Bayesianism vs scientism

There is an unfortunate divide in the rationalist tribe between Bayesians and believers in scientism. Bayesians are those who rationally incorporate all sources of information when choosing what credence to have in different propositions. You have prior credences that are set by common sense, theoretical arguments, empirical information and so on. You then update from those priors with new information, whether that is from personal observation, social science, theory or whatever. Believers in scientism in contrast form their beliefs by putting lots of weight on published scientific evidence over other types of evidence.

I think scientism is the wrong approach and can be costly. It is also among the leading reasons not to defer to the scientific establishment on some key questions; it is a case where the requirements of epistemic modesty are not as they might appear. A lot of experts with comprehensive knowledge of the scientific literature have the wrong epistemology and oftentimes, for that reason, we shouldn’t defer to them. I will illustrate this with examples.

Masks

The Bayesianism vs scientism cleavage has played out recently in the disagreement between experts about the efficacy of face masks. Some experts have come out strongly in favour of masks, whereas some have cast doubt on their efficacy. For example, in August, a Swedish epidemiologist said:

“Mr Ludvigsson noted that in a meta-analysis by the WHO of 29 studies that showed face masks were effective, only three concerned their use outside hospitals and of those that did not none involved Covid-19.”

This is a paradigmatic scientistic attitude. Mr Ludvigsson casts doubt on whether masks work outside hospitals and for covid because there haven’t been any studies testing them outside hospitals and for covid. The Bayesian approach, in contrast, would update on the information from all of the studies, even though the context is not exactly the same in the studies as what is being proposed now. 

They would also take into account the basic science of viral transmission, and use common sense. We know that covid spreads via droplets that are released from the mouth or nose when an infected person coughs, sneezes, or speaks. People can catch covid when those infectious droplets get into their mouth, nose or eyes. This is where common sense kicks in: if you put a mask in the way of the droplets from my mouth or nose, then that makes it less likely that the droplets will get from my mouth or nose into yours. We even have video footage of masks doing the blocking.

Even if masks have only been tested for influenza and not covid, we still understand the mechanism by which they work – droplet blocking. If they work for influenza, which spreads in the same way as covid, then they will very likely also work for covid. 

The scientistic view is that to know whether we should recommend that people wear masks in enclosed spaces like shops, buses and the tube, we would need to have a high-quality study (preferably an RCT) of that exact thing. However, that exact thing can never be done twice. Any intervention that we impose will be different in some way from the version of the intervention that has been tested. 

To illustrate, consider this dialogue:

Scientism: Ok, we have the evidence: masks work on buses. 

Bayesian: Great! One thing – all the masks you tested were blue. Do yellow masks work?

Scientism: Well, we didn’t study that, but of course yellow masks work.

Bayesian: How do you know if you didn’t study it?

Scientism: There is nothing about yellow masks that would make them not work if blue masks work – colour is irrelevant.

Bayesian: Do you have a scientific study showing that colour is irrelevant?

Colour is indeed irrelevant. The argument for this is that the colour of the masks is not going to have an effect on the mechanism by which the mask works, which is blocking droplets. Knowledge of the mechanism of transmission tells us the results will generalise to yellow masks. But this argument is not available to scientism. 

This is why the experts have disagreed about masks. World-leading experts have got this one wrong, and it is down to their mistaken scientistic epistemology. Unusually, someone who just relied on sturdy common sense would be more likely to be right than an expert who knew the whole scientific literature really well but assimilated it in a scientistic way. 

The minimum wage

I am going to preface this by saying that I am in favour of more redistribution – I am opposed to the minimum wage because it is bad for low-skilled people. Economics 101 states that if you introduce a minimum wage, employers will demand less labour – they will lay people off or demand fewer hours from them. If you think the demand curve for labour slopes downwards, then a minimum wage will cause firms to economise on labour.

