Tim Harford's Blog, page 12

If I want to get fitter, should I wear a fitness watch?

We have a tendency to sleepwalk into adopting new technologies, and my new fitness-tracking watch is no exception. Ever the late adopter, I bought an entry-level model with a single aim: helping me pace myself on my Saturday morning Parkrun. But oh, the bells and the whistles!

A heart-rate monitor. A step counter. Sleep monitoring. Tracking my “streaks” of exercise. A VO2 max tracker. An “intensity minutes” tracker. A calories-burnt counter. Access to training plans. A link to Strava, so my friends can comment on my exercise and I can comment on theirs. Unkindest of all, the Fitness Age indicator. I didn’t sign up for any of this, yet the watch’s app displays them all for my consideration. And now I am obsessed.

Ever the empiricist, I started to wonder what the likely impact of all this quantification was. Would the fitness tracking actually improve my fitness? Would it backfire in some gruesome way? Or, perhaps, both at once?

Early studies of this question were not wholly encouraging. One randomised controlled trial, with results published in 2016, found that adding fitness trackers to a weight-loss programme made the programme less effective. While participants tended to lose some weight with or without the trackers, those with the trackers lost less weight than those without. For those who love counterintuitive findings, this discovery is fun. Yet it is unclear quite how to interpret the finding, or even how seriously to take it. (The study, incidentally, found no significant difference in diet or physical activity between the two groups. Was the effect real and robust, or a fluke?)

If we think fitness trackers might backfire, it’s worth pondering how exactly that could happen. One possibility is that people become so obsessed with hitting their targets that they cheat, perhaps shaking the watch or phone vigorously in the hope of racking up extra steps.

But it’s one thing to occasionally cheat the algorithm and hit a meaningless target, then feel a bit silly about it. It’s quite another to suggest that people are so busy trying to con the fitness tracker that they actually do less exercise than if there was no tracker at all.

Another risk is that the trackers might demotivate people by turning a pleasurable activity into a chore. There is some evidence of that in another 2016 research paper titled “The Hidden Cost of Personal Quantification”. In one of the studies described in that paper, participants went for a walk wearing pedometers, some with the step count visible and some with the step count covered. People with a visible step count walked more, but enjoyed themselves less. That is intriguing and certainly suggests a backfire mechanism. On the other hand, that was just one walk. Over the course of weeks and months, are we to picture someone who used to love walking, but then walks less because their smartwatch starts telling them how many steps they’ve completed?

A third risk — and this seems more plausible to me — is that people are driven by their fitness trackers to over-exercise, or to favour one narrow form of exercise, with the result that they become injured and then discouraged.

There is a final possibility: perhaps fitness trackers work perfectly well.

Thankfully, we do not need to rely on these early studies: the intervening years have brought us vastly more data. In 2022, Lancet Digital Health published a systematic review that tried to bring together all the credible research done to that date, covering 164,000 people. The study came to exactly the conclusion you might expect, if you weren’t tying yourself in knots of counterintuition: fitness trackers do help people to be fitter.

More specifically, wearable activity trackers lead people to walk more — 1,800 steps or 40 minutes of extra walking per day — and to lose some weight (1kg) on average. There is also evidence, albeit weaker evidence, that fitness trackers lead people to burn more calories, improve blood sugar and cholesterol, improve wellbeing, reduce disability, and lower levels of pain, anxiety and depression. Emotional wellbeing improves and resting heart rate falls.

Some of these apparent benefits are small or uncertain but, broadly speaking, the picture is what you’d hope: people who were given fitness trackers in a randomised trial were more active than those who, at random, were not. That extra physical activity led to all the benefits we might expect.

None of these studies was designed to answer the question, “If I want to get fitter, should I buy a fitness watch?” Instead, they answer the stranger question, “If I was given a fitness watch as part of an academic study, would I get fitter?”

Consider the parallel pair of questions: “If I want to take up running, should I buy some running shoes?” and, “If I was given some running shoes as part of an academic study, would I run more?” For most purposes, the answer to the first question is obvious and the answer to the second is irrelevant.

Perhaps that’s how I should view my fitness watch. It’s like a gym membership or an exercise bike: great if you use it, pointless if you don’t. And for now, I’m using it. Although it feels rather more like it is using me.

Written for and first published in the Financial Times on 11 October 2024.

Loyal readers might enjoy the book that started it all, The Undercover Economist.

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Trick questions, first instincts, and the benefits of thinking twice

A first impression suggests that there is nothing to be gained from reading Alex Bellos’s new book of puzzles, Think Twice (Puzzle me Twice in the US), except an hour or so of pleasant diversion. But as the book makes clear, first impressions can be misleading. 

Bellos is offering a very particular kind of puzzle: the kind where there is an obvious answer, and the obvious answer is wrong. One might describe such puzzles as “trick questions”, but this is no mere frippery. It is hard to think of a conundrum that offers us more practical lessons than the trick question.

For example: which teapot holds more, a tall elegant one, or a squat but slightly wider pot? The answer: look at where the spout ends. The teapot can tower as high as you like, but if the opening of the spout is low down, you won’t find it carrying much tea. The appearance of a grand scale can be deceptive: the lesson is to look for the weakest link in any system.

Or try this one: “Jack is looking at Anne, but Anne is looking at George. Jack is married, but George is not. Is a married person looking at an unmarried person?” That’s multiple choice: yes, no or cannot be determined.  Bellos set this one to grizzled veterans of his newspaper puzzle column, and warned them they’d get it wrong. Seventy-two per cent of them did — worse than the proverbial dart-throwing chimp. The psychologist Keith Stanovich has found that the typical failure rate on that puzzle is even higher, at more than 80 per cent.

Or, a classic of the genre: Agatha and Zoe have a combined age of 50. Agatha is 40 years older than Zoe. How old is Zoe?  That one is absurdly easy if you take a moment to stop and think. Many people don’t and blurt that Zoe is 10 years old.

But why would they hesitate anyway? Our minds are machines for reaching swift conclusions in a fast-moving world. Slowing down to reason in fine detail takes an effort of will.

Still, sometimes it pays to stop and think again. Consider the problem facing countless students as they sit multiple-choice exams, writing down an answer and then having second thoughts. Should they stick with their first instincts or should they switch? There is an overwhelming consensus on this question. Students, instructors and even some exam guides warn the hesitating candidate to stick with their first thought. “Many students who change answers change to the wrong answer,” admonishes one guide — which, when you think about it, may be true but is also not a good basis for advising students not to change. 

While the consensus may be overwhelming, it is quite wrong. A century of academic research into the question demonstrates clearly that when you have second thoughts on a multiple-choice test, it’s a good idea to change your answer. Indeed, the gap between our beliefs and the evidence is so stark that psychologists have given it a name: the “first-instinct fallacy”. Our first instincts are often right, to be sure. But when we have second thoughts, that’s a sign of trouble: second thoughts usually occur to us for a reason.

Why are we so reluctant to indulge our second thoughts? Psychologists Derrick Wirtz, Dale Miller and Justin Kruger (he of the Dunning-Kruger effect) have conducted experiments showing that we tend to misremember the results of switching answers. We tend to recall times when switching was a mistake, and overestimate how often we got good results from sticking to our first guess. The same researchers also found evidence that people were frustrated by teammates in a quiz game who switched answers, regardless of their overall performance in the game.

And this research on the first-instinct fallacy presumes that the second thoughts even occur. All too often, they do not. Bellos’s book challenges readers to think twice (the clue is in the title), and yet many still stumble into the cognitive traps he sets. When an answer leaps into our heads and feels right, it is easy to mistake that feeling for the truth.

As we step away from multiple-choice questions and puzzle books and into the everyday information environment of media and social media, we are endlessly being confronted with claims that feel intuitively true (or intuitively absurd) and leaping to conclusions. One is rarely warned to think twice on X or Facebook, but the warning would be useful nevertheless. 

This is not mere speculation: Gordon Pennycook, David Rand and others, behavioural scientists who study misinformation and how we respond to it, have found that people who do poorly with tricky puzzle questions (the term of art is “cognitive reflection problems”) are more likely to share online misinformation and they are also more likely to fall for falsehoods of a politically partisan nature.

That’s a striking finding: it suggests that spotting fake news is more a matter of calm reflection than it is of raw intelligence or technical expertise. An encouraging finding, too — if only we can find a few oases of calm on the internet.

Written for and first published in the Financial Times on 4 October 2024.

Loyal readers might enjoy the book that started it all, The Undercover Economist.

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Cautionary Tales – Murder at Halloween: The Edinburgh Body Snatchers

In 1827, Edinburgh, Scotland was a world centre for anatomical study, but there was a shortage of cadavers for medical students to dissect. Two men, William Burke and William Hare, spotted a grim business opportunity. They began sourcing bodies – by any means possible…

In this episode of Cautionary Tales, recorded live at the Podcast Show in London, true crime meets economics. Tim Harford’s hair-raising story explores a question: what makes some markets acceptable, and others repugnant?

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Further reading

Several enjoyable books pick over the bones of the historical sources on Burke and Hare. Our favourites were The Anatomy Murders by Lisa Rosner, and Brain Bailey’s Burke and Hare: The Year of the Ghouls.

Alvin Roth’s article Repugnance as a Constraint on Markets was published in the Journal of Economic Perspectives in 2007. Roth expands on his ideas in an interview with the Harvard Business School. 

Should everyone earn their pay rise?

Mozart and Haydn were composing string quartets a quarter of a millennium ago, when the industrial revolution was in its infancy. Since then, the scale of the world economy has increased at least a hundredfold and material living standards in western Europe have grown 20 times over, perhaps more. Our ability to travel, build, calculate, communicate or simply produce food has been transformed beyond recognition. And yet the productivity of a live recital of Haydn’s Emperor quartet hasn’t budged: it still takes four musicians between 25 and 30 minutes to play.

This is the essence of what has become known as “the Baumol effect” or, more dishearteningly, “Baumol’s cost disease”. The basic problem was laid out by economists William Baumol and William Bowen in Performing Arts, the Economic Dilemma in 1966, amid much hand-wringing about the perception that the performing arts were ridden with waste and mismanagement. Whether or not that was true, Baumol and Bowen argued, “The basic difficulty arises, not from any of these sources, but from the basic structure of live performance.”

The Baumol effect describes the challenge that arises when some sections of the economy are rapidly advancing while others are standing still. If you would like to listen to people play Haydn live, you will probably need to pay them a competitive wage. And in a flourishing economy, what counts as a competitive wage is always increasing. If the productivity of musicians doesn’t change, but their wages keep growing to keep pace with the rest of the economy, then paying people to perform Haydn is going to feel more and more like an expensive luxury.

But that is not why the Baumol effect is on people’s lips today. The concern now is not the price of a night at the concert hall, but the cost of healthcare, social care and education. Instead of a cellist, think of a nurse changing a dressing on a wound, or a care worker helping a person with dementia get dressed in the morning, or a kindergarten teacher instilling some of the basics of reading and counting to a class of four-year-olds. To demand that these people become “more productive” feels like the same sort of basic error as insisting that the string quartet play louder and faster. Perhaps it cannot or should not be done.

If the Baumol effect is to blame for the woes of public services, we have a choice. We can let the wages of public sector workers fall behind and, over time, lose some of the best of them. We can hope that labour-intensive services, from care work to classical concerts, will be performed on a voluntary or semi-voluntary basis. Or we can decide that, much like live performances of Haydn, we don’t need them as much as once we did.

Alternatively, we can agree that the increased cost is something we are prepared to pay for. After all, the Baumol effect is a direct consequence of productivity gains elsewhere in the economy. By definition, it implies that the money is available to pay those higher wages. Is this story really a good explanation of what is happening to the UK’s struggling NHS or public services more generally? Should we all be paging through our Baumol and Bowen to understand the problem?

Only up to a point. A report from the Institute for Fiscal Studies (IFS), published in May, finds that between 1997 and 2019, public sector productivity grew at 0.2 per cent per year, while in the private sector the productivity growth rate of a broadly comparable measure was 0.8 per cent. Average wages of full-time employees, on the other hand, grew at the same rate in public and private sectors. So far, so Baumol-ish.

But the recent travails of the NHS cannot be laid at the feet of the Baumol effect. Ben Zaranko, one of the authors of the IFS report, suggests that since 2020 the key elements have been the strain of the pandemic and the consequences of a long period of under-investment in capital and management capability. To the extent that this is a story of a string quartet, it’s a group of five stressed musicians trying to organise and promote their own concerts, while sharing three threadbare instruments.

The Baumol effect is a useful rebuttal to those who assume that every worker must “earn” their pay rises by becoming more productive. That’s nonsense; they can always earn their pay by quitting and doing something else. Still, while we shouldn’t dogmatically insist that public sector wages cannot rise unless public sector productivity rises in lockstep, we shouldn’t be too quick to accept the strictures of Baumol’s string quartet. By assumption, Baumol and Bowen ruled out the idea that musicians might record their performances or use amplification to reach larger audiences. They were focused only on traditional live performances and the cost of those performances. Fine. But it would be unwise simply to assume that nothing can be done to raise the productivity of doctors and teachers.

In any case, the Baumol effect is best seen as a good-news story. It is a tale in which parts of the economy become dramatically more productive. Indeed, even if every part of the economy enjoys productivity gains, Baumol effects will apply to the extent that some are increasing productivity faster than others. Those who fret about the Baumol effect should perhaps fret more about the alternative: slow productivity growth everywhere. That is all too easy to imagine.

Written for and first published in the Financial Times on 27 September 2024.

Loyal readers might enjoy the book that started it all, The Undercover Economist.

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My biggest productivity mistake

From time to time, my editor will suggest that I write a column about how to be more productive. It’s a sure way to trigger imposter syndrome because, whether or not I appear productive from the outside, I certainly don’t feel productive on the inside. In fairness to myself, and to anyone who worries that they should be getting more done, personal productivity is a fiendishly hard problem.

It demands willpower, since there is always usually some pleasant distraction available.

It demands judgment too. Even a fairly straightforward-seeming question, such as which task to do and when, is going to depend on a shifting kaleidoscope of variables: whether you have the time, the tools, the energy. As the world changes, tasks will frequently become more urgent or irrelevant.

This makes getting things done a far more dynamic problem than, say, decluttering. Marie Kondo’s simple advice to throw away any possessions that do not spark joy works brilliantly for socks and broken calculators, but it will not help you prioritise your inbox. There are too many options and everything is moving too fast. One does not simply declutter one’s To Do list.

And a final challenge to anyone trying to get everything done: that goal is simply beyond us all. As Oliver Burkeman explains in his new book Meditations for Mortals, “the incoming supply of things that feel as though they genuinely need doing isn’t merely large, but to all intents and purposes infinite. So getting through them all isn’t just very difficult. It’s impossible.” Delude yourself about this, as most of us do every morning, and stress and disappointment will inevitably follow. No wonder so many of us beat ourselves up at our failure to live up to our own impossible productivity aspirations.

This week, then, let’s change the script. Instead of handing down yet more tablets of stone, let me reflect on my own productivity mistakes. My biggest problem is that I always have too many projects on the go. Columns, book chapters, speeches and podcast scripts vie for my attention. This is not without its advantages. Variety is fun, as well as offering some protection from the vicissitudes of a career in the media. Projects cross-fertilise each other and if you get stuck on something, you can switch to something else that is equally worthwhile. Many of the great artists and scientists have been inveterate slow-motion multitaskers.

And yet I think many people, myself included, tend to accumulate more active projects than they can reasonably handle. Each project has its own intellectual and organisational overhead, and there’s a risk of a cognitive traffic jam, as more mental energy is spent switching between projects than doing them. There are some tricks to reduce this sense of overload, but I have never found a permanent fix.

“One thing at a time,” advises no less a sage than Arnold Schwarzenegger, and who am I to argue? And yet I have never managed to break myself free from the slow-motion multitasking habit, and I have never really tried.

My second productivity confession is that I respond to email too quickly. I realise that risks being a humblebrag, along the lines of “my biggest weakness is that I work too hard”. But it’s not difficult to be responsive to email: all that is required is a simple filing system and a willingness to make decisions.

Indeed, that’s the problem. Email is so easy to deal with that it’s tempting to let email replace hard work. Faced with a genuinely difficult task, it’s the path of least resistance to open up my inbox instead. It doesn’t feel like I’m ducking the real work — what could be more professional than dealing promptly with email? But ducking the real work is exactly what I’m doing. For me, the most dangerous distraction is not YouTube or Instagram: it’s the things such as email, which are nearly, but not quite, the work that needs to be done.

My rapid emails are a symptom of a deeper productivity malaise: a habit of switching on my computer without having my To Do list at hand. Lacking a clear plan for what I was going to do, habit takes over, and I am deep in the email inbox, letting other people’s priorities override my own. On a good day, there’s plenty of email, so at least I’m getting something done. On a bad day, I clear the inbox quickly and am then in danger of losing my grip and browsing the internet looking for something to do.

The solution is childishly simple. I should ensure that whenever I switch on my computer I have in front of me a good list of what I need to do. It is a huge step towards forging ahead and doing it. The fact that I do not always follow this childishly simple advice may make it seem more childish still.

I suppose I could always get my computer to remind me. In 2018, Alex Williams, Harmanpreet Kaur, Gloria Mark and others presented research about using chatbots to stay on task. Their bot pops up to prompt people to reflect on their goals for the day — either what they wanted to do, or how they wanted to feel. Both kinds of prompts were effective at getting people to focus on the real work — for an hour or so. And then? Then the effect starts to fade. Gloria Mark has suggested writing the goal on a sticky note so the memory lasts a little longer.

It seems absurd that I and many others neglect so basic a thing as to remind ourselves what we wanted to do when we sat down at the computer. But with distraction only a click away, get those sticky notes out.

Written for and first published in the Financial Times on 20 September 2024.

Loyal readers might enjoy the book that started it all, The Undercover Economist.

I’ve set up a storefront on Bookshop in the United States and the United Kingdom. Links to Bookshop and Amazon may generate referral fees.

Cautionary Tales – The Poet who Toppled the British Empire

India, 1930. Sarojini Naidu is marching towards a British-controlled saltwork; behind her is a long column of protestors all dressed in white. The great campaigner for India’s Independence, Gandhi, is now in jail. In his place, he’s chosen Naidu to lead this movement against the hard and fearsome British Empire.

Naidu and her marchers want change, and they want to achieve it peacefully. India’s fate, they believe, depends on a non-violent path to resistance.

Today, there will be violence. But it won’t come from them.

This is the final episode in a four-part series about how to succeed without being a jerk. This episode is based on David Bodanis’ forthcoming book How To Change The World, which will be published in 2025.

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How a mind-boggling device changed economic history

At the London School of Economics, a few weeks before Christmas, in 1949, the Lionel Robbins seminar was about to begin. The prestigious event was at the razor’s edge of postwar economic thought: Robbins, a giant of economics, had made the LSE a rival to John Maynard Keynes’s Cambridge, recruiting future Nobel laureates such as Friedrich Hayek, John Hicks, Arthur Lewis and the classicist turned economist James Meade.

This lecture, however, promised to be more of a curiosity than a masterclass. Meade had persuaded Robbins to invite an unlikely speaker: a small, shy, incessantly smoking mature student from New Zealand, who had just failed in his attempt to get a degree in sociology. Meade’s protégé had brought an extraordinary device with him — a Heath Robinson-esque contraption resembling an adventure playground for non-existent fish. Half a dozen or more Perspex tanks were linked together through a network of pipes, dams and sluice gates and filled with water stained a deep pink with cochineal dye. It looked like the sort of thing a mad genius might produce if asked to design a water clock. What it could have to do with economics was anyone’s guess. But curiosity is a powerful thing, and many of the School’s finest economists were there to gawp at what promised to be an outlandish display.

The subject of this sudden attention, Alban William Phillips, had been born on a dairy farm in Te Rehunga in rural New Zealand 35 years earlier. His father, Harold, had equipped the farm with a flush toilet, a generator powered by a waterwheel, and electric light, long before the neighbouring farms had any such wonders. As a result, Bill Phillips and his siblings were able to read late into the night — or at least until Harold called “lights out”, and inserted a lever into a winch in the bedroom, which pulled a wire, which pulled a chain, which, far across the farmyard, disconnected the wheel from the generator and plunged the bedroom into darkness.

Harold taught his children to build crystal radios, zoetropes and toys. His wife, Edith, a schoolteacher, encouraged them to study. School was nine miles away and Phillips soon tired of cycling, so he got hold of a broken-down old truck that the adults regarded as far beyond repair. Phillips disagreed — and he fixed it. Aged 14, he used to drive his classmates to school, parking a discreet distance away from the eyes of his teachers.

Phillips might have been expected to go to university — he passed every exam — but there was a problem. In 1929, a collapse in share prices on the other side of the world, at the New York Stock Exchange, had set in motion the Great Depression. Its effects lasted for years, and reached as far as a dairy farm in Te Rehunga. Prices for agricultural commodities plummeted, and Harold and Edith simply couldn’t afford to send their son off to study. Phillips became an apprentice electrician at a hydroelectric power station instead.

As well as diverting an enterprising young New Zealander from going to university, the Depression changed the course of history and revolutionised economics. How could it be otherwise? Economists asked themselves what was happening, why and whether anything could be done about it. They took new measurements, formulated new theories and proposed new policies, all concerned with the question of economic performance as a whole — as something rather different from the sum of its parts. Macroeconomics was born.

Pioneering macroeconomists fought to make sense of this intractable global economic slump. What they had in common was a sense that the economy was a thing that could break — and therefore a thing that could be mended. The most famous among them was Keynes, who sprang to prominence after the publication of his book The Economic Consequences of the Peace, a blistering critique of the Treaty of Versailles which ended the first world war, and who consistently criticised British economic policy throughout the 1920s. But there were others, such as Simon Kuznets, who masterminded the construction of national accounts for the US, or Phillips’s mentor, James Meade. As a student in the late 1920s, Meade had abandoned his study of classics and took up economics instead, horrified by the widespread unemployment he saw around him and determined to do something. He later became an influential figure in the wartime governance of the British economy. All these men shared a touch of economic genius, but they also shared something else: a determination to take action.

Keynes declared at the start of the Depression that the economy was suffering from “magneto trouble” — a technical fault that might bring the entire machine grinding to a halt, but which could be fixed rather simply with the right tools and understanding. In other words, macroeconomists approached the broken economy in much the same way as 14-year-old Phillips approached that old truck.

In 1935, the apprentice electrician left Te Rehunga to see the world. Steve Levitt, a co-author of Freakonomics, was once dubbed “the Indiana Jones of economics”, but if that swashbuckling label belongs to anyone, it’s Phillips. In between leaving New Zealand and his first brush with economics in 1946, Phillips worked in a gold mine, hunted crocodiles, busked with a violin, rode the Trans-Siberian railway and was arrested by the Japanese and accused of spying. He eventually pitched up in London and signed up for the LSE. Then the war started, and he joined the Royal Air Force, which promptly sent him back to the other side of the world.

In the RAF, Phillips established himself as an outstanding engineer, working to upgrade the obsolete aeroplanes that were supposed to defend British-held Singapore from Japan. Days before Singapore surrendered, he found himself on the last convoy to flee the city, onboard the Empire Star. The cargo ship designed to carry 23 passengers had been packed with 2,000, many of them women and children. When the convoy was discovered and attacked by Japanese planes, Phillips found a new use for his talents as an engineer. He brought a machine gun up on deck and improvised a mounting for it. Then he stood there for hours, fending off the attackers as bombs fell around him.

This extraordinary performance earned him the MBE medal, but didn’t spare him from spending more than three years in a Japanese prisoner-of-war camp. Conditions were bad. Phillips later said that the small men survived and the taller men starved. He was one of the small ones. By the end of the war, he weighed just seven stone (45kg). To keep everyone cheerful and up to date on news from the outside world, Phillips continued with his engineering improvisations. He built concealed radio sets, one of which was tiny enough to be hidden from the guards in the heel of his shoe. He would have been tortured and killed had it been discovered. He also designed and built little immersion heaters, which the inmates used every evening to make hundreds of morale-boosting cups of tea. The guards never worked out why the camp lights flickered and dimmed each evening.

Phillips made light of his prison-camp experiences, and it was not until many years later that the darkest episode was revealed. In the summer of 1945, he was one of thousands of men transferred to a death camp, where they watched their captors mount machine guns on the walls, pointing inwards, and were forced to dig their own mass graves. One of the other prisoners was the writer Laurens van der Post. In his memoir The Night of the New Moon, he describes the camp, and a daring escapade with a “young New Zealand officer” who was capable of performing “a near miracle” with his engineering. Phillips, van der Post and another officer broke into the commander’s office in search of spare parts for the tiny radio. Phillips repaired it just in time to hear the news: the Americans had dropped an apocalyptic bomb on Hiroshima. The end of the war was at hand. After a few tense days, the Japanese camp commander admitted defeat; the prisoners would be freed.

When Phillips returned to London at the war’s end, he resumed his studies at the LSE. He took up sociology, a degree that contained some basic economics modules, and became intrigued by the engineering-style mathematical equations that were becoming popular in the new subject of macroeconomics. He started skipping his sociology lectures and disappearing to his landlady’s garage in the suburb of Croydon, where he put together a hydraulic representation of the equations his lecturers had been scribbling on the blackboards.

One of those lecturers was James Meade. Meade might easily have been taken aback when a student who had all but abandoned sociology approached him with a proposal to rework the calculus of economics as a study in plumbing. Instead, thanks to his patronage, Phillips was given the opportunity to demonstrate his mind-boggling machine in the exacting forum of the Robbins seminar in late 1949. It was his big chance, a last opportunity to demonstrate that he had something serious to contribute to the brave new world of macroeconomics.

Cigarette never far from his lips, Phillips began by fiddling around at the back of the array of Perspex pipes and tanks and starting up a pump that had been scavenged from a Lancaster bomber. The pink-dyed water began to squirt into a tank at the top of the machine, and from there flow down from one container to another. The sound of the pump screeched in the background like a kitchen blender as Phillips demonstrated what the machine could do.

The professors were astounded. Perhaps they would have been less so had they known more about his unorthodox education — the differential equations he’d studied by correspondence course, the hydraulic engineering he’d learnt as an apprentice, the mechanical scavenging and repurposing he’d begun on the farm and perfected in the defence of Singapore. The machine worked perfectly. Within five minutes, the entire room was buzzing with excitement at what Phillips had created: the first-ever computer model of a country’s economy.

The Moniac, or Monetary National Income Analogue Computer, is these days often just called The Phillips Machine. It churned out solutions to equations, using hydraulics instead of differential calculus to calculate the answers. It was a simple computer, although not quite as simple as one might assume. It could solve nine differential equations simultaneously and within a few minutes — a feat that was impossible by hand. Even in the 1950s, economic models were worked out by rooms full of human “computers”, typically women armed with paper and calculators to provide the mathematical equivalent of a typing pool. It would be years before digital computers could support economic models as complex as the Moniac’s.

Phillips made 14 machines in all, most Mark II Moniacs, expanded versions of the original machine. The original machine went to the University of Leeds. Others ended up at Cambridge, Harvard, Melbourne, Manchester and Istanbul. Some went to corporations or ambitious governments in developing countries, from the Ford Motor Company to the Central Bank of Guatemala.

At seven feet tall and four or five feet wide, the Moniac Mark II seems an imposing if rather quaint piece of equipment today. Down the centre of the machine runs a Perspex-fronted column, intersected every foot or so with weirs and sluice gates leading off to side chambers. Column sections are neatly marked INCOME AFTER TAXES, CONSUMPTION EXPENDITURE and DOMESTIC EXPENDITURE. One compartment, the size of a small tropical fish tank, is labelled INVESTMENT FUNDS. Along one wall is a curved dam made of flesh-coloured plastic, marked LIQUIDITY PREFERENCE FUNCTION. At the top corners of the machine are two spools of paper, poised to scroll gently as four pens connected to different floats wait, ready to trace lines up or down like a seismograph, recording the ebb and flow of the “economy”. A few plastic pipes, looking as though they have been scavenged from washing machines, are tucked away behind the machine. At the bottom is a large tank marked NATIONAL INCOME. A small pipe leads from it back to the top of the machine, where the flow of “money” can begin again.

If the Moniac was the result of exquisite engineering skill, Phillips’s flash of inspiration — that hydraulics could be used to solve complex systems of equations — was close to genius. Of course, the hydraulic computer was less flexible than the digital computers that would eventually supersede it. Each equation quite literally had to be carved into the flow-control system of the Moniac, in small squares of Perspex set in a neat white frame, with a thermometer-like scale along the side. The equations themselves were slots, one in each piece of Perspex, each with a particular shape and angle, snugly holding a peg that ran smoothly on brass rails. Each peg was attached to a float and a sluice gate, so that as the water level in a tank rose, the peg would move up and — depending on the shape of the slot — would also move sideways, opening or closing the sluice gate. Phillips had calibrated his equations to what was then known about the British economy: how much income people tended to put aside as savings, for example, or the overall response of supply and demand to prices. To his surprise, he found that the machine was watertight enough to be accurate to within 2 per cent — a higher level of precision than was required given the quality of the economic statistics of the day.

To the cognoscenti, the machine was more than just a brilliant technical achievement. It also embodied some groundbreaking economics. For example, when moving between an old steady state and a new one, after some change in the economy, the machine produced cycles or even turbulence for a time, meticulously recorded by the rise and fall of the seismographic pens. These turbulent transitions were beyond the capabilities of the theorists to analyse. They simply had to ignore such dynamics at the time, and even now cannot fully cope with them. Another example: the Moniac allowed for floating exchange rates. Today, the dollar, the pound, the euro and the yen all have free-floating exchange rates against each other, but Phillips lived in a world where countries tried to peg their currencies to each other, or to the price of gold.

The LSE’s establishment rushed to give Phillips a job. Within a decade, he had been made professor, then a rare honour in British academia. For a man with no honours degree and no economics qualifications of any kind, he hadn’t done so badly.

Phillips’s money machine was as much loved in its day for the sheer ingenious exuberance of the thing as for its computing abilities. It was celebrated in Punch magazine and, much later, in Terry Pratchett’s novel Making Money. It also became an influential teaching aid. At the LSE, Meade attached two Moniacs together, one standard and the other a mirror-image, plugging the “export” pipe of one into the “import” pipe of the other in order to represent a model of international trade between the US and UK. He would then invite pairs of students to play the role of chancellor of the exchequer and Federal Reserve chair, manipulating interest rates or other variables in an attempt to increase the national income of their respective nations. Among the economic policymakers who cut their teeth in these lectures was perhaps the Fed’s most successful chair, Paul Volcker.

Eventually, the Moniacs fell into disuse. Today, only three are operational. An engineering professor at Cambridge, Allan McRobie, refurbished one to full working order. The central bank of New Zealand also keeps a working machine on display. A third is in Istanbul. The LSE kept the mirror-image machine as a teaching aid until 1992. It was then transferred to the Science Museum in London, where it sits dormant in a great hall facing the Difference Engine created by the father of computing Charles Babbage.

The water that flows around the Phillips machine is a good analogy for the way a macroeconomist thinks about the economy in terms of financial flows and reservoirs, of large quantities sloshing to and fro. Macroeconomists contemplate big glugs of spending power devoted to different ends: private consumption, government spending, investment, the purchase of imports. And these financial flows do not simply swell or evaporate of their own accord. They can be dammed, redirected and siphoned off by the choices of citizens and, in particular, by the whims of economic policymakers, who can alter interest rates, taxation or the quantity of money produced by central banks.

Phillips may have revolutionised the study of economics. But he didn’t solve the problem of how to keep the macroeconomic machine forever ticking over smoothly. That much is obvious from the lingering after-effects of the 2008 financial crisis, or today’s debates about how to fight inflation or boost productivity. Twenty years ago, we might have thought of economic stability as a solved problem, and economic growth as the natural order of things. That is no longer true. Once again, our economies look to be suffering from “magneto trouble”, and economists are hungry for solutions.

Perhaps the time has come for that Bill Phillips spirit. We need, once again, to find the same attitude to a misfiring economy that young Bill had to his clapped-out truck, that everyone thought beyond repair. We need, once again, economists who can roll up their sleeves and fix things.

Written for and first published in the Financial Times on 12 July 2024.

This essay is adapted from my book, The Undercover Economist Strikes Back.

I’ve set up a storefront on Bookshop in the United States and the United Kingdom. Links to Bookshop and Amazon may generate referral fees.

What we can and can’t say about what we do and don’t know

Earlier in the summer, the Democratic party and its supporters faced a difficult decision: should they gently but firmly sideline President Joe Biden from the 2024 ticket? There were plenty of reasons to agonise over the decision: loyalty to Biden; the daunting practicalities of the switch; fear of the chaos that might ensue; nervousness that the likely replacement, Biden’s vice-president Kamala Harris, wasn’t up to the job.

But such nerve-racking judgment calls are meat and drink to the likes of Nate Silver, author, poker player and widely admired forecaster of election results. In his new book On The Edge, Silver examines and admires the culture of what he calls “The River” — people who think probabilistically, are happy to be contrarian and have a high tolerance for taking risks.

For a Riverian such as Silver, the decision was simple. There was plenty of data from opinion polls indicating that Biden was likely to lose the election. The same data suggested that most plausible replacements, including Harris, would do better. Yes, there was some risk in ejecting Biden, but overall it was a bet worth making. That’s how the world looks to a Riverian. (Most politicians are not Riverians but, notably, many of the financiers and entrepreneurs who fund political campaigns are.)

There is much to be said for thinking probabilistically and for being willing to take reasonable risks. Yet, as John Maynard Keynes wrote in 1937, some things — like “the prospect of a European war . . . or the price of copper and the rate of interest 20 years hence” — are profoundly uncertain. “About these matters there is no scientific basis on which to form any calculable probability whatsoever. We simply do not know.”

One could disagree with that, as statistician David Spiegelhalter does in his forthcoming book The Art of Uncertainty. Surely when assessing the chances of war in 1937, one could do more than merely shrug. Still, Keynes was on to something. A political forecaster can look at the opinion polls. A poker player can calculate the odds that the next card revealed will be an ace. But the geopolitical analyst can do no better than make an educated guess.

Should we then refuse to dignify deep uncertainty with a confected probability estimate? There is something to be said for avoiding quantification: scenario planners often view probability estimates as a distraction. Would Hitler invade Poland? Rather than ask “How likely is that to happen?” it might be more fertile to ask “What would we do if he did?”. For contingency planning, and for trying to broaden our understanding of what might be possible, that is not such a bad approach.

Yet there are dangers in shying away from a guess at probabilities. For the psychologist Phil Tetlock, famous for his research into “superforecasters”, vague verbiage lets fortune-tellers off the hook. A statement such as “Keir Starmer may find the path ahead will bring unexpected challenges” might sound insightful until you reflect for a minute.

Another risk is that words such as “likely” or “common” do not convey what we think they do. When you are told constipation is a “common” side-effect of statins, what does that suggest to you? As Spiegelhalter explains, a survey of patients reckoned “common” meant about a third of the time, but to regulators in the UK and the EU a “common” side-effect happens between 1 and 10 per cent of the time.

These ambiguities can have serious consequences. In 1961, the US joint chiefs of staff reckoned there was a 30 per cent chance that an invasion of Cuba by exiles, supported by the US, would topple Fidel Castro’s regime. In a report to the president, this number was translated into “a fair chance”. But “a fair chance” could mean anything. President Kennedy gave his approval to what became the Bay of Pigs fiasco, thinking his advisers were confident of success. They should have stuck to the numbers after all.

Sometimes we have a good idea of the risks we face, and sometimes we don’t have a clue. Sometimes trying to think through the probabilities is a clarifying exercise, and sometimes it offers nothing more than false reassurance. So what to do? Spiegelhalter admiringly describes the five-stage approach of zoologist John Krebs, who as chair of the Food Standards Agency had to deal with the BSE crisis. The five steps are: tell people what you know, what you don’t know, what you’re doing to find out, and what they can do in the meantime. Finally, remind them that the advice may change.

These are solid principles for communicating in an uncertain situation. But they are also a strong starting point for thinking rigorously in an uncertain world. We should all be asking ourselves what we know, what we don’t and how we plan to fill the gap in our knowledge.

This, perhaps, suggests a gap in the risk-taking Riverian viewpoint. The word “experiment” does not make it into Silver’s index. For a poker player that may make sense: in a game of poker the only way to find out is to bet. Much the same is true if you’re planning an invasion of Cuba. But often, intelligent experiments can resolve uncertainty at minimal cost.

Often, but not always. Silver and Spiegelhalter would both call themselves Bayesians, a word Silver defines as “comfortable quantifying . . . intuitions and working with incomplete information”. But if Bayesian rings a bell, it is also the name of Mike Lynch’s luxury yacht, which so shockingly sank last month. Some risks blindside us all.

Written for and first published in the Financial Times on 6 September 2024.

Loyal readers might enjoy the book that started it all, The Undercover Economist.

I’ve set up a storefront on Bookshop in the United States and the United Kingdom. Links to Bookshop and Amazon may generate referral fees.

Cautionary Tales – Reason, Wrath and Rebellion on the High Seas

Early morning, April 1789. Captain Bligh is abruptly dragged from his cabin. Wrists bound, bayonet pressed to his chest, he and a few loyal sailors are forced into a tiny launch and set adrift on the vast Pacific Ocean. This far from land, no-one is likely to survive for long.

History remembers Captain Bligh as a cruel, petty tyrant. The reality is more complicated. Bligh championed rational thought and showed his men great kindness on that famous voyage on the Bounty – yet it ended in mutiny. So what went wrong?

This is the third episode in a four-part series about how to succeed without being a jerk. It’s based on David Bodanis’ book The Art of Fairness: The Power of Decency in a World Turned Mean.

[Apple] [Spotify] [Stitcher]

Misinformed about misinformation

After a spasm of concern about the role of misinformation in fuelling racist riots in England, don’t expect things to calm down: the US election is approaching, and with it a crescendo of anxiety about online lies.

The received wisdom now seems to be that misinformation — or perhaps Russian disinformation — is everywhere, that ordinary citizens are helpless to distinguish truth from lies, and furthermore that they do not want to. This was a narrative that began in 2016, the year in which the UK voted for Brexit after a campaign dominated by a lie on the side of a bus, in which Donald Trump, a serial fabulist, won the US presidency and in which “post-truth” entered the discourse.

But there is a problem with this story of ubiquitous online misinformation. In fact, there are three.

The first is that the story encourages a corrosive cynicism about everything. A world in which everyone is lying to you is a world in which you can pick and choose whatever you want to believe and to reject. If you know the liars are out there, you’ll be careful; if you think the liars are everywhere, you might give up on the idea of truth altogether. (This was a central argument of my 2020 book, How To Make The World Add Up.)

The second problem is that by emphasising the role of misinformation, we risk misunderstanding our political problems and their solutions. For centrist dads like me, it was unsettling to realise that many people were willing to give their votes to Brexit and to Donald Trump. The idea that they didn’t really mean it, but were led astray by deceptive propaganda, was perversely comforting. That idea helped shield us from the unpleasant possibility that people voted for Brexit and for Trump with their eyes wide open.

The idea that misinformation was to blame for everything was a distraction too. For media outlets, narrow fact-checking is an attractive business, easily delivering crisp conclusions. But while fact-checking is important, it can also amplify misinformation when it is clumsily done. Even when elegantly performed, it can pull the spotlight away from the key issues. This was a central story of the Brexit referendum campaign, when disproportionate attention was paid to the issue of how much money the UK really sent to the EU, and not enough attention was paid to the knotty policy questions that emerged only after the voters had spoken.

The third and most important problem with the narrative that misinformation is all around us? It’s not true. A recent article in Nature by Ceren Budak, Brendan Nyhan, David M Rothschild, Emily Thorson and Duncan J Watts argues that the commentariat talks about misinformation in a way that is increasingly divorced from rigorous evidence.

For example: how much misinformation is there, and in front of whose eyes is it being placed? Here, there is a stark contrast between perception and reality. Researchers constructed a list of nearly 500 “untrustworthy” websites operating in 2016, but of all the visits made to news sites by US citizens in 2016, this long list of dubious sources explains less than 6 per cent. Other researchers use different methods but reach similar conclusions: extremist content and deceptive news stories are not negligible, but represent a small slice of what people are watching and reading.

It’s fair to say that 6 per cent is a higher proportion than anyone would want, but the figure is much lower than people seem to fear. A Gallup study in 2018 found that US adults believe 65 per cent of news on social media is misinformation. That suggests to me that we should be less concerned about people falling for fake news stories and more worried that ordinary citizens are cynical about stories that are trustworthy.

Not only does misinformation represent a small fraction of online traffic, it is a small fraction which disproportionately attracts a small minority. A paper published in Science in 2019 by Nir Grinberg, Lisa Friedland and others examined Twitter behaviour during the 2016 election and concluded that “only 1 per cent of individuals accounted for 80 per cent of fake news source exposures . . . individuals most likely to engage with fake news sources were conservative leaning, older, and highly engaged with political news”. In other words, the audience for fake news on Twitter in 2016 was a tiny minority of users, most of whom would have voted for Trump in any case.

None of this is to suggest that misinformation is a trivial problem. If 5 or 10 per cent of social media “news” is wrong, that’s a serious concern. I warned last summer that a classic disinformation tactic is to blame a real heinous crime on an entirely innocent group — exactly the kind of lies that circulated after the murder of children in Southport. Lies that circulate among a small minority can still do a lot of harm, especially if that minority enthusiastically turns to intimidation and violence.

And I remain worried about the possibility of a co-ordinated disinformation attack, which if well-timed and well-aimed could swing a close election, and which demands forethought and defensive measures that liberal democracies have been slow to embrace.

These problems are all real. But they require focused attention, not pearl-clutching about fake news. Most of us only hear about the latest online lies because they are being repeated by political elites, or by mainstream news sources — sometimes in a well-meaning but risky “fact-checking” exercise. When it comes to misinformation, social media companies surely have a case to answer. But they are not the only ones who should be looking in the mirror.

Written for and first published in the Financial Times on 30 August 2024.

Loyal readers might enjoy the book that started it all, The Undercover Economist.

I’ve set up a storefront on Bookshop in the United States and the United Kingdom. Links to Bookshop and Amazon may generate referral fees.