Universal Basic Income already is a targeted system

A common response to our work on Universal Basic Income as an anti-poverty policy is the following: ‘Well, that’s going to cost a lot of money. Rather than giving money to everyone, including lots of people who don’t need it, it would be better to target all that money on the poorest people, who really need it. You will have create a bigger anti-poverty effect that way’. There is a version of this argument here, for example.

Though this argument seems intuitively right, it’s actually not, oddly. UBI schemes of the kind we have advocated are in fact both universal (everyone gets them) and really well targeted at the poor. In fact, UBI schemes can be designed to have any precision and profile of social targeting that a policy-designer could imagine. In this post, I try to explain why.

The important thing to bear in mind is that the fiscal interaction between the state and the citizens is a two-way thing: there are both taxes (citizen to state) and transfers (state to citizen). When assessing how targeted a system is, you have to consider both of these: what is the net effect of the taxes and transfers on the income of each individual or household?

This means that although with a UBI, the transfer is universal, the net effect can be anything you like: you just set tax rates and thresholds appropriately. You can make it regressive, flat, progressive, targeted at the bottom 3%, targeted at the bottom 18%, or anything else you want to do.

In fact, here’s a theorem: the net effect of any non-universal benefit, for example a means-tested one, can be redesigned as a UBI with appropriate modification to the tax code. In the box below is a proof of this theorem (it’s really not complex). Here is the intuitive example. Let’s say you want just the bottom 10% of the income distribution to get £100 a week. You could make a transfer of £100 week to the bottom 10%; or you could, with equivalent financial effect, give everyone £100 a week and claw an extra £100 a week back from the top 90% by changing their tax thresholds and rates.

It follows that the right distinction to make is not between targeted transfer systems on the one hand and universal ones on the other. As we have seen, universal systems can be targeted. The right distinction is between ‘absent by default’ systems (the transfer is not made unless you actively apply for it), and ‘present by default’ systems (the transfer is made automatically to everyone). The question then becomes: why prefer a present-by-default system over an absent-by-default one? Why is it better, instead of giving £100 to 10% of the population, to give £100 to 100% of the population and then claw it back from 90% of them?

Actually, there are really good reasons. Absent-by-default schemes have a number of drawbacks. From the administrative side, you need an army of assessors and officers to examine people’s applications and try to keep track of their changing circumstances. But this is really hard: how can you tell how much need someone is in, or how sick they are? It means the state getting intrusively involved in people’s personal lives, and making judgements that are very difficult to make. From the user side, demonstrating eligibility is difficult and often humiliating. Even in terms of what they set out to achieve, absent-by-default systems fail. The point of the social safety net is to provide security and certainty. These are the things that people in adversity most need, and which help them make good decisions in life. Yet absent-by-default schemes like those that currently operate in most countries generate insecurity—rulings on eligibility can change at any time—and uncertainty—applicants don’t know if their application is going to succeed or be knocked back, or even when a decision will be made. And in an absent-by-default system, the support that comes through comes through retrospectively, after a delay in which the application has been assessed. By this time the person’s circumstances could have changed again, or they have got into an even worse predicament of homelessness or debt, which will cost even more to sort out.  

The other great drawback of absent-by-default systems is that they always generate perverse incentives. If you have to demonstrate unemployment in order to continue to qualify, then you have an incentive not to take some part-time work offered to you; if you have to demonstrate poverty, you have an incentive never to build up savings; and if you have to demonstrate ill health, you have an incentive to remain sick. It is very hard to avoid these perverse incentives in an absent-by-default system.  

Why do countries mostly have absent-by-default systems, when those systems have such obvious drawbacks? Sir William Beveridge was aware of their drawbacks back in the 1940s when he designed the UK’s current system. He favoured presence by default for child benefit and for pensions, and this has largely been maintained. He was against means testing for some of the reasons described above, but more means testing has crept into the UK system over the decades. He did however make more use of absence by default than a full UBI would. That’s because the economic situation seventy years ago was so different from the one we face now.  

Seventy years ago, people of working age tended to have single, stable jobs that paid them the same wage over time, and this wage was generally sufficient for their families to live on. The two circumstances where they needed the social safety net were cyclical unemployment, and inability to work due to illness or accident. These circumstances were rare, exceptional, and easy to detect: it is relatively easy to see if a factory has been shut down, or someone has broken a leg in an industrial accident.  

By contrast, today, many people have multiple concurrent or consecutive economic activities. The incomes from these fluctuates wildly and unpredictably, as in the gig economy or zero-hours contracts. It is often insufficient to live on: 61% of working-age adults in poverty in the UK today live in a household where at least one person works. The situations of need that Beveridge’s systems were designed to respond to were rare and exceptional. In the UK and other affluent countries today, need is frequent, can crop up anywhere, and waxes and wanes over time. An absent-by-default system cannot keep up with, or even assess, situations like this in any kind of reasonable or efficient way. The perverse incentives also loom large, as people avoid taking on more hours or activities so as not to trigger withdrawal of benefits.

You might by now be convinced that a transfer system that is both universal and well targeted at the poor is logically possible. But I need to convince you that it is practically possible too. Figure 1 shows the net effect on people in different deciles of the income distribution of a starter Universal Basic Income scheme for the UK, as recently modelled by Reed and colleagues. The important thing about this scheme is that it is realistic and affordable. With just modest changes to the tax code, chiefly the abolition of the personal zero-tax earnings allowance, it is fiscally neutral. That means, the government does not have to spend any more money than it already does, even in the short term, in order to bring the scheme in. As you can see, although everyone would get the payments, the net benefit would be hugely greatest for the poorest 10% of the population; somewhat beneficial for everyone below the median; and only a net cost to the richest, who would be net payers-in to an even greater extent than they already are.

Figure 1. Effects of the introduction of the starter Basic Income scheme on the incomes of households in different income deciles in the UK (percentage point change on the status quo). From Reed et al. (2023).   

This starter scheme would see a universal payment of £63 a week, about 70 euros. Sixty-three pounds does not seem like very much, but the scheme would still have a dramatic immediate impact on poverty. Using the conventional definition of poverty as 60% of the median income, the number of working age adults in poverty would fall by 23%, and children in poverty by 54%. The well-being impact would be larger than these figures imply, because people would have the predictability of a regular amount coming in each week that they knew would always be there. The long-run distributional consequences could be even more positive, as certainty and lack of perverse incentives allow people towards the end of the income distribution to be more active and become more productive.  

The threshold project: Recruiting post-docs

I am recruiting two post-docs to join us (in the Evolution and Social Cognition team, based in the Institut Jean Nicod, in the garden of the Ecole Normale Supérieure, here in Paris) for a new project called THRESHOLD. The advert is here. The deadline for applications is 11 December 2024. This blog post gives some more information about the projet.

Theories of human economic decision making are based on a simple model called a value function, or utility function; a mapping between the amount of money people have (or will receive), and their valuation of the situation. The typical function assumed is the dotted line in figure 1: the function is smooth; people like having more money better than less; but the amount of extra value they get with each additional euro is less than the last (aka diminishing returns). This means that people should always be risk-averse, since dropping down from where you currently are is always worse than going up by an equivalent number of euros.

Figure 1. Two value or utility functions: smooth (dotted); and with a desperation threshold (solid)

In recent work, we’ve been considering the consequences of entertaining an alternative model, where the value function is more jagged: more like a cliff-edge than Pareto’s smooth hills of pleasure. For example, you need to make rent, so you need say 600 euros on the 1st of the month. As long as you have the 600, it’s ok; the difference between 601 and 610 is not a big deal. But the difference between 601 and 599 is a huge deal. It could be the difference between keeping your apartment and losing it, which would mean a huge bump in your welfare. If you do lose the apartment, things could not be much worse: missing paying your rent by 10 euros or 200 euros might have much the same welfare consequence. In other words, there might be abrupt steps in the value function, and other bits where it is more or less flat; like the solid line in figure 1.

If there are abrupt steps – which we call desperation thresholds – then we would expect people’s behaviour to be rather variable (see the paper for the full set of predictions). With resources just above a threshold, people should be super risk-averse, because their main preoccupation should be not to fall down the cliff. This might mean they fail to take risks it would otherwise be rational to take. On the other hand, if their resources are currently below a desperation threshold, they may become super risk-prone, and take risks it is otherwise irrational to take. This is because those risks hold a small chance of moving them into a state where their immediate welfare would be enormously improved.

In the project, we want to apply this kind of thinking to the decision making of people living in conditions of resource scarcity (urban poverty, in particular). In essence, we want to understand the paradox of poverty. On the one hand, many studies show that people with lower incomes are more risk averse than those with higher incomes. On the other hand, all the gambling shops and fixed-odds betting terminals are in the places where the people on lowest incomes live. And a lot of really risky (and low yield) crime is committed by people at the bottom end of the income distribution. How can we square this paradox? People in poverty are both the most risk averse and the most risk prone? Desperation threshold models suggest that people might undergo quite rapid flips in behaviour – from risk averse to risk prone – due to very small fluctuations in the resources available to them, if those fluctuations move them over a threshold of urgent need in either direction. This would give life near the threshold an unpredictable and volatile quality.  

The project, funded by the ANR, will run from January 2024 and last for four years. It will have three work packages. Work package 1 will be a community study of a population living in challenging economic circumstances, using mixed methods. We want to understand what material resources mean to people. In particular, we want to understand how people represent their material situation, and how they understand its possible changes and their possible responses to those changes.

Work package 2 will take an experimental approach. We want to investigate whether, when you confront people with a desperation-threshold situation, they respond in the ways the theoretical models predict they will. Moreover, by creating multi-participant experimental microsocieties, we can try to understand what the emergent consequence will be for an interacting network if some of its members are facing desperation. Work package 2 will build on this already published work that lays out the experimental paradigm.

Finally, work package 3 will apply the insights of the other two packages to public policy and institution design. How would you design a welfare system if your goal was to make sure no-one would ever face desperation (as opposed, for example, to channeling resources to those you deem most deserving, or those for whom the productivity benefit would be greatest)? Can we predict the consequences of distributional changes and economic shocks for societal indicators like crime and addiction, by taking desperation thresholds into account?

The people I am looking for are, specifically: a researcher to concentrate on the field study for work package 1; and a researcher who will lead the experimental program of work package 2. For work package 1, the ideal would be someone with community research experience, good enough French to work in France, and maybe even existing community relationships. However, I can work around any of these three (for example, we could do the study in a different country for someone whose experience is elsewhere). The main criterion is skill in, and commitment to, working in the field in a community facing economic adversity. For work package 2, the person would need to be excited by the design and analysis of experimental studies. The two researchers would work together and would be able to gain experience in the other’s work package too.

The two positions could start as early as April 2024, but it can wait until later in the year two. Please circulate the link if you think there are people who should see it; and please apply!

Figure 2. The ENS. Yes, it was founded in the year III. Though it wasn’t that year III. And it was somewhere else at the time. And then it stopped existing for a bit. But still, it’s really nice.

It probably is that bad

The discipline of psychology is wringing its hands about its failure to make enough substantial and dependable scientific progress over the last fifty years of effort. First, we blamed our methods: hypothesizing after the results were known, researcher degrees of freedom, p-hacking and the rest. Then, we went after the theories: theories in psychology were so arbitrary, so vague in their relation to anything we could measure, so foundation-less, and so ambiguous, that tests of them were both much too easy, and much too hard. They were much too easy in that they could always be deemed a success. They were much too hard, in that the tests did not generally lead to substantive, cumulative, coherent knowledge. Reforms to the theory-building process were urged (here, here, here). Actually, these critiques were not new: Paul Meehl had made them floridly decades earlier. Writing in the last century, but in a parlance that would have been more at home in the century before, he compared the psychology researcher to: “a potent-but-sterile intellectual rake, who leaves in his merry path a long train of ravished maidens but no viable scientific offspring.”

I read all this with interest, but I remember thinking: “it can’t really be that bad.” I didn’t come across that many obviously terrible theories or terrible tests in my day to day life, or so I felt. I assumed that authors writing about the theory crisis – who obviously had a point in principle – were exaggerating how bad the situation was, for rhetorical effect.

Recently, Joanna Hale and her colleagues have made the important contribution of creating a database of theories in psychology (more specifically, theories that relate to behaviour change). All of the theories are represented in a common formal and graphical way. The database is here, and the paper describing its construction is here.

The database gives us a few useful things about each theory. First, a list of the constructs, the things like self-efficacy or self-esteem or normative motivation or health beliefs or whatever, which constitute its atomic elements. Second, a list of the relations between them (self-efficacy influences normative motivation, self-esteem is part of self-efficacy). And third, combining the first and second, a nice graphical representation, a kind of directed acyclic graph or DAG: which construct, according to the theory, does what to which other construct?

The genius of this database is that our array of theoretical tools (76 different theories, no less) is laid out before us on the bench in utter clarity. I have to say, my immediate reaction is: oh dear, it really is that bad.

Why do I say this? If you look at figure 1 I think you will see why. I chose this theory more or less at random; most are not much different.

Fig 1. Example representation of a theory, from the theory database. I chose it pretty much at random; they are nearly all like this.

The first and most obvious problem is that the theories contain many links, an average of 31 and a maximum of 89. And that is the direct connections. A connected network with 31 direct links probably has thousands of distinct indirect ways of getting from any upstream construct A to any downstream construct B. Some of these pathways will be mutually suppressive: A has a positive influence on B; but also a positive influence on M which has a negative influence on B. So what should be the empirical covariance of A and B, given that the directions of these associations are specified by the theory but their strengths are not? The theory is consistent with: positive (the direct pathway is dominant); negative (the indirect is dominant); or null (the two pathways cancel each other out). In short, pretty much any pattern of associations between non-adjacent constructs could probably be accommodated in the theory’s big, leaky tent. It’s generally unclear what the systemic effect will be of intervening at any point or in any direction. Moreover, with 31 links and null hypothesis significance testing at p < 0.05, something is definitely going to be associated with something else; there will always be statistically significant results to discuss, though their actual significance will be unclear.

The multiplicity of links is an obvious problem that hides, I think, the much more fundamental one. Psychology’s problem is really one of ontology. In other words, what should be our atoms and molecules? What is in our periodic table? What is the set of entities that we can put into boxes to draw arrows between; that we can fondly imagine entering into causal relationships with other entities, and making people do things in the world?

In the 76 theories, there were 1290 unique constructs. Even allowing for fuzzy matching of names, 80% of those constructs only appeared in a single theory. No construct appeared in all the theories. Only ‘behaviour’ and ‘social’ appeared in more than half the theories, and those are hardly tightly defined. It’s like having 76 theories of chemistry, 80% which name completely unique types of building block (mine’s got phlogiston!), and which contain no type of building block common to them all.

The fact that we lack a stable ontology is really what makes our results so hard to interpret. Let’s take the theory known as ‘the systems model of behaviour change’ (figure 2). The theory distinguishes between (inter alia): the perception of self; the perception of social influence; attitudes; motivation to comply; and health intention. These constructs are all supposed to enter into causal relations with one another.

Figure 2. The database diagram for the Systems Model of Behaviour Change.

Suppose we measure any two of these, say motivation to comply, and health intention. We find they correlate significantly, at say r = 0.4. At least three things could be going on: (1) the theory is confirmed, and motivation to comply influences health intention; (2) our measurement of at least one of the constructs is impure; one of the questions that we think of as measuring motivation to comply is a really bit reflective of health intention too; thence the correlation is a methodological artifact; (3) motivation to comply and health intention are really the same thing, measured in two noisy ways using different questions; (4) neither motivation to comply or health intention is really a thing, so the correlation is meaningless.

The difficulty, it seems to me, is that the measurement issues cannot be solved whilst the ontological ones are still live (and, probably, vice versa). If we are not sure that X and Y are really two things, then we never know how to interpret the covariance of their measurements. Maybe we haven’t measured them purely; maybe we shouldn’t be measuring them separately; or maybe we have learned something about the structure of the world. None of the various criteria of measurement reliability or validity that circulate in psychology really helps that much. This criticism is most obviously applicable to correlational research, but it affects experimental manipulations too.

The ontological problem is really hard. You might think you can purify your ontology, get it down to bed rock, by eliminating all entities that could be redescribed in more atomic terms. But this approach account cannot be right. Taking it literally, we would need to remove from our ontologies all kinds of very useful things: atoms, elements, organisms, and genes, for example. There would be no science but subatomic physics, and it would take forever to get anywhere. No, there are all kinds of things we want to hang onto even though we know they can be eliminated by redescription.

The criterion for hanging on to an ontological category has to be much looser. Something like that: it reliably shows up for different observers; it is an aspect of a stable level of physical or biological organisation; and it proves itself useful and generative of understanding. Though this is far from clear cut, most of psychology’s ontological cabinet probably does not comply. In fact, who knows where the 1290 constructs in the database come from? Probably a combination of ordinary language, folk psychology, loose analogies, academic carpet-bagging, and random tradition. That’s really our problem.

There is no simple answer to this difficulty. The much-advocated ‘doing more formal modelling’ is not a solution if the entities whose relations are being formally modelled are flaky. Some ontologies are better than others. Generally the better ones (i.e. more stable, and leading to clearer and more accurate predictions) are more rooted in either biology (that is, either neuroscience or evolutionary biology), or in computational frameworks that have proved themselves predictive in a detailed way on lower-level problems (I am thinking of Bayesian models of cognition and their social applications, as discussed here). But, for many parts of ‘whole-person’ psychology, scientific performance in some coefficient of determination sense is not enough. We also want to maximise intuitive gain. The theoretical terms have to generate some insight, not least in the very people whose behaviour is their subject. Some ontologies probably do more for intuitive gain, others for biological realism, and it is hard to find the middle way.

One thing is for sure: we don’t need any more than our (at least) 1290 constructs. Perhaps there ought to be a global ontological non-proliferation treaty. I imagine a permanent conference, domiciled in St. Kitts or Geneva, where teams quietly work towards voluntary reduction in psychology’s ontological stockpiles. Volunteers?

Phoebe and the paradox of tragedy

All summer long, our little cat Phoebe spent much of her time squeezed onto the kitchen window bar, gazing out into the garden. How sweet, I thought, she is looking out on the sunshine and flowers. Coming home and encountering her yet again in position, we would say ‘she must really like sitting there’.