In spite of this, as this IGM poll shows, there is active disagreement among leading economists about whether minimum wages will make it harder for the lower paid to find work:

Some of the experts’ answers are influenced by how interpret the term ‘noticeably’, but others justify their arguments with scientistic claims, such as 

  • “I’m not aware of any strong evidence demonstrating this result.” (David Autor)
  • “The empirical evidence now pretty decisively shows no employment effect, even a few years later. See Dube, Lester and Reich in the REStat” (Michael Greenstone)
  • “Yes, I know the Econ 101 answer but the evidence suggests the effect on employment is between small and 0.” (Richard Thaler)

These statements suggest that one’s view of the minimum wage should be determined by what the median study finds about the effects of the minimum wage. But really when we are assessing this claim we need to consider economic theory, common sense and all the other evidence that demand curves for labour slope downward. Here is Bryan Caplan on the strength of the case from economic theory and common sense:

“In the absence of any specific empirical evidence, I am 99%+ sure that a randomly selected demand curve will have a negative slope. I hew to this prior even in cases – like demand for illegal drugs or illegal immigration – where a downward-sloping demand curve is ideologically inconvenient for me. What makes me so sure? Every purchase I’ve ever made or considered – and every conversation I’ve had with other people about every purchase they’ve ever made or considered.”

He goes on to argue that empirical evidence from other parts of economics should also update us towards minimum wages having a disincentive effect. This includes

  • The literature on the effect of low-skilled immigration on native wages. The strong consensus is that high levels of low skill immigration have little effect on native wages. This implies a near horizontal demand curve for low-skilled labour. 
  • The literature on the effect of European labor market regulation, which shows that regulations that increase the cost of hiring people causes high unemployment in Europe. 
  • The literature on Keynesian macroeconomics. Keynesian macroeconomics suggests that nominal wage rigidity causes short-term unemployment. This makes it highly likely that government-imposed wage rigidity causes unemployment. 
  • The literature on the effects of price controls, on rent, energy and agriculture, which bolster the textbook story of price floors. 

On this last point, Caplan makes a version of the point I made above about masks:

“If you object, “Evidence on rent control is only relevant for housing markets, not labor markets,” I’ll retort, “In that case, evidence on the minimum wage in New Jersey and Pennsylvania in the 1990s is only relevant for those two states during that decade.” My point: If you can’t generalize empirical results from one market to another, you can’t generalize empirical results from one state to another, or one era to another. And if that’s what you think, empirical work is a waste of time.”

The empirical work on the employment effects of the minimum wage is mixed. The majority of studies find a negative effect on employment, but some prominent studies do not. But this is pretty much what we would expect to find if the minimum wage did indeed have a negative effect on employment. Empirical social science research is not very good. Most published research is false. John Ioannidis has found that nearly 80% of the reported effects in the empirical economics literature he studied are exaggerated, typically by a factor of two, and with one third inflated by a factor of four or more. 

Minimum wage studies are especially likely to find false negatives. Studies of the minimum wage usually test the effects of minimum wage levels that are low ($4 – $11) and so they are antecedently likely to find effects that are dotted either side of zero. Moreover, when assessing the effect of the minimum wage, you are comparing a counterfactual to the real world that is affected by innumerable other forces, including every other labour market policy, the plans of literally every business in the area, all other economic forces that could affect a region, etc. Then there is the problem of actually measuring changes in demand for labour properly. So, we have very noisy data measuring a small treatment effect – of course we will find some surprising results, which are very likely false negatives. The rational thing to do is not to update very much.

In advance of examining any evidence about the employment effects of the minimum wage, your prior that it reduces employment should be something like >99%. Upon observing any study showing that the minimum wage does not have an effect on employment, you shouldn’t update much because empirical research is not very good. Caplan establishes this formally here.

A randomista take on UK politics

The table below shows ten headline policies in the 2019 Conservatives and Labour manifestos (Brexit aside), as well as some of my own top picks, in no particular order

ConservativesLabourMe
Increase spending on the NHSA green industrial revolution, including more funding for low carbon technology and more state control of climate and energy policyEncourage clean energy innovation and expand on and strengthen the UK’s mix of flexible regulations and carbon pricing. 
Additional funding of social care and a cross-party resolution on how to improve social careExpansion of public transportRelax restrictions on house building in urban centres, taking planning decisions out of the hands of local property owners. 
School fundingIncrease funding for the NHS and social careIntroduce a land value tax, or common ownership self-assessed tax
Cut national insurance or payroll taxesA national education service to provide lifelong vocational technical and academic educationAbolish stamp duty 
Additional funding for childcareSpend more on policingFund greater tax credits for those on low incomes by increasing income tax on the very wealthy 
Increased funding for the policeIncrease funding of, and devolve power to, local councilsIncreased high skilled immigration 
Measures to cut utility bills Increase the minimum wage and expand employment rights, including a 32 hour week in ten yearsIntroduce responsive road pricing
A points-based immigration systemIncrease legal guarantee of various forms of identity inequalityIncrease funding for public transport, especially in the North. 
Upgrading rail systems in the northScrap universal credit and work to develop a viable alternativeRelax drug laws.
Net zero economy by 2050Large increase in building of social housingEstablish a new government body for socially beneficial high-risk science projects

Now I am going to cross out the policies that have not, in any relevant social context, been tested by a randomised control trial. In bold are the policies that definitely cannot, for practical or ethical reasons, be tested by RCTs.

ConservativesLabourMe
Increase spending on the NHS, building new hospitals and employing more staffA green industrial revolution, including more funding for low carbon technology and more state control of climate and energy policyEncourage clean energy innovation and expand on and strengthen the UK’s mix of flexible regulations and carbon pricing. 
Additional funding of social care Expansion of public transportRelax restrictions on house building in urban centres, taking planning decisions out of the hands of local property owners. 
More funding for schoolsIncrease funding for the NHS and social careIntroduce a land value tax, or common ownership self-assessed tax
Cut national insurance or payroll taxesA national education service to provide lifelong vocational technical and academic educationAbolish stamp duty 
Additional funding for childcareSpend more on policingFund greater tax credits for those on low incomes by increasing income tax on the very wealthy 
Increased funding for the policeIncrease funding and devolve power to local councilsIncrease high skilled immigration 
Measures to cut utility bills, including regulations Increase the minimum wage and expand employment rights, including a 32 hour week in ten yearsIntroduce responsive road pricing
A points-based immigration systemIncrease legal protection of various identity groupsIncrease funding for public transport, especially in the North. 
Upgrading rail systems in the northScrap universal credit and work to develop a viable alternativeRelax drug laws.
Net zero economy by 2050Large increase in building of social housingEstablish a new government body for socially beneficial high-risk science projects

If you were feeling very ambitious, you could test the effect of increased funding for schools and the health service with an RCT – maybe employ the new nurses and teachers in a treatment region and compare to a control region. However, the statistical power of the RCT would not be very good, and even if the whole government became convinced of the value of this, it would be political suicide. 

What becomes clear from performing this exercise is that RCT-evaluable policies are not now, nor will they ever be, where the action is when it comes to the big UK policy questions. The highest impact things one would want to do have not been tested by RCTs and there is no way they could ever be in the future. If we were allocating the effort of economists in the UK, less than 1% of it should focus on things that can be tested by RCTs.

This raises the question – why is so much of the economics profession and philanthropy focused on RCT-evaluable things when their attention turns to low- and middle-income countries? What is the difference between rich and poor countries that makes RCTs the right approach in one context but not another?

Capitalism, markets, greed

This post ties together two other posts I have written on capitalism, markets and morality.

The following things are all different but are often not distinguished properly:

  • Capitalism – The private ownership of the means of production
  • Markets – A system in which buyers and sellers engage in exchange
  • Ethos of selfishness – People have very limited duties to benefit others and have extensive permission to engage in self-interested action.
  • Egalitarianism – Equality of outcome or opportunity for outcome is intrinsically good.
  • Utilitarianism – Everyone’s happiness counts equally, so more count for more.

The pros and cons of all of these things are quite different. Some of these things are foundational ethical theories, some are theories of personal morality, some are evaluations of culture, and some are institutional systems of ownership.

Today, whether one believes in an egalitarian society is predictive of whether one is anti-capitalist, anti-big business, anti-market, anti-ethos of selfishness and anti-bourgeois morality. Also, whether one is pro-capitalist, pro-business, or pro-market is predictive of whether one is pro-ethos of selfishness or pro-bourgeois morality. I think there is room for a more nuanced mix of these beliefs.

Capitalism & Socialism

Capitalism is defined very specifically as the private ownership of the means of production. The main argument for it is that it seems to have played a major role in the greatest increase in human welfare ever over the last 200 years. Moreover, experiments with socialism – extensive public ownership of the means of production – tend to go very badly.

The Labour Party’s Clause IV used to say:

“To secure for the workers by hand or by brain the full fruits of their industry and the most equitable distribution thereof that may be possible upon the basis of the common ownership of the means of production, distribution and exchange, and the best obtainable system of popular administration and control of each industry or service.”

Clause IV was altered by Tony Blair in the 1990s to be focused not on socialism, but on the broader ethical aims of the party. It is at least worth noting that it is a very long walk from the claim that it would be better to have a prosperous and equal society to the claim that Tesco should be taken into state ownership. There seem to be many other ways to achieve the aim of a prosperous and egalitarian society, such as redistribution, free childcare, increased skills training, and so on.

Being a pro-capitalist egalitarian is a live option – this is social democracy.

Going further, I think there are good social welfarist and egalitarian arguments for a common-ownership self-assessed tax, which would not be capitalistic.

Capitalism, big business and markets

Capitalism and big business are different to a market-economy. Firms are not markets. Herbert Simon a thought experiment to make this clear:

Suppose an alien intelligence were to study a strange world with “a telescope which reveals social structures”. Pointed at the Earth, Simon argued, that telescope would show lots of solid green areas with faint interior contours linked by a network of thin red lines. Both colours would be dynamic; new red links would form and old ones perish; some green blobs would grow, others shrivel. Now or then one blob might engulf another.

The green blobs in Simon’s vision were firms and other organisations in which people work; the red lines, market transactions. And if asked what the long-range scanner revealed, the observer would reply “large green areas interconnected by red lines” not “a network of red lines connecting green spots”.

The Economist

In a large company like Amazon or Tesco, decisions are not made by the market mechanism. Rather, the activities of managers and employees are determined by management structures and by algorithms.

Uber is a platform that provides a market for its drivers and riders to buy and sell services on. When demand increases, the price of a ride increases with surge pricing, so drivers are incentivised to provide more rides and consumers are incentivised to reduce their demand. To reiterate, most decisions in firms are not made like this – there is no market system set up to determine who does what project, rather managers or algorithms decide how it is done and who does it.

Conceptually, there could be a market economy that is not capitalist. The common-ownership self-assessed tax is one way this could happen. Under that system, everyone sets a price for all of their property, and they would have to sell if someone bids that price. The higher they set the price, the higher the tax they pay. This would increase market transactions and encourage more accurate pricing of assets, but it would do away with a key feature of private property, which is that you have monopoly rights over what you own – if you don’t want to sell then you don’t have to.

Another non-capitalist market system would be a system of worker-run cooperatives operating in a market economy. Thus, each firm would be owned and democratically run by its employees. The feasibility and scalability of this system is questionable because cooperatives are disincentivised to grow and accept new members.

Moreover, it is again a long walk from the claim that it would be better to have a prosperous and egalitarian society to the claim that we should not use market prices to make investment and production decisions. One could be in favour of a market economy, but also find other ways to realise a prosperous and equal society, such as redistribution, free childcare, skills training, and so on.

Suppose we were thinking about how to distribute cabbage. On the anti-market approach, we would not use prices, but would instead use state planning. A bureaucracy would have to decide how much cabbage was needed in Oxford on a given day, what type of cabbage people wanted, where they wanted to get it from, how they wanted it packaged, and so on. Doing this without feedback from prices is hard.

In a market system, if demand for cabbage rises, then supermarkets in a competitive market increase their prices. This sends a signal to consumers to limit their consumption of cabbage relative to other vegetables. This also sends a signal to cabbage growers to increase their production of cabbages to meet demand. This kind of information is lost in the absence of market prices.

An ethos of selfishness

Many people in rich Western societies think that their moral responsibilities are heavily circumscribed. Provided people stick to the rules and look after their family, any benevolent acts are purely supererogatory. I think the ethos of selfishness is wrong and that people in fact have quite extensive duties of benevolence. However, this is completely conceptually distinct from one’s assessment of the value of markets and capitalism.

Indeed, I think it is plausible to be pro-market and pro-capitalism but also in favour of extremely stringent duties of benevolence that require thoroughgoing self-abnegation.

The UK economy since 1980

A lot of the attention people put into following the news would be better directed at assessing long-term trends. The example I look at in this post is the key underlying facts about the UK economy, which I don’t think most people know very well, sometimes because they get distracted by noise. Overall, things have been going quite well.

Growth and inequality

Economic growth has been pretty healthy over the last 40 years, with average real incomes doubling over that time, and a clear acceleration in the trend in growth after 1980

It is less well-known that on most measures, inequality has been pretty flat since 1990, and the bottom 10% of earners have seen pretty good income growth, especially from 1990 onwards, with incomes increasing by about 60%. The picture that emerges is one of a rising tide lifting all ships:

The Gini coefficient – one measure of inequality has also been pretty flat since 1990

These measures of inequality are all after taxes and transfers, so they account for the effects of redistribution, which increased after Labour took power in 1997.

Unemployment

Unemployment in the UK has also been consistently low, below many of our European neighbours.

Saving lives vs saving the economy

As COVID-19 tore through China, Iran, Italy and Spain, killing thousands of people and overwhelming health systems, governments across the world took the extraordinary step of imposing lockdowns, which remain in place in many countries today:

The lockdown has created huge economic costs, with unemployment in the US now the highest it has been since World War 2. This has led many people to ask – at what point do the economic costs of the lockdown stop being worth it? When does the cure become worse than the disease? To answer this, we need some way to compare health costs with economic costs. 

Some people find such comparisons distasteful, arguing that we should never let people die merely for the sake of the economy. Views such as these effectively give saving lives infinite weight, but this leads to counterintuitive conclusions. For example, in our day-to-day lives, we all impose small risks of death on others through mundane tasks such as driving. But if death has infinite weight, then driving must always be wrong. Moreover, it is important to recognise that “the economy” is not an inanimate thing, but something that has important effects on people’s wellbeing, for example by providing employment prospects and income.  

How, then, can we resolve the awful trade-off between lives and the economy?

What is your life worth, statistically?

One popular approach in economics is to try to convert all the costs and benefits into money. When doing this for lives, we can use what is known as the ‘Value of a Statistical Life‘. Rather than asking people what they would pay to avoid certain death (presumably infinite), we ask them how much money they would accept in exchange for an increase in risk of death. Suppose someone is willing to take an extra $1,000 for an additional 1-in-10,000 risk of death by working as an ice road trucker. If 10,000 truckers are each paid to take on that added 1-in-10,000 risk, then the “expected” number of deaths (expected in a probabilistic sense, that is, the probability of death multiplied by the number at risk) is 1. So economists multiply that $1,000 by 10,000 workers to get the “Value of a Statistical Life.” The result: $10 million. This, the argument goes, is what the US government should be willing to pay to save a life. 

Although popular, the Value of a Statistical Life is subject to numerous problems. 

Firstly, the Value of a Statistical Life implies that whether governments happen to know who will be killed by a policy makes a vast difference to the costs and benefits of that policy. Suppose a government is faced with two options:

A. Introduce a pollution regulation that produces $10 billion in economic benefits but with certainty will kill 100,001 people, but we don’t know who they are.

B. Introduce a pollution regulation that produces $10 billion in economic benefits, but will definitely kill one person – Brian. 

