Tim Harford The Undercover Economist

Articles published in 2019

Political change can feel elusive, until the dam bursts

Deus ex machina was the ancient Greek theatrical convention of resolving the unresolvable by crane-lifting a god on to the stage to make everything better again through divine fiat. Right now, a bit of deus ex machina sounds pretty sweet.

Many people hoped that special counsel Robert Mueller’s Russia probe would play that role in the US. Its conclusions would be so damning as to sweep away the knotty problem of Donald Trump without the grinding task of finding support for a different president next year. But it was never likely that congressional mathematics would allow impeachment, nor even that Mr Mueller’s report (assuming we ever get to see it) would contain anything to sway anyone either way. We all, surely, know what we think about Mr Trump by now.

In the UK, some Remainers have been hoping the divine plot twist would be supplied by a record-breaking petition. Almost 6m people have demanded that the UK revoke Article 50 and walk out of the Brexit tragedy before the final act. On Tuesday, the government gave its response: get lost, Citizens of Nowhere. (I paraphrase.) Perhaps the following day’s “indicative votes” in parliament would resolve things? They were indicative of something, at least: gridlock.

Still, change can happen, and sometimes with astonishing speed. A few years ago, the project of Brexit was the pipe-dream of a few obsessives. The percentage of Britons naming EU membership as the most important issue was in the low single digits. Now Brexit is the official goal of the two largest political parties, albeit one they are finding it rather hard to hit.

Similarly, the changes that Mr Trump has wrought upon American and global politics are too numerous to list. True, most of them are changes for the worse — but it is hard to make the claim that stasis is inevitable.

What explains this curious sense that we are somehow dealing with chaotic change and futile stasis all at once? One explanation — offered in Cass Sunstein’s recent book, How Change Happens (UK) (US) — is what he calls “partyism”. The name deliberately echoes vices such as racism and sexism; Professor Sunstein argues convincingly that many of us now dismiss entire groups of people on the basis of their political affiliation.

For example, views of interracial marriage have become dramatically more tolerant. Yet cross-party marriage is now beyond the pale for many. Prof Sunstein reports that in 2010, about 49 per cent of Republicans and 33 per cent of Democrats would feel displeased if their children married outside their political party — up from about 5 per cent in 1960. A similar trend has taken place in the UK.

Political scientists Shanto Iyengar and Sean Westwood used a common (if controversial) measure of subconscious bias, the “implicit association test”, to examine partyism. They found party affiliation produced stronger measures of implicit bias than did race.

One might argue that there is nothing intrinsically wrong with partyism. Rather than unjustifiably judging people based on their gender or ethnicity, we justifiably judge them for the choices they have made. Still, an environment where parties command unswerving support from their own base and unswerving loathing from the opposition is not one conducive to rational discussion. That, perhaps, accounts for the feeling of stasis: we feel that nobody is listening and nobody wants to compromise.

Despite the sense of gridlock, it is clear that dramatic change is possible. A hostile takeover of an existing party structure can turn partyism from a force for inaction into a force for radical change. The Brexiters have managed it, as has Jeremy Corbyn, the leader of the Labour party, and, most spectacularly, Mr Trump.

Existing political parties aren’t the only agents of change. In countries where the voting system permits it, new parties have surged forward. Even in the UK, where the electoral system gives an enormous advantage to large established parties, Leave and Remain have become stronger sources of political identity than traditional parties.

Outside the realm of traditional politics, consider the #MeToo movement — a catalyst for a dramatic and overdue reassessment of what behaviour society will tolerate from powerful men.

These changes are so sudden because we are social beings. We often don’t know how we feel until we see that other people are taking a stand. It seems that nothing is changing and nothing will ever change until a critical threshold is reached, and the dam bursts. Issues that were ignored become salient. We go from shrugging our shoulders to marching in the streets. These changes are unpredictable, and we often mislead ourselves after the fact into thinking that they were inevitable all along.

This, then, is the process of political change: long periods of stasis, sudden bursts of activity, and a good deal of luck. Behind it all, a long slog of persuasion, mobilisation and frustration — less a glorious pilgrimage than an endless treadmill. No wonder most of us would prefer divine intervention.

 

Written for and first published in the Financial Times on 29 March 2019.

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Alan Krueger, a master-economist for our age

Written for and first published in the Financial Times on 22 March 2019.

At the start of John Maynard Keynes’s obituary of Alfred Marshall comes a question: why is it so hard to be a good economist? Keynes’s answer was that “the master-economist must possess a rare combination of gifts . . . no part of man’s nature or his institutions must lie entirely outside his regard.”

This week the profession is mourning another great economist. Alan Krueger killed himself last weekend at the age of 58. What would be a bewildering blow under any circumstances is heavier still because the professor was an authority on happiness and pain.