Weeks went by and it began to unsettle me. This is starting to seem obsessive; she has become like Edward in Harold Pinter’s A Slight Ache, staring up the lane from the scullery to see if the silent match-seller is in sight. Finding her unresponsive, curled up in her bed when I came down to make the morning tea gradually went from being charming to worrying. Has she worn herself out with her vigil? What if looking out all day and night is actually a horrific and exhausting chore? What if it is making her ill? Eventually, in an insomniac moment, I could not stop myself descending at 3am, to discover the silhouette of Phoebe by moonlight, at her post, peering fixedly into the gloom.  

We took her to the country for a couple of weeks. My anguish heightened a notch when, on returning and being released from her cat carrier, she sprinted downstairs to her post, where the window now had a greasy streak from her pressed nose, and stuck there.

A little later, the evidence became incontrovertible. Two huge tom cats were having a territory war in the street outside; one or other would patrol past every day or two. It was appalling for her to spy one, brazenly milling outside (female cats outside oestrus – and Phoebe is neutered – have no interest in sex; but they are worried about competition and violence). She would fill the kitchen with low moans, her tail bushed, almost foaming at the lips in her terror, but could not pull her gaze away. It took her many minutes to calm down. Phoebe didn’t like looking out from her post; she could not help it. The garden was not a scene of beauty; it was a site of mesmerising threat.

Phoebe and her problems remind me of David Hume’s essay Of tragedy. Why do people pay attention to representations – tragedies, horror movies, dark paintings – whose emotional effects include, prominently, negative emotions such as fear, anxiety and disgust? As you can imagine there is a substantial literature on this problem (see here for example). All of the many offered solutions seem to me special pleading or failures to really resolve it. We admire the beauty of the construction (Hume’s answer). We enjoy the moral evaluation that our own negative feelings are justified, or enjoy seeing the baddie get their comeuppance. Or, negative emotions produce arousal and we like arousal (even if negative in source) when we have nothing much else to do. Or, the negative emotions in question are not really negative but counter-evidentially positive, maybe because you have distance from or control over them, or because you frame them a certain way. And so on. But the point is, Phoebe spent her summer on the window bar without seeing any baddies get their comeuppance; without admiring any artistry; without being paradoxically ennobled; without having any detachment or control; certainly without moral vindication. Yet, there she was.

Whether the paradox of tragedy is even a paradox rather depends on your underlying model of how minds work. Intuitively, humans adopt the naïve utility calculus as their working model of the mind. That is, we assume that people (or cats) do actions because they like them; their liking is what makes them do the actions. Hence, the paradox: if they are doing things that seem to make them feel awful, those things must not really make them feel awful (or they wouldn’t be doing them); there must be some convoluted way in which they actually like those things, all evidence to the contrary. Thence all the various epicycles to explain how this could be the case, to square the evidence of our senses with the obvious violation of the naïve utility principle.  

But the naïve utility calculus is an everyday working model – a folk theory – not a good scientific account of how minds actually work. Minds are bundles of evolved mechanisms, mechanisms that generate attention and motivation to certain categories of things: conspecific and allospecific threats, potential food, potential allies, potential shelter, and so on. We don’t attend to those things for some higher-order reason such as we like them, or we estimate that we will have greater hedonic utility if we attend to them. We attend to them because they capture our attention, given the design of the mental mechanisms we have. As John Tooby and Leda Cosmides argued, humans are best conceived of as adaptation executors, not maximizers of fitness, utility, or pleasure. A fortiori they would apply this to cats too. From this point of view, there is no paradox whatever about Phoebe allocating all her time to a vigil that made her feel dreadful. Her mind was telling her she needed to keep an eye on that stuff, like it or not. Even in humans, it’s really, really difficult to switch off mechanisms when they are doing their thing, even though we have enough self-reflection to understand sometimes that we are self-harming in the process. Think of behavioural addictions, or devastating unrequited love.

How does this help with the paradox of tragedy in art? For one thing it shows that if you base your philosophy and psychology on a folk theory of the mind, you will generate apparent scientific puzzles that have no solution (other than: don’t start from there!). As my colleagues Edgar Dubourg and Nicolas Baumard have argued, artistic representations are cultural technologies. They are deliberately made by producers in order to capture the attention of consumers, just like you would make a shoe to protect a foot. Those producers understand something about the minds of audiences, like cobblers understand something about the anatomy of feet. So, naturally, the producers include ingredients that are good at causing mental adaptations in the audience to allocate attention: they include predators and rivals, love objects and moral regularities, places of shelter and places to flee, and so on. (There is a TEDX talk in French by Edgar on his work here.)

Producers typically include a range of different ones of these ingredients, to keep up the interest and lessen habituation. Thus, there is a very large set of different possible genres and sub-genres with different mixes of ingredients. But there is no requirement that artistic representations have to be positive in some general affective sense; they just have to succeed at making other minds pay attention. For humans, they have other requirements too, in order to endure. They have to hang together in some kind of plausible way, and the most durable ones have to repay cognitive reflection and communication. Artistic representations can be co-opted for other purposes such as teaching or there creation of coalitions. But those things are not their functions, and, to the point, there is no particular paradox if they incite mainly negative emotion rather than mainly positive emotion.

Ludwig Wittgenstein wrote that if a lion could speak, we would not be able to understand it. I think the point is that what is relevant and attention-grabbing to a creature depends what kind of mind that creature has; and that in turn depends, in Wittgenstein’s words, on the creature’s ‘form of life’. In more contemporary parlance, we would call this the ecology within which the creature’s mental mechanisms have evolved and developed. An unmoving tom cat sitting on the pavement is not my idea of an attention-grabbing spectacle (though come to think of it, isn’t there a late Samuel Beckett play that is more or less that?). Who knows how captivating, how nuanced, how dreadful, it was to Phoebe? If cats made art, maybe that is the art they would make.

October update: Autumn has come, the tom cats have gone, and Phoebe has left her position on the window bar.

Does greater inequality cause worse health? No! And: kind of yes!

The question of whether greater economic inequality makes people’s health and wellbeing worse is an important one. The literature has been moving fast over recent years, and the debate has moved on somewhat since my previous essay.

It can all get a bit technical and econometric at times. The questions most people care about are: (1) is the relationship between inequality and health really a cause and effect one?; and: (2) if we make our country more equal, for example by increasing benefits or cutting taxes on the rich, will we improve health? Somewhat paradoxically, I am going to answer (from my current understanding of the literature): ‘kind of no’ to the first question; and ‘yes’ to the second.

First, let’s look at the very brief history.

Act One:

In which a slew of papers appears, showing that countries, or US states, with greater inequality in incomes had lower life expectancy, worse health and mental wellbeing, and a host of other poor outcomes like lower trust and higher crime, when compared to countries or states with lower inequality. Inequality here was measured as the dispersion of the distribution of incomes, typically captured by the Gini coefficient; and many of these studies controlled for the median per capita income of the country. It’s not how rich you are, the argument went, it’s how big the gap is within your society. Big gap is bad, above and beyond how much money people have in absolute terms. The finding of the Gini-bad health correlation was sufficiently recurrent as to produce claims that this was a general finding about humans and what they need to be healthy.

Act Two:

In which a medley of articles, mostly by economists, argues that the correlation between income inequality and average wellbeing is a kind of statistical artefact. When inequality is greater, the poorest people within that society are also poorer. If you think about it, it must be true that, other things being equal, when the inequality is greater, the poor are poorer. Imagine you have two countries both with median incomes of $50,000, one of which is more equal and the other more unequal. Visualize them as two distributions of incomes, distributions whose medians are in the same place. The poorest people in the unequal one must be poorer in absolute terms (further to the left) than the poorest people in the equal one. That’s just what it means for it to be a more dispersed distribution. Now, what’s really bad for health and wellbeing is being poor, and what is more, it’s a non-linear relationship. At a certain point, being a bit poorer makes your health a lot worse. So if the poorest people in society X are a bit poorer, their health is a lot worse, and hence the average health of the whole population is lower. (In a more unequal society, the richest people are also richer than the rich in a more equal society; but beyond a certain point, being richer does not increase your health much, so the positive effect of greater inequality on health – via the rich getting even healthier – is statistically small).

Controlling for the median incomes of the two countries does not eliminate the confound between the income of the poorest people and inequality: in my example, the median incomes of the two societies are the same. Thus, a series of studies argued that the correlation between countries’ Ginis and measures of aggregate health or wellbeing mostly (though perhaps not entirely) comes down to the poorest people in the more unequal countries having lower individual incomes. Tom Dickins and I just published a recent example of the genre, using data from 28 European countries. We showed that the association between the Gini coefficent and average health or life satisfaction is greatly attenuated once you control for individual income.

The difference between the poverty-pushers and the inequality-urgers is very subtle: both, in practice, both think it would be better for health in countries like the UK and USA if economic resources were redistributed. The real difference between their claims only becomes clear when you examine some wildly improbable counterfactual scenarios. Imagine an economic windfall that doubled the real incomes of everyone in bottom half of the income distribution, and trebled the real incomes of everyone in the top half. Do you think average health would get better or worse? For a poverty-pusher, the answer is better, because everyone’s incomes have gone up, including big income increases for the people currently facing poverty. For a purist inequality-urger, the answer is worse, because it is the gap that matters per se. We seem unlikely to get to see the results of that experiment any time soon. In the mean time, both camps agree that bringing the incomes of the worst-off closer to the median of the distribution in countries like the US and UK is a good goal: it would reduce both poverty and inequality. Both camps also agree that taxing wealth or very high incomes is a reasonable way to do this: for the inequality-urgers, that’s a good in itself, because it reduces the gap. For poverty-pushers, it’s the rich who can most afford to contribute more without suffering any meaningful decline in their well-being.

Act Three:

In which social psychologists repeat the search for correlations between the Gini coefficient and subjective measures of health and wellbeing. They improve on the work of Act One by using larger data sets, often including data over time rather than just a single cross-section. They tend to focus on inequality over smaller areas, such as US counties, rather than larger ones, such as US states or countries. This is, they argue, a double virtue. There are thousands of US counties, and only 50 US states. So you have much more statistical power when you use the smaller unit. Plus, people are really bad at knowing anything about the inequality of their entire country. They spend most of their lives moving around the smaller place where they live, and meeting the other people who live there. The Gini coefficient of a whole country is unlikely to be related to anything in people’s actual lived experience of inequality; the Gini coefficient of their town or county just might be. So it’s a better test of the causal potency of inequality to affect people if you use the local-scale measure. And, in fact, when people on low incomes move to rich neighbourhoods, thereby increasing the inequality they experience in their daily lives, their health and wellbeing improve rather than getting worse.

The Act Three studies conclude that there is no consistent relationship between inequality, as measured by the Gini coefficient, and happiness or health (for example here and here). Their studies are big and they are pretty firm about this. Their argument, note, is different from the Act Two guys. The Act Two guys said that there was a relationship, but it was largely explained away by individual income. The Act Three guys said there was no relationship to explain away in the first place.

And so?

And so, dear reader, where is the hypothesis that more inequality is bad for health, as they say, at?

First, I don’t think the current evidence supports the contention that the magnitude of the gap is in itself directly harmful to human health to any substantial extent. The primary grounds for saying this comes from the Act Two studies: when you control for the curvilinear effects of individual income, most (though maybe not absolutely all) of the association between inequality and health goes away. Inequality is associated with poor population health, because when the inequality is bigger, a greater fraction of the people face material scarcity. But, it is material scarcity that actually puts the causal boot in at the individual level. Concretely, the proximal reason people living in poverty in Tennessee have terrible health is not that the difference between their incomes and those of millionaires elsewhere in the state is too big. It’s that their incomes are not sufficient to live well on, given the society they live in. (I put this last rider in because I always get the response; yes, but their incomes are higher than the rich of yesteryear. Well maybe, but a lot of things cost more now than they did in yesteryear, including some really important things like food and access to healthcare.)

The secondary grounds for saying that inequality is not in itself the causal agent of harm is that when you measure the size of the income gap at the local-area scale, like the town or country, it seems to explain no variation in health outcomes (see Act Three). But the local-area scale is the area at which people are most likely to actually experience inequality in their lives. It’s odd in a way. When you measure inequality at a huge scale of measurement where people would be unlikely to be able to actually detect it (the country), you find associations. Where you measure it at a scale closer to their lived experience, those associations are absent. This does rather support the view that it can’t be the inequality per se that is the causal force at the proximal level. (By the way, I think the reason the associations hold at the large scale of countries better than the small scale of cities or countries is that the former contain a broader range of incomes, and the effect is largely mediated by individual income, as per Act Two.)

However, despite saying that inequality is not an important direct influence on health at the individual level, I do think that if we reduced inequality in developed countries, population health would improve. I am pretty much as sure of this as I am of anything in social science. This is simply because when you change inequality, you change the distribution of individual incomes. Specifically, you raise the incomes of the poor, for whom it will make a vast difference in health and wellbeing; and slightly reduce the incomes of the rich, who will scarcely feel it. So, the total amount of well-being goes up. (An important corollary of my position is that raising the incomes of the poor would improve population health whether or not it reduced the wealth of the rich, that is, regardless of its impact on the Gini. It’s just that, as it happens, the best levers we have for improving the incomes of the poor will also reduce the Gini.)

So: is the association between (country-level) inequality and population health causal, or not? Here, you have to say ‘it depends what you mean by causal’. On one view of causality, the way for example we say that AIDS is caused by the HIV virus, then, no; I don’t think we have identified, in the Gini coefficient, a pathogenic agent that causes the individual-level harm in such a way as to satisfy the Koch postulates. On the other hand, what people generally care about when they talk about cause is something like: would it regularly make a difference to health if we reduced the inequality of the income distribution? On this view of causality–which is sometimes referred to as an interventionist or manipulationist view–then I would have to say yes. Across the range of conditions that presently exist in developed countries, then available interventions that reduced inequality would generally, unless they had some weird negative by-products like causing a famine or a war, improve population health and wellbeing, possibly by a lot. Sorry if that’s rather a philosopher’s conclusion, but it seems to make sense of the conflicting literature.

There’s one more thing to say about the size of the gap in society. It may not per se have much effect on most people’s wellbeing. But I’ve been persuaded, notably by Darren McGarvey’s book The Social Distance Between Us, that it could have a big effect on the wisdom of our leaders. Broadly speaking, when social gaps are big, the people in power make worse decisions, and the people not in power are less able to hold them to account. This is because the ruling caste has so little contact with what the rest of the people are actually experiencing, and vice versa, that it is almost impossible for them to make appropriate decisions that work for the public good. And their constituents become disengaged, which means less public deliberation and input into the processes that are supposed to make the country better. The consequences of this gulf between the imaginary world that politicians are making policy for and the actual world of people’s lived experience are so evident that I scarcely need provide examples (consider the UK of the last twenty years, e.g.). If this factor is important, then it’s actually a different kind of argument for reducing inequality:- by doing so, we could get better institutions and better solutions to the challenges that we face.

What do people want from a welfare system?

All industrialised societies feature some kind of welfare system: institutions of the state that transfer material resources to certain categories of people or people who find themselves in certain kinds of situation. Non-industrialised societies have systems of social transfers too, albeit sometimes more informal and not organised by the state. People seem to think this is a good thing, or at least necessary. This raises the question: what do the public think a good welfare system would be like? How generous do they want it to be, and how would they like it to distribute its resources?

Polls in European nations consistently find most people expressing strong support for the welfare state. But there is a problem with this: when asked, a lot of people express support for tax cuts too. And for lots of other things, things that probably can’t all be achieved at the same time. This has led to one view in political science that most people’s policy preferences are basically incoherent (and hence, not much use in setting public policy). There is another interpretation, however.

Imagine you ask me whether I would like more generous benefits for people with disabilities, and I say yes; and you ask me if I would like tax cuts, and I say yes to that too. This might seem incoherent. But really, you should interpret my response to the first question as being other things being equal (i.e. if this move could be made without perturbing anything else) then I would favour more generous benefits for people with disability; and other things being equal I would favour tax cuts. Well doh. Of course if you could have lower taxes and everything else remain just as good, that would be nice. If you ask me about tax cuts without telling me about what would have to be discontinued to allow for them, you are implying they could be made with no loss to other social goods. But favouring tax cuts that cause no loss to other social goods is a totally different position than favouring tax cuts at the expense of something else. We should not confuse the two (and hence, by the way, you should distrust polls who say that say 107% or whatever of the British public want tax cuts; 107% of them also want better hospitals too). There is nothing incoherent about favouring other-things-being-equal tax cuts, but also preferring spending on benefits to be maintained in the event that the two goals conflict.

In other words, just asking people baldly about one thing, like tax cuts, doesn’t really tell you about the most interesting question, which is: given that different social goods, all of which we might want, are in conflict, how do you – the public – want them to be traded off against one another? How much more tax would you pay for higher benefits, or how much more poverty would you tolerate in order for taxes to be lower?

A popular method for studying how people make policy trade-offs is the conjoint survey. The researcher thinks of all the possible dimensions a policy could vary on. Let’s imagine our policy is a meal. It could vary on the dimension of cost (with levels: $1, $10 $50, etc.); deliciousness (1-10); style (French, Chinese , Italian, Ethiopian); nutritional value; carbon footprint; and so on. Now, we randomly generate all the possible meals within this multiverse, using all the combinations of levels of each attribute. Then we repeatedly present randomly chosen pairs of these policies, and the respondent says which one they think is better.

Because of the random generation, some of the policies are unicorns: the utterly delicious meal that costs $1 and has minimal carbon footprint. And some are donkeys: the $100 disgusting meal. But when you give enough choices to enough participants, you begin to be able to estimate the underlying valuation rules that are driving the process of choice. In effect, you are doing multiple regression: you are estimating the other-things-being equal effect on the probability of a policy getting chosen when its deliciousness is 6 rather than 5, or its cost $20 rather than $10. Valuation rules allow you to delineate preferences about trade-offs, by comparing the strength of a dispreference on one dimension with the strength of a preference on another. For example, people might be prepared to pay $3 for each increment of deliciousness. The trade-offs can be different for different groups of respondents: maybe those on low incomes will only pay $1 for each increment of deliciousness, meaning that in life they end up with cheaper and less delicious meals.

In a new study, Joe Chrisp, Elliott Johnson, Matthew Johnson and I used a conjoint survey to ask what 800 UK-resident adults want out of the welfare system. We made all of our welfare systems somewhat simple (a uniform weekly payment with one level for 18-65 year olds and a higher level for 65+). We then varied four kinds of dimensions:

1) Generosity: How big are the payments?

2) Funding: What rates of personal income tax should people pay to fund it? And would there be other taxes like wealth or carbon taxes?

3) Conditionality: Who would get it? What would they have to do to demonstrate or maintain entitlement?

4) Consequences: What would be the effect of the policy on societal outcomes, specifically, the rate of poverty, the degree of inequality, and the level of physical and mental health?

People in fact made very coherent-looking valuations, at least on average. And, yes, other things being equal, they wanted income taxes to be lower rather than higher. But the strongest driver of choice was the effect on poverty: people want the welfare system to reduce poverty, and they like it when it reduces poverty a lot (figure 1).

Figure 1. Estimated marginal effects on the probability of policy choice of rates of income tax (top); and effect on poverty (bottom). The dots are central estimates and the lines, 95% confidence intervals.

In the figure, a value to the left of the vertical line means that having that feature made people less likely to choose the policy, all else equal; and a value to the right of the vertical lines means having that feature more likely to choose the policy. This is compared to a reference level, which in this case is the current UK income tax rates for the upper graph, and the current rate of poverty for the lower one. So, the more a welfare system reduces poverty, the more likely respondents are to choose it; the more it increases poverty, the less likely are to choose it; and the effect is graded – the bigger the reduction in poverty, the better.

There were other features that also affected preferences. People like the idea of funding welfare from a wealth tax or a corporate or individual carbon tax, relative to the government borrowing more money. And they quite liked the welfare system to improve physical and mental health, and reduce inequality – or at least, not to make these things worse. However, none of these was as strong as the desire to see poverty reduced.

We also varied who would get the benefit (citizens, residents, permanement residents), and what the conditions would be (have to be unemployed, means testing….). None of these design features made much difference. This is something of a surprise since a big theme in the recent literature on public preference over welfare systems is the idea of deservingness: people don’t want welfare payments to go to the wrong kind of people, where wrong is conceived as slackers, free-riders or foreigners, and this saps, or can be deployed in order to sap, their support for welfare institutions. The way I read our results, these deservingness concerns are mostly pretty weak in the grand scale of things. People want a welfare system to reduce poverty in the best value-for-money way; they don’t care too much about the design choices of the institution so long as it does this.

The findings shown in figure 1 allow us to pit a given income tax rise against a given effect on poverty. For example, would people by prepared to pay ten more percentage points in order to halve the poverty rate? You work this out simply by summing the coefficients, negative for the tax rise, positive for the poverty cut, and seeing if the result is greater than zero. This exercise reveals a zone of possible acceptability, a range of income tax rises that people would find acceptable for a sufficiently large cut in poverty (figure 2).

Figure 2. Zones of acceptabilty and unacceptability for combinations of income tax rises and poverty change. The area shown in red would on average be unacceptable, and that shown in yellow would be acceptable. The status quo is shown in white.

These findings are quite noteworthy. Really substantial income tax rises – ten percentage points or more – would be acceptable on our average to our respondents, as long as they delivered a big enough decrease in poverty. British political parties currenrly work on the consensus that any talk of income tax rises is politically unfeasible. The Labour Party is currently and rapidly distancing itself from any hint of tax rises of any kind, including wealth tax, which our results and other research suggests would be popular. When the Liberal Democrats proposed a 1% increase in the basic rate of income tax in 2017, it was viewed as politically risky. Our results suggest they could have been an order of magnitude bolder and it could have been popular.

A worry you might well be having at this point is: well yes, this was all true of the particular sample you studied, but maybe they were particularly left-wing; it wouldn’t play out that way in the population more broadly. In fact, we already went some way to mitigate this by weighting our sample to make it representative of voting behaviour at the 2019 General Election. Also, and more interestingly, people of different sub-groups (left/right, young/old) differed only rather modestly in their valuations. Figure 3 shows figure 2 again but respectively for Conservative and Labour voters in 2019. You might think that we would see that Conservative voters want lower tax at any cost, while Labour voters want redistribution at any price. Not at all: both groups have a trade-off frontier, it just looks a bit different, with Labout voters valuing the poverty reductions a bit higher relative to the tax rates than Conservative voters do. But both groups have an area of possible acceptability of income tax rises, and these areas overlap. Ten percentage points on income tax to halve poverty, for example, would be acceptable even to Conservative voters, and therefore a fortiori to other groups.

Perhaps these results are not surprising. We already know that there is strong support for a social safety net, and that people care about the outcomes of the worst off. Our findings just show people accept that it has to be paid for. So really the pressing question is: how have politicians come to believe that tax rises are completely politically impossible in contemporary Britain, when this and other research suggests that this is not the case? For example, a review in The Guardian of Daniel Chandler’s recent book Free and Equal, which proposes a moderate Universal Basic Income and tax rises to find it, basically said: nice idea, but who’s going to vote for that in the Red Wall? (The Red Wall refers to electoral districts in the Midlands and North of England thought of as something of a bellwether. ). Yet, both our present study and our previous research in the Red Wall give the same answer: most people. Chandler’s proposals are exactly in the zone that commands broad assent in the Red Wall, and even amongst people who have recently voted Conservative.

Without wanting to go too dark on you, I have to remind you of the evidence that the opinions of the average voter don’t actually matter very much in politics as it stands (at least in the USA). What parties propose is influenced by the views of the rich and by organized business, and pretty much unresponsive to the views of everyone else. Interestingly, this narrow sectional interest gets mythologised and re-presented as ‘the views of the person in the street’; but this is mainly a kind of ‘proletariat-washing’. A small group of people who have a lot of power and influence don’t want to reduce poverty by raising taxes. The Labour party, by choosing not to propose doing so, is courting this group. What gets passed as wooing the public is really wooing the elite. They might have judged, and perhaps rightly, that wooing this group successfully is necessary to win power, but let’s not confuse this with following public preference. The median British voter may well favour something much more transformational.

How can I explain this to you?

One of the big problems of the social and human sciences is the number of different kinds of explanations there are for what people do. We invoke a great range of things when we talk about why people do what they do: rational choice, conscious or unconscious motivations, meanings, norms, culture, values, social roles, social pressure, structural disadvantage…not to mention brains, hormones, genes, and evolution. Are these like the fundamental forces in physics? Or can some of them be unified with some of the others? Why are there so many? It is not even clear what the exhaustive list is; which elements on it could or should be rephrased in terms of the others; which ones we can eliminate, and which ones we really need.

It’s bad enough for those of us who do this for a living. What do the general public make of these different constructs? Which ones sound interchangeable to them and which seem importantly different? The explanation-types are sometimes grouped into some higher-order categories, such as biological vs. social. But how many of these higher groupings should there be, and what should be their membership?

In a recent paper, Karthik Panchanathan, Willem Frankenhuis and I how people understand different types of explanations; specifically, UK adults who were not professional researchers. We gave participants an explanation for why some people do something. For example, in a certain town, a large number of murders are committed every year. Researchers have ascertained that the explanation is….and then one of 12 explanations. Having done this, we then presented the participants with 11 other explanations and asked them: how similar is this new explanation for the behaviour to the one you already have? Thus, in an exploratory way, we were mapping out people’s representations of the extent to which an explanation is the same as or different from another.

The basic result is shown in figure 1. The closer two explanations are to one another on the figure, the more similar they were seen as being. We used a technique called cluster analysis to ask how many discrete groupings it is statistically optimal to divide the graph into. The answer was three (though it depends a bit on the parameter values used). There was one grouping (hormones, genes and evolution) that definitely stood apart from all the rest. These are obviously exemplars of what people have in mind when they speak of ‘biological explanations’. The remainder of the explanations was more of a lump, but when it did divide, it fell into one group that was more about things originating in the individual actor’s head (choice, motivation, meaning, psychological traits); and another that was more to do with the expectations, pressures, and obligations that come from the way the wider social group is structured (culture, social roles, social pressure, opportunity); in other words, forces that came into the actor from outside, from society.

Figure 1. Network representation of how similar participants viewed different explanations as being. A shorter distance between two explanations means they were viewed as more similar, a longer distance that they were viewed as more dissimilar. The key is: HORmones; GENes; EVOlution; a psychological TRAit; MOTivation; CHOice; MEAning; CULture; social ROLe; social PREssure; CHIldhood experience; and OPPortunity.

What we recovered, perhaps reassuringly, was a set of distinctions that is widely used in philosophy and social science. Our participants saw some explanations as biological, based on sub-personal processes that are not generally amenable to reflection or conscious volition. These were perceived as a different kind of thing from intentional psychological explanations, based on mental processes that the person might be said to have some voluntary say in or psychological awareness of, and be responsible for. These in turn were perceived as somewhat different from social-structural explanations, which are all about how the organisation and actions of a wider network of people (society) constrains, or at least strongly incentivises, individuals to act in certain ways. In other words, we found that our participants roughly saw explanations as falling into the domains of neuroscience; economics; or sociology.

