Tim Harford The Undercover Economist

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Articles from the New York Times, Forbes, Wired and beyond – any piece that isn’t one of my columns.

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The real answer to the problem of texting while driving

The UK government is — again — cracking down on driving while using a mobile phone. Tougher sanctions and sharper enforcement will no doubt make some difference. But the real risk of driving while impaired — either drunk, or using a phone — is not the risk of losing your licence. It’s the risk of being in a serious accident. That’s not enough to change the behaviour of some people. What will?

A cardinal rule of behaviour change is: make it easy.

A fine example is the idea of the “designated driver”, the person who stays sober and drives his or her inebriated friends home. It’s a clever concept. The designated driver is the hero, “the life of the party”, who makes it possible for everyone else to drink socially. Friends take turns to be the designated driver, tapping into deep habits of reciprocity. And the question, “who’s the designated driver?” reinforces the social norm that drunk-driving just isn’t right.

What’s the equivalent for texting while driving? It’s not immediately obvious. Distracted driving, like drunk-driving, is dangerous. But the parallel is imperfect because the decision-making process is very different. Having some drinks with friends, knowing I must drive later, is one kind of stupidity. Glancing at a phone which pings at me as I drive across town, then impulsively trying to tap out a reply, is a different kind.

Many of us have deeply ingrained habits of checking our phones and responding to their beeps. That’s not an accidental glitch in the interface: our phones are designed to interrupt us. Ad-funded apps need to attract our attention as often as possible. Public safety demands that we “make it easy” to ignore our phones while driving; the phones themselves want the exact opposite.

Most phones have an “airplane mode”, but not an obvious “drive mode”, despite the fact that your phone is vastly more likely to cause an accident in a car than in a plane. That should change. Smartphones should have, as standard, an easily accessible, well-publicised drive mode. Drive modes do exist, and in the US, the National Highway Traffic Safety Administration has been pushing the idea. But they’re not prominent.

Drive-mode phones might automatically read out text messages, automatically reply to such messages with “sorry, I’m driving”, and send incoming calls directly to voice mail — while allowing drivers to play music and use satellite navigation. In short, drive-mode phones would stop pestering us for our attention.

But why aren’t drive modes more popular? Perhaps we’re waiting for a clever marketing campaign: the “designated driver” idea managed to get itself into The Cosby Show and Cheers.

But we also have to recognise the perverse incentives at work. Many of us want to be distracted less by our phones — not just while driving, but in meetings, during conversations, at mealtimes and in the bedroom. The phones themselves want something rather different. Distracted driving is an acute symptom of a wider problem: distracted living.



Written for and first published in the Financial Times.

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2nd of March, 2017Other WritingComments off
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Kenneth Arrow, economist, 1921-2017

Kenneth Arrow, who has died aged 95 at his home in Palo Alto, California, on Tuesday was a towering figure in 20th century economics. In 1972, at the age of 51, he won one of the first Nobel memorial prizes in economics, the youngest winner then or since. Yet even a Nobel Prize understates Arrow’s contribution to economic theory. A brilliant mathematician, he ranged widely, breaking ground in areas that have subsequently yielded many further Nobels, including risk, innovation, health economics and economic growth.

Two achievements are particularly celebrated: his impossibility theorem about the paradoxes of social choice, and his welfare theorems, which formalised the most famous intuition in economics — Adam Smith’s idea that a market produces social good from individual selfishness.

Born in New York on August 23 1921 to immigrant parents, Kenneth Joseph Arrow had his formative experiences shaped by poverty — his businessman father “lost everything” in the Depression. But Arrow flourished at school and received an MA in mathematics from Columbia University at the age of 19. He interrupted his graduate studies to serve as a wartime weather researcher and US Army Air Corps captain.

His doctorate, published in 1951, made up for lost time. The thesis explored the problem of turning individuals’ preferences into a picture of what a society as a whole preferred. Scholars had long known that voting systems could produce perverse results but Arrow went further, showing that the very idea of “what society prefers” was incoherent. He set out four reasonable sounding requirements for building social preferences from individual ones — and proved that no system could satisfy all four of those requirements.

Arrow then turned to the familiar problem of supply and demand. In a well-functioning market for a single good such as apples, there is an efficient outcome with a price at which the number of apples supplied would equal the number of apples demanded.

But that was just one market. It was influenced by the market for pears, for agricultural land, for farm labourers and even for bank loans. Each market pushed and pulled others. What happened when one considered the interactions between every market in the world?

Working at times with the French economist Gérard Debreu, Arrow demonstrated that the intuitions from a single market could be generalised. First, there was a general equilibrium at which prices equalised supply and demand in every market at once. Second, this equilibrium was efficient. And third, any efficient allocation of resources could be reached by redistributing wealth and then letting competitive markets take over. Markets could still fail, but Arrow’s analysis explained the circumstances under which they would succeed.

Alongside such deep theoretical work, Arrow made many contributions to practical economic problems from insurance to healthcare to climate change. On occasion he took an active role on politically contentious issues, and was co-author of the 1997 “Economists’ Statement on Climate Change”, which warned of the dangers of global warming.

He was also noted for his love of gossip and his quick wit. One story tells of Arrow and a colleague waiting for an elevator to take them down, while several passed them going up. The colleague wondered aloud why everyone was going up. The immediate reply: “You’re confusing supply with demand.”

Arrow spent most of his career at Stanford University, apart from an 11-year spell at Harvard. He married Selma Schweitzer in 1947; she died in 2015. He is survived by his sons David and Andrew. He is also survived by his sister Anita, who married Robert Summers, a noted economist and brother of Nobel laureate Paul Samuelson. Her son, Arrow’s nephew, is the former US Treasury secretary Lawrence Summers.
Written for and first published in the Financial Times.

 

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23rd of February, 2017Other WritingComments off
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Undercover Friday – Lies and Statistics

A friendly guide to fake news…

Since this seems as topical as ever, a few interesting titbits. Here’s an attempt by two economists (Gentzkow is widely admired, haven’t encountered Alcott before) to quantify the electoral impact of fake news stories circulating through social media. Here’s the wonderful Maria Konnikova on “Trump’s Lies vs Your Brain” – although it’s not going to cheer you up.  William Davies takes a step back and asked where statistics originally came from, why we no longer seem to trust them, and what comes next. And here’s a brilliant-looking reading list from two academics at the University of Washington on “Calling Bullshit” in the modern age. And my own feature article – almost a year old now, dated in some ways and horrifyingly relevant in others, is “How Politicians Poisoned Statistics“.

Musical recommendation

Try Jimmy Scott, “Holding Back the Years”. (UK) (US) A sublimely restrained cover of Nothing Compares 2U and much else.

Books

I’ve been reading Daniel Levitin’s “A Field Guide to Lies and Statistics” (UK) (US) – so far does what it says on the tin. Clearly written and explained although these will be familiar ideas to many readers of this blog.

Or why not build your own Brutal London? (UK) (US) A papercraft kit of London’s best hunks of concrete.

Discovery of the week, though, is the Alan Moore classic “The Ballad of Halo Jones” (UK) (US). It’s weird and sprawling and flawed and I loved it.

My own book “Messy” is now out and available online in the US and UK.

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27th of January, 2017Other WritingComments off
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The Undoing Project – Book Review

Michael Lewis could spin gold out of any topic he chose but his best work has shone a spotlight into corners of the world that weren’t getting enough attention until Lewis came along. Liar’s Poker described bond trader Lewis Ranieri and the way securitisation revolutionised Wall Street in the 1980s. Moneyball covered baseball manager Billy Beane and anticipated the “quants” taking over the world. And The Big Short depicted Steve Eisman and Michael Burry, the men who spotted the financial crisis coming and bet vast sums on it.

The Undoing Project, then, is a departure, because it’s a biography of two well-established figures: Daniel Kahneman and Amos Tversky, the Israeli psychologists whose partnership produced the foundations of what we now call behavioural economics. Despite an introduction by Lewis declaring that he hadn’t heard of them until 2003, neither man remotely counts as an unknown.

When Tversky died young, in 1996, he was on the secret shortlist for a Nobel memorial prize in economics, and received a detailed obituary in The New York Times. Kahneman won the Nobel economics prize in 2002 and published his own bestselling book, Thinking, Fast and Slow, in 2011. Their ideas are everywhere; it’s almost impossible to find a book in the “smart thinking” section of a bookshop that doesn’t cite Kahneman and Tversky: an irony, since their work highlights many of the ways in which our thinking isn’t smart at all.

For example, they identified the “representativeness heuristic” — our tendency to make judgments by comparing an example to some mental model. When we meet a nervous, geeky-looking gentleman we note that he matches our stereotype of a programmer and, therefore, probably is a programmer. We forget that most of the people we meet are not, in fact, programmers, no matter how much they might resemble them.

This matters, because when judging probabilities we often skip over the real question, “Is this likely?”, in favour of a representativeness question: “Does this match my preconceptions?”. “Is the lump likely to be a malignant tumour?” becomes “Does the lump match my idea of what a malignant tumour looks like?”. It’s a reasonable rule of thumb that can lead us seriously astray.

All this is well known to anyone who has read Kahneman himself or popularisations of his work, so what does Lewis add? He’s a far better writer than most, meaning that even the familiar is fresh. And there is a great deal here that feels new. Lewis has done his homework; he has evidently talked to the right people — with the inevitable omission of the much-missed Tversky — and he knows how to tell a story simply, powerfully and with an eye for the telling detail.

Yet The Undoing Project gets off to a shaky start with a chapter discussing the selection of basketball players and the way in which basketball scouts commit various cognitive errors. Perhaps the success of Moneyball encouraged Lewis and his editor to think this was wise but it adds very little to our appreciation of the main characters, and much of the chapter is baffling unless one happens to be a fan of American sports.

All is forgiven in chapter two, when we meet the young Danny Kahneman, a Paris-raised Jew whose family spend the war dodging the Nazis and their sympathisers. No matter how many accounts one reads of such horrors, the reader is filled with sadness and a kind of awe at the survivors. At the age of seven, Danny was caught on the streets after curfew by an SS soldier. The man didn’t notice the yellow star under his sweater; instead, he hugged little Danny and, full of emotion, showed him a photograph of another young boy. Then he gave Danny some money and sent him on his way. “People were endlessly complicated and interesting,” Kahneman recalled.

Tversky is no less deftly portrayed: as a child, he was so bullish that he was willing to leap from a high diving board despite being unable to swim — he simply arranged for a bigger boy to be on hand to drag him to safety. As a soldier, Tversky saw a comrade pull the pin on a grenade-like explosive, then faint. As his commanding officer yelled orders to stay put, Tversky dashed forward, dragged the stricken man a few yards away, then dived to cover him, taking the shrapnel into his own body. Yet he berated his own men for carelessly taking risks. “If a bullet is going to kill me, it has my name on it anyway,” they would say. Tversky, a quick wit, reminded them that many bullets were addressed “To Whom It May Concern”.

Today, Kahneman and Tversky’s view of human psychology is widely accepted, and thanks to his longevity and his Nobel Prize, Kahneman is a more famous figure than Tversky. But Lewis takes us back in time, conjuring up the 1970s, when their ideas were new and controversial, they were operating in the backwater of Israeli academia, and when it was the mesmerising Amos rather than the quiet Danny who won all the attention.

Behavioural economics itself is not a major part of the book. Richard Thaler, the most important intellectual conduit between Kahneman and Tversky and economics, does not appear in the story until the closing chapters. While Tversky loved to have an intellectual foe to slay, it would diminish his work with Kahneman to define it merely as a takedown of textbook economics. By writing less about behavioural economics Lewis gives Kahneman and Tversky’s ideas room to breathe.

Lewis admires his subjects and believes they are right about everything important. He has no time for rational economic man, and brutally dismisses one noted critic of Kahneman, the psychologist Gerd Gigerenzer. But this isn’t a hagiography. Tversky is depicted as intellectually aggressive, contemptuous of many academics and perversely compelled to needle the vulnerable Kahneman. Meanwhile, a new side to Kahneman emerges. In my limited personal experience, Kahneman seems wise, kindly and stoic in the face of his advancing years. But Lewis describes the younger Kahneman as depressed, envious of his celebrated partner and desperately needy.

Nevertheless, it is clear that Lewis is cheering our heroes on, and the reader cannot help but join him. The story he tells of their intellectual love affair, and its painful disintegration, is vivid, original and hard to forget.
Written for and first published in the Financial Times.

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23rd of December, 2016Other WritingComments off
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Thomas C. Schelling, 1921 – 2016

Thomas C. Schelling, who died on December 13 at the age of 95, was a self-described “errant economist” who worked as a Cold War strategist and won the most prestigious prize of his profession.

Schelling was a popular winner of the Nobel memorial prize for economics. Journalists found his lively prose and counterintuitive ideas easier to describe than the complex equations of his fellow laureate Robert Aumann.

But the Californian-born economist was an unlikely laureate. His ideas were rich and influential — and easily expressed in plain English. He highlighted weaknesses in standard economic approaches, deploying vivid thought experiments more suited to moral philosophy than to economics, and rarely cited other academics.

Instead, Schelling used academia as a vantage point from which to advise the administrations of Presidents Kennedy, Johnson and Nixon. He was at Harvard University for 31 years, and said of one role there that it had given him a decade of “freedom to write and to consult, and I spent much of my time, especially during the summer, doing advisory work for the government.”

That advisory work drew on one discipline in particular.

Game theory had been dreamt up by the mathematician John von Neumann, as an attempt to model in mathematical terms human interactions from poker through to strikes or cartels.

The Hungarian-born von Neumann was a hawk (“If you say why not bomb [the Soviets] tomorrow, I say why not today?”) but Schelling took game theory in a new direction. He emphasised that even the most implacable foes could find areas of common interest — most obviously, during the Cold War, the necessity of avoiding mutual annihilation.

To this end, in the late 1950s and the 1960s, Schelling’s advisory work and his publications focused on issues of effective deterrence, communication, and the strategic limitation of arms. He was a consultant for Stanley Kubrick’s 1964 film Dr Strangelove, a nuclear annihilation comedy which introduces a “doomsday device”. The device is the ultimate deterrent: it will be triggered automatically in the case of war. Alas, it’s a secret, which limits the deterrent effect.

The doomsday device was the perfect illustration of some of Schelling’s favourite themes: strategic commitment, miscommunication, and unintended consequences. It is no coincidence that it was Schelling who insisted that Washington and Moscow establish a secure hotline and work out protocols for ensuring it was tamper-proof. This attention to details that others overlook was a spark for his best academic work. It is also is one reason why nuclear weapons have not been used since 1945.

Schelling ended his advisory work with a letter opposing the 1970 US military campaign in Cambodia. He later worked on the problem of addiction, developing models of self-control that were precursors to what is today known as behavioural economics. This research was partly motivated by his own long and eventually successful struggle to stop smoking. And in 1980, at the request of President Carter, he became one of the first economists to work on the problem of human-induced climate change.

He also anticipated the use of complexity science in economics with a celebrated “chessboard” model of segregation. This showed how two racial groups could completely segregate from each other in a chain reaction despite being quite comfortable in a mixed neighbourhood.

These days such modelling is done on a computer, but Schelling originally explored the idea in a notebook doodle on a long flight. “It was hard to do with pencil and paper,” he told the FT in a 2005 interview. “You had to do a lot of erasing.”

Thomas Crombie Schelling was born in Oakland, California, on 14 April 1921. His father was in the US Navy, but despite Thomas Schelling’s crew cut, square jaw and family history, he did not fight in the war. For medical reasons, the military would not accept him. Instead he studied economics at the University of California, Berkeley and earned his PhD at Harvard. After a spell working on the Marshall Plan, he taught at Yale, Harvard and finally the University of Maryland.

Schelling married Corinne Saposs in 1947. After that four-decade marriage ended in divorce, he married Alice Coleman, who survives him, as do four sons, two stepsons and his younger sister, Nancy.

Written for and first published in the Financial Times.

17th of December, 2016Other WritingComments off
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How the shock of Brexit could make the British economy stronger

In 1975, the American jazz pianist Keith Jarrett found himself in an unenviable position. Shortly before beginning one of his improvised solo performances, he discovered that some backstage bungle had left him with an old rehearsal piano. It was out of tune, tinny and had sticky keys and pedals. After protesting and realising nothing could be changed, he decided to play anyway. The flaws in the piano pushed him to play in a new style, discovering fresh ways to express himself. And against all expectations — certainly against Jarrett’s — the result was a masterpiece: The Koln Concert album.

I have been thinking about the unplayable piano a lot since Britain voted to leave the EU. By any conventional analysis Brexit was an act of economic self-harm. But by any conventional analysis, a creaking little piano does not make for great music either. Might the UK economy somehow burst into a display of unexpected virtuosity in unpromising circumstances? Let us review the sticky keys and see what fresh tunes might be playable.

First, immigration. The debate on this has taken a xenophobic turn but the pure economics of tighter immigration also looks challenging, particularly for agriculture, catering, the National Health Service and higher education. Since EU migrants have more than paid their way, discouraging them will also weigh on public finances.

Second, trade. We don’t know what the post-Brexit trade landscape will look like but the UK will find it harder to remain an open economy. It will be more difficult to integrate with pan-EU supply chains, the costs of imports will rise and, while exporters benefit from a weaker pound, they may find themselves facing higher tariffs and, more important, non-tariff barriers.

Third, financial services. London will be a less attractive financial centre hub if it cannot be used as a base to provide financial services across the EU. US banks, in particular, may find Dublin, Frankfurt, Paris or New York to be more sensible vantage points to serve the EU market.

These, then, are the obstacles. What are the opportunities? As labour markets tighten, companies may invest more in skills and particularly in capital: better tools, smarter software and more robots. We may see a more productive economy with higher wages, at least for those who can manage the robots rather than be replaced by them.

If the UK economy cannot integrate smoothly with EU suppliers, that will raise costs but it may also stimulate more local networks. This import-substituting strategy is often associated with the policies of Latin American strongmen but it has occasionally worked.

Is there a bright side from a weaker City? Perhaps. A country that exports a lot of a commodity such as oil can start to suffer from the “Dutch disease”, a condition resulting from a currency so strong that it becomes almost impossible to do anything except pump oil and spend the earnings. In principle, the same thing might occur with a very concentrated industry such as the high finance of the City of London. If the oil — or the high finance — dries up then the exchange rate weakens and other industries can flourish. Perhaps this is part of what we are seeing now as the pound falters, and perhaps the misfortune of the City will be beneficial to other industries such as software or high-tech manufacturing.

There is also the possibility of building affordable houses. Once the country’s tabloid press can no longer blame Brussels about red tape, they may turn their fire on the British regulatory thicket holding back the economy: land use restrictions. If we had built more houses where people wished to live, fewer people would be feeling left behind and blaming Lithuanians for troubles that were engineered in Westminster.

All this suggests a British economy with a larger presence as a producer and consumer of high-tech software and robotics: the Japan of Europe, although hopefully without the quarter-century of economic stagnation. It is not impossible. Data collected by Massachusetts Institute of Technology’s Atlas of Economic Complexity project suggest that the UK has untapped capacity in industries such as cars and precision engineering.

I do not believe in “economic models”. Models are all very well when we are talking about Lego. When it comes to a major 21st-century economy, things are too complicated for that. We will have to see what emerges. The situation looks unpromising but so, too, did Keith Jarrett’s unplayable piano.

First written for the FT’s “Future of Britain” project.

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31st of October, 2016Other WritingComments off
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Why everyone should give a TED talk and how to do it

I found out the hard way that bad public speaking is contagious. As a schoolboy I was pretty good at speeches, in a schoolboyish way. I won competitions; being a sharp, witty speaker was a defining part of who I felt myself to be.

Then I grew up and started a corporate job, and something strange happened. My talks sagged into “presentations”, burdened by humourless clip art and plodding bullet points. The reason? I was surrounded by people who were stuck in the same beige offices giving the same beige presentations. Like many workplaces, we had reached an unspoken consensus that giving bad talks was just the way things were done.

Aside from tradition — and it is a powerful one — why else are most talks bad talks? One reason is fear. Being afraid does not itself make a speech bad; fear can make a talk electrifying or touching. But most speakers take the coward’s way out. Afraid of running out of words, they overstuff their speeches. And they prop themselves up by projecting their speaking notes on the wall behind them, even though everyone knows that providing rolling spoilers for your speech is a terrible idea.

A second reason is lack of preparation. Most speakers rehearse neither their argument nor their performance. That is understandable. Practising in front of a mirror is painful. Practising in front of a friend is excruciating. Rehearsing offers all the discomfort of giving a speech without any of the rewards of doing so. But it will make the end result much better.

For these reasons, I think you should give a TED talk. Almost anyone can. All you need is 18 minutes, a topic and an audience — if only your cat. No matter how often or how rarely you usually speak in public, the act of trying to give a talk in the tradition of TED will change the way you think and feel about public speaking.

As with anything popular, TED talks have their critics, but it is hard to deny that the non-profit organisation behind the videoed presentations on subjects from science to business has helped reinvent the art of the public speech.

TED talks are vastly more entertaining than traditional lectures, while more thought provoking than most television. But that is TED from the point of view of the audience. From the view of an aspiring speaker, the lesson of TED is that most speakers could raise their game. A few TED talks are by professional politicians or entertainers such as Al Gore or David Blaine. Most are not.

There are more than 1,000 talks on the TED website with more than 1m views, typically delivered by writers, academics or entrepreneurs who have been giving mediocre talks as a matter of habit, and who have been suddenly challenged to stop being mediocre. Faced with the obligation to deliver the talk of their lives, they decided to do the work and take the necessary risks.

These speakers have been offered good advice by the organisers of TED, but that advice has never been a secret. It is now available to anyone in the form of TED Talks (buy in the UK) (buy in the US), a guide to public speaking from Chris Anderson, the TED boss. It is excellent; easily the best public speaking guide I have read. (I should admit a bias: I have spoken twice at TED events and benefited from the platform that TED provides.) Unlike many in the genre, Anderson’s book is not a comprehensive guide to going through the motions of wedding toasts and votes of thanks. Instead, it focuses on the stripped-down TED-style challenge: an audience, a speaker, plenty of time to prepare, and 18 minutes to say something worth hearing.

There is no formula for a great talk, insists Mr Anderson, but there are some common elements. First and most important: there is a point, an idea worth hearing about. Second, the talk has a “throughline” — meaning that most of what is said in some way supports that idea. There may be stories and jokes, even surprises — but everything is relevant.

Third, the speaker connects with those listening — perhaps through humour, stories, or simply making eye contact and speaking frankly. Finally, the speech explains concepts or advances arguments by starting from what the audience understand, and proceeding step by step through more surprising territory. It can be very hard for a speaker to appreciate just how much she knows that her audience do not. One reason to rehearse is that an audience can tell you when they get lost.

Most speakers are able to do some of this, some of the time — an interesting anecdote, a funny line, an educational explanation. We are social beings, after all. We have had a lot of practice talking.

Much of what turns a half-decent talk into a brilliant one is the ruthless excision of the fluff — the throat-clearing introduction, the platitudes, the digressions, the additional points that obscure the central message, and the “er, that’s about it” conclusion. With an audience of 60 people, for instance, every minute you waffle is an hour of other people’s time you are wasting. Sharpen up.

My only quibble is that the book offers less to a speaker who is short of preparation time. Because Mr Anderson is so keen to tell speakers how to prepare, he does not fully engage with the challenge of improvised speaking or debating.

Marco “Rubot” Rubio’s presidential dreams may have been snuffed out because he seemed over-rehearsed and unable to improvise. And Martin Luther King Jr’s greatest moment as a speaker — the second half of “I have a dream” — was unscripted. Sometimes the improvised response is more powerful than a prepared speech can ever be.

Instead, Mr Anderson’s aim is to help readers give a full-blown TED talk, despite the hard work that entails. Fair enough. Preparing to give a high-stakes speech is like training for a marathon or studying for an exam: even if you only do it once, the process will teach you things you will always remember.

Written for and first published in the Financial Times.

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A short-cut to speeches

A TED-style talk takes weeks of preparation. What if you have hours, or minutes, to prepare?

• Say something worth hearing. “It’s not about you,” says Chris Anderson, who warns that business presentations are often sales pitches or boasts. He adds that the same information will land much better if it is “here’s what we’ve learnt” rather than “look how great we’ve been”.

• Less is more. Once you have found something worth saying, focus. Strip it down to a single core point. Everything about your speech — stories, jokes, statistics, graphics — should connect to that point.

• Your speaking notes should not intrude. Bullet points are a good idea if they are written on handheld cards, but not when projected on the wall behind you. If your speech is scripted, do not try to memorise it if you have no time, but become familiar with it. “There’s a big difference between being 90 per cent down in the script, and 60 per cent up and connected,” says Anderson.

• You are usually your own best visual aid. By all means use pictures, diagrams or video when they are good. But do not use substandard slides as wallpaper; when you have nothing to show, show nothing. Hit “B” to blank the screen and focus attention on you, or use empty slides.

• Practise. Even one run-through with a friend will help. Or find an empty room and record yourself on your phone. It is awkward but worth it.

• First and final impressions last. Improvised talks often suffer from a slow start and a limp finish. Think of a good opening and closing, and practise them. If you can start and finish strongly, you and your audience will both feel better.

11th of May, 2016Other WritingComments off
Highlights

How Politicians Poisoned Statistics

We have more data — and the tools to analyse and share them — than ever before. So why is the truth so hard to pin down?

In January 2015, a few months before the British general election, a proud newspaper resigned itself to the view that little good could come from the use of statistics by politicians. An editorial in the Guardian argued that in a campaign that would be “the most fact-blitzed in history”, numerical claims would settle no arguments and persuade no voters. Not only were numbers useless for winning power, it added, they were useless for wielding it, too. Numbers could tell us little. “The project of replacing a clash of ideas with a policy calculus was always dubious,” concluded the newspaper. “Anyone still hankering for it should admit their number’s up.”

This statistical capitulation was a dismaying read for anyone still wedded to the idea — apparently a quaint one — that gathering statistical information might help us understand and improve our world. But the Guardian’s cynicism can hardly be a surprise. It is a natural response to the rise of “statistical bullshit” — the casual slinging around of numbers not because they are true, or false, but to sell a message.

Politicians weren’t always so ready to use numbers as part of the sales pitch. Recall Ronald Reagan’s famous suggestion to voters on the eve of his landslide defeat of President Carter: “Ask yourself, ‘Are you better off now than you were four years ago?’” Reagan didn’t add any statistical garnish. He knew that voters would reach their own conclusions.

The British election campaign of spring last year, by contrast, was characterised by a relentless statistical crossfire. The shadow chancellor of the day, Ed Balls, declared that a couple with children (he didn’t say which couple) had lost £1,800 thanks to the government’s increase in value added tax. David Cameron, the prime minister, countered that 94 per cent of working households were better off thanks to recent tax changes, while the then deputy prime minister Nick Clegg was proud to say that 27 million people were £825 better off in terms of the income tax they paid.

Could any of this be true? Yes — all three claims were. But Ed Balls had reached his figure by summing up extra VAT payments over several years, a strange method. If you offer to hire someone for £100,000, and then later admit you meant £25,000 a year for a four-year contract, you haven’t really lied — but neither have you really told the truth. And Balls had looked only at one tax. Why not also consider income tax, which the government had cut? Clegg boasted about income-tax cuts but ignored the larger rise in VAT. And Cameron asked to be evaluated only on his pre-election giveaway budget rather than the tax rises he had introduced earlier in the parliament — the equivalent of punching someone on the nose, then giving them a bunch of flowers and pointing out that, in floral terms, they were ahead on the deal.

Each claim was narrowly true but broadly misleading. Not only did the clashing numbers confuse but none of them helped answer the crucial question of whether Cameron and Clegg had made good decisions in office.

To ask whether the claims were true is to fall into a trap. None of these politicians had any interest in playing that game. They were engaged in another pastime entirely.

Thirty years ago, the Princeton philosopher Harry Frankfurt published an essay in an obscure academic journal, Raritan. The essay’s title was “On Bullshit”. (Much later, it was republished as a slim volume that became a bestseller.) Frankfurt was on a quest to understand the meaning of bullshit — what was it, how did it differ from lies, and why was there so much of it about?

Frankfurt concluded that the difference between the liar and the bullshitter was that the liar cared about the truth — cared so much that he wanted to obscure it — while the bullshitter did not. The bullshitter, said Frankfurt, was indifferent to whether the statements he uttered were true or not. “He just picks them out, or makes them up, to suit his purpose.”

Statistical bullshit is a special case of bullshit in general, and it appears to be on the rise. This is partly because social media — a natural vector for statements made purely for effect — are also on the rise. On Instagram and Twitter we like to share attention-grabbing graphics, surprising headlines and figures that resonate with how we already see the world. Unfortunately, very few claims are eye-catching, surprising or emotionally resonant because they are true and fair. Statistical bullshit spreads easily these days; all it takes is a click.

Consider a widely shared list of homicide “statistics” attributed to the “Crime Statistics Bureau — San Francisco”, asserting that 81 per cent of white homicide victims were killed by “blacks”. It takes little effort to establish that the Crime Statistics Bureau of San Francisco does not exist, and not much more digging to discover that the data are utterly false. Most murder victims in the United States are killed by people of their own race; the FBI’s crime statistics from 2014 suggest that more than 80 per cent of white murder victims were killed by other white people.

Somebody, somewhere, invented the image in the hope that it would spread, and spread it did, helped by a tweet from Donald Trump, the current frontrunner for the Republican presidential nomination, that was retweeted more than 8,000 times. One can only speculate as to why Trump lent his megaphone to bogus statistics, but when challenged on Fox News by the political commentator Bill O’Reilly, he replied, “Hey, Bill, Bill, am I gonna check every statistic?”

Harry Frankfurt’s description of the bullshitter would seem to fit Trump perfectly: “He does not care whether the things he says describe reality correctly.”

While we can’t rule out the possibility that Trump knew the truth and was actively trying to deceive his followers, a simpler explanation is that he wanted to win attention and to say something that would resonate with them. One might also guess that he did not check whether the numbers were true because he did not much care one way or the other. This is not a game of true and false. This is a game of politics.

While much statistical bullshit is careless, it can also be finely crafted. “The notion of carefully wrought bullshit involves … a certain inner strain,” wrote Harry Frankfurt but, nevertheless, the bullshit produced by spin-doctors can be meticulous. More conventional politicians than Trump may not much care about the truth but they do care about being caught lying.

Carefully wrought bullshit was much in evidence during last year’s British general election campaign. I needed to stick my nose in and take a good sniff on a regular basis because I was fact-checking on behalf of the BBC’s More or Less programme. Again and again I would find myself being asked on air, “Is that claim true?” and finding that the only reasonable answer began with “It’s complicated”.

Take Ed Miliband’s claim before the last election that “people are £1,600 a year worse off” than they were when the coalition government came to power. Was that claim true? Arguably, yes.

But we need to be clear that by “people”, the then Labour leader was excluding half the adult population. He was not referring to pensioners, benefit recipients, part-time workers or the self-employed. He meant only full-time employees, and, more specifically, only their earnings before taxes and benefits.

Even this narrower question of what was happening to full-time earnings is a surprisingly slippery one. We need to take an average, of course. But what kind of average? Labour looked at the change in median wages, which were stagnating in nominal terms and falling after inflation was taken into account.

That seems reasonable — but the median is a problematic measure in this case. Imagine nine people, the lowest-paid with a wage of £1, the next with a wage of £2, up to the highest-paid person with a wage of £9. The median wage is the wage of the person in the middle: it’s £5.

Now imagine that everyone receives a promotion and a pay rise of £1. The lowly worker with a wage of £1 sees his pay packet double to £2. The next worker up was earning £2 and now she gets £3. And so on. But there’s also a change in the composition of the workforce: the best-paid worker retires and a new apprentice is hired at a wage of £1. What’s happened to people’s pay? In a sense, it has stagnated. The pattern of wages hasn’t changed at all and the median is still £5.

But if you asked the individual workers about their experiences, they would all tell you that they had received a generous pay rise. (The exceptions are the newly hired apprentice and the recent retiree.) While this example is hypothetical, at the time Miliband made his comments something similar was happening in the real labour market. The median wage was stagnating — but among people who had worked for the same employer for at least a year, the median worker was receiving a pay rise, albeit a modest one.

Another source of confusion: if wages for the low-paid and the high-paid are rising but wages in the middle are sagging, then the median wage can fall, even though the median wage increase is healthy. The UK labour market has long been prone to this kind of “job polarisation”, where demand for jobs is strongest for the highest and lowest-paid in the economy. Job polarisation means that the median pay rise can be sizeable even if median pay has not risen.

Confused? Good. The world is a complicated place; it defies description by sound bite statistics. No single number could ever answer Ronald Reagan’s question — “Are you better off now than you were four years ago?” — for everyone in a country.

So, to produce Labour’s figure of “£1,600 worse off”, the party’s press office had to ignore the self-employed, the part-timers, the non-workers, compositional effects and job polarisation. They even changed the basis of their calculation over time, switching between different measures of wages and different measures of inflation, yet miraculously managing to produce a consistent answer of £1,600. Sometimes it’s easier to make the calculation produce the number you want than it is to reprint all your election flyers.

Very few claims are eye-catching, surprising or emotionally resonant because they are true and fair

Such careful statistical spin-doctoring might seem a world away from Trump’s reckless retweeting of racially charged lies. But in one sense they were very similar: a political use of statistics conducted with little interest in understanding or describing reality. Miliband’s project was not “What is the truth?” but “What can I say without being shown up as a liar?”

Unlike the state of the UK job market, his incentives were easy to understand. Miliband needed to hammer home a talking point that made the government look bad. As Harry Frankfurt wrote back in the 1980s, the bullshitter “is neither on the side of the true nor on the side of the false. His eye is not on the facts at all … except insofar as they may be pertinent to his interest in getting away with what he says.”

Such complexities put fact-checkers in an awkward position. Should they say that Ed Miliband had lied? No: he had not. Should they say, instead, that he had been deceptive or misleading? Again, no: it was reasonable to say that living standards had indeed been disappointing under the coalition government.

Nevertheless, there was a lot going on in the British economy that the figure omitted — much of it rather more flattering to the government. Full Fact, an independent fact-checking organisation, carefully worked through the paper trail and linked to all the relevant claims. But it was powerless to produce a fair and representative snapshot of the British labour market that had as much power as Ed Miliband’s seven-word sound bite. No such snapshot exists. Truth is usually a lot more complicated than statistical bullshit.

On July 16 2015, the UK health phentermine secretary Jeremy Hunt declared: “Around 6,000 people lose their lives every year because we do not have a proper seven-day service in hospitals. You are 15 per cent more likely to die if you are admitted on a Sunday compared to being admitted on a Wednesday.”

This was a statistic with a purpose. Hunt wanted to change doctors’ contracts with the aim of getting more weekend work out of them, and bluntly declared that the doctors’ union, the British Medical Association, was out of touch and that he would not let it block his plans: “I can give them 6,000 reasons why.”

Despite bitter opposition and strike action from doctors, Hunt’s policy remained firm over the following months. Yet the numbers he cited to support it did not. In parliament in October, Hunt was sticking to the 15 per cent figure, but the 6,000 deaths had almost doubled: “According to an independent study conducted by the BMJ, there are 11,000 excess deaths because we do not staff our hospitals properly at weekends.”

Arithmetically, this was puzzling: how could the elevated risk of death stay the same but the number of deaths double? To add to the suspicions about Hunt’s mathematics, the editor-in-chief of the British Medical Journal, Fiona Godlee, promptly responded that the health phentermine secretary had publicly misrepresented the BMJ research.

Undaunted, the health phentermine secretary bounced back in January with the same policy and some fresh facts: “At the moment we have an NHS where if you have a stroke at the weekends, you’re 20 per cent more likely to die. That can’t be acceptable.”

All this is finely wrought bullshit — a series of ever-shifting claims that can be easily repeated but are difficult to unpick. As Hunt jumped from one form of words to another, he skipped lightly ahead of fact-checkers as they tried to pin him down. Full Fact concluded that Hunt’s statement about 11,000 excess deaths had been untrue, and asked him to correct the parliamentary record. His office responded with a spectacular piece of bullshit, saying (I paraphrase) that whether or not the claim about 11,000 excess deaths was true, similar claims could be made that were.

So, is it true? Do 6,000 people — or 11,000 — die needlessly in NHS hospitals because of poor weekend care? Nobody knows for sure; Jeremy Hunt certainly does not. It’s not enough to show that people admitted to hospital at the weekend are at an increased risk of dying there. We need to understand why — a question that is essential for good policy but inconvenient for politicians.

One possible explanation for the elevated death rate for weekend admissions is that the NHS provides patchy care and people die as a result. That is the interpretation presented as bald fact by Jeremy Hunt. But a more straightforward explanation is that people are only admitted to hospital at the weekend if they are seriously ill. Less urgent cases wait until weekdays. If weekend patients are sicker, it is hardly a surprise that they are more likely to die. Allowing non-urgent cases into NHS hospitals at weekends wouldn’t save any lives, but it would certainly make the statistics look more flattering. Of course, epidemiologists try to correct for the fact that weekend patients tend to be more seriously ill, but few experts have any confidence that they have succeeded.

A more subtle explanation is that shortfalls in the palliative care system may create the illusion that hospitals are dangerous. Sometimes a patient is certain to die, but the question is where — in a hospital or a palliative hospice? If hospice care is patchy at weekends then a patient may instead be admitted to hospital and die there. That would certainly reflect poor weekend care. It would also add to the tally of excess weekend hospital deaths, because during the week that patient would have been admitted to, and died in, a palliative hospice. But it is not true that the death was avoidable.

Does it seem like we’re getting stuck in the details? Well, yes, perhaps we are. But improving NHS care requires an interest in the details. If there is a problem in palliative care hospices, it will not be fixed by improving staffing in hospitals.

“Even if you accept that there’s a difference in death rates,” says John Appleby, the chief economist of the King’s Fund health think-tank, “nobody is able to say why it is. Is it lack of diagnostic services? Lack of consultants? We’re jumping too quickly from a statistic to a solution.”

When one claim is discredited, Jeremy Hunt’s office simply asserts that another one can be found to take its place

This matters — the NHS has a limited budget. There are many things we might want to spend money on, which is why we have the National Institute for Health and Care Excellence (Nice) to weigh up the likely benefits of new treatments and decide which offer the best value for money.

Would Jeremy Hunt’s push towards a seven-day NHS pass the Nice cost-benefit threshold? Probably not. Our best guess comes from a 2015 study by health economists Rachel Meacock, Tim Doran and Matt Sutton, which estimates that the NHS has many cheaper ways to save lives. A more comprehensive assessment might reach a different conclusion but we don’t have one because the Department for Health, oddly, hasn’t carried out a formal health impact assessment of the policy it is trying to implement.

This is a depressing situation. The government has devoted considerable effort to producing a killer number: Jeremy Hunt’s “6,000 reasons” why he won’t let the British Medical Association stand in his way. It continues to produce statistical claims that spring up like hydra heads: when one claim is discredited, Hunt’s office simply asserts that another one can be found to take its place. Yet the government doesn’t seem to have bothered to gather the statistics that would actually answer the question of how the NHS could work better.

This is the real tragedy. It’s not that politicians spin things their way — of course they do. That is politics. It’s that politicians have grown so used to misusing numbers as weapons that they have forgotten that used properly, they are tools.

You complain that your report would be dry. The dryer the better. Statistics should be the dryest of all reading,” wrote the great medical statistician William Farr in a letter in 1861. Farr sounds like a caricature of a statistician, and his prescription — convey the greatest possible volume of information with the smallest possible amount of editorial colour — seems absurdly ill-suited to the modern world.

But there is a middle ground between the statistical bullshitter, who pays no attention to the truth, and William Farr, for whom the truth must be presented without adornment. That middle ground is embodied by the recipient of William Farr’s letter advising dryness. She was the first woman to be elected to the Royal Statistical Society: Florence Nightingale.

Nightingale is the most celebrated nurse in British history, famous for her lamplit patrols of the Barrack Hospital in Scutari, now a district of Istanbul. The hospital was a death trap, with thousands of soldiers from the Crimean front succumbing to typhus, cholera and dysentery as they tried to recover from their wounds in cramped conditions next to the sewers. Nightingale, who did her best, initially believed that the death toll was due to lack of food and supplies. Then, in the spring of 1855, a sanitary commission sent from London cleaned up the hospital, whitewashing the walls, carting away filth and dead animals and flushing out the sewers. The death rate fell sharply.

Nightingale returned to Britain and reviewed the statistics, concluding that she had paid too little attention to sanitation and that most military and medical professions were making the same mistake, leading to hundreds of thousands of deaths. She began to campaign for better public health measures, tighter laws on hygiene in rented properties, and improvements to sanitation in barracks and hospitals across the country. In doing so, a mere nurse had to convince the country’s medical and military establishments, led by England’s chief medical officer, John Simon, that they had been doing things wrong all their lives.

A key weapon in this lopsided battle was statistical evidence. But Nightingale disagreed with Farr on how that evidence should be presented. “The dryer the better” would not serve her purposes. Instead, in 1857, she crafted what has become known as the Rose Diagram, a beautiful array of coloured wedges showing the deaths from infectious diseases before and after the sanitary improvements at Scutari.

When challenged by Bill O’Reilly on Fox News, Trump replied, ‘Hey Bill, Bill, am I gonna check every statistic?’

The Rose Diagram isn’t a dry presentation of statistical truth. It tells a story. Its structure divides the death toll into two periods — before the sanitary improvements, and after. In doing so, it highlights a sharp break that is less than clear in the raw data. And the Rose Diagram also gently obscures other possible interpretations of the numbers — that, for example, the death toll dropped not because of improved hygiene but because winter was over. The Rose Diagram is a marketing pitch for an idea. The idea was true and vital, and Nightingale’s campaign was successful. One of her biographers, Hugh Small, argues that the Rose Diagram ushered in health improvements that raised life expectancy in the UK by 20 years and saved millions of lives.

What makes Nightingale’s story so striking is that she was able to see that statistics could be tools and weapons at the same time. She educated herself using the data, before giving it the makeover it required to convince others. Though the Rose Diagram is a long way from “the dryest of all reading”, it is also a long way from bullshit. Florence Nightingale realised that the truth about public health was so vital that it could not simply be recited in a monotone. It needed to sing.

The idea that a graph could change the world seems hard to imagine today. Cynicism has set in about statistics. Many journalists draw no distinction between a systematic review of peer-reviewed evidence and a survey whipped up in an afternoon to sell biscuits or package holidays: it’s all described as “new research”. Politicians treat statistics not as the foundation of their argument but as decoration — “spray-on evidence” is the phrase used by jaded civil servants. But a freshly painted policy without foundations will not last long before the cracks show through.

“Politicians need to remember: there is a real world and you want to try to change it,” says Will Moy, the director of Full Fact. “At some stage you need to engage with the real world — and that is where the statistics come in handy.”

That should be no problem, because it has never been easier to gather and analyse informative statistics. Nightingale and Farr could not have imagined the data that modern medical researchers have at their fingertips. The gold standard of statistical evidence is the randomised controlled trial, because using a randomly chosen control group protects against biased or optimistic interpretations of the evidence. Hundreds of thousands of such trials have been published, most of them within the past 25 years. In non-medical areas such as education, development aid and prison reform, randomised trials are rapidly catching on: thousands have been conducted. The British government, too, has been supporting policy trials — for example, the Education Endowment Foundation, set up with £125m of government funds just five years ago, has already backed more than 100 evaluations of educational approaches in English schools. It favours randomised trials wherever possible.

The frustrating thing is that politicians seem quite happy to ignