Tim Harford The Undercover Economist

Undercover EconomistUndercover Economist

My weekly column in the Financial Times on Saturdays, explaining the economic ideas around us every day. This column was inspired by my book and began in 2005.

Undercover Economist

We’re actually decent people in a crisis – and stories claiming otherwise do harm

First there was the panic buying. Then came the selfish, reckless refusal to maintain physical distance: the beach parties in Florida and the house parties in Manchester; the 500-mile round trip to admire the Lake District and the mass sun-worshipping in London parks. And there’s worse: the scam artists; the people who use coughing as an assault; the thieves who loot medical supplies from hospitals.

These coronavirus stories perpetuate a grim view of human nature. That grim view is mistaken, a persistent and counterproductive myth. There are some terrible people in the world, and some ordinary people behaving in a terrible way, but they make headlines precisely because they are rare. Look more closely and the evidence for mass selfishness is extremely thin.

Start with the reports of panic buying, which for many people were the first glimmers of the trouble that lay in store. By the middle of March in the UK, the newspapers were full of stories about shortages of toilet paper, flour and pasta. The natural assumption was that we were a nation of locusts, stripping the supermarkets as we selfishly piled shopping carts high with produce.

But Kantar, a consultancy, told me that a mere 3 per cent of shoppers had bought “extraordinary amounts” of pasta. Most of us were merely adjusting our habits to life spent away from restaurants, sandwich bars and offices with their own loo paper. We all went shopping a bit more often, and when we did, spent a little more. No cause for collective shame, but it was enough to strain supermarket supply chains.

What about those who ignore pleas to keep their distance? Again, the misdeeds are exaggerated. Lambeth council grumpily closed Brockwell Park in south London, complaining of 3,000 visitors in a single day — not mentioning that the park might easily see 10 times that number on a normal sunny Saturday, nor that taking exercise in a park is perfectly permissible.

Exaggerating problems might drive web traffic or make zealous officials feel important, but these tales of misbehaviour are likely to be counterproductive. If we are told that others are acting selfishly, we feel inclined to be selfish, too. As Yossarian of Catch-22 put it, “I’d certainly be a damned fool to feel any other way, wouldn’t I?”

The psychologist Robert Cialdini has, with colleagues, studied this insight in the Petrified Forest National Park in Arizona. When visitors were told that the forest was being endangered because others were stealing petrified wood, they stole too. When tourists were told — truthfully — that the vast majority of visitors were leaving the wood untouched, they did likewise I would not be at all shocked to learn that scolding reports of sunbathing only encourage more of us to sunbathe.

The surprising truth is that people tend to be­have decently in a crisis. To the British, the all-too-familiar example is the cheerful demeanour of Londoners during the Blitz. In hindsight that seems natural. But Rutger Bregman’s forthcoming book Humankind points out that in the 1930s Winston Churchill and others feared pandemonium if London was attacked from the air. Britons failed to take this lesson to heart: they assumed that when German cities were bombed, German civilians would crack. They didn’t. These myths have fatal consequences.

Nor is calm co-operativeness restricted to times of war. In the wake of a catastrophic earthquake in Turkey in 1999, the emergency relief expert Claude de Ville de Goyet berated media organisations for propagating what he called “disaster myths”. “While isolated cases of antisocial behavior exist,” he wrote, “the majority of people respond spontaneously and generously.”

The writer Dan Gardner, who punctured the disaster myth in a series of viral tweets, was repeatedly rebutted by people who regarded New Orleans after Hurricane Katrina as a potent counter-example.

That only underlines the malevolence of the myth. At the time, rumours ran wild about the murder and rape of children inside the Louisiana Superdome; but when the national guard showed up, armed and prepared for pitched battle, they were met instead by a nurse asking for medical supplies. Fear of civil disorder may well have caused more harm than the civil disorder itself — as when people trying to walk out of New Orleans across the bridge to nearby Gretna were turned back by armed police.

This pandemic has no exact precedents, but the evidence from past disasters suggests that we should expect more of each other. Many people and businesses took voluntary action on social distancing while both the British and US governments dithered; the UK administration was also surprised by how many people quickly volunteered to help with transport and supplies for vulnerable people.

We can be both nimble and altruistic, and perhaps the authorities should start taking that into account in their future policies. Given clear guidance as to the best thing to do, most of us try to do it.

Rebecca Solnit wrote in A Paradise Made In Hell: “What you believe shapes how you act.” Let’s start by believing in each other; kind acts will follow.

Written for and first published in the Financial Times on 17 April 2020.

My NEW book The Next Fifty Things That Made the Modern Economy is out in the UK in May and available to pre-order; please consider doing so online or at your local bookshop – pre-orders help other people find the book and are a BIG help.

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Undercover Economist

For peace of mind in the pandemic, let go of impossible To Do lists

Nearly a century ago there was a grand café near the University of Berlin. Academic psychologists who took lunch there marvelled at the memory of one of the waiters: no matter how large the group and how complex the order, he could keep it all in his head. Then one day, or so the story goes, someone left a coat behind. He hurried back into the café, only to find that the waiter didn’t remember him. This feat of amnesia seemed almost as remarkable as the feat of recollection that had preceded it. But the waiter had no trouble explaining the discrepancy: “When the order has been completed, then I can forget it.”

Two of the psychologists in the group, Kurt Lewin and Bluma Zeigarnik, decided to investigate. In 1927, Zeigarnik published research demonstrating that people had a much greater recall of uncompleted tasks than completed ones — a finding that became known at the Zeigarnik effect. Do you lie awake at night churning through everything you’ve promised yourself you’ll do? That’s the Zeigarnik effect tormenting you. The blessed release of forgetting comes only when you, like the waiter, know the task is complete.

That brings me to the pandemic, which has done nothing to reduce the number of our sleepless nights. Some of us have children to homeschool. Some of us have elderly relatives to worry about; some of us are the elderly relatives in question. Some of us have never been busier; others have already lost their jobs. One experience is common, however: wherever the virus has started to spread, life is being turned upside down.

It’s a strange time, but some of the anxiety can be soothed by harnessing the Zeigarnik effect. Our stress levels are rising in part because that long list of things to do that we all carry around — on paper, digitally, or in our heads — has been radically rearranged. It’s as though the Berlin waiter had, mid-order, been asked also to chop onions, answer the phone and draft a shopping list.

Simple jobs such as getting a haircut or buying toilet paper now require planning. Paperwork has multiplied, from claiming refunds on cancelled holidays to writing letters of condolence. Many of us have intimidating new responsibilities, notably the guilt-inducing task of organising our children’s home schooling. In many cases, the old tasks haven’t even been cancelled, merely postponed, with delivery dates to be confirmed. Our subconscious keeps interrupting with reminders of incomplete — sometimes incompletable — tasks. No wonder we feel anxious.

Fortunately, the psychologists E J Masicampo and Roy Baumeister have found that a task doesn’t have to have been completed to trigger that pleasant slate-wiping forgetfulness. Making a clear plan for what to do next will also work. That Berlin waiter could have saved some of his mental energy if he had decided to write everything down. So, to harness the Zeigarnik effect to keep your sanity in a lockdown, get your to-do list in order.

Start with a piece of paper. Make a list of all the projects that are on your mind. David Allen, author of the cult productivity manual Getting Things Done, defines a project as “any multistep outcome that can be completed within a year” — anything from trying to source weekly groceries to finding a new job.

That list should have three kinds of projects on it. First, there are the old projects that make no sense in the new world. Write down the mothballed tasks and file them away; you’ll see them on the other side. Other tasks will disappear forever. Say your goodbyes. Ten seconds of marking the fact that the project has been obliterated may banish a vague sense of unease in the long run.

Then there are the existing projects, some of which have become more complicated — like that haircut. Again, a few moments with a pen and paper will often tell you all you need to know: What’s changed? What do I now need to do? What, specifically, is the next step? Write all that down.

Third, there are brand new projects: set up a home office; keep the children busy and entertained; help out vulnerable neighbours. In each case, the drill is the same: sketch out the project, ask yourself what is the very next action that needs taking, and write it down.

Occasionally, you may encounter something that’s on your mind that has no feasible next step. Some people fret about the fate of western civilisation. I worry about an elderly relative, suffering dementia in a locked-down nursing home and unable to comprehend a video chat. If there is literally nothing to be done except to wait and hope, acknowledging that can itself be a useful step.

I won’t pretend that in this frightening time all anxiety will be banished by clarifying a to-do list. It won’t. But you may be surprised at how much mental energy the process saves. There will be no convivial meals at any grand cafés for a while; the sooner we can acknowledge that, the sooner we can mentally unclench our grip on that half-completed order for lunch.


 Written for and first published in the Financial Times on 10 April 2020.

My NEW book The Next Fifty Things That Made the Modern Economy is out in the UK in May and available to pre-order; please consider doing so online or at your local bookshop – pre-orders help other people find the book and are a huge help.

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Undercover Economist

How do we value a statistical life?

The coronavirus lockdown is saving lives but destroying livelihoods. Is it worth it? I’ve been accused of ignoring its costs. For an economist, this is fighting talk. Love us or hate us, thinking about uncomfortable trade-offs is what we economists do.

Three points should be obvious. First, we need an exit strategy from the lockdowns — a better strategy than President Donald Trump’s, “One day it’s like a miracle, it will disappear.” Expanding emergency capacity, discovering better treatments, testing for infection and testing for antibodies could all be part of the solution, along with a vaccine in the longer term.

Second, the economic costs of any lockdown need to be compared with the costs of alternative policies, rather than the unachievable benchmark of a world in which the virus had never existed.

Third, the worth of a human life is not up for discussion. The man who persuaded me not to quit economics, Peter Sinclair, died on 31 March after contracting Covid-19. He was a man of unlimited kindness, and I shall miss him very much. His life, like the life of any named individual, was priceless.

Yet no matter how much we want to turn our gaze away from the question, it hangs there insistently: is this all worth it?

We spend money to save lives all the time — by building fire stations, imposing safety regulations and subsidising medical research. There is always a point at which we decide we have spent enough. We don’t like to think about that, but better to think than to act thoughtlessly. So what are we willing to sacrifice, economically, to save a life?

A 1950 study for the US Air Force ducked this question, recommending a suicidal military strategy that valued pilots’ lives at precisely zero. Other early attempts valued lives by the loss of earnings that an early death would cause — effectively making retired people worthless, and the death of a child costly only if the child could not be replaced by a new baby.