So far, so good. However, it got a bit murkier when we investigated perceptions of compatibility. Philosophers have been keen to point out that although reductionist neuroscience explanations, intentional psychological explanations, and social-structural explanations are explanations of different styles and different levels, they are in principle compatible with one another. They will be, once we have polished off the small task of knowing everything about the world, completely inter-translatable. Every behavi0ur that has an intentional explanation has, in principle, a reductionist neurobiological explanation too. When you privilege one or the other, you are taking a different stance, not making a competing claim about what kind of entity the behaviour is (it’s a perspectival decision, not an ontological commitment). In other words, when you give a neuroscience explanation of a decision, and I give an intentional psychological one, it is not like a dispute between someone who says that Karl Popper was a human, and someone who says that Karl Popper was a horse. Both our accounts can be equally valid, just looking at the behaviour through a different lens.

In our study, we asked a different group of people how compatible all the different types of explanation were, where, we told participants that compatible means both explanations can be true at the same time. The degree of rated compatibility was almost perfectly predicted by how similar the explanations had been rated by the people in the first sample (figure 2). In other words, explanations, for our participants, can only be true at the same time to the extent that they are similar (a norm explanation and a culture explanation for the same thing can both be true; a norm explanation and a hormonal explanation cannot). This is not really normatively right. An explanation for a fatal car accident can be given in terms of the physics (such and such masses, such and such velocities, such and such forces), and also in terms of the intentional actions (the driver’s negligence, the pedestrian’s carelessness, the mechanic’s malevolence). These explanations would be quite dissimilar, but perfectly compatible.

Figure 2. The compatibility of two explanations (rated by one group of people) plotted against the similarity of those two explanations (rated by a separate group).

Our respondents’ incompatibilism, if it turns out to be typical of a wider group of people, could be problematic for science. No more so than in the case of ‘biological’ explanations for human behaviour. These being seen as the most dissimilar from intentional or social-structural explanations, they ended up being seen as rather incompatible with those others. In other words, if you say that XX’s violent outbursts are due to levels of a particular hormone, people perceive you as asserting that it must not be the case that XX is motivated by a genuine sense of moral anger; or that XX has been forced into their position by a lifetime of discrimination. Really, all three things could be simultaneously true, and could be important, but that may not be what people infer. Thus it seems worth stating – again and again, even if to you this feels obvious – that studying the neurobiological or evolutionary bases of something does not mean that the intentional level is irrelevant, or that social factors cannot explain how whatever it is came to be the case. We scientists usually see these different levels as all parts (more accurately, views) of the same puzzle; but certain audiences – many, perhaps – might see giving an explanation at a different level as more like claiming that the jigsaw puzzle is actually a chess set.

What is going on when researchers choose one kind of explanation rather than another? For example, what is at stake when we say ‘depression is a biological condition’? If what I have said about explanations being in-principle inter-translatable is true, then depression is a biological condition, but no more so than supporting Red Star FC, or having insufficient money to pay the rent, are biological. Depression is also a psychological condition, and also a social-structural one. Everything is an everything condition. In other words, ‘depression is a biological condition’ ought to assert precisely nothing at all, since explaining biologically is no more than a stance, a stance that can be taken about anything that happens to humans. The subset ‘biological’ conditions is the whole set, and perfectly overlapping with the set of psychological and social ones.

Yet, when people say ‘depression is biological’, they often seem to think they have asserted something, and indeed are taken to have done so. What is that thing?

When you choose to advance one type of explanation rather than the other, you haven’t logically ruled anything in or out, but you have created a different set of implicatures. You are making salient a particular way of potentially intervening on the world; and down-grading other possible ways of intervening. This comes from the basic pragmatics of human communication. Explanations, under the norms of human communication, should be not just true, but also relevant. In other words, when I explain an outcome to you, I should through my choice of words point you to the kind of things you could modify that would make a difference to that outcome. (Causal talk is all about identifying the things that could usefully make a difference to an outcome, not all of the things that contributed to its happening. When I explain why your house burned down on Wednesday, ‘there was oxygen in the atmosphere on Wednesday’ is a bad explanation, whereas ‘someone there was smoking on Wednesday’ is a good one. )

So, when I say ‘depression is a biological disorder’, I am taken to mean: if you want to do something about this depression thing, then it is biological interventions like drugs that you should be considering. And thus, by implication, depression is not something you can best deal with by talking, or providing social support, or increasing the minimum wage. Choosing an explanatory framing is, in effect, a way of seizing the commanding heights of a debate to make sure the search for remedies goes the way you favour. This is why Big Pharma spent so many millions over the years lobbying for psychiatric illnesses to be seen as ‘biological disorders’ and ‘diseases of the brain’ (all those findings and books about that you read in the 1980s and 1990s – they were basically Big Pharma communications, sometimes by proxy). This sets the stage for thinking more meds is the primary way of thinking about the suffering in society. We found some evidence consistent with this in our study: when we provided a ‘biological’ explanation for a behaviour, participants spontaneously inferred that it would be hard to change that behaviour, and that drug-style interventions were more likely to be the way to do it successfully.

The hostility of social scientists to ‘biological’ explanations is somewhat legendary (in fact, like a lot of legends, it’s common knowledge in some vague sense but a bit difficult to really pin down). When social scientists say ‘X [X being morality, literature, gender roles, or whatever] cannot be explained by mere biology!’, what they mean to say is not: ‘I deny that the creatures doing X are embodied biological creatures causally dependent on their nervous systems, arms, and feet to do it.’ What they are saying is something much more like: ‘I am worried that if you frame X in terms of biology, the debate will miss the important ways in which social-structural facts, or deliberate reasoning processes, have actually made the key difference to how X has come out.’ And perhaps: ‘I am particularly worried that couching X in biological terms will lead all kinds of people to assume that X must always be as it is, and could not be re-imagined in healthier ways.’ Hence, as sociologist Bernard Lahire recently put it: ‘to get too close to biology in the social sciences is to risk being accused of naturalising the current social world, of being conservative.’ In effect what social scientists are saying is not, the biology stuff is not true, but that it is not the most relevant stuff we could be talking about.

A very similar point applies to the argument between rational-choice approaches and social-structural ones. You know the old quip: economics is all about how people make choices, and sociology is all about how they have no choices to make. Essentially, critics of rational-choice economics are not saying: ‘I deny that X came about because lots of people did one thing rather than something else they could have done, and this is causally due to their agency and relative valuations of the various courses open to them’. They are saying something more like ‘I am worried that by focussing on the choice processes of the individuals involved, we will neglect the broader social configurations and institutions that are responsible for the fact that the options they had to choose between were all bad ones’; or, ‘I am particularly worried that by invoking the language of choice, the only interventions we will end up thinking about are information-giving and silly nudges, not reforming society so people have better opportunities in the first place’ (for a big debate on this topic, see here).

What to do? Fortunately, the implicature that a adopting biological framing means the appropriate level of intervention is pharmacological is a defeasible one (on defeasible and non-implicatures, see here). That is, it will be assumed to be true, unless the contrary is specified. You can, without contradiction, say: ‘depression is a biological condition, but it turns out that the best way to reduce its prevalence is to improve the social safety net, because it is brought on by poverty and isolation’. As it turns out, you not only can say this; you need to.

Treating causes, not symptoms

Yesterday saw the launch of our report ‘Treating causes not symptoms: Basic Income as a public health measure’. The report presents the highlights of a recently-ended research project funded by the National Institute for Health and Social Care Research. This has been an interdisciplinary endeavour, involving policy and political science folk, health economists, behavioural scientists, community organizations, and two think tanks.

The public has Manichean intuitions about health. On the one hand, people feel very strongly that an affluent society should compensate and protect its members against the spectre of ill health. This is particularly true in the UK with its strong tradition of socialized care. They will support spending large amounts of money to make good health inequalities. But when you suggest that the best way for society to make good health inequalities is by removing the poverty that lies upstream of them, people often baulk. You can’t do that, surely?

I think there are a few reasons for this reaction. One is that different lay models of causation govern the two domains. Ill health seems to be all about luck, the kind of luck society should insure us against. No one sets out to get ill. Poverty seems, perhaps, to be more about character, effort and intentional action, and hence is a domain where people generally feel that individuals should fend for themselves. If there were financial handouts, some people (it is feared) would set out to live off them; but no-one suggests that because the hospitals are free, people set out to become ill and live in them. In reality, the differences between the domains of health and wealth are not so clear: health outcomes reflect character and choices as well as luck and circumstances; and financial outcomes involve a lot of luck and structural barriers as well as effort. So, some difference in kind between the two domains is not a sufficient reason for limiting policy interventions to just one of them.

Another reason for resistance is that people assume that the cost of reducing poverty is so enormous that trying to intervene at that level is simply unfeasible. Clearing up the mess we might just be able to afford; but the price tag of avoiding the mess in the first place is astronomical. It’s not clear that this is right. If reducing poverty is expensive, not reducing it is really expensive too. Already, around 45% of UK government expenditure is on the National Health Service. That direct cost is so high because the population is so sick. As well as the illnesses that need treating, there is all the work that people cannot do due to ill health. A quarter of working-age adults in the UK have a long-standing illness or condition that affects their productivity. Many of these involve stress, depression and anxiety, conditions where the income gradient is particularly steep.

These considerations raise at least the theoretical possibility that if we reduced poverty directly – via cash transfers – there might not have to be a net increase in government spending. Yes, there would be an outlay. But on the other hand, health would improve; healthcare expenditures would go down; the cost of cleaning up other social pathologies like crimes of desperation would be reduced; people would be more productive; and hence tax takes would increase. And, as I have long argued, there would be a double dividend. As we reduced people’s exposure to the sources of ill health that they cannot control, they would spontaneously take more interest in looking after themselves in the domains they can control, because it would be more worth their whiles to do so. Eliminating poverty is an investment that might not just be affordable, but even profitable.

It’s all summed up in figure 1 (yes, you can tell I am becoming a real social scientist, I have a barely-legible diagram with lots of boxes and many arrows between them). Reducing poverty hits the social determinants of health. It’s cleaning the stream near its source. Downstream, the individual determinants of health are improved; downstream of that, there are better health outcomes; and downstream of that, all the social and economic benefits. Depending on the costs, and on the strengths of the various connections, there might be cash transfer systems that would pay for themselves.

Figure 1. Direct and indirect economic effects of basic income.

This is the possibility that the NIHR funded us to model. That they would do so gives you some indication of the health crisis times we are living in. The NIHR is a hard-headed funder whose mission is to get the best possible cost-benefit ratio for the UK healthcare pound. Even they – hardly utopian or politically radical by mission – can see that paying for ever-better sticking plasters might not be the only course worthy of serious consideration.

To chunk through the net consequences of a cash transfer scheme as per figure 1 involves a lot of estimates: estimating the effect of the scheme on the distribution of household incomes; estimating the effects of household income on physical and mental health; and estimating the effects of better physical and mental health on economic behaviour and tax revenues. Each of these steps is full of uncertainty of course. It’s been a privilege to work alongside my health economics colleagues who have made serious attempts to estimate these things, as best they can, based on data. There were some things we were not able to estimate and made no attempt to include in the models. For example, I suspect that making people’s lives more predictable, as you would with a basic income, has a positive health value above and beyond the actual amount of income you give them. This is not factored into the calculations. Neither is the likely reduction in crime, and hence in the fear of crime. Thus, if anything, I think our estimates of potential benefits of reducing poverty are pessimistic.

I urge you to have a look at the report to see whether you find the case compelling (and there are more detailed academic papers in the pipeline). We consider three scenarios: a small basic income of £75 a week for adults under 65, with the state pension for over 65s staying as it is now; and then a medium scheme (£185) and a generous scheme (£295). I will focus here on the small scheme since the results here, for me, indicate what a no-brainer this kind of action is. Our small scheme is already fiscally neutral, with just some small changes to tax, means-tested benefits and national insurance. In other words, this scheme would cost the government nothing even without factoring in the population health benefits. Yet, it would be redistributive, with 99% of the poorest decile of households increasing their incomes by more than 5%. And because the poorest households are the ones where there is most ill health, its benefits would be dramatic despite its modest size.

Our model suggests that the small basic income scheme could prevent or postpone 124,000 cases of depressive disorder per year, and 118,000 cases of physical ill-health. The total benefit to UK population health is estimated at 130,000 QALYs per year.  The QALY is a somewhat mysterious entity beloved of health economists. Very roughly, we can think of one QALY an additional year of perfect health for one person, or two extra years in a state of poorer health that they value only half as much. So, if 130,000 people, instead of dying, lived a year in perfect health, then 130,000 QALYs would be gained. That’s a lot. The department of health values a QALY at £30,000 for cost-benefit purposes. That is, if you want to be hard-headed, then it’s worth paying up to £30,000 to achieve an extra QALY of population health. That means it would be worth paying £3.9 billion a year for our basic income scheme, if it were to be evaluated as purely a health policy (imagine it, for example, as a drug, or a type of physical therapy). As I have already stressed, the scheme is fiscally neutral: it costs the government no more than the current system of taxes, allowances, and benefits does. The scheme is, arguably, a healthcare intervention worth £3.9 billion, available today at zero cost using only technologies that already exist. The predicted health benefits of the medium and generous schemes were much larger still; but of course, their upfront cost is larger too.

Naturally, there are many uncertainties in an exercise such as this. We took the observed associations between income and health as causal, assuming that if you boosted income, health would follow. This is an inference, and a contentious one. The way we made it – by looking at within-individual health changes when income declined or increased – is probably about the best way currently possible. But, its validity is something reasonable people could dispute. For me it brings home the serious need for proper trials of cash transfer policies, something we have written about elsewhere. Then the causal basis of the projections could be much stronger. Even accepting the limitations though, I think the case is hard to ignore. This project has made me feel more strongly than ever that there are better societies out there, in a galaxy not at all far from our own; and that we lack only rational and imaginative leaders to guide us there.

On poverty and addiction

Reading descriptions of the lives of people living in adverse economic conditions, something that will strike you over and over again is how often addiction comes up: to alcohol, to tobacco, to other drugs, or to behaviours such as gambling. There is addiction in all strata of society, but, from the novels of Zola to today, it seems specially prevalent where people have the least access to money and power. Is this really true, and, if so, how could we possibly explain it?

Epidemiological evidence confirms that it is really true. In the USA, the prevalence of smoking is about twice as high amongst those in routine/semi-routine occupations compared to managers and professionals. Smokers of all classes try to quit; managers and professionals are more likely to succeed. Addictive substances often show double dissociations with class: people with more money can afford to consume more of the substance, since they have more money; but people with less money are more likely to end up consuming to the point where it causes them life problems. So, for example, higher-SES young people in France consume more cannabis overall; but lower-SES young people are more likely to be frequent users. The double dissociation is particularly clear for alcohol. In many studies, it is people of higher SES who consume more alcohol on average, but people of lower SES who are most likely to die from the consequences of alcohol. As for behavioral addictions, the companies that run gambling machines know where to put them: in the areas of the highest economic deprivation.

Yes, addiction is related to poverty. But so are many other things. The existence of socioeconomic gradients is such a pervasive feature of affluent societies that it extends to almost everything you can measure. Is addiction more steeply related to income than other things? The only evidence for this that I have been able to find comes from the study of alcohol-related mortality. People of lower SES are more likely to die from the consequences of alcohol; but of course they are more likely to die tout court. Probst et al. meta-analysed studies that compared the SES difference in alcohol-attributable mortality to the SES difference in overall mortality in the same populations. They concluded that the high-low SES differences in alcohol-related mortality were typically 1.5-2 fold larger than the high-low SES differences in mortality overall.

Let’s assume that these gradients reflect something about poverty causing increased addictive behaviour (not of course an easy thing to demonstrate, but I’ll come back to that at the end). How can we explain why?

First, we need to characterise what kinds of substances and activities can create addiction. Jim Orford, in his wide-ranging book Power, Powerless and Addiction suggests that things can be addictive if they (a) have the capacity to produce a short-term boost in mood; (b) they can be consumed frequently in small chunks; and (c) they entrain processes that tend to increase their own consumption over time. If you focus on (a) and (b), the socioeconomic gradient seems very intelligible. In the flow of everyday experience, people facing greater economic adversity are often in worse mood (there is abundant evidence that this is true, and there are good reasons for it); and, plausibly, they have less access to alternative mood-boosting inputs that come with affluence and high status.

There are other bodies of thought we can draw on to fill out this idea. There is the ‘rational addiction’ tradition that comes from economics. The essence of this idea is that people might, under some circumstances, choose to consume an addictive substance, even in the full knowledge that this will lead to future dependence. They will do so when it maximises their long-term utility; in other words when the value they place on all the mood boosts they will get outweighs the disutility of the present and future costs of use. The literature on rational addiction has got a bit bogged down in some rather inside-baseball issues, such as whether people reduce consumption in response to price rises that have been announced but not implemented yet. This is an important test because it establishes whether they are considering future consumption, not just present consumption, in their decisions to consume; but it distracts from the more general insights the rational addiction model might provide.

As often with rational actor models, the rational addiction model seems like a kind of useful fiction. On one hand it is obviously false. People usually don’t make those computations, certainly not explicitly. Plus, the rational addiction model in its original form cannot account for the fact that people constantly try to quit, often without success; or that they spend money on having other people force them to stop them from consuming . To explain these phenomena, you need to add something call time-inconsistent preferences, namely that what I value happening at time point t flips as t approaches the present. On the other hand, the rational addiction model is many-fold better than unhelpful and non-explanatory appeals to ‘lack of self-control’ or ‘the culture of poverty’. It sees people who consume as full and normal agents, albeit agents constrained by the option sets available to them. Those option sets are often not great. In poverty, either the marginal benefits of addictive consumption might be higher (because your mood is often worse and this makes it boosting it more valuable), or the opportunity costs of addictive consumption are lower (for example, the job you could lose is awful anyway, or there is no prospect of ever converting the cigarette money into owning a house).

A related and useful literature is that on pain and analgesia. Addictive substances tend to be analgesic: they reduce pain. Much of the drug addiction in the USA and other developed countries involves opioid drugs. These are so effective at pain relief that they have long been used in surgery. Indeed, it was their approved medical use that lies at the root of the iatrogenic addiction crisis. What is less well known is that alcohol, nicotine and cannabis all have fairly well-studied analgesic effects. It is not a metaphor when people say they drink or smoke to ease the pain.

Pain is socioeconomically distributed. There’s evidence of socioeconomic gradients in severe pain in Austria, and dental pain in the UK. Physical pain and emotional pain are on the same continuum (anti-inflammatories like ibuprofen reduce depressive symptoms after all), and I wager that emotional pain shows at least as much of a gradient as physical pain does, probably more. Studies conclude that the socio-economic gradient of pain is currently unexplained; but perhaps, in fact, its explanation is all too obvious. Pain is the unpleasant experience associated with the appraisal that you are being damaged. The ability to feel pain is there for a reason. If you can get out of the painful situation, you will. But if you have no alternative but to go on being damaged, then self-medication looks like the next best thing.

If poverty causes pain and low mood, then really there is no mystery to the fact that people in poverty rely more heavily on mood-boosters. Property (c) of addictive substances – they catalyse their own use – is still a problem. But you can see why it is easier to start and more difficult to stop if you face poverty and adversity. This leads to the simple prediction that increasing people’s incomes will reduce their consumption of analgesic-addictives.

What I love about this prediction is how counter it runs to most people’s intuitions. When Nicaragua introduced an direct cash transfer programme, a senior official predicted that “husbands [would be] waiting for wives to return in order to take the money and spend it on alcohol“. A brake on the introduction of cash transfers in Kenya was “the widespread belief that cash transfers would either be abused or misdirected in alcohol consumption“. Does the evidence back up these intuitions?

Reader, it does not. For the World Bank, David Evans and Anna Popova reviewed all the studies that they could find looking at the impact of a change in income on either consumption of or expenditure on alcohol and tobacco. They concluded that “almost without exception, studies find either no significant impact or a significant negative impact of [cash] transfers.” Restricting the analysis to the 17 estimates that came from randomized control trials, 14 went in the negative direction, and the 3 in the other direction were small. It’s worth thinking about how strong a test this is. Some people, who were generally in low and middle income countries and had strong financial constraints, were suddenly given higher incomes to spend. It’s not just that they did not use it to increase their expenditure on these addictive goods. They more often than not decreased it. Doing social science, I have heard it said, is the search for the small set of things that is both surprising and true. I would add, surprising, true, and makes a difference. It would be good if this were one of that set.

Innateness is for animals

Innate or acquired? Genes or culture? Nature or nurture? Biological or psychological? People are inveterately fond of trying to divide human capacities into two sorts. Commentators often seem to think that determining which capacity goes in which box is the main preoccupation of the evolutionary human sciences. (And because there is ‘evolutionary’ in the name, they think the evolutionary human sciences must be about claiming capacities for the innate/genes/nature side that the social sciences had wanted to put in acquired/culture/nurture; not really.)

In fact, innate/acquired, nature/nurture sorting is not something most of us are especially interested in. Our main hustle is that it is always both, rendering the distinction (at least as applied to mature adult capacities) somewhere between arcane and unhelpful. If it’s acquired, it’s because there are innate resources that make this possible; if it’s culture, it’s because the human genome enables this possibility, and so on. We are not interested in sorting, but in figuring out how and why things actually work. To butcher the famous exchange from The African Queen: the nature/nurture distinction, Mr. Allnut, is what we are put in this world to rise above.

But still, the widespread desire to sort capacities into two kinds persists. Why? Philosophers who have examined the problem agree that the innate/acquired dichotomy, and its companion nature/nurture, are folk or lay concepts: distinctions didn’t originally arise from formal scientific enquiry, and lack clear definitions in most people’s minds. Many but not all scientific constructs begin life as folk concepts: ‘water’ did, for example, but ‘the Higgs boson’ did not. Folk concepts can go on to give rise to useful scientific concepts. There is genuine debate in philosophy about whether a useful scientific concept of innateness can be constructed, and if so what it should be (see e.g. here and here). But regardless of how this debate is resolved, we can ask where the folk concept of innateness comes from and how people use it.

In a new paper, I argue that the folk concept of innateness is made for animals. More exactly, we have a specialized, early-developing way of thinking about animals (this way of thinking is sometimes known as intuitive biology). The folk concept of innateness comes as part of its workings. When we think about animals, we are typically concerned to rapidly learn and make available the answers to a few highly pertinent questions. First, what kind is it? Second, what’s the main generalization I need to know about that kind (will it eat me, for example, or can I eat it)? The cognition that we develop to deliver these functions is built for speed, not subtlety. It assumes that all the members of the kind are for important purposes the same (if one tiger’s dangerous, they all are), and that their key properties come straight out of some inner essence not modifiable by circumstance (doesn’t matter if you raise a tiger with lambs, it’s going to try to eat them sooner or later). When people (informally) describe a capacity as ‘innate’, part of our ‘nature’ and so on, what they mean is just this: the capacity is typical (it’s not just the one individual that has it, but the whole of their kind), and fixed (that capacity is not modifiable by circumstance). In other words, they think about that capacity the way they think about the capacities of animals.

Unfortunately, animals are not really like this. In fact, in animal species, individuals are different from one another, and far from interchangeable. This is so counter most people’s perceived experience that Darwin had to spend dozens of pages in the first part of On the Origin of Species convincing the reader that it was the case, since variation was so crucial to how his idea of natural selection worked. Moreover, animal behaviour is actually very strategic and flexible: it could well be that by raising your tiger differently, you end up with a very differently-behaving beast. But, intuitive biology is not there to make us good zoologists. It’s there to make us eat edible things and not get eaten by inedible ones.

The idea that the folk concept of innateness is part of intuitive biology is not new. All my paper does is to test some obvious predictions arising from it. Working with UK-based non-academic volunteers, I found that how ‘innate’ people reckon a capacity is in humans is almost perfectly predicted by the extent to which they think other animals have it too (figure 1A). If you present people with the same capacity possessed either by an animal or a human, they think it is more likely to be innate in the animal case (with a huge effect size; figure 1B). And, even, if you tell people about an alien creature and tell them that one of its capacities is innate, they imagine that alien as less human-like than if you tell them that it had to learn its capacity, or tell them nothing at all (figure 1C). So, there is a special connection between ‘X being an animal’ and ‘X’s capacities seeming ‘innate’’.

Figure 1. Some results from my studies. A. People think a capacity is innate in humans to the extent they also think it is present in other animals. B. People think the same capacity is more likely to be innate when it is found in an animal than a human. C. People think an alien is less human-like if they are told that one of its capacities is innate than if not told this.

If innateness is for animals, then we should intuitively think the capacities of humans are not innate. Indeed, several studies have shown that lay people have this prior (here and here). This is because our dominant mode for thinking about people is quite different from our dominant mode for thinking about animals. With other people, we are generally trying to manage some kind of ongoing, individual-to-individual dynamic relationship, for example of collaboration or competition. To be able to do this, you need to track individual persons, not kinds, and track what they currently know, believe, possess or are constrained by, not rely on a few context-free generalities. In other words, when we think about people (for which we use intuitive psychology), we naturally incline to thinking about what is idiosyncratic, thoughtful and contingent. Whereas for animals we pay insufficient spontaneous attention to their uniqueness and context, for humans we only pay attention to that. This sense of the idiosyncratic, the thoughtful and the contingent is what people seem to mean when they talk informally about behaviours being not innate, not in the genes, not biological and so on.

However, my participants readily assented that some capacities of humans were innate, capacities like basic sensing, moving, circadian rhythms, and homeostatic drives like hunger and thirst. These are the things about humans that you can still think about using intuitive biology: the capacities of humans qua animals. They are not the things that affect the depth of a friendship or the bitterness of a dispute; the things about people qua social agents. We tend to view other people as dual-aspect beings, having basic, embodied animal features, and complex, idiosyncratic person features; we think about these, respectively, with intuitive biology and intuitive psychology. We kind of know that these are two aspects of the same entity, but the link between the two aspects can go a bit screwy sometimes, leading to beliefs in dualism, ethereal agents, souls that leave bodies, and other shenanigans. What is often odd and jangling for people is when the language of animal bodies (genes, evolution and so on) is used in explanations for the capacities of individual people as social agents (their knowledge, decisions, and morality). That feels like it can’t be right.

This is rather a problem for researchers like me, who believe that our embodied natures and our capacities as social agents have rather a lot to do with one another (indeed, are descriptions of the same thing). If you talk about an evolved, innate or biological basis to human moral and social capacities, your audience may take you to be saying something quite different from what you intend. Specifically, you make be taken as wanting to reduce humans to beasts; to deny the critical influence of context; or to argue that human social systems must always come out the same. None of these actually follows from saying that a capacity has an evolved, innate or biological basis. It’s the folk concepts bleeding through into the scientific debate. And folk concepts, Mr. Allnut, are what we are here to rise above.