He discovered, for example, that prime-age men who had quit the labour force were twice as likely as employed men to take painkillers. He studied how unemployed people spend their hours, and showed that actively searching for work was an intensely sad task.

With Nobel laureate Daniel Kahneman, he collected evidence on happiness that remains my benchmark for social scientists’ ability to shed light on wellbeing. Prof Kahneman once warned me that expert advice can go only so far. Much happiness and sadness is genetically determined: “We shouldn’t expect a depressive person to suddenly become extroverted and leaping with joy.” Those words are much on my mind this week.

Yet Krueger’s life invites us to reflect on what economists at their best can achieve. The most obvious fact to note about his career is its breadth. He studied pollution, inequality, social mobility, terrorism, the gig economy, and the music industry.

This is a vivid illustration of the versatility of the economist’s tools, but Krueger used them to make a lasting mark. The most famous example, with his colleague David Card, was a study of the impact of minimum wages on jobs. It stands to reason that every increase in a minimum wage will destroy marginal jobs, hurting some of the most vulnerable people in the workforce.

Profs Card and Krueger, however, weren’t content to stick with the theory. They wanted to know how big the effect was. This is a tough problem. While minimum wages might cause unemployment, a booming job market might influence politicians to raise the minimum wage, so cause and effect are tangled together. Their research, therefore, looked at fast-food industry jobs in two neighbouring states: New Jersey and Pennsylvania, only one of which had raised the wage floor. They found the rise hadn’t dented employment at all.

Not every economist was convinced, and by itself that result might have been a fluke. But the pair had developed a powerful method that could — and would — be repeated. Economists are now far more willing to allow that minimum wage increases can make sense.

Perhaps just as important, economists now believe that evidence can complement or even overturn theory. Economics was once theory-driven for a reason: the data was patchy and controlled experiments were rare. It was almost unheard of to produce evidence that was credible enough to outweigh theory.

Krueger was at the heart of what became known as the credibility revolution in economics: the idea that evidence could be powerful enough to make a difference — and that economists should gather and analyse it with that aim in mind. In a tweet last year, he declared: “The idea of turning economics into a true empirical science, where core theories can be rejected, is a BIG, revolutionary idea.”

However, while voraciously curious, Krueger had no interest in clever studies for their own sake. (Even his whimsical investigation of the music business, fuelled by personal enthusiasm, teaches broader economic lessons. “I think Taylor Swift is an economic genius”, he said.) In general, he wanted to answer the big questions about human wellbeing.

His work on the gig economy is a case in point. With the rise of companies such as Uber it became clear that many workers were putting in highly irregular hours. He promptly started surveying workers about whether they relished the flexibility or suffered from the insecurity. He showed that these contingent work arrangements weren’t new — the Uber workforce was the new tip of a long-hidden iceberg. He chased down the answers to questions other people were only beginning to ask.

“He wouldn’t speculate,” says Betsey Stevenson, who, like Krueger, is a labour economist who held senior positions in the Obama administration. “He would gather the data.”

That data could then be used to influence policy, as he showed during three stints working for the US government, including as the chairman of President Obama’s Council of Economic Advisers. He was also admired as a generous mentor of other economists: his influence goes well beyond his publications.

Were Keynes to be writing about the “master-economist” today, his list of requirements might have changed little: intensely curious about the human experience; energetic in gathering the data; willing to let the evidence change his or her views; a persuasive writer; determined to influence policy to improve the world. Nobody could have matched up better than Alan Krueger.

 

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Superstar companies lose their lustre

Everyone seems to agree that we live in a “superstar economy” — one in which the leading companies (the likes of Apple, Amazon and Alphabet) are making dramatic strides both in productivity and in profitability. In response to this conventional wisdom the only question is: how should regulators respond?

There is a case that we should let the superstars keep doing what they do. Enjoy the fruits of their creativity. The smartphone! Internet search that works! Next-day delivery of next week’s landfill! For now, the superstars are innovative and efficient. In due course new monopolists will arise, motivated to seize the crown.

This case is not absurd, although my own instincts point the other way. Profit-minded monopolists can be innovative, but all too often they fail to adapt. More often markets deliver because they support a messy, pluralistic process of trial and error.

If that view is right, government intervention may be necessary to prevent the monopolies of today choking off the innovations of the future. One possibility is to break up the largest companies. Regulators might rule that a company cannot simultaneously own a platform while also offering products on it. This is the position taken in an artful argument published last week by US presidential hopeful Elizabeth Warren.

An alternative approach, set out this week by the UK’s Digital Competition Expert Panel, is to regulate the behaviour of the big digital groups rather than to change their structure. Regulators could insist on standards for data sharing and interconnection with established players, allowing smaller competitors to grow on or around the existing platforms.

I’m sympathetic to both approaches, although worry that it is easy for regulators to do more harm than good. Ms Warren’s rousing call to arms might easily lead to fruitless antitrust trench warfare. But set aside for a moment the argument about how to respond to the superstars and ask a different question. What if they are actually economic white dwarfs, dense but dim and fading?

That seems a strange conjecture. It appears to contradict the problem of laggard companies: research from the OECD suggests that many companies are far less productive than those at the frontier of their industrial sector, and that this gap is getting bigger. This suggests that superstars are blazing hot and the problem lies with the rest of the economy.

But much depends on what we mean by superstar companies. The OECD research focuses on highly productive concerns. Many of them are surprisingly small, with revenues in the tens of millions rather than the tens of billions.

Another alternative is to look at the most valuable 20 companies in the US economy, and the most valuable four in each of 60 or so different sectors, whether or not they are digital and whether or not they are highly productive. This is the approach taken by Germán Gutiérrez and Thomas Philippon, economists at New York University, in a new working paper. This perspective casts doubt on the very idea that the superstars of the US economy are particularly large or productive by postwar standards.

Compared with their forebears, these companies are unremarkable in both their sales and their employee numbers. They have a larger economic footprint than the leaders of 20 years ago, but smaller than 40 years ago. Alphabet, Amazon and Apple are impressive companies, but so were Intel, Microsoft and Walmart 20 years ago, or General Electric, General Motors and IBM before them.

Any large group contributes to the productivity of the economy as a whole in two ways: directly, by producing output, and indirectly, by drawing in resources from less productive players. Messrs Gutiérrez and Philippon reckon that the direct contribution of the leading companies is smaller than it used to be, while the indirect contribution has not increased by enough to compensate. Overall, they calculate that the contribution of the star companies to labour productivity growth in the US has fallen by 40 per cent since the year 2000.

This is a surprising result. Part of the explanation may lie in measurement: it is never easy to measure productivity, particularly in services and even more so in services provided free of charge in exchange for data and attention. But the “fading star” result may well be real, and surprising only because we often let the big digital groups stand as symbols of scale and market power. There is more to the US economy than Silicon Valley.

The US economy does seem to have a monopoly problem: concentration is increasing in most industries. Companies make money less by becoming more efficient, and more by exploiting their pricing power.

There is plenty for US antitrust authorities to get their teeth into. Perhaps they should take a look at Europe, where competition policy is more robust and politically independent, while EU markets have become more competitive and less profitable than those in the US. That may not be a coincidence.

Written for and first published in the Financial Times on 15 March 2019.

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Fifty Things That Made The Modern Economy Season Two

I’m delighted to announce that Season Two of “Fifty Things That Made the Modern Economy” is up and running. Our first episodes included our Christmas special, followed by the Langstroth Beehive, Cellophane, and the Gyroscope – with more appearing on the feed on a weekly basis. If you want listen to the episode about bricks and you just can’t wait, hop over to 99% Invisible – one of the best podcasts on the planet and an inspiration for Fifty Things – where the brilliant Roman Mars presents three of his favourites, including the brick in all its glory.

If you like the series and fancy reading the book – all the nerdy detail in one handy package, plus a few extra thoughts we couldn’t squeeze onto the radio – then in the UK it’s called Fifty Things That Made The Modern Economy while in the US, it’s Fifty Inventions That Shaped The Modern Economy

And if you want to delve deeper, try Bee Wilson’s book The Hive or the magisterial Brick: A World History  – or my history of technology reading list. I love my job.

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9th of April, 2019MarginaliaRadioResourcesComments off

Black holes in data affect health and wealth

Nearly seven decades ago, the noted psychologist Solomon Asch gave a simple task to 123 experimental subjects: to pick which one of three quite different lines was the same length as a “reference” line. Asch had a trick up his sleeve: he surrounded each subject with stooges who would unanimously pick the wrong line. Confused, the experimental subjects were often — not always — swayed by the error of those around them.

I’ve written before about these experiments, but there’s something I neglected to mention: not a single one of the stooges nor the experimental subjects was female.

If Asch had conducted all-women experiments, he would have discovered that women tend to conform to the group more often than men. Perhaps this omission doesn’t matter. Retellings of the Asch experiment have tended to exaggerate the conformity that was demonstrated, while glossing over the fact that it was an all-male study. The two biases may cancel each other out.

Still, it is a lesson in how easy it is to ignore important data — or to assume that they are comprehensive, when in fact they omit half the planet.

Invisible Women (US) (UK) a new book by Caroline Criado Perez, explores countless cases in which everything from the height of the top shelf to the functionality of an iPhone is predicated on the assumption that the user will be male. (Apple once released a “comprehensive” health app that could track your selenium intake but not menstruation.)

Much of this imbalance has nothing to do with data, but some of it does — and this “gender data gap” is particularly important because good statistics are one of the only windows we have into the lives of an entire population, rather than just a handful of friends.

Consider the UN Sustainable Development Goals, admirable targets to improve the lives of 7.5bn people. Yet as development economists Mayra Buvinic and Ruth Levine have pointed out, while one of these goals is gender equality, we lack much of the data on whether that goal is being achieved.

Some missing numbers — for instance, on sex-trafficking — are obvious. Others are more subtle, such as the ubiquitous choice to measure the income not of individuals but of households. Does that household income come from a man, a woman or both?

We shouldn’t assume that the balance between “wallet and purse” is irrelevant. Economist Shelly Lundberg and colleagues studied what happened when in 1977, child benefit in the UK was switched from being a tax credit (usually to the father) to a cash payment to the mother. That measurably increased spending on women’s and children’s clothes relative to men’s. The UK’s new universal credit is payable to a single “head of household”; that curious decision may well favour men. Given the data we have, it will be hard to tell.

The story is often told of the accidental discovery of sildenafil (Viagra). Intended as a treatment for angina, the clinical trial revealed a side-effect: magnificent erections. Had the original trial included women, we might have fortuitously discovered a treatment for severe period pain. As it was, men got their miracle drug but women are still waiting. We can’t confidently prescribe sildenafil as a safe and effective treatment for period pain because, as Ms Criado Perez reports, only a small and suggestive trial has yet been funded.

There are many data gaps out there — statistician David Hand calls them “dark data”. There are the unpublished studies that produce less interesting or lucrative results than published ones. There are the voters who are coy about confessing their voting intentions to pollsters — the “shy Tory” effect. There are the psychology experiments that study only “WEIRD” subjects — Western, Educated and from Industrialised Rich Democracies.

We have plenty of statistics on shares and currencies, but not much on debt and derivatives. What Gillian Tett called the submerged iceberg of financial markets got less attention, until it turned out to have holed the entire financial system below the waterline in 2007.

There is no simple way to shine a light on all this dark data. There is a reason why it is easier to collect statistics in a rich country than a poor one, and why fluent speakers of English are more likely to fill in the UK census form. Collecting data on who bears the burden of “life admin” is harder than collecting that on primary paid occupations. But what we count and what we fail to count is often the result of an unexamined choice. We can make better choices, both by involving ordinary citizens in survey design, and by trying to get more women and minority groups into economics and statistics.

It is hardly encouraging that the Office for National Statistics has just been found wanting in a sexual discrimination case, but there is hope. The president of the Royal Statistical Society, the managing director of the International Monetary Fund and both heads of the UK Government Economic Service are all women. Still, plugging data gaps takes time, and considerably more thought than I once gave to Solomon Asch’s curious experimental line-up.

 

Written for and first published in the Financial Times on 8 March 2019.

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Why happiness is easy to venerate, hard to generate

In 1972, the teenage king of Bhutan, Jigme Singye Wangchuck, declared that “gross national happiness is more important than gross domestic product”. The sound bite has been echoed approvingly down the years, although the king may just have been making excuses. Bhutanese GDP per person was then the grinding poverty of about a dollar a day. If I were king of such a country, I’d be tempted to change the subject, too.

Clearly he had a point. Most of us would rather be poor and happy than rich and depressed. If so, gross national happiness seems a fine goal. But it is one thing for a monarch to announce that happiness is important. It’s quite another to make people happy. Shangri-La does not move from fiction to reality just because we desire it.

Bhutan has not always lived up to its own hype. Same-sex intercourse is illegal, which suggests a country with a less-than-expansive view of whose happiness matters. Three decades ago, around 100,000 of the Nepali-speaking Lhotshampa minority fled Bhutan to escape military persecution during a campaign of ethnic cleansing on a colossal scale. One-sixth of the entire population of Bhutan ended up in refugee camps in Nepal.

Even setting aside this enormity, it’s hard to see that Bhutan paid much more than lip service to gross national happiness. They hosted conferences, but according to a recent IMF working paper, nobody in the government collected systematic indicators on happiness until 2005. The World Happiness Report ranks Bhutan at 97th out of 156 countries, down from 84th a few years ago. Happiness is easy to venerate, but hard to generate.

Perhaps I am doing a disservice to a small kingdom wedged between sparring regional powers. It can’t be easy. And Bhutan has a lesson to teach us all — maybe we should think a little less about over-arching goals and a little more about specifics.

Consider some of the issues that are notoriously bypassed by GDP, the most common measure of economic activity: digital services are hard to value, while by design GDP omits any consideration of inequality or environmental damage. Unpaid work — of which men do a great deal, and women a great deal more — is also left out.

But if our aim is (for example) to reduce carbon emissions, we don’t achieve it by moaning about GDP. We achieve it with specific policies such as carbon taxes and investments in public transport and a renewable-friendly electric grid. Neither gender equality nor respect for unpaid work would be automatically improved by any change in the way national income accounts are computed.

And when Bobby Kennedy movingly commented that GDP “does not include the beauty of our poetry or the strength of our marriages”, he was quite right. Nevertheless I fail to see how any solution follows, whether for connubial harmony or American verse.

The specifics matter when it comes to happiness, too. Broad research into the causes of national happiness has tended to produce banal conclusions: we tend to compare ourselves to others, unemployment makes us miserable, and we hate being ill. There is nothing here to suggest that we need to overhaul commonplace policies such as redistributive taxation, the avoidance of recessions, and support for public health.

Just as with GDP itself, it is only when we move to the specifics that gross national happiness becomes useful. Richard Layard, one of the leading happiness researchers, argues that mental illness is a leading cause of misery, and that it can be treated very cost-effectively. That seems useful enough to me.

What is not useful is the sense that measuring GDP is the problem, and measuring gross national happiness is the solution. Few societies have ever really focused on either. We should all be happy about that.

 

Written for and first published in the Financial Times on 1 March 2018.

My book “Fifty Things That Made the Modern Economy” (UK) / “Fifty Inventions That Shaped The Modern Economy” (US) is out now in paperback – feel free to order online or through your local bookshop.

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Just because you’re paranoid, doesn’t mean the algorithms aren’t out to get you

If you do not like the price you’re being offered when you shop, do not take it personally: many of the prices we see online are being set by algorithms that respond to demand and may also try to guess your personal willingness to pay. What’s next? A logical next step is that computers will start conspiring against us. That may sound paranoid, but a new study by four economists at the University of Bologna shows how this can happen.

The researchers allowed two simple artificial intelligence algorithms to compete against each other in a setting where they simultaneously set prices and reaped profits accordingly. The algorithms taught themselves to collude, raising prices from the cut-throat competitive level towards what a monopolist would choose. Price cuts were met with price wars, after which collusion would return. Just because you’re paranoid, it doesn’t mean the computers are not out to get you.

This is not a surprising result for anyone who — like me — squandered their youth studying the theory of industrial competition. Robert Axelrod’s book The Evolution of Cooperation (US) (UK) published in 1984, described a tournament in which computers played a “prisoner’s dilemma”, a scenario analogous to two competing sellers. The best approaches used the threat of punishment to sustain co-operation. They were also simple: not something that a machine-learning system would struggle to discover.

An obvious question is, who — if anyone — should be prosecuted for price fixing when the bots work out how to do it without being told to do so, and without communicating with each other? In the US, where the Federal Trade Commission has been pondering the prospect, the answer seems to be no one, because only explicit collusive agreements are illegal. The bots would only be abetting a crime if they started scheming together. Tacit collusion, apparently, would be fine.

This is a reminder that algorithms can misbehave in all kinds of intriguing ways. None of us can quite shake the image of a Skynet scenario, in which an AI triggers a nuclear war and then uses Arnold Schwarzenegger as the model for a time-travelling robot assassin on a mission to suppress human resistance. At least that strategy is refreshingly direct. The true scope of algorithmic mischief is much subtler and much wider.

We are rightly concerned about algorithms that practice racial or sexual discrimination, by accident or design. I am struck by how quickly tales of racist algorithms have gone from novelty to cliché. The stories may fade but the issue is not going away.

Algorithms that simply magnify human errors now appear almost quaint. In 2012, the Financial Times had a headline, “Knight Capital glitch loss hits $461m”; those were innocent times.

Then there were those T-shirts selling on Amazon a few years ago, offering offensive slogans such as “Keep Calm and Hit Her”, and bizarre ones such as “Keep Calm and Skim Me”. Hundreds of thousands of slogans were assembled by an algorithm and, if any appealed, the vendor would print them on demand. “We didn’t do it, it was the algorithm,” was a weak defence in 2013, but at least it was novel. That is no longer true.

We are also realising that the algorithms can amplify other human weaknesses — witness recommendation engines on YouTube and Facebook that seem to amplify disinformation or lead people down the dark tunnels of conspiracy thinking or self-harm.

By no means are all malevolent programs an accident; some are designed with mischief in mind. Bots can be used to generate or spread misinformation. Jamie Bartlett, author of The Dark Net (US) (UK), warns of a future of ultra-personalised propaganda. It is one thing when your internet-enabled fridge knows you’re hungry and orders yoghurt. It’s another when the fridge starts playing you hard-right adverts because they work best when you’re grumpy and low on blood sugar. And unless we radically improve both our electoral laws and our digital systems nobody need ever know that a particular message was whispered in your ear as you searched for cookies.

Obviously, both the law and regulators must be nimble. But ponder, too, the challenges for corporate public relations and social responsibility departments. The latter is about being a good corporate citizen; PR is about seeming to be so. But who takes corporate responsibility for a harmful or tasteless decision made by an algorithm?

It is not an entirely new problem. Before there was tacit collusion between algorithms, there was tacit collusion between sales directors. Before companies blamed rogue algorithms for embarrassing episodes, they could blame rogue employees, or their suppliers. Can we really blame the bank whose cleaning subcontractor underpays the cleaning staff? Or the sportswear brand opposed to sweatshop conditions, whose suppliers quietly hire children and pay them pennies?

The natural answer is: we can and we do, but subcontracting is a source of both deniability and complexity. Subcontracting to algorithms complicates matters, too. But we are going to have to figure it out.

 

Written for and first published in the Financial Times on 22 February 2019.

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Is life a bet, or an experiment?

Since the official Brexit policy of the UK government now seems to be “accidents happen”, it is a nourishing age for those who dine on uncertainty. Most of us, however, started feeling queasy long ago. If you’re looking for guidance as to how to digest the unpredictabilities of life, why not turn to a poker player for advice?

Annie Duke, author of Thinking In Bets (UK) (US), says that “wrapping our arms around uncertainty and giving it a big hug will help us become better decision makers”. Fair enough. If we’re going to have to eat our uncertainty broccoli anyway, it may be best to swallow it down before it goes cold and limp.

As the winner of several million dollars as a professional poker player, Ms Duke has some credibility on this point. But is she right?

One quibble is that games have a more tightly-defined spectrum of uncertainty than reality does. Edward Thorp, a mathematician who achieved considerable success at blackjack and as a hedge fund manager, found (UK) (US) that the true risks he faced in the casinos were not an unlucky turn of the card, but crooked dealers and poisoned coffee. Not for nothing does Nassim Taleb, author of The Black Swan (UK) (US) warn of the “ludic fallacy” — treating the unknown risks of life as though they were the known risks of a game of chance.

Still, poker is a more instructive game than many others. John von Neumann, the brilliant mathematician who laid down the foundations of game theory in the late 1920s, was a poker player. Poker was no mere computational problem like chess, he said: “Real life consists of bluffing, of little tactics of deception, of asking yourself what is the other man going to think I mean to do, and that is what games are about in my theory.”

So what does poker teach us about “wrapping our arms around uncertainty”? Ms Duke offers us several lessons.

One is that, since luck matters as well as skill, bad decisions can have good outcomes, and vice versa. If you drive drunk, you will probably get home without killing anyone, but that would not make drunk driving a good decision.

A second lesson is that we should always be willing to ask ourselves, “do I want to bet on that?” — it’s easy to be overconfident if there are no obvious consequences for being wrong. A bet forces us to think about the odds and the possibility that someone else may know better.

So there is much to be said for thinking in bets. Yet we should not overlook an alternative approach to uncertainty: thinking in experiments. An experimental thinker views the uncertainties of the world as something to be resolved through tentative trial and error. Try something modest or reversible; an experiment doesn’t need to be a double-blind, randomised controlled trial to yield useful information. If it works, do more of it.

Some decisions are by their nature irreversible. Each big poker hand is a one-shot proposition that does not offer much scope for experiment. The same could be said of some investments: if you think shares in Tesla are cheap, there is little to be said for buying just one share and watching it to find out what happens to its price. An experiment cannot help; instead you must figure out whether the odds are in your favour, and take the plunge.

But other decisions are more experimental. In these cases, the choices can be made in stages, with each step designed to reveal some information. From Marvel’s decision to publish the Spider-Man comics (that went well) to Google’s launch of the G+ social network (that didn’t) a company can see what works and then either redouble its efforts or abandon the project. For an individual, anything from a new hobby to a new career can be treated as an experiment.

Many of the decisions we make are reversible. Only our stubbornness makes them permanent. Thinking in bets forces a commitment, which is sometimes helpful but sometimes not. Thinking in experiments allows us to learn.

I thought of all this when reading of poker professional John Hennigan’s $30,000 bet that he could move to Des Moines, Iowa, and live there, just for a few weeks. As Ms Duke tells the story, Mr Hennigan was bored out of his mind within days, and paid $15,000 to buy himself out of the bet and move back to Las Vegas. That’s thinking in bets at its worst: an idle thought (“should I move to Des Moines?”) became a high-stakes zero-sum game. Fun — if you like that kind of thing.

A few years ago, my family were agonising over a similar question (“Should we move to Oxford?”). We vacillated and made lists of pros and cons. What resolved the uncertainty was realising the decision could be an experiment: rather than selling up, we could rent a place in the city for a year to see how things worked out. Running this experiment created some additional costs, but we have never regretted doing it.

Thinking in bets is a rigorous and admirable habit, but not everything has to be a high-stakes poker hand. If you can make it work, thinking in experiments is less painful.

 

 

Written for and first published in the Financial Times on 15 Feb 2019.

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Why inflation is good for us

Not long ago, I wrote a column in defence of central banks. Some readers were quick to disagree. Central banks had failed to maintain “the real value of our fiat currencies”, wrote one, urging me to ponder how inflation had eroded the true value of savings over the decades.

A glance at Venezuela, where inflation over the past year has been more than 100,000 per cent and the economy is breaking down, reminds us that this is no idle complaint. Central banks must keep inflation under control. But what does “under control” mean? How much inflation is too much? And — a question only an economist could ask — how much inflation is too little? It goes without saying that hyperinflation is an economic catastrophe, so the first thing to check is whether hyperinflation is likely in an advanced economy — or indeed a competently governed country of any sort. It is not.

In 2012, economists Steve Hanke and Nicholas Krus assembled a list of every confirmed episode of hyperinflation in history. There weren’t very many: 56 in total, mostly in the 20th century, to which we might add recent outbreaks in Zimbabwe, Iran, Venezuela and perhaps North Korea. France suffered a bout in the 1790s, but most instances of hyperinflation occurred either in central European states after the first world war (including the infamous crisis in Weimar Germany), or during or immediately after the second world war (including Hungary, history’s worst example of hyperinflation), or in the eastern bloc as the Soviet Union disintegrated.

Hyperinflation does not strike at random, and it does not happen because central banks briefly slumber. It must be manufactured by the relentless printing of money, generally as the last resort in the face of political dysfunction alongside a severe fiscal crisis. Perhaps it is rash to say so, but I think we can set aside fears of hyperinflation in an advanced economy today. If it ever does happen, it will be only one element in a far more comprehensive economic disaster.

But the readers who emailed to complain about inflation did not express concerns about hyperinflation. They are worried about low-level ambient inflation, the kind that central banks not only tolerate, but actively seek. Central banks do not try to maintain “the real value of our fiat currencies”, but to erode them, typically by 2 per cent a year. They have often been explicitly instructed to do so by elected politicians.

Are those instructions wise? Even 2 per cent inflation will halve the value of money in 36 years. That seems bad, but let’s try to pin down why it might matter. It may help to remember what it is that we expect any good currency to do.

First, we want it to serve as a medium of exchange, allowing me to pick up a loaf of bread without having to persuade the baker to swap it for a copy of The Undercover Economist Strikes Back. Inflation at 2 per cent a year — or 5, or even 20 — does not prevent money serving as a medium of exchange.

The second, and perhaps most fundamental, role of money is as a stable unit of account. It helps us understand the economic forces around us, whether a particular product is expensive or cheap, without resorting to a calculator. Hyperinflation destroys that. “Are we ruined or in clover?” asks a character in an Erich Maria Remarque novel set in the Weimar hyperinflation. No one knows. But moderate inflation will not boggle minds on a trip to the shop.

Inflation does more obvious damage to money’s third role, which is as a store of value. If you stick your currency under the mattress then inflation will hurt you. It will also hurt if you have a non-indexed pension, or cannot find a high-interest savings account. Normally, however, a well-functioning financial sector offers returns to compensate for inflation.

That has not been the case since the 2008 financial crisis, of course. But the pain savers are feeling is not because central banks have carelessly let inflation take off. It is the result of a deliberate policy of low interest rates to stimulate spending and investment. Perhaps this policy is a mistake, perhaps not. But it would be wrong to view it as a dereliction of duty.

Another source of pain is governments’ fondness for using inflation as a way to grab a bit more revenue, by taxing nominal interest payments. It’s an insult for savers, but let’s be realistic: the tax would be levied somehow anyway. Inflation is sometimes the taxman’s chisel, but he has other tools.

It is surprisingly difficult to find any serious costs to low levels of inflation. In contrast, the benefits are easily stated: more room to stimulate the economy in a recession, and more room for real wages to adjust if they must. Olivier Blanchard, during his time as chief economist of the IMF, even floated the idea that the inflation target should be 4 per cent, not 2 per cent. He is by no means alone in that opinion. Like a low dose of aspirin, a low dose of inflation is unlikely to do much harm — and it can prevent an economic heart attack.

 

Written for and first published in the Financial Times on 8 Feb 2019.

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How high should the top rate of tax be, and who should pay it?

What should the top rate of income tax be? Should it be 70 per cent, as has been informally suggested by the young star of the US Democratic party, Congresswoman Alexandria Ocasio-Cortez? That instinctively feels too high to me. But, as an economist with sporadic hopes of making logical arguments based on evidence, I admit that “instinctively feels too high” is a weak response.

What about 50 per cent, the official policy of the UK’s opposition Labour party at the last general election? Or zero, the optimal top rate that emerged from a thought experiment posed by the late James Mirrlees, a Nobel laureate in economics?

An alternative is to tax wealth instead of income, as US Democratic Senator Elizabeth Warren has proposed. But — at least in principle — there is not much difference between a small annual tax on total wealth and a large tax on the nominal return generated by that wealth.

To make the case for a top rate of tax above 70 per cent, it helps to believe four things.

The first is that taxable income itself won’t evaporate in the face of a high rate, as it did in the UK when the top tax rate was briefly raised from 40 to 50 per cent in 2010, then cut to 45 per cent. Most high earners found it easy to realise income early, or late, and avoid the 50 per cent rate. A permanent increase is harder to avoid; so is an increase that is enforced with determined (or draconian) measures; as is an increase levied by a large economy with global legislative reach such as the US. In smaller economies such as the UK’s, the very rich are more likely to take themselves elsewhere for any given tax rate.

One academic paper produced by Emmanuel Saez (a star in the study of inequality) and Peter Diamond (a Nobel laureate and colleague of Mirrlees) estimated that the combined rate of tax on the income of high earners could be 73 per cent in the US without proving counter-productive. Another paper, published in the same journal, by Gregory Mankiw and co-authors, put the optimal top rate at just under 50 per cent instead. The difference lies in the assumptions.

The second thing one needs to believe is that the rich will barely miss any extra income if tax rates rise. The truth of this is unknowable, although another famous study from yet more Nobel laureates, Daniel Kahneman and Angus Deaton, suggests that money will not improve your everyday mood and wellbeing after an income of $75,000 a year or so. To reach their conclusions about the 73 per cent rate, Professors Diamond and Saez assume that a dollar is 25 times more valuable to a person on about $50,000 a year than to a person on $500,000. That is not an insane assumption, but it’s an assumption nonetheless.

If you accept these first two beliefs, the economic case for a high top rate of tax follows. A high rate maximises revenue if the tax base doesn’t shrink too much, and revenue maximisation is a reasonable goal if it’s true that the rich would barely notice the lost income.

But this argument ranges far beyond economics. If you like high tax rates, the third thing it helps to believe is that inequality is intrinsically corrosive. Perhaps it undermines democracy. Perhaps it causes stress, envy or resentment. The empirical evidence is not much help here; it is sketchy and often seems tendentious. Causal channels are unclear: does inequality lead to a hollowed-out state? Or does a hollowed-out state enable inequality? Perhaps a thought-experiment is more helpful here: how would you feel about a policy that simply confiscated resources from the super-rich and destroyed them? Would such a policy be a criminal waste and a grotesque infringement of liberty, or a helpful rebalancing of the scales?

Then there’s a fourth, often unstated, belief: that the rich have so much money that a high rate of tax will raise serious revenue. That depends on who you regard as “rich”. Ms Ocasio-Cortez mentioned a threshold of $10m. Profs Diamond and Saez focused on the highest earning 1 per cent of taxpayers, implying that the band would apply above around $500,000 a year. The Labour party wanted its highest rates to apply on incomes over £100,000.

These are very different definitions of “rich” and they have very different implications for revenue. For example, Ms Ocasio-Cortez’s income threshold of $10m is higher than that required to get into the top 0.01 per cent of the US income distribution: about 16,000 families. This tiny slice of the US population receives a less-than-tiny 5 per cent of total US income — which nevertheless implies that 95 per cent of income is earned by those making less.

The super-rich are a tempting target, but a serious attempt to raise revenue cannot stop with them. Whether we are talking about income or wealth, the lion’s share lies not with the billionaires but with the comfortably off. It is nice to talk about taxing somebody else’s money, but in a world of chronic budget deficits and worsening demographics, the ethics and economics of higher tax rates are unlikely to remain someone else’s problem.

 
Written for and first published in the Financial Times on 1 Feb 2019.

My book “Fifty Things That Made the Modern Economy” (UK) / “Fifty Inventions That Shaped The Modern Economy” (US) is out now in paperback – feel free to order online or through your local bookshop.

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