Since Brian’s willingness to pay to avoid death is infinite, the Value of a Statistical Life implies that A is better than B, even though it kills 100,000 more people, which is clearly wrong. One way to avoid this is to say that only risk of death, rather than death itself, is valuable, but this is the opposite of the truth. 

Secondly, there is lots of evidence that people are poor at thinking about small probabilities. Many-fold decreases in the chance of harm do not produce proportionate decreases in people’s willingness to pay to avoid it. It is, therefore, not clear why we should let these judgements determine governments’ life-and-death decisions. Moreover, the values produced by this method are highly sensitive to people’s wealth and to the options they have to choose from. Charles Koch’s willingness to pay for personal safety is much higher than a 25-year-old farmer in Ohio, but that doesn’t mean his life is worth more than the farmer’s, it just means he has more money. 

In light of these and other methodological issues, it is not surprising that studies using similar methodologies have set the value of a statistical life as low as $100,000 and as high as $76,000,000.

This suggests that the value of a statistical life approach is fraught with problems.

Wellbeing analysis

The value of a statistical life tries to make health and money comparable by converting health costs to money. A more promising approach is wellbeing analysis: we compare health and monetary costs in terms of their effects on wellbeing. In other words, we should figure out the effects on wellbeing of saving lives, and the effects on wellbeing of avoiding economic problems such as unemployment and reduced consumption. We can measure and compare these costs using what are known as Wellbeing-Years (WELLBYs). 

WELLBYs recognise that wellbeing is dependent on quality and quantity of life. If someone dies prematurely, then they miss out on the good things in life. Other things equal, it is worse for a 40-year-old to die than an 85-year-old because the 40-year-old will miss out on more of the good things in life. WELLBYs also track quality of life. Fortunately, there is now a voluminous literature on the effects of different life events on wellbeing, such as unemployment, loneliness, divorce and so on. Average wellbeing in the UK is 7.5 on a 0-10 scale, and we have lots of data on how external events can push people up or down this scale. 

Richard Layard and other economists have put wellbeing analysis to use in their paper ‘When to release the lockdown‘. Releasing the lockdown would have various positive effects on wellbeing, including:

  1. Increasing people’s incomes now and in the future. 
  2. Reducing unemployment now and in the future. 
  3. Improving mental health and reducing suicide, domestic violence, addiction and loneliness. 
  4. Restoring schooling. 

On the negative side, releasing the lockdown 

  1. Increases the final number of deaths from the virus (as well as from other conditions which may get undertreated if health services become overstretched with COVID-19 patients). 
  2. Increases road deaths, commuting, CO2 emissions and air pollution. 

To see how WELLBYs work, take the example of income. The literature in psychological science suggests that a 1% gain in income increases wellbeing by 0.002 points. Layard et al. argue that if we release the lockdown in June rather than July, income will decline by 5.1% as a percentage of annual income. The effect on wellbeing for each person of this is therefore 5.1*0.002. Spread across the whole UK population of 67 million, this is 663,000 WELLBYs.

Against this, we have to balance the costs to health of releasing the lockdown. Layard et al. argue that each extra month of lockdown saves 35,000 lives from COVID-19. They argue that since COVID-19 disproportionately affects the elderly, each person saved would otherwise live another 6 years on average (at wellbeing level 7.5). So, each extra month of lockdown saves 1.5 million WELLBYs (35,000*6*7.5). Given some probably debatable assumptions, Layard et al. estimate that the net costs and benefits of the lockdown break down as follows:

Net benefits of releasing the UK lockdown on the stated date rather than in May (in WELLBYs, 10k)

June 1July 1Aug 1
Benefits
Income-48-114-200
Unemployment-79-161-245
Mental health-20-43-69
Confidence in government-9-22-44
Schooling-5-10-13
Costs
COVID-19 deaths158316474
Road deaths51015
Commuting102030
CO2 emissions71421
Air quality81624
Net benefits2726-7

(Adapted from Layard et al. page 2)

Thus, on Layard et al.’s assumptions, releasing the lockdown in mid-June would be optimal, with the net benefits declining thereafter – releasing in August would actually be worse than releasing now due to the rising economic costs. Layard et al. themselves say that the numbers in the table above are purely illustrative, so we should not take this conclusion literally. Nevertheless, the quantitative framework is an important contribution. 

Wellbeing is arguably not all that matters, but almost all ethical viewpoints agree that wellbeing is morally important. The new science of wellbeing analysis should be a key guide for governments making decisions about when to end the lockdown.

Economics, prioritisation, and pro-rich bias

tl;dr: Welfare economics is highly relevant to effective altruism, but tends to rely on a flawed conception of social welfare, which holds that the more someone is willing to pay for a good, the more utility or welfare they would get from consuming that good. (I use ‘welfare’ and ‘utility’ interchangeably here). This neglects the fact that differences in willingness to pay are often merely due to differences in initial resource endowments. As a consequence, welfare economics is biased towards policies that favour the rich. Effective altruists should be aware of these problems, and economists should adopt a revised conception of social welfare.

**

Effective altruism is the use of reason and evidence to promote the welfare of all as effectively as possible. Welfare economics is highly relevant to effective altruism because it aims to show which policies or actions would best maximise social welfare. The modern discipline of economics was heavily influenced by early utilitarian thought, and economics has influenced effective altruism in numerous ways with tools such as cost-effectiveness-analysis and Disability Adjusted Life Years. Welfare economics is, in my view, the most useful and practically applicable prioritisation tool currently available to governments. However, as I will now argue, mainstream welfare economics relies on a flawed theory of social welfare, which leads to pro-rich bias in policy evaluation.

I hope this post will improve understanding of welfare economics among effective altruists. It would also be useful for economists to recognise these problems and take a revised approach.

Touting and social welfare

I will bring out this issue by discussing the question of ticket ‘touting’ or ‘scalping’. Economists are somewhat unusual in believing that touting is actually a good thing because it corrects for underpriced tickets. Here is The Economist on the issue:

“Flint-hearted economists might note that a secondary market suggests that the seats were underpriced. Cheaper tickets meant to boost equal access lure in touts, for whom low prices mean bigger premiums. And more scalpers means more disappointed fans in the queue.

Rather than allowing touts to profit, the play’s producers could take a cue from “Hamilton”, a wildly successful Broadway musical, and raise prices for the premium seats until demand falls in line with supply (even at up to $849 per ticket, some argue that “Hamilton” is too cheap). But the Potter producers seem to be more worried about impecunious wizarding fans losing out than about the prospect of touts swiping surplus.

Stamping out the secondary market entirely means preventing people selling their tickets to those who value them more. This inefficiency is wince-inducing for economists…” [emphasis added]

According to some economists, ticket touting improves allocative efficiency.

Allocative efficiency occurs when there is an optimal distribution of goods according to consumer preferences, or, in other words, when social welfare is maximised.

The argument goes as follows. By selling tickets at a single price on a first come first served basis, some people who really want to go to the show will be unable to go. When the ticket is underpriced, Pete, who is willing to pay no more than $50 for a Book of Mormon ticket, can get a ticket, but Rich, who is willing to pay up to $1000, doesn’t get a ticket.

Crucial Premise: Necessarily, the more someone is willing to pay for a good, the more welfare they get from consuming that good.

So, by meeting the market demand of those willing to pay more or, in other words, ensuring that price is closer to marginal utility, touts ensure that social welfare is maximised.

The vast majority (>68%) of economists believe touting increases social welfare, as shown by this IGM poll (a good place to find the views of economists on lots of different topics). It’s somewhat unclear whether they do so on the basis of the argument from allocative efficiency and the Crucial Premise, but I would bet that a significant portion do endorse that argument.

What’s wrong with this argument?

I’m going to argue that the foregoing argument fails because the Crucial Premise is false. (Note that touting might be justified by other arguments).

I’ll first clarify the assumptions made in the argument.

Utilitarianism = Agents ought to perform the act which maximises total social utility or welfare.

A large portion of economists accept preference utilitarianism, according to which utility is conceived of as preference satisfaction. When evaluating policy, many economists like to say that they put morality to one side, but this is seldom true. In actual fact, they are appealing to preference utilitarianism. This is a moral theory.

Some economists believe that allocatively efficient outcomes might involve large inequalities and therefore be unfair. Consequently, they endorse an equity or fairness constraint on preference utilitarianism. In philosophical terms, this is equivalent to preference utilitarianism with a welfare egalitarian constraint. Proponents of such a theory tend to recommend that governments correct inequality through redistribution.

The pro-touting argument combines preference utilitarianism and the Crucial Premise, concluding that touting is justified because it maximises social welfare.

With this clarified, we can now explore why the pro-touting argument does not work. The Crucial Premise is false. It is not necessarily true that willingness to pay for a good is an indicator of how much utility one would get from a good. This is obvious. For example, suppose that Pete is very poor and Rich is very rich. As a consequence, Pete willing to pay up to $50 for a Book of Mormon ticket, but Rich is willing to pay up to $1,000. But this does not necessarily mean that Rich would get more utility from watching the Book of Mormon than Pete. All it shows is that Pete doesn’t have as much money. It might be the case that Rich would mildly enjoy the show, but Pete would absolutely love it.

Indeed, imagine that Pete has no money at all. According to the view that, necessarily, the more one is willing to pay for a good the more utility one derives from it, Pete would not gain utility from the consumption of any good, even food or water. This is absurd.

We can avoid this by correcting for inequality in income or resources between individuals when assessing willingness to pay. We could, for example, ask what Pete would be willing to pay for a ticket if he had as much money as Rich. Thus, hypothetical, rather than actual, willingness to pay would determine consumer preference. Consumer preference would not be revealed by actual market demand. If so, then it is not necessarily true that touting tickets at higher prices increases social welfare by allocating tickets to those who would get most utility from them.

Not only is it not necessarily true that actual willingness to pay determines consumer preference, it is not even usually true. Differences in willingness to pay are to a significant extent and in a huge range of cases driven by differences in personal wealth rather than by differences in consumer preference. Rich people tend to holiday in exotic and sunny places at much higher rates than poor people. This is entirely a product of the fact that rich people have more money, not that poor people prefer to holiday in Blackpool. I think the same holds for the vast majority of differences in market demand across different income groups.

In sum, the argument for touting from preference utilitarianism and the Crucial Premise fails.

Implications for welfare economics

This is one instance of a serious general problem for contemporary welfare economics. Equating market demand and utility without correcting for inequality in income or resources leads economists to pro-rich bias. It is this same flaw that led the 1995 IPCC report to conclude, on the basis of a willingness to pay approach, that Indian lives were worth less than American lives.[1]

It is easy to see how this bias could come into play for pretty much all policies assessed by welfare economics. Economists will neglect inequality and tend to recommend that goods be distributed by market prices.

This is not a criticism of preference utilitarianism from equity or fairness. I am not saying that only aiming to maximise social welfare is inegalitarian, and I am not saying that equality is intrinsically valuable. I am saying that preference utilitarianism alone, properly conceived and without an equity constraint, favours more egalitarian outcomes than economists acknowledge.

One advantage of holding that actual willingness to pay determines preference is that it is easier to measure than hypothetical willingness to pay. For this reason, in some cases it may be more practicable to approximate preference utilitarianism (properly conceived) with the Crucial Premise + an independent equity constraint. This equity constraint would be justified on utilitarian grounds, rather than on the grounds that equality is intrinsically important.

The downside of this is that economists would still be giving an inaccurate account of what constitutes preference satisfaction. The statement “touting optimises the distribution of goods according to consumer preference, but is inequitable” is false because the first conjunct is false.

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Thanks very much to Stefan Schubert for comments.

 

[1] The great John Broome discusses this on p.15 here – http://users.ox.ac.uk/~sfop0060/pdf/Valuing%20policies%20in%20response%20to%20climate%20change,%20some%20ethical%20issues.pdf