The late Thomas Schelling, a Nobel Prize-winning economist, mocked these errors as he imagined the death of a family breadwinner like himself: “His family will miss him, and it will miss his earnings. We do not know which of the two in the end it will miss most, and if he died recently this is a disagreeable time to inquire.”

There must be a better way to weigh the choices that must be weighed. But how? Schelling suggested focusing not on the value of life, but on the value of averting deaths — of reducing risks. A life may be priceless, but our actions tell us that a statistical life is not. The engineer Ronald Howard has proposed a convenient unit, the “micromort” — a one-in-a-million risk of death.

Implicitly, we constantly weigh up small risks of death and decide if they are worth it. Despite inconsistencies and blind spots in our behaviour, we value reducing risks to our own lives very highly, but not infinitely so. We vote for governments that hold our lives in similarly high regard. For example, the US Environmental Protection Agency values a statistical life at nearly $10m in today’s money, or $10 per micromort averted. I have seen lower numbers, and higher.

I am giving most of my figures as conveniently round numbers — there is too much uncertainty about Covid-19 to be more precise. But if we presume that 1 per cent of infections are fatal, then it is a 10,000 micromort condition. Being infected is 100 times more dangerous than giving birth, or as perilous as travelling two and a half times around the world on a motorbike. For an elderly or vulnerable person, it is much more risky than that. At the EPA’s $10 per micromort, it would be worth spending $100,000 to prevent a single infection with Covid-19.

You don’t need a complex epidemiological model to predict that if we take no serious steps to halt the spread of the virus, more than half the world is likely to contract it. That suggests 2m US deaths and 500,000 in Britain — assuming, again, a 1 per cent fatality rate. If an economic lockdown in the US saves most of these lives, and costs less than $20tn, then it would seem to be value for money. (By way of comparison, each 20 per cent loss of gross domestic product for a quarter represents a cost of about $1tn.)

One could quibble with every step of this calculation. Perhaps some of those who die were so ill that they would have died of other causes within days. Perhaps Covid-19 is not quite so dangerous. Yet it is clear that with so many lives at stake, we should be willing to pay huge costs to protect them.

We must remember something else: the risk of being wrong. We will inevitably make mistakes. The measures we take to contain coronavirus might do more damage to people’s livelihoods than necessary. Or we might allow the virus too much leeway, needlessly ending lives. In a spreading pandemic, the second mistake is much harder to repair than the first.

Fighting this virus demands economic sacrifices: not without limit; and not without end. But if not now, then when?


Written for and first published in the Financial Times on 03 April 2020.

My NEW book The Next Fifty Things That Made the Modern Economy is out in the UK in May and available to pre-order; please consider doing so online or at your local bookshop – pre-orders help other people find the book and are a huge help.

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Undercover Economist

Can we contain viral misinformation about coronavirus?

Is there anything we can do to contain the spread? I’m not talking about coronavirus. I’m talking about the misinformation.

The UK’s Daily Express has suggested that the World Health Organization has long known about the disease known as Covid-19. (It hasn’t: it just talked about a hypothetical pandemic scenario involving an equally hypothetical Disease X.) Other newspapers asked if satellite images showed mass cremations of Covid-19 victims. (No.)

In Kenya, audio from a training exercise was widely shared on WhatsApp, leading people to confuse the simulation with reality. Everywhere, social media posts peddle snake oil and trade in conspiracy theories.

A popular Facebook image shows that Dettol’s label claims to kill coronavirus and asks, were they forewarned? Maybe — although it would be quite the bioweapon conspiracy if a bunch of incompetent label designers were in the loop. A more plausible explanation is that “coronavirus” also applies to the viruses that cause Mers, Sars and indeed some varieties of the common cold.

It is important not to exaggerate the reach of such stories but they are too popular for comfort. They are smeared around the information ecosystem by a combination of fear, a mistaken desire to help, the gossip instinct and, perhaps most important, a belief that official sources aren’t telling us the truth.

A few weeks ago, for example, a reader wrote to me: “Whilst the ‘official’ death rate for the coronavirus is repeatedly stated in the media as being 2 per cent, I believe this is a false statistic . . . the real death rate is somewhere between 6 per cent and 18 per cent. IT IS CERTAINLY NOT 2 per cent!” He even added a spreadsheet.

My instinctive reaction was the opposite of those spreading the misinformation: that if the death rate was that high, we’d know about it. And indeed, when I spoke to epidemiologist Nathalie MacDermott of King’s College London, she reassured me that my reader’s otherwise-rigorous spreadsheet had missed a detail which explained his alarming conclusion: some cases are so mild that they never reach the notice of medical professionals.

What stuck with me was an intelligent reader’s mistrust of the “official” number. The Chinese authorities may well have reasons to fear the truth, but there is no reason to believe international experts are engaged in a cover-up. Experts can be corrupt or mistaken, and sometimes one must look behind a curtain of official denial. Yet in technical matters such as the danger of Covid-19, an epidemiologist is far more likely to be right than our untutored intuitions.

There are plenty of paranoid conspiracies about Covid-19 circulating on social media — check the website of Full Fact, a UK-based fact-checking organisation, for a selection. They are just a small sample of the falsehoods circulating on all topics. Sometimes they are an attempt to get clicks and thus revenue; sometimes it is deliberate disinformation designed to skew political debate or drown out the truth; sometimes untrue ideas are just catchy. Can we contain all this misinformation any more than we are containing the new coronavirus?

