Income only seems to explain a very small part of that relationship between work and mental health. Knowing these sorts of things can make it easier for us to think about how policy changes the impact on these factors. So, for example, welfare policies or more radical suggestions like universal basic income or UBI, might influence health.
Ruth Dundas:
You mentioned there Universal Basic Income, and that's one policy that you're interested in. Can you explain a little bit more about Universal Basic Income and why it's being considered?
Rachel Thomson:
The idea of it is that it's quite simple one. It's a regular payment, paid in cash to all individuals within a society. It doesn't necessarily need to be designed to be enough to be able to live on, or what we call the kind of ‘livable’ UBI - although many people suggest that it should be, and that would be the kind of ideal for them. So the way that that kind of differs from our current welfare system in the UK is obviously that everybody receives this UBI. So it's not what we call conditional. So it's you don't have to do things, you don't have to prove things, to kind of prove that you're eligible for it. Everybody's just automatically allowed to get it and automatically transferred it, and people who are interested in this, who are kind of advocating for UBI as a policy say that the advantages of that is that it will give people much more freedom to choose what they want to do with their lives, while also providing them with kind of financial security. And that's especially important in times of kind of of economic difficulties. So times like recessions. Particularly, people have talked about it in the context of kind of the changing work environment that we're all experiencing just now with kind of increased use of automation in some jobs potentially declining over the next kind of decade or so.
Ruth Dundas:
Thanks for that. And the way that you've described it, it's sort of economic policy or something to do with like welfare or social policy. So why is it important to evaluate the health impacts and also any impacts on health inequalities?
Rachel Thomson:
So you're quite right, so the motivation for why people talk of introducing UBI is often not always to do with health. It's much more around these kind of economic measures like people's involvement in the workforce. For example, that's often not talked about. But from our perspective, as health researchers and given what we know about how economic factors, things like financial security can influence health, it certainly makes sense that a policy like UBI, which is quite a radical departure from what is kind of currently on the scene, could have quite a big influence on health and well-being. It certainly has potential to. And we know that this is kind of transferable. We know that other Social Security policies certainly influence health; there's a good amount of evidence. So much that's probably been talked about on this podcast about how that influences health. In terms of inequalities, so kind of health inequalities effects of the policies and why we might be interested in that. As I mentioned, UBI is quite a radical departure from our current Social Security system. And so it's a universally delivered benefit. That's really quite different from policies which are targeted according to need. So this can potentially be positive and it can potentially reduce the stigma of receiving benefits, which we know is a real concern for a lot of people who are in receipt of benefits and may put people off applying for them. But there’s also a risk that these types of universal policies can increase potential inequalities inadvertently. So for example, if the people who would most benefit from the payment or service don't have as easy access to it as those who might not necessarily need it as much. So it's very much dependent on kind of how the policy is delivered. And the other question is that or the other important point here is that UBI as a policy approach is likely to be very expensive, particularly if we're talking about it being something that's a kind of amount you can live on. So there's a really genuine question there about how much it would improve things and in particular what the impact might be on inequality. So who stands to gain compared to the current system, and who stands to lose out?
Ruth Dundas:
Thanks, Rachel. We might come back to some of the points about inequalities later.
Lia Demou:
Yeah. So, Rachel, you've clearly told us why it's important to evaluate UBI and health and inequalities. Can you talk to us a little bit about why you chose to look at UBI's health effects using simulation modelling and what exactly did you do?
Rachel Thomson:
Yeah, absolutely. Because it is quite an unusual way to kind of look at this question. Part of the reason that we decided to do what we did is that there's never been a comprehensive trial of a fully universal UBI and certainly not in a high income country, although they've been talked about quite a lot and often not being able to go ahead. That's largely because they're very, very expensive to run and politically quite difficult, it requires political buying over a very long period of time, particularly if you're talking about something that delivered to an entire population rather than just a restricted group. And in these types of situations, policy modelling where we essentially try and create a simplified simulated version of the world to try out policies can be really helpful to kind of bolster that evidence base in the absence of real world studies. So in our case, to do that, we took the information from that earlier research I talked about on the relationships between income, employment and mental health and added these to an existing economic simulation model using a process called micro simulation. The UBI policies that we tested, we did a few. So we included some that were more generous and that were more kind of livable incomes and some that were less generous, so more around the level of current benefits. And we tried those out in a simulated population just focusing on working age adults - that was the bit we were particularly interested in.
Lia Demou:
Great. Definitely very interesting methodology to use here. What are the key findings from your analysis?
Rachel Thomson:
The biggest takeaway I think from the work that we've done is that we found that our findings were very dependent on the assumptions that we made and assumptions that the model made about how people were going to respond to UBI in relation to work decisions. So in our main modelling, the economic model predicted that people receiving the UBI would reduce their working hours in response to that, and particularly for the kind of more generous, livable UBI. And that actually had an overall negative effect on mental health. It's because, as I mentioned earlier, we know that moving out of work has a much bigger effect on mental health than kind of changes in income and this negative effect on mental health was worse for men. Now in contrast, if instead we told the model to assume that fewer people would stop working, which is not unreasonable given actually, when we're having very small UBI trials, it doesn't seem like people are as likely as you might think to kind of stop or reduce their hours, UBI in that situation has the potential to improve mental health and particularly in that case for women. They saw more benefit than for men, and also for those with less education. So there seemed to be a kind of socioeconomic gradient in the effect sizes. Now the effects were overall quite small, but still, even though they were small, with that kind of more positive modelling where a few people stopped working, what we saw was that UBI would potentially prevent about 112,000 cases of common mental health problems across the UK working age population. So that's things like anxiety, depression. The other thing just to say about our main findings is that the policies were really expensive. So as part of our economic part of the modelling we could kind of run very large increases in income taxes to pay for most of the costs of the policies, kind of past the point where survey evidence tells us people are willing to pay in terms of taxes. The most generous UBI out of the model would still cost £65 billion wayward and above that, so that's the kind of scale of costs that you're talking about here. So that money to support a policy like this this would have to come from somewhere else within the economy. Whether that's a different tax or kind of like either money from somewhere else.
Ruth Dundas:
You certainly made the case that the use of simulation is a powerful tool to do this analysis. But can you explain a little bit more about how you make sure the simulation is as accurate as possible and maybe cover some of the limitations of this approach? We can validate the model against data from the real world to see how its predictions relate to what's actually happened in the past. And we've done that with our model and it seems to do fairly well. We also peer review all of our methods. So if you at the end are able to go and look at the paper, you'll see what we link to. Kind of big technical paper about the model and that people are able to go and look at and kind of scrutinise. And we also publish the studies that we use to kind of fully parameterize the model. So all the effect sizes when those have been published as well. But just as importantly, throughout the building of the model, we had really intense discussions with the public, with stakeholders, with experts to kind of ask them what they thought was missing from the model and also what they see as the most important pathways from policies like UBI to kind of health and health inequalities. Some kind of remaining limitations about what I've done in this particular study and that we're going to try and minimise in the future is at the minute it very much focuses on the pathways from UBI to health that go via changes in income and changes in employment status. So just like whether or not you have a job or don't have a job. So we're probably going to be missing some additional pathways there, whether that's around the kind of quality of work, the number of hours that you work, reduction in stigma, increased choice and control over your life. And actually, since this paper, we've done some systems mapping workshops for people who have lived experience of poverty and these have generated some really fantastic insights into where there might be gaps that we're hoping to kind of take forward and modify the model.
Lia Demou:
Well this research, Rachel, is clearly very important. How did you maximise the impact of your results, the findings?
Rachel Thomson:
Well, I'm talking to people about it, so things like this podcast, but also kind of more widely so as part of our public engagement, we've kind of been feeding back those findings as well as kind of taking information from people to make things better. And we've also been discussing our findings with policymakers as well. And so kind of going along to things like Public Health Scotland, Welsh Government. the European Commission...We already have some existing links, but kind of expanding those links and trying to find people who are particularly interested in this and interested in making decisions about taking these types of policies or similar policies forward. Also, as well as doing that afterwards, we kind of do a lot of engagement in advance of making decisions about what to do. So we did that before this and we're doing it now for things that we're gonna do next, so that we really look at what's relevant to people - whether that is policy makers or also just announced to the public. And I think importantly being really responsive to feedback, positive and negative about what our work means and what it doesn't mean and how we can make it better.
Lia Demou:
Great. We usually finish off by asking our guests on what are the implications for health inequalities? So it'd be great to get your take on what we need to do to tackle inequalities.
Rachel Thomson:
Yeah, absolutely. So I can, I guess from the perspective of just this one study. So I think what we kind of cautiously said is that we think UBI does have potential to improve mental health, especially for women and those with less education it seems, so in terms of inequalities. That's the groups that might potentially be more likely to benefit. But it is very costly and I think there's an important question there about what would be the opportunity cost, if you like, of a policy like this. So that's basically a fancy way of saying, you know, if we do this, what do we not do instead? And how do we kind of measure that up? And I think there's a real question about, you know, can we do this type of policy? Can we design it in a different way so that it costs less but still gets most of the benefits? For example, Scottish Government have now begun discussions around the idea of a minimum income guarantee, where instead of a UBI which is free to absolutely everybody, there is a policy where essentially what it says is no one in our society should be trying to live on less than X amount of money. You can either achieve that through just a cash benefit, but also potentially for business services. I think it's a really important question or discussion to have around kind of what's the best approach to kind of get these benefits like this one in our modelling and whether UBI is the way to go for that or whether there are other things you could do. I think also from my perspective I think more kind of real world evidence is needed about how people across a whole population and how a whole economy might respond to a livable UBI in terms of how people's work behaviours might change and what that would kind of do to things like productivity. If everyone in the society is eligible for UBI, I think we don't have a great sense of what that would look like yet. And as I've shown in this paper, that actually has a big impact on what the health effects might be. There's assumptions about whether people are going to work in exactly the same way as they did before or whether that behaviour is going to change. And hopefully, another implication for kind of health and health inequality research is that you know where we can't do trials actually policy modelling like this can be a really useful approach to try and kind of fill some of that evidence gap.
Ruth Dundas:
Well, thanks, Rachel, for talking to us today. It was really interesting to hear about your research on UBI. For details and links about where to find the paper and other information about the participants in the podcast, you can find that in the podcast notes. And thank you for listening.