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

Society and the profiteroles paradox

Ken is in a restaurant, pondering his choice of dessert. Ice cream, profiteroles or a cheese plate? He’s about to request a scoop of ice cream when the waiter informs him that the profiteroles are off the menu. “I see,” says Ken. “Well, I’ll have the cheese, please.”

Ken’s behaviour is odd enough to be a piece of surrealist comedy. But what seems ludicrous from an individual is easy to imagine in an election. Think of George W Bush as ice cream, Ralph Nader as profiteroles and Al Gore as the cheese plate. If Nader had not been on the menu in the 2000 US presidential election, then Gore would have been president instead of Bush. Since Nader himself was never a serious contender, it seems odd that his presence changed the result. But we’ve grown used to this sort of thing in politics.

Still, we might ask: is there a way to assemble individual preferences into social preferences without generating surreal outcomes? That was the first of many big problems studied by the great economist Kenneth Arrow, who died last month at the age of 95. His answer: no.

To understand Arrow’s answer, imagine a society in which every individual has a ranking expressing their preferences over every possible outcome. Let’s say that we can read minds, so we know what each person’s ranking is. All we need is some system for combining those individual rankings into a social ranking that tells us what society as a whole prefers.

Arrow named this putative system a constitution. What properties would we like our constitution to have? It should be comprehensive, giving us an answer no matter what the individual rankings might be. And it wouldn’t fall prey to the profiteroles paradox: if society prefers ice cream to cheese, then whether profiteroles are available or not shouldn’t change that fact.

We want the constitution to reflect people’s preferences in common-sense ways. If everyone expresses the same preference, for example, the constitution should reflect that. And we shouldn’t have a dictator — an individual who is a kind of swing voter, where the constitution reflects only her preferences and ignores everyone else.

None of these properties seem particularly stringent — which makes Arrow’s discovery all the more striking. Arrow’s “impossibility theorem” proves that no constitution can satisfy all of them. Any comprehensive constitution will suffer the profiteroles paradox, or arbitrarily ignore individual preferences, or will simply install a dictator. How can this be?

Let me now attempt the nerdiest move in more than 11 years of writing this column. Since there’s no idea in economics more beautiful than Arrow’s impossibility theorem, I’m going to try to outline a proof for you — very sketchily, but you may get the idea.

Imagine that our constitution must deliver a choice between ice cream, profiteroles and cheese. Step one in the proof is to note that there must be a group whose preferences determine whether society as a whole prefers cheese or ice cream — if only because the constitution must respect a unanimous view on this. Call this group the Cheese Group. The Cheese Group might include everyone in society, but maybe it’s a smaller group of swing voters.

The next step is to show that the Cheese Group doesn’t merely swing the decision between cheese and ice cream, but also over profiteroles and any other dessert we might add to the menu. We can show this by creating cases where it’s impossible for the Cheese Group to express a preference between cheese and ice cream without profiteroles being caught in the middle. This means that the Cheese Group actually gets to decide about everything, not just cheese and ice cream.

Finally, having established that the Cheese Group is all-powerful, we show that we can make it smaller without destroying its power. Specifically, we can keep dividing it into pairs of sub-groups, and show that at each division either one of the sub-groups is all-powerful, or the other one is.

In short: we prove that if any group of voters gets to decide one thing, that group gets to decide everything, and we prove that any group of decisive voters can be pared down until there’s only one person in it. That person is the dictator. Our perfection constitution is in tatters.

That’s Arrow’s impossibility theorem. But what does it really tell us? One lesson is to abandon the search for a perfect voting system. Another is to question his requirements for a good constitution, and to look for alternatives. For example, we could have a system that allows people to register the strength of their feeling. What about the person who has a mild preference for profiteroles over ice cream but who loathes cheese? In Arrow’s constitution there’s no room for strong or weak desires, only for a ranking of outcomes. Maybe that’s the problem.

Arrow’s impossibility theorem is usually described as being about the flaws in voting systems. But there’s a deeper lesson under its surface. Voting systems are supposed to reveal what societies really want. But can a society really want anything coherent at all? Arrow’s theorem drives a stake through the heart of the very idea. People might have coherent preferences, but societies cannot. We will always find ourselves choosing ice cream, then switching to cheese because the profiteroles are off.

Written for and first published in the Financial Times.

My book “Messy” is available online in the US and UK or in good bookshops everywhere.

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Undercover Economist

Has Facebook ruined the news?

“Our goal is to build the perfect personalised newspaper for every person in the world,” said Facebook’s Mark Zuckerberg in 2014. This newspaper would “show you the stuff that’s going to be most interesting to you”.

To many, that statement explains perfectly why Facebook is such a terrible source of news. A “fake news” story proclaiming that Pope Francis had endorsed Donald Trump was, according to an analysis from BuzzFeed, the single most successful item of news on Facebook in the three months before the US election. If that’s what the site’s algorithms decide is interesting, it’s far from being a “perfect newspaper”.

It’s no wonder that Zuckerberg found himself on the back foot after Trump’s election. Shortly after his victory, Zuckerberg declared: “I think the idea that fake news on Facebook, which is a very small amount of the content, influenced the election in any way . . . is a pretty crazy idea.” His comment was greeted with a scornful response.

I should confess my own biases here. I despise Facebook for all the reasons people usually despise Facebook (privacy, market power, distraction, fake-smile social interactions and the rest). And, as a loyal FT columnist, I need hardly point out that the perfect newspaper is the one you’re reading right now.

But, despite this, I’m going to stand up for Zuckerberg, who recently posted a 5,700-word essay defending social media. What he says in the essay feels like it must be wrong. But the data suggest that he’s right. Fake news can stoke isolated incidents of hatred and violence. But neither fake news nor the algorithmically driven “filter bubble” is a major force in the overall media landscape. Not yet.

“Fake news” is a phrase that has already been debased. A useful definition is that fake news is an entirely fabricated report presenting itself as a news story. This excludes biased reporting, satire and lies from politicians themselves.

At first glance, such hoaxes appear to be ubiquitous on Facebook. The BuzzFeed analysis finds that the five most popular hoax stories were more successful than the five most popular true stories. (This list of true stories includes the New York Post’s “Melania Trump’s Girl-on-Girl Photos From Racy Shoot Revealed”, a reminder that not all mainstream journalism is likely to win a Pulitzer.)

But hoax stories are less significant than this analysis suggests — partly because Facebook is not the main source of news for Americans (that’s still television news), and partly because true reports will generally be covered in some form by dozens of outlets, which will dilute the popularity of any one version. Each hoax, however, is unique. No wonder the most popular hoaxes outperform the most popular true reports.

In January 2017, two economists, Hunt Allcott and Matthew Gentzkow, published research studying exactly how prevalent fake news had been before the election. Their clever method tested people’s recall of fake news, as compared with true news stories and “placebo” stories — fake fake news, invented by the researchers. People didn’t remember many fake news stories, and claimed to remember quite a few placebos. Overall, there just didn’t seem to be enough fake news to swing the election result — unless it was potent stuff indeed, even in small doses.

“The average voter saw one fake news story before the election,” Gentzkow told me. “That number is a very different picture from what you might get from watching the public discussion.”

Of more concern is that Facebook — and its “most interesting to you” algorithm — simply supplies news that panders to each user’s ideological biases. It’s undoubtedly true that we surround ourselves with people who agree with us on social media. But it’s not clear that Facebook’s algorithm is the biggest problem here. Twitter was politically polarised even in the days when it used no algorithm at all. And newspapers have ideological biases too.

One recent study of online news reading was conducted by Seth Flaxman, Sharad Goel and Justin Rao, who had access to browser data from Microsoft, and used it to examine how people consumed news online. They found a mixed picture: social media did seem to push stories that were further from the centre of the political spectrum but they also exposed people to a greater variety of ideological viewpoints. That makes sense. Reading the same newspaper every day is a filter bubble too.

Gentzkow studied the contrast between online and offline news using data from 2004-2009, working with fellow economist Jesse Shapiro. They found little evidence then that online news consumption was more polarised than traditional media. But things are changing quickly. “My guess is that segregation is noticeably and meaningfully higher than in the past,” Gentzkow says, “but still quite modest.”

This feels like an important moment. Fake news is not prevalent, but it could become so. Filter bubbles are probably no worse than they have been for decades — but that could change rapidly too.

“A lot ultimately hinges on what the motivations of American voters are,” says Gentzkow. “Do people actually care at all about getting the truth and having accurate information?”

He’s hopeful that, deep down, people watch and read the news because they want to learn about the world. But if what voters really want is to be lied to, then Facebook is the least of our problems.

Written for and first published in the Financial Times.

My book “Messy” is available online in the US and UK or in good bookshops everywhere.

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Undercover Economist

What raspberry farms can teach us about inequality

Raspberries are a petit-bourgeois crop, while wheat is a proletarian crop — or so says political scientist James C Scott in his remarkable 1998 book Seeing Like a State (UK) (US). That makes it sound as though Scott is musing on matters of taste. In fact, he’s highlighting the link between what we produce, and the political and economic structures that production makes possible. Wheat is a proletarian crop, says Scott, because it works well on industrial farms. Harvesting can be mechanised. Not so easy with raspberries, which are best cared for on a small farm. They are difficult to grow and pick on an industrial scale.

Such distinctions once mattered a great deal. We associate the invention of agriculture with the rise of ancient states but, as Scott points out in a forthcoming book, Against the Grain, much depends on the crop. Wheat is well-suited to supporting state armies and tax inspectors: it is harvested at a predictable time and can be stored — or confiscated. Cassava works differently. It can be left in the ground and dug up when needed. If some distant king wanted to tax the cassava crop, his armies would have had to find them and dig them up one by one. Agriculture made strong states possible, but it was always agriculture based on grain. “History records no cassava states,” he writes.

The technologies we use have always affected who gets what, from the invention of the plough to the creation of YouTube. Economists know this but our analytical tools are not well-suited to distinguishing wheat from raspberries or cassava. The brilliance of gross domestic product is the way it manages to measure all economic activity with the same yardstick — but that is also, of course, its weakness. Nevertheless, we try. Many researchers have examined whether countries with rich endowments of mineral resources — oil, copper, diamonds — tend to do better or worse as a result. The balance of opinion is that there’s a “resource curse”. Why?

Sometimes the problem is obvious enough — for example, natural resources sustained a quarter-century of civil war in Angola, where the government could fund itself with oil while the rebels mined and sold diamonds. Sometimes it’s more subtle: a country that exports a valuable commodity will experience a strengthening of its exchange rate. This makes it harder to sustain any sort of industry that isn’t connected to the commodity itself.

Still, we’ve lacked the statistical tools to paint a compelling picture of these issues, important though they seem to be. Now a new research paper from a team at the Massachusetts Institute of Technology tries to explore how the mixture of products a country produces might influence a critical economic outcome: income inequality. The team includes César Hidalgo, author of Why Information Grows (UK) (US), about whose work I’ve written several times. Over the past few years, Hidalgo has been trying to map what he calls “economic complexity”, using statistical techniques from physics rather than economics.

Complexity isn’t straightforward to measure — is a million dollars of reinsurance more or less complex than a million dollars of liquefied natural gas or a million dollars of computer games? Hidalgo’s method looks at a country’s merchandise exports. Sophisticated economies tend to export many different products, including the most complex. Complex products tend to be exported only by a few economies.

In previous work, Hidalgo and colleagues have shown that economic complexity is correlated with wealth, but there are some economies that are spectacularly sophisticated but only modestly wealthy (South Korea is one) while other economies are very rich but not especially sophisticated (such as Qatar). This new analysis finds a relationship between inequality and lack of economic complexity.

Holding other things constant, the simplest economies tend to be the most unequal; the more sophisticated ones tend to be more equal. It’s raspberries and wheat all over again. Or, if you prefer, the difference between a business such as oil (which employs a few people at high wages), textile work (which generates lots of jobs, but at low wages) and making precision components (which requires many skilled and well-paid workers). The oil-based economy will tend to be the most unequal, while the precision-engineering economy will tend to be the most equal.

There are exceptions: Australia’s economy is surprisingly simple thanks to a dependence on natural resources, but not especially unequal. Mexico is an outlier in the other direction, with a sophisticated but unequal economy. This research answers some questions and raises others. There’s a large and unsatisfying literature on the relationship between inequality and growth. Are unequal societies dynamic and entrepreneurial or dysfunctional patron-client states? The MIT study suggests that what’s been missing from these questions is a measure of economic complexity.

And what about financial services? They seem both sophisticated and highly unequal — an exception to the rule? Hidalgo’s data are silent on the topic. But Hidalgo himself isn’t persuaded that banking is particularly complex.

“Most countries have financial services,” he tells me. “But few countries know how to design new microprocessors or new medicines.” By that measure, and others, he thinks financial services are cruder than we tend to think. Perhaps. If so, the City of London has more in common with the oilfields of the North Sea than we are inclined to admit.
Written for and first published in the Financial Times.

My book “Messy” is available online in the US and UK or in good bookshops everywhere.

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Undercover Economist

How to catch a cheat

Should the rules and targets we set up be precise, clear and sophisticated? Or should they be vague, ambiguous and crude? I used to think that the answer was obvious — who would favour ambiguity over clarity? Now I am not so sure.

Ponder the scandal that engulfed Volkswagen in late 2015, when it emerged that the company had been cheating on US emissions tests. What made such cheating possible was the fact that the tests were absurdly predictable — a series of pre-determined manoeuvres on a treadmill. VW’s vehicles, kitted out with sensors as all modern cars are, were programmed to recognise the choreography of a laboratory test and switch to special testing mode — one that made the engine sluggish and thirsty, but that filtered out pollutants.

The trick was revealed when a non-profit group strapped emissions monitors to VW cars and drove them from San Diego to Seattle. In some ways, that’s a crude test: outside the laboratory, no two journeys can be compared precisely. But the cruder test was also the test that revealed the duplicity.

The VW case seems like a strange one-off. It isn’t. Consider the “stress tests” applied by regulators to large banks. These stress tests are disaster scenarios in which a bank calculates what would happen in particular gloomy situations. But, in 2014, US regulators started to notice that banks had made very specific, narrow bets designed to pay off gloriously in specific stress-test scenarios. There is no commercial logic for these bets — but they certainly make it easier to pass the stress test. VW all over again — with the difference that what the banks were doing was apparently perfectly legal.

If tests and targets can fail because they are too predictable, they can also fail because they are too narrow. A few years ago, UK ambulance services were set a target to respond to life-threatening situations within eight minutes of receiving an emergency call. Managers soon realised that they could hit the target more easily if they replaced a two-person ambulance with an independent pair of paramedics on bikes. And many responses were written down as seven minutes and 59 seconds, but few as eight minutes and one second — suspiciously timely work.

Perhaps we’d be better off handing over the problem to computers. Armed with a large data set, the computer can figure out who deserves to be rewarded or punished. This is a fashionable idea. As Cathy O’Neil describes in her recent book, Weapons of Math Destruction (UK) (US), such data-driven algorithms are being used to identify which prisoners receive parole and which teachers are sacked for incompetence.

These algorithms aren’t transparent — they’re black boxes, immune from direct scrutiny. The advantage of that is that they can be harder to outwit. But that does not necessarily mean they work well. Consider the accuracy of the recommendations that a website such as Amazon serves up. Sometimes these suggestions are pretty good, but not always. At the moment, Amazon is recommending that I buy a brand of baby bottle cleanser. I’ve no idea why, since all my children are of school age.

A teacher-firing algorithm might look at student test scores at the beginning and end of each school year. If the scores stagnate, the teacher is presumed to be responsible. It’s easy to see how such algorithms can backfire. Partly, the data are noisy. In a data set of 300,000, analysts can pinpoint patterns with great confidence. But with a class of 30, a bit of bad luck can cost a teacher his or her job. And perhaps it isn’t bad luck at all: if the previous year’s teacher somehow managed to fix the test results (it happens), then the new teacher will inherit an impossible benchmark from which to improve.

Just like humans, algorithms aren’t perfect. Amazon’s “you might want to buy bottle cleanser” is not a serious error. “You’re fired” might be, which means we need some kind of oversight or appeal process if imperfect algorithms are to make consequential decisions.

Even if an algorithm flawlessly linked a teacher’s actions to the students’ test scores, we should still use it with caution. We rely on teachers to do many things for the students in their class, not just boost their test scores. Rewarding teachers too tightly for test scores encourages them to neglect everything we value but cannot measure.

The economists Oliver Hart and Bengt Holmström have been exploring this sort of territory for decades, and were awarded the 2016 Nobel Memorial Prize in Economics for their pains. But, all too often, politicians, regulators and managers ignore well-established lessons.

In fairness, there often are no simple answers. In the case of VW, transparency was the enemy: regulators should have been vaguer about the emissions test to prevent cheating. But in the case of teachers, more transparency rather than less would help to uncover problems in the teacher evaluation algorithm.

Sometimes algorithms are too simplistic, but on occasions simple rules can work brilliantly. The psychologist Gerd Gigerenzer has assembled a large collection of rules of thumb that perform very well in predicting anything from avalanches to heart attacks. The truth is that the world can be a messy place. When our response is a tidy structure of targets and checkboxes, the problems really begin.

Written for and first published in the Financial Times.

My book “Messy” is available online in the US and UK or in good bookshops everywhere.

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Undercover Economist

How being wrong can help us get it right

There’s an academic I know — very well respected — who especially values one of his collaborators. This particular colleague isn’t invaluable because of his creativity or intellect, says my professor friend, but because “he is willing to tell me when I’m wrong, and that’s rare”. It is indeed rare. Perhaps even rarer is the practice of seeking out colleagues because they give frank criticism.

I certainly don’t enjoy being told that I’m wrong. And it seems that I’m not alone. A recently published working paper from Paul Green and Francesca Gino of Harvard, and Bradley Staats of the University of North Carolina, caught people in the act of avoiding criticism. The particular kind of criticism that interested the researchers was where I think I’m doing a good job, and then you tell me that I’m not. (In the jargon, this is “disconfirmatory feedback”.)

Green, Gino and Staats looked at data from an internal peer feedback process in a medium-sized company over several years. They were able to show that when disconfirmatory feedback arrived, workers would then avoid contact with the people who had given them the unwelcome comments. This is the exact opposite of my professor friend’s behaviour — but, I think, a much more typical response. We don’t like it when people tell us that we’re failing.

The irony is that disconfirmatory feedback is the most useful kind of feedback imaginable. If I’m making serious mistakes while cruising along in a complacent bubble of self-satisfaction, I badly need someone to explain exactly what I’m doing wrong. But what I need and what I might enjoy are, of course, quite different.

In certain corners of the business world, it’s become fashionable to talk openly about failure — some would say to “celebrate failure”, although that’s a lazy description. A botched surgical procedure or a fatal traffic accident aren’t things to be celebrated, but they should be discussed, analysed and learnt from. The most obvious way to do this is through a postmortem: all is lost, the project failed, the patient died, so let’s at least try to do better next time.

Less painful, though, is psychologist Gary Klein’s idea of the “pre-mortem”. The pre-mortem is an exercise in which you try to imagine scenarios in which your project fails. Such scenarios are likely to suggest simple ways to prevent disaster.

Alternatively, one can try to learn from other people’s mistakes rather than one’s own. In 2009, Cass Phillipps, a conference producer based in San Francisco, found herself feeling alienated by Silicon Valley conferences packed with gung-ho founders describing their runaway successes. She set up an alternative, “FailCon”, where people came to dissect their failures — in many ways, an enormously more informative experience for attendees.

Phillipps has now stopped organising FailCon — in part, she tells me, because the urgency has gone: “The internet is filled with postmortem stories.” But the basic idea is sound and has spread. For instance, a new book by development economists Dean Karlan and Jacob Appel, Failing in the Field (UK) (US), is simply a catalogue of all the mistakes they’ve made while trying to evaluate projects, and a discussion of what others might do to avoid the same errors.

Still, the real trick, says Cass Phillipps, is to spot and fix your mistake before it becomes fatal. But while “how I failed and what I learnt” is a safe enough topic for a conference or a book, “Help! Help! I need help now!” is a much rawer message.

So I turned to Ashley Good, the CEO of “Fail Forward”, a consultancy that helps organisations turn failures into more productive experiences. I asked her why it’s difficult to cope with failures in real time. One reason: panic.

“Failure tends to push us into a stress response,” she says, and that promptly leads to denial, finger-pointing, self-flagellation, cover-ups or “any number of dysfunctional reactions that limit our ability to learn”. That means that the first step after discovering some major screw-up is to take a deep breath and try to calm down.

The second step, says Good, is to “be respectful and kind”. That’s good advice at any time, of course — but particularly when emotions are running high and there’s a problem to be solved. And a third step is to take some individual responsibility: to ask, “What could I, personally, do differently now to avoid this sort of thing in future?”

Ultimately, the aim of all this is not to “celebrate” a disaster but to make things better, by fixing the current problem, if possible, and by preventing a recurrence. That means asking cool questions about what the problem really is.

When the dancer and choreographer Twyla Tharp earned scathing early reviews for her musical Movin’ Out, she asked a trusted colleague to transform the pile of criticism into a checklist for improvement. This depersonalised the criticism and turned it into a to-do list. And it worked: the revised show won Tony awards and enjoyed a long run.

Tharp has something in common with the professor who values his frankly critical collaborator: both of them recognise that thoughtful criticism isn’t something to be avoided — or, for that matter, something to be celebrated. It’s something to be used.

 
Written for and first published in the Financial Times.

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Undercover Economist

Remind me what was so great about trade?

When our first child was born, I had an office job. My wife’s exhausting and non-remunerated profession was stay-at-home mother. Later, she retrained as a portrait photographer. To let her return to the labour market, we needed to hire a nanny. There is more to such a decision than money but, on purely financial terms, this was a no-brainer: the nanny earned less than either of us, so by freeing us to earn money in other ways, the Harford household was richer as a result.

Yet what makes obvious sense for a household can become strange and threatening in a different context. Imagine: the proud independent nation of Harfordia had a thriving childcare sector (my wife), but it was undercut by cheap foreign competition (the nanny). There was a vast bilateral trade deficit with the nanny, and Harfordia’s homegrown childcare sector was devastated. Bad!

Though Harfordia’s photography sector boomed as a result, you can bet that’s not what the populists would be pointing to.

Free trade suddenly seems to have few supporters. Some of Britain’s more effervescent Brexiters are free-traders, it is true, but with friends like that, who needs enemies? So I thought it was worth reminding ourselves just what was supposed to be so great about free trade in the first place.

The first and most fundamental insight is that all human civilisation is built on some sort of trade. I’m not much of a farmer but, fortunately, I am able to trade the books I write for food and for the electricity that lets me cook. Even my books rely on others to make the paper, design the word-processing software, bind the pages, design the covers, handle the logistics . . . Some of this I could do myself, albeit slowly and incompetently. Other things I couldn’t begin to attempt.

The second insight is that while international trade seems to involve competing with foreigners, it’s often more illuminating to see it as a battle between domestic producers. My home town of Oxford makes Minis, which we can export in exchange for camembert. But what if a post-Brexit government decides to hammer the camembert trade? It’s not impossible: cabinet minister Liz Truss did once describe the UK’s reliance on foreign cheese as a “disgrace”.

French cheese makers would lose out but so, too, would the Mini factory in Oxford. The French use their camembert to buy our cars; if we’re buying less camembert, it means they’re buying fewer cars.

This isn’t because of any French retaliation. It’s simply a reflection of the fact that there are two ways to make cheese in the UK: the obvious way, using cows, and the indirect way, by making cars and then trading the cars in exchange for cheese. The British cheese industry is, in a very real sense, directly competing with the British car industry. Protect one with a tariff, and you hurt the other.

Economists disagree about most things, but for a couple of centuries they’ve agreed about the merits of free trade, basically for the reasons outlined above. But some readers may be faintly aware of cracks in that consensus — haven’t economists realised that free trade is sometimes bad?

Broadly, the answer is “no” — economists remain thoroughly persuaded of the merits of international trade. But there are cautionary notes. First, modern trade agreements tend to be loaded with rules — food safety, financial regulation, intellectual property — that are not about tariffs. Some of these rules are closely connected with trade itself: long arguments at customs can restrict trade just as surely as a border tariff. But others have little to do with trade, and sometimes the rules are simply bad. So you can favour free trade yet oppose some “free-trade” agreements, as many economists do.

An important paper, “The China Shock”, published by economists David Autor, David Dorn and Gordon Hanson, showed convincingly that US manufacturing sectors that have been particularly exposed to competition from China have been hurt deeply and lastingly. Just like Harfordia’s childcare sector, they’ve been wiped out. That’s not a surprise to an economist. What is a surprise is that, many years after the initial shock, people hadn’t managed to retrain or relocate and find good new jobs. The US economy, more flexible than most, is less flexible than we’d thought.

One can’t help wondering how easy it will be for the UK economy to replace deeply established patterns of inter-EU trade with something more global. Such changes can be wrenching.

But deep down, trade is just another kind of productive technology — a technology that turns Minis into camembert. Like any productive technology, it makes us richer. But it creates winners and losers, and the winners may take their good fortune for granted while the losers are acutely aware of what they’ve lost. The losers have votes too. And if they’re frustrated about China, let’s see what happens if self-driving vehicles put several million truckers and taxi drivers out of work.

We need to find a better response to the strains of the modern world. “Build a wall” is clearly a message that sells, but it’s not a policy that will help. Our international trading system has helped boost both prosperity and peace. It would be a shame if something were to happen to it.

Written for and first published in the Financial Times.

My book “Messy” is available online in the US and UK or in good bookshops everywhere.

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Brexit as a game of Chicken

At times such as these, I wish I could hear what Thomas Schelling had to say. It might be too much to claim that Schelling was one of the most intriguing characters of the 20th century but he was certainly one of the most interesting economists. He began his career working on the Marshall Plan before advising the administrations of Presidents Kennedy, Johnson and Nixon on nuclear strategy.

As well as studying deterrence, segregation and addiction, he was one of the first economists to ponder climate change. In 2005, he shared the Nobel Memorial Prize in Economics. Schelling died in December 2016 at the age of 95. Schelling was one of the fathers of nuclear non-proliferation, and I think I know what he might have made of Donald Trump apparently welcoming the idea of a new nuclear arms race. But it’s Schelling’s insights on the Brexit negotiations that I’d really like to have.

In his absence, I’m going to have to guess.

First: to be an effective negotiator often means accepting some risk of disaster. The simplest model of this is the game of “Chicken”, in which two leather-clad rebels get into their cars, and drive towards each other at a furious pace. The first one to veer off the road loses his dignity, unless neither of them swerve, in which case both of them will lose a lot more than that.

Chicken is an idiotic game, whose players have little to gain and much to lose. But Chicken teaches us that you can gain an advantage by limiting your own options. Imagine detaching your steering wheel and flamboyantly discarding it as you race headlong towards your opponent. Victory would be guaranteed. Nobody would drive straight at a car that cannot steer out of the way. But here’s a worrisome prospect: what if, as you hurl your own steering wheel out of the window, you notice that your rival has done exactly the same thing?

All this matters because both the UK and the EU are doing their best to give the impression that they’ve thrown their steering wheels away. Control of immigration is non-negotiable, says Theresa May. Fine, says the EU — in that case membership of the single market is out of the question. Fine, says May: we’re out. Don’t let the door hit you as you leave, says the EU.

It’s easy to see why both sides are behaving like this — it’s the logic of Chicken. But the eventual result may be something no sane person wants: a car crash. In May’s recent speech, she set out her willingness to risk such a crash by saying she might walk away without a deal. That does make some sense: it’s how you act if you want to win a game of Chicken. But there are games of Chicken that nobody wins.

That leads to a second insight from Schelling: the difference between deterrence and what he called “compellence”. Deterrence dissuades action, but compellence means persuading or threatening someone so that they do act. In his 1984 book Choice and Consequence (US) Schelling pointed out that deterrence is easier. A deterred person does nothing, so need not admit that the deterrence worked, but a compelled person must visibly acquiesce.

Unfortunately, the process specified under Article 50 leaves the UK in the awkward position of trying to achieve compellence. The default option is the car crash, a disorderly fracture with the EU. Anything else requires all 28 countries involved to take prompt constructive action. May and her chancellor Philip Hammond have made some (faintly) threatening noises about how the EU should play along, but such threats can only work if they compel an energetic and active response. That’s far from certain — compellence is hard.

Of course, a broad, constructive agreement is in everyone’s interest. As May rightly said: “Trade is not a zero-sum game: more of it makes us all more prosperous.” It stands to reason, then, that the EU should embrace free trade in goods and services with the UK — as should the many other trading partners that foreign secretary Boris Johnson tells us are “queueing up” to sign deals with the UK.

To which Schelling might respond: just because a mutually beneficial deal is achievable doesn’t mean it will be achieved. Mutual benefit isn’t enough. If it was, we wouldn’t need a free-trade deal at all. Every country would have unilaterally abandoned all barriers to trade long ago. Back in the real world, trade deals are stubbornly difficult and time-consuming to negotiate. To add to the difficulty, May badly needs to sign a deal with someone — Trump, perhaps, or China’s president Xi Jinping. But neither Trump nor Xi badly need to sign a deal with her. This is not a great starting point.

It’s quite possible that a sensible deal will be reached. But not certain. Sometimes, in international relations, events take on their own unwelcome momentum. Consider the dark comedy Dr Strangelove (1964) in which — spoiler alert — civilisation is destroyed by a series of highly amusing miscalculations. One of the script advisers for the movie? An economist called Thomas Schelling.

Written for and first published in the Financial Times.

My new book “Messy” is now out and available online in the US and UK or in good bookshops everywhere.

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Why economists should be more like plumbers

What kind of economist should I be when I grow up? The opening weeks of the year have brought an embarrassment of answers.

Andrew Haldane, chief economist of the Bank of England, won headlines for comparing economists to weather forecasters. Alas, it was not a flattering comparison: Haldane mentioned Michael Fish’s infamous October 1987 forecast on primetime British TV, which offhandedly reassured viewers that there wouldn’t be a hurricane so “don’t worry”. The warning was followed by a severe storm that killed 18 people in the UK and four in France.

But if economists are like weather forecasters, the lesson is that they should keep trying. Meteorologists have a difficult job yet they do it well — partly with the help of half-a-million weather measurements a day and powerful supercomputer simulations. Perhaps economic forecasting should emulate that approach. For now, many serious economists think that economic forecasting is for fools and charlatans, and that real economists have a different job entirely.

What, then, is that job? Beatrice Cherrier, a historian of economic thought, points out that economists have long looked for an appealing metaphor. In the 19th century, economics was part science, part moral philosophy and part art. Later, economists liked to compare themselves to physicists, borrowing the jargon, the methodology and the mathematics of physics. With the discipline inspiring awe after the splitting of the atom, it must have been tempting for economists to seek the same quality of insight — not to mention the prestige and the funding.

Whether economics has really been strengthened by ideas from physics remains a matter of controversy. Some critics say that economists should embrace ideas from psychology. Others simply argue that economists have copied the wrong kind of physics and, if they used more up-to-date technical tools, they’d achieve better results.

An alternative view is that economics should be a practical, problem-solving discipline. The most famous proposal along these lines is a throwaway remark from John Maynard Keynes, who looked forward to the day when economists would be “humble, competent people on a level with dentists”.

Humility and competence sound good to me — and dentistry seems an appealing model in other ways. Dentists don’t forecast how much tooth decay you might suffer over the next decade; they tell you to floss and to lay off the fizzy drinks. Dentists know that their job is not forecasting but preventing or solving problems.

But Tony Greenham, a programme director at the RSA, recently declared that Keynes was quite wrong. Dentistry is built on objective science, says Greenham, but economics is not: economic analysis should involve clashing schools of thought, debating ideas in front of a public who must then make their choices at the ballot box. Greenham has a point, of course. Economics will never be a hard science, so there must always be room for debate. And most economic policy decisions produce winners and losers, each with a right to be heard.

Still, if dentistry offers a practical, evidence-based approach to solving problems, I’m not sure that Greenham is wise to warn economists away from that goal unless there really is no hope. Several leading economists have argued that economics should have a more practical bent. Al Roth, Nobel laureate in economics, says that economists should be like engineers. Roth has designed systems for matching students to schools and kidney donors to recipients, and his argument is that when designing such a system it’s not enough to get the broad outlines right — as a physicist or an economic theorist might — but the details too.

Meanwhile Esther Duflo — too young for a Nobel but hugely celebrated in the profession — recently gave the prestigious Ely Lecture in Chicago. She argued that economists should act like plumbers, or at least that, “some of us should do some of it some of the time.”

For Duflo, plumbing is even more practical than engineering: not only must the plumber install the system, she must observe and tinker with it as leaks and blockages become apparent. Issues that weigh heavily in theory may be trivial in practice, and vice versa.

So perhaps I should be a meteorologist, or dentist, or engineer, or plumber — or, as others might advise, psychologist, epidemiologist, historian, anthropologist or data scientist? Of course, the wonderful and frustrating thing about economics is that each of these approaches — and others — has something to offer as we try to comprehend the dizzying interactions of the economy all around us. No wonder economics is so much fun — and so hard to do well.

As I pondered all this career advice, I couldn’t help but think of Bill Phillips. Phillips was born in 1914 to a New Zealand farming family. He learnt engineering via correspondence course, and was a gold miner, crocodile hunter and war hero. He studied sociology but became an economics professor at the London School of Economics. He produced perhaps the most-cited macroeconomic paper ever written, describing the “Phillips curve”. He learnt several languages and, later in life, was fascinated both by complex dynamic systems and by the economy of China. He also built the first computer model of the British economy. It was a hydraulic computer — a system of equations, crafted in plumbing.

Now that’s an economist.

Written for and first published in the Financial Times.

My new book “Messy” is now out and available online in the US and UK or in good bookshops everywhere.

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An Optimist’s Guide to 2017

Unless you are paid to write obituaries, 2016 was a grim year. In the UK, half the voters were so aghast at the state of the nation that they voted to leave the EU; the other half were aghast at the result. If my colleague Gideon Rachman is right, a train-crash Brexit negotiation is likely to disappoint both sides. In the US, a similar situation prevails: half the country is appalled at the prospect of President Trump, while the other half elected him because they were appalled at the status quo.

We can remind ourselves that things would be very much worse if we lived in Syria — but while that’s reason for gratitude, it’s hardly a source of comfort. Yet there’s a lot going right in the world. Noticing the good news as well as the bad is not just reassuring — it’s also essential for making reasoned policies. So, here are five reasons to be cheerful in 2017.

• We’re healthier than ever before. A century ago, global average life expectancy at birth was just 35. When I was born, it was 60. Recently it rose above 70. Even in Africa and the former Soviet Union, where life expectancy fell in the 1990s, the upward trend has resumed and longevity is now at the highest level yet recorded. Partly this progress is thanks to far more widespread access to good sanitation. And it’s partly because there are treatments — vaccines and antibiotics, for example — that were not available for any money 100 years ago but now cost pennies. Charles Kenny, author of Getting Better (UK) (US), wrote: “Countries as poor and wretched as Haiti, Burma and the Congo have infant mortality rates today that are lower than those that any country in the world achieved in 1900.”

There is a much-noted exception to this finding. Late in 2015, economists Anne Case and Nobel laureate Angus Deaton found that mortality has recently been increasing in middle-aged non-Hispanic whites in the US. The finer details of that finding have been disputed but it’s certainly clear that this particular group hasn’t been enjoying the advances in health that are so widespread elsewhere. Yet it’s only striking news because lack of progress in health is so unusual.

• Despite this increase in life expectancy, the number of people living on the planet is increasing much more slowly than in the 20th century. World population growth, which was an unsustainable 2 per cent a year in the 1960s, has been falling steadily and is about to drop below 1 per cent a year. This is good news for the planet.

• The world economy continues to grow and, despite a decade of economic distress in the US and Europe, world growth rates have reliably exceeded 3 per cent. At such a rate, the world economy itself doubles in size every 20-25 years. Such growth poses serious environmental challenges but, on balance, it’s a lot better than stagnation. According to data assembled by the economist Max Roser, the proportion of the world’s population living in the most extreme poverty has fallen from about 95 per cent two centuries ago to about 60 per cent 50 years ago to about 10 per cent today.

• The fruits of this growth are not quite so unevenly distributed as some commentary would have us believe. There is no one simple way to measure global income inequality but it’s reasonable to describe it as falling: China and India, after all, are large, poor and growing quickly. In the US, income inequality has risen. But in the UK, it has not — at least, not for a generation. Income inequality across most of the UK population increased dramatically in the 1980s but has fallen a little since then. At the very top of the UK income distribution, inequality continued to increase for longer. Yet it fell after the financial crisis, and the share of income enjoyed by the top 5 per cent, top 1 per cent and top 0.1 per cent is lower today than it was in 2000. Inequality is still high in the UK, but this is an old problem rather than a worsening one.

• Finally, there’s the decline in war, murder, torture and many other kinds of violence over the long run, certainly since 1945 and, arguably, over a much longer period. It was most famously documented by Steven Pinker in his 2011 book The Better Angels of Our Nature (UK) (US). Is this certain to continue? Perhaps not in a world where nuclear war is possible. Nevertheless, so far, so good.

None of this is to suggest that all is well. There’s plenty to concern any reasonable person, from the growth of nationalism in Europe, to Donald Trump’s apparent belligerence, to the alarming changes in the planet’s climate, to the ability of terrorists to strike in Europe’s capitals. So I’m worried about what 2017 has in store for us. But it’s not because I think the world is going to hell. It’s because I think we have so much progress to celebrate — and so much to lose.

Written for and first published in the Financial Times.

My new book “Messy” is available online in the US and UK or in good bookshops.

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Embrace the digital pile-up

One of my resolutions this year is to get more done. I seem to make the same vow every year and I suspect that many discerning readers of the Financial Times have a similar perennial yearning. But thanks to the research I did for my latest book, Messy, and a fascinating new book from Ofer Bergman and Steve Whittaker, I now feel I have a better sense of why some tactics work and others fail.

Their book, The Science of Managing Our Digital Stuff (US), is an academic tome addressing a deeply practical pair of questions: how do we all cope with the ever-increasing influx of emails, documents, photographs and bookmarks? And how can we do better?

Two strategies suggest themselves: organise and label everything meticulously (the “filer” approach), or organise nothing at all and search when you need something. We could call this latter tactic the “search everything” approach — or “hoarding”.

Both strategies can work in certain circumstances but both also turn out to have serious weaknesses. Filers struggle because getting so carefully organised takes too much time, and filer strategies often break down as users become busier and busier. But, more importantly, filers often suffer from “premature filing”, as they try to categorise incoming messages they don’t yet have the context to understand fully. Folder structures that make sense at the time are often incomprehensible later. And far too much low-value stuff is filed when it should have been deleted, becoming digital chaff that obscures the target.

Meanwhile, hoarders risk drowning in a sea of email: it’s impossible to make sense of an inbox with 14,284 emails. Yes, one can use email search — in 2011 Whittaker and four colleagues showed that when you’re trying to find an email needle in your archive haystack, search works at least as well as navigating through a folder structure. But Bergman has shown why we tend to resist searching: it feels like hard work. It’s more cognitively taxing than clicking through folder trees, a process that uses visual memory without much effort. We like folders because they feel natural in a way that search does not. And most important: search only works if you remember what you’re searching for.

When coping with paper documents, there’s a handy intermediate strategy between filing and hoarding: “piling”. Pilers let documents accumulate on their desk, sometimes informally grouped by topic or project. The piles are self-organising because recently handled documents end up going back on top. Whittaker and Julia Hirschberg have shown that pilers tend to keep smaller archives. The stuff in their piles is well used, unlike the redundant folders of the tidy filers. Piling looks messy but it works.

But email poses a particular challenge — is there a strategy that imitates the informal accessibility of the desktop piles, yet works in a fast-moving inbox? I think there is.

Here are the principles of “email piling”. First, email piling should be simple — crude enough that it’s quick and misfiling is almost impossible. Second, it should be organised around taking action. Ultimately, you’re not building a library, you’re keeping track of stuff that you need to do. Therefore, third: it should be visible. Your piles are reminders to take action, so they shouldn’t be hidden away.

So: crude, visible and built around taking action. The corollary of all this is that if you have an email that doesn’t require your action, you can archive it, safe in the knowledge that the search box will produce it again if needed. As a result, your email pile will be a jumble but a small one — just like the paper piles that Whittaker and Hirschberg studied.

That’s the theory, then. And in practice? I use Gmail’s “multiple inbox” function to sort my emails into three categories: yellow star for stuff to do, blue star for stuff to read and red star for stuff that’s waiting for someone else. (Assigning the star requires just a click or two.) Unlike normal folders, all three of these categories are in plain sight whenever I open Gmail itself: three simultaneous colour-coded inboxes.

***

I find this digital piling works remarkably well, at least for me. Most emails don’t fit in any of the categories — a sign that it should be replied to and/or archived immediately. The “to do” inbox is small enough that I don’t feel anxious that things will be lost. And, as an added benefit, if I check email on my phone and see that it requires a proper reply from a proper keyboard, I can dump it in my “to do” inbox and it vanishes from the phone to reappear on the computer, where it can be properly handled. When the email disappears, so does the compulsive anxiety to tap out a response with one thumb.

I have a few other folders but only for very well-defined bits of information I know I need to keep.

This isn’t a system that tries to organise emails once and for all, or tidy them away out of sight. The aim is to manage them as they come through. Rudimentary and unsophisticated might not be the ideal approach to life in general. It works very well for email.

Written for and first published in the Financial Times.

My new book “Messy” is now out and available online in the US and UK or in good bookshops everywhere.

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