The theory that ideas spread, mutate and evolve much like a living organism — or a virus — was popularised by the evolutionary biologist Richard Dawkins, who in 1976 coined the word “meme” as an analogue to “gene”. The possibility of ideas “going viral” was radical in the 1970s. Now it is a cliché — but it is still instructive.

The sudden interest in the disease, for example, has given new life to dormant posts promoting herbal cures for coronaviruses. Strange ideas mutate and multiply in their own niches, such as social media groups favouring vaccine conspiracies or the idea that mobile phones make you sick. Such groups are inclined to disbelieve the official version of anything.

It is tempting to dream that a grand plan can contain both problems. We hope a new law, or a change in Facebook’s algorithm, will dispel lies — just as we hope that Covid-19 can be foiled by quarantine (ideally of other people) or by the miraculous appearance of a working vaccine.

Such top-down moves can help. A society with strong health services is in a better position to face a pandemic; similarly we can strengthen our institutions against misinformation. Facebook announced this week that it will be “removing false claims and conspiracy theories” — late in the day. But the company has long worked with fact-checkers such as Full Fact to flag false stories.

Yet ultimately, a resilient society needs to practice some bottom-up hygiene, if that is not an unfortunate phrase. To deal with a virus, we should wash our hands and try not to touch our faces. Similarly, the strongest defences against misinformation are people less given to paranoia and to sharing ideas without thinking. We should all stop and reflect before circulating alarming claims. Count to 10, and ask yourself whether this is really the best thing to amplify. Whether fighting a virus, or a viral scare story, each one of us needs to erect small barriers to slow the contagion. Alone, those barriers may seem trivial. Collectively, they work.

Written for and first published in the Financial Times on 06 March 2020.

My NEW book The Next Fifty Things That Made the Modern Economy is out in the UK in May and available to pre-order; please consider doing so online or at your local bookshop – pre-orders help other people find the book and are a BIG help.

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Undercover Economist

Why it’s too tempting to believe good news about the coronavirus

Wishful thinking is a powerful thing. When I read about a new disease-modelling study from the University of Oxford, I desperately wanted to believe. It is the most prominent exploration of the “tip-of-the-iceberg hypothesis”, which suggests that the majority of coronavirus infections are so mild as to have passed unrecorded by the authorities and perhaps even un­noticed by the people infected.

If true, many of us — perhaps most of us in Europe — have already had the virus and probably developed some degree of immunity. If true, the lockdowns have served a valuable purpose in easing an overwhelming strain on intensive care units, but they will soon become unnecessary. If true.

But is it true? If it is, it stands in stark contrast to the far grimmer modelling from a group at Imperial College London, which concluded that if the epidemic was not aggressively contained, half a million people would die in the UK — and more than 2m in the US. Models such as this one helped to persuade the British government to follow much of continental Europe in putting the economy into a coma.

The differing perspectives are made possible by the fact that the data we have so far are not very good. Testing has been sporadic — in some places, shambolic — and everyone agrees that large numbers of cases never reach official notice. We do have solid statistics about deaths, and as the epidemiologist Adam Kucharski, author of The Rules of Contagion, observes, a wide variety of scenarios are consistent with the deaths we’ve seen so far. Perhaps Covid-19 is uncommon and deadly; perhaps it is ubiquitous and kills only a tiny proportion of those it affects. Deaths alone cannot tell us.

This uncertainty is unnerving. John Ioannidis, an iconoclastic epidemiologist, wrote on March 17 that Covid-19 “might be a one-in-a-century evidence fiasco”. Prof Ioannidis’s argument is that some infections are being missed, and we have little idea how many. Therefore we have little idea how deadly Covid-19 really is.

He speculates that the fatality rate could plausibly lie between one in 100 and one in 2,000 cases. Either way, it is dangerous; but the difference is vast. And if the scale of our ignorance about coronavirus may seem hard to swallow, bear in mind that the fatality rate for the H1N1 swine flu pandemic in 2009 was still being debated years later.

Prof Ioannidis has form: 15 years ago he published a study with the title “Why Most Published Research Findings Are False”. That claim seemed outrageous at the time, but subsequent efforts to reproduce famous experiments in psychology have revealed that he was on to something important. We know less than we think.

But we are not completely ignorant. Alongside the death total, there are other clues to the truth. For example, thousands of people were evacuated from Wuhan city in late January and February and most of them were tested. A few tested positive and several were indeed symptom-free, but not the large majority that the Oxford version of the tip-of-the-iceberg hypothesis would imply.

The entire population of the town of Vò in Italy was repeatedly tested and, while half of the positive cases were asymptomatic, that is still much less than the Oxford model might lead us to expect.

So while it is possible that most of us could have been infected without ever knowing — and that herd immunity is within easy reach — it is not likely. That may explain why neutral experts have responded to the Oxford study with caution, and some concern that it might provoke a reckless response from individuals or policymakers.

So, what now? First: stay indoors if you want to save many lives and prevent health systems from being overwhelmed. The bitter experience of Italy and Spain demonstrates the importance of flattening the peak of the epidemic. That remains true even if, as we might hope, the epidemic is much milder and more widespread than we currently believe. It might have been tempting to wait and gather more evidence — but faced with an exponentially rising pile of corpses, “wait and see” is not an option.

Second: health systems should expand capacity, buying more ventilators and more protective equipment for doctors and nurses. In all but the most optimistic scenarios we will need them now, we will need them later in the year and we will need them from time to time in the future. This crisis is teaching us that we should have had more spare capacity all along, despite the cost.

Third: test, test, test — and not only using the current tests to detect infection, but new ones for antibodies that should show whether people have already had the virus and have developed some degree of immunity. Sunetra Gupta, a professor on the Oxford team, says that such tests may start to produce results in a matter of days.

The epidemiologists are doing their best, but they are not omniscient. They need facts with which to work. Gathering those facts systematically is one of many urgent tasks ahead of us.


Written for and first published in the Financial Times on 27 March 2020.

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Undercover Economist

Why the crisis is a test of our capacity to adapt

“It’s really quiet,” said the proprietor of Oxford’s best falafel stall when I popped over to buy lunch on Monday. It is even quieter now. Meanwhile, my wife emailed friends to ask if we could help: both of them are doctors and they have three children and a parent undergoing treatment for cancer. “Thanks We will be in touch,” came the reply. No time for more. It may be quiet for the falafel man, but not for them.

There, in miniature, is the economic problem that the coronavirus pandemic has caused, even in its early stages. For everyone who is overworked, someone else has little to do but wait. The supermarkets have struggled to meet a rush of demand for some goods, but that should pass. “We are not going to run out of food, so chill,” Yossi Sheffi tells me. He’s an MIT professor and an authority on supply chains.

While the pressure on the supermarkets may ease, the strain on the healthcare system will not. It is already intense and will get much worse. Yet while clinicians are overstretched, others wonder when the next job is coming from. From the falafel seller to the celebrity chef, the hotel porter to the millionaire motivational speaker, many tens of millions of people around the world are fit and eager to work, yet unable to.

This is a test of flexibility and imagination. Gourmet restaurants are shifting to takeaway service; conference speakers are building portable studios. Best of all is when we find ways to turn idle resources into weapons in the fight against the virus. It is hard not to cheer when reading tales of distillers turning their stills to the task of producing hand sanitiser, or hoteliers offering their empty rooms to doctors and nurses.

But it is a much tougher task, for example, to make more urgently needed ventilators. In the mid-20th century, William Morris, a man who made his fortune manufacturing British cars, turned his workshops to the task of producing “iron lungs” for people paralysed by polio. It’s an inspiring precedent for his successors at Meggitt, McLaren and Nissan scrambling to emulate him by building ventilators to use in the current crisis, but it took time.

Prof Sheffi reckons that it would be straightforward for, say, an automobile parts supplier to retool in a matter of months, and having many thousands of extra ventilators by the autumn would certainly be better than nothing. But to produce complex equipment from scratch in weeks, perhaps using 3D printing, would be a miraculous achievement even if regulations are loosened, as they should be.

Yet harder is to find more nurses and doctors; intensive care units do not operate themselves. And even for less specialist staff, the task is larger than it might seem because of what the late Thomas Schelling, a Nobel laureate economist, called “the acceleration principle”. Let’s say that Europe has 10m hospital orderlies, with an annual turnover of 30 per cent. That means 3m need to be trained each year, 1m at a time on a four-month training course.

Now let us aim to expand gently to 11m over the next four months. It doesn’t sound much — just a 10 per cent increase. Yet the training programme must double in scale to accommodate it, because now 2m rather than 1m orderlies are enrolled in the same four-month window. The same logic applies to anything we need more of, from the personal protective equipment that is in desperately short supply in our hospitals, to the internet bandwidth that we will all be using more of, while working from home.

The task, then, is immense. But we must try. Under any conceivable scenario, we would not regret trying to expand emergency medical care several times over. If it is impossible, so be it. But if it is merely expensive and difficult, such costs are trivial compared to the costs of suspending everyday life for weeks or months.

And there is some hope: efforts are already under way to persuade doctors and nurses who have retired or switched careers to return, and to put medical students to work at once. We could quickly train new medical support staff to perform focused and limited roles. I can only imagine the breadth of the skills needed to be an intensive care nurse, but if we cannot have more experienced nurses with complex skills, let us at least support them with people who can quickly be trained to change an oxygen tank or turn a patient in bed.

Even those apparently ill-suited to intensive care duty — the 75-year-old retired doctor, the community volunteer with first aid training, or even furloughed airline crews — could indirectly support health systems. While medical professionals staff the wards, I would gladly pay taxes to fund online advice from a retired doctor, a virus test administered by an air steward, or stitches and bandages from a St John Ambulance volunteer.

Killing two birds with one stone never sounded easy to me. But there is no excuse now not to be radical. This crisis is a test of many things. Not least among them is our capacity to adapt.


Written for and first published in the Financial Times on 20 March 2020.

My NEW book The Next Fifty Things That Made the Modern Economy is out in the UK in May and available to pre-order; please consider doing so online or at your local bookshop – pre-orders help other people find the book and are a huge help.

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Will economists ever be as good at forecasting as meteorologists?

The UK’s national weather service, the Met Office, is to get a £1.2bn computer to help with its forecasting activities. That is a lot of silicon. My instinctive response was: when do we economists get one?

People may grumble about the weather forecast, but in many places we take its accuracy for granted. When we ask our phones about tomorrow’s weather, we act as though we are gazing through a window into the future. Nobody treats the latest forecasts from the Bank of England or the IMF as a window into anything.

That is partly because politics gets in the way. On the issue of Brexit, for example, extreme forecasts from partisans attracted attention, while independent mainstream forecasters have proved to be pretty much on the money. Few people stopped to praise the economic bean-counters.

Economists might also protest that nobody asks them to forecast economic activity tomorrow or even next week; they are asked to describe the prospects for the next year or so. True, some almanacs offer long-range weather forecasts based on methods that are secret, arcane, or both — but the professionals regard such attempts as laughable.

Enough excuses; economists deserve few prizes for prediction. Prakash Loungani of the IMF has conducted several reviews of mainstream forecasts, finding them dismally likely to miss recessions. Economists are not very good at seeing into the future — to the extent that most argue forecasting is simply none of their business. The weather forecasters are good, and getting better all the time. Could we economists do as well with a couple of billion dollars’ worth of kit, or is something else lacking?

The question seemed worth exploring to me, so I picked up Andrew Blum’s recent book, The Weather Machine, to understand what meteorologists actually do and how they do it. I realised quickly that a weather forecast is intimately connected to a map in a way that an economic forecast is not.

Without wishing to oversimplify the remarkable science of meteorology, one part of the game is straightforward: if it’s raining to the west of you and the wind is blowing from the west, you can expect rain soon. Weather forecasts begin with weather observations: the more observations, the better.

In the 1850s, the Smithsonian Institution in Washington DC used reports from telegraph operators to patch together local downpours into a national weather map. More than a century and a half later, economists still lack high-definition, high-frequency maps of the economic weather, although we are starting to see how they might be possible, tapping into data from satellites and digital payments. An example is an attempt — published in 2012 — by a large team of economists to build a simulation of the Washington DC housing market as a complex system. It seems a long way from a full understanding of the economy, but then the Smithsonian’s paper map was a long way from a proper weather forecast, too.

Weather forecasters could argue that they have a better theory of atmospheric conditions than economists have of the economy. It was all sketched out in 1904 by the Norwegian mathematician Vilhelm Bjerknes, who published “The problem of weather prediction”, an academic paper describing the circulation of masses of air. If you knew the density, pressure, temperature, humidity and the velocity of the air in three dimensions, and plugged the results into Bjerknes’s formulas, you would be on the way to a respectable weather forecast — if only you could solve those computationally-demanding equations. The processing power to do so was to arrive many decades later.

The missing pieces, then: much better, more detailed and more frequent data. Better theory too, perhaps — although it is striking that many critiques of the economic mainstream seem to have little interest in high-resolution, high frequency data. Instead, they propose replacing one broad theory with another broad theory: the latest one I have seen emphasises “the energy cost of energy”. I am not sure that is the path to progress.

The weather forecasters have another advantage: a habit of relentless improvement in the face of frequent feedback. Every morning’s forecast is a hypothesis to be tested. Every evening that hypothesis has been confirmed or refuted. If the economy offered similar daily lessons, economists might be quicker to learn. All these elements are linked. If we had more detailed data we might formulate more detailed theories, building an economic map from the bottom up rather than from the top down. And if we had more frequent feedback, we could test theories more often, making economics more empirical and less ideological.

And yet — does anyone really want to spend a billion pounds on an economic simulation that will accurately predict the economic weather next week? Perhaps the limitations of economic forecasting reflect the limitations of the economics profession. Or perhaps the problem really is intractable.

Written for and first published in the Financial Times on 21 February 2020.

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Undercover Economist

Why moonshots matter

Tim Bradshaw, head of the Russell Group of leading UK universities, has a curious tale to tell about failure. A few years ago he visited the Cambridge office of an admired Japanese company to find them fretting about the success rate of their research and development. At 70 per cent, it was far too high: the research teams had been risk-averse, pursuing easy wins at the expense of more radical and risky long-shots.

The late Marty Sklar, a Disney veteran, once told me a similar tale — if his colleagues weren’t failing at half of their endeavours, they weren’t being brave or creative enough. My boss at the World Bank 15 years ago had the same worry that too many projects were succeeding.

When the same concern arises in such wildly different contexts, we may be worrying about a common problem: a systematic preference for marginal gains over long shots. It’s not hard to see why. It is much more pleasant to experience a steady trickle of small successes than a long drought while waiting for a flood that may never come.

While marginal gains add up, they need to be refreshed by the occasional long-shot breakthrough. Major innovations such as the electric motor, the photo­voltaic cell or the mobile phone open up new territories that the marginal-gains innovators can then explore.

With this in mind, it’s hard not to sympathise with the UK Conservative party’s promise to establish “a new agency for high-risk, high-pay-off research, at arm’s length from government” — a British version of the much-admired US Defense Advanced Projects Research Agency.

Originally known as Arpa, now Darpa, it is most famous for creating Arpanet, the precursor to the internet. It also supported early research into satellite navigation and the windows-and-mouse system for operating a computer. And it helped to catalyse interest in self-driving cars. With successes like that, nobody seems to mind that Arpa’s failure rate is often said to be around 85 per cent. High-risk, high-pay-off indeed.

A collection of essays published recently by the think-tank Policy Exchange concurs that we need an Arpa for the UK. I’ve long argued for the importance of long-shots — the subtitle of one of my books is “why success always starts with failure” — so I can’t help but agree. Yet if this was easy, the UK would have an Arpa already.

At the casino it is easy to double the rewards by doubling the risk, but in the world of research, the trade-off is not so straightforward. While a low failure rate may indeed signal a lack of originality and ambition, we cannot simply decide to fail more often in the hope that originality will follow.

Arpa itself has approached this problem by hiring high-quality scientists for short stints — often two or three years — and giving them control over a programme budget to commission research from any source they wish.

Meanwhile, the Howard Hughes Medical Institute, a foundation, deliberately looks for projects with an unusual or untried approach, but a large potential pay-off. One study suggested that HHMI gets what it pays for — more failures, but larger successes, compared with other grant-makers funding researchers of a similar calibre.

Another large obstacle looms: how long will politicians find failure to be a sign of boldness and originality? Eventually, they will simply call it failure. Now that Arpa has a 62-year record, it is easy to forget that the agency was initially written off by some critics.

A new UK agency will face pressure to deliver. That sits uneasily with the desire to support risk-taking. Consider Arpa’s younger sibling, Arpa-E, created in 2009 to fund new energy projects. As of this week, the section of the Wikipedia entry on Arpa-E entitled “Accomplishments” is empty. Ouch.

The problem is more acute for a UK Arpa, because it is likely to have less funding — perhaps £200m a year. Is that enough? When Arpa’s head Charles Herzfeld heard the initial pitch for the proto-internet, in 1965, he responded, “Great idea . . . Get it going. You’ve got a million dollars more in your budget right now. Go.”

That is $10m-$30m in today’s money — depending on how one adjusts for spending power. It is hard to imagine a modern-day Herzfeld blowing a tenth of the UK-Arpa’s budget after a 20-minute meeting. We are on the Triceratops-horns of a trilemma. Be cautious, or fund lots of risky but tiny projects, or fund a few big, risky projects from a modest budget and accept that every single one may flop.

Keeping this new agency “at arm’s-length from government” is essential. Indeed, Safi Bahcall — the author of Loonshots — persuasively argues that such agencies need to be at arm’s length not just from government but from everybody. Yet somehow they must focus on real, practical, front-line problems. Not too close, not too distant. Not too many successes, but not too many failures, either. It’s quite a balancing act. Still, I’d pay for a ticket to this circus. Let’s give it a try.

Written for and first published in the Financial Times on 14 February 2020.

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Undercover Economist

The statistics behind the spread of ideas

Everyone loves a good idea. It’s even better when the idea becomes a tangible innovation, a better mousetrap that anyone can use and every mouse should fear. The awkward truth, however, is that even in a polished form, good ideas can be slow to spread.

Anaesthetic and antiseptic offer an instructive contrast. Both were developed in the mid-1800s. Anaesthetic spread faster than a hula-hooping craze. Atul Gawande explained in the New Yorker, “within seven years, virtually every hospital in America and Britain had adopted the new discovery”. Antiseptic, in contrast, took a generation to catch on.

“The puzzle is why,” noted Dr Gawande, before conceding that it is not a puzzle at all. Anaesthetic solves an immediate problem: a patient screaming and writhing in agony. Antiseptic is a defence against an invisible killer, infection, that acts only with a delay.

Unfortunately, many innovations are more like antiseptic than anaesthetic: they solve problems that can only be seen through a statistical lens. People are slow to embrace what they cannot see. A few years ago, researchers at the OECD looking at the diffusion of global productivity gains concluded that there was a growing gap between productive companies and the laggards. The gulf was huge — typically a fivefold productivity gap per worker, even after adjusting for differences in the equipment available.

Whether the innovation is a hardier variety of seed, a safer pharmaceutical compound or a more reliable manufacturing process, the benefits will rarely be as obvious as slumbering through surgery. Such ideas often spread all too slowly.

There are other barriers to the diffusion of innovation. If people feel they can’t adapt a new idea to their own purposes, or try it out on a small scale, they will resist. One major obstacle is social: evangelists for innovation are often rather different kinds of people from their audience. Agronomists are not farmers; pharmaceutical sales representatives are not general practice doctors; inventors are different from the rest of us. We will gladly imitate our peers, although that still raises the question of who will go first. One influential early study of hybrid corn in Iowa between 1926 and 1941 found that a few farmers would experiment with the new seed in small quantities to see how things worked out. Even the early adopters took things cautiously, while others watched. Farmers would then eventually copy their neighbours.

It is tempting to shrug and conclude that this is simply a tough problem. But there is no need to despair. Late last year, the British Medical Journal published a study that caught my attention, in part because of the cross-disciplinary team of authors: Alex Walker and Ben Goldacre (epidemiologists), Felix Pretis (an economist) and Anna Powell-Smith (a data scientist) — but also because those authors were looking at the diffusion of innovation in an innovative way.

The study examined how quickly National Health Service general practice clinics in England caught up with best practice in prescribing two types of drug. In one case, the birth-control pill Cerazette came off patent in 2012, at which point patients should generally have been prescribed cheaper generic versions of the drug, desogestrel. In the other, national guidelines were changed to recommend a different antibiotic for urinary tract infections.

NHS England publishes anonymised data, every month, describing the drugs being prescribed by GPs across 8,000 clinics. If you have time, you can noodle around on OpenPrescribing.net — a platform developed by Ms Powell-Smith and Dr Goldacre — looking for patterns.

And since that sounds like hard work, the BMJ study uses a statistical tool to spot whenever a clinic seems to have changed its clinical practice, and whether they did so promptly or gradually, or suddenly but after a delay, or not at all. The patterns are clear to the naked eye once pulled out of the mass of data: here’s a clinic that swiftly and sharply switched to the cheaper generic drug; here’s a clinic that never read the email. A follow-up study performs a similar analysis for statins.

What’s remarkable about all this is how unremarkable it really is. The diffusion of innovation could once only be studied in small settings and by taking considerable pains. But this is the 21st century: the NHS has made the data available to allow us to watch a good idea spreading across the nation, or not, almost in real time.

This is, of course, an atypical situation. It is unusual to be able to collect such a large set of high-quality data, showing who has or has not embraced a new idea. And it is unusual to have such sharply defined innovations: either the doctor prescribes the new drug to patient X or she does not. Still, being able to observe leaders and laggards in the NHS is no small thing. It should be straightforward to prod the laggards — and to ask the leaders how they do it. And Dr Goldacre’s group have published their statistical tools. Hopefully, it won’t take too long for the idea of using them to spread.


Written for and first published in the Financial Times on 7 February 2020.

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Undercover Economist

Why we need to disagree

A few days after Christmas in 1978, United Airlines Flight 173 ran into trouble on its descent into Portland, Oregon. The landing gear should have descended smoothly and an indicator light blinked on to indicate all was secure. Instead, there was a loud bang and no light.

While the crew tried to figure out whether the landing gear was in position or not, the plane circled and circled. The engineer mentioned that fuel was running low, but didn’t manage to muster enough forcefulness to convey the urgency to the captain, who was focused on the landing gear. Finally, when the first officer said “we’re going to lose an engine, buddy”, the captain asked, “why?”

The plane crashed shortly afterwards. Ten people died. The lesson: sometimes we can’t bring ourselves to speak up, even when lives are at stake.

It might seem strange, in this politically divided age, to call for people to speak out if they see things differently. But our current political discourse doesn’t quite qualify. (Abuse is not an argument, as any Monty Python fan knows.)

Useful dissent means serious engagement with people who see the world differently — or, perhaps, the courage to puncture the consensus of one’s own tribe. It is far more common to see people seeking out like-minded groups, while politicians are happy to deliver hellfire sermons to their own choirs.

That is a shame. Within a cohesive group, the mere demonstration that disagreement is possible can have liberating effects. Charlan Nemeth, a psychologist at the University of California, Berkeley, studies dissent. (Her recent book is titled, No!: The Power of Disagreement in a World that Wants to Get Along – or in the US, In Defense of Troublemakers; at least we can reliably expect transatlantic disagreement over titles.) When she arrived at the university she found her office a little too austere, and decided to put down a rug.

“These offices are all the same for a reason,” remonstrated a colleague. She kept the rug anyway — and before long, her colleagues started putting rugs in their offices, too. Apparently, few people had liked the austere offices but nobody was willing to admit that. It took Prof Nemeth’s low-level troublemaking to shatter the illusion of consensus.

Prof Nemeth has studied disagreement during brainstorming sessions. One rule of brainstorming is not to criticise the ideas of others. When she and colleagues ran their sessions, they found that groups produced more ideas if the “do not criticise” rule was reversed, encouraging participants to “debate and even criticise each other’s ideas”.

Dissent can free us to place rugs in our offices, or express our individuality in more important ways. It can also stimulate our ideas and creativity. And — as the case of Flight 173 suggests — if we hesitate forcefully to disrupt a group conversation, that can deny others a vital piece of information.

Matthew Syed, in his book Rebel Ideas (this one also has a different title in the US; there’s something in the air…) draws the same conclusion from a disastrous attempt on Everest in 1996. Mr Syed argues that junior members of the expedition had useful pieces of information about the weather and their equipment but tended to stay silent, deferring to the team leaders.

A similar dynamic is at play in lower-stakes environments. One study, conducted by Garold Stasser and William Titus, asked undergraduates to discuss hypothetical candidates for a student society president.

The researchers gave each participant a different fact sheet; some facts were given to everyone in the discussion, but others were disclosed to only one person. People rarely spoke up about their private information, and the conversation revolved — redundantly — around what the whole group knew already rather than trying to find out what wasn’t widely known. There was an opportunity for everyone to learn from everybody else, but it proved more comfortable to focus on knowledge that they all had in common.

The truth is that disagreement is hard. We find it unpleasant to be disagreed with, and it can be painful to be a dissenter. Prof Nemeth notes that when she hired actors to play the role of dissenters in experiments studying group dynamics, the actors found it distressing to be on the receiving end of hostility. Some even asked for “combat pay”.

Even in gentler settings, we underestimate the benefit of friction. One study of problem solving (conducted by Katherine Phillips, Katie Liljenquist and Margaret Neale) simply contrasted small groups of friends with those of three friends plus a stranger. The groups with an outsider did much better at solving the problems, even though the strangers had no special expertise: their mere presence raised everyone’s game.

Nevertheless, the groups of friends enjoyed themselves more and had more confidence in their answers — confidence that was, of course, badly misplaced.

We rarely appreciate it when someone is speaking out rather than fitting in. But whether it is as trivial as a rug, or as vital as a fuel gauge in a circling aircraft, we need people who see things that we don’t. We need them to speak up. And we also need to listen when they do.

Written for and first published in the Financial Times on 31 January 2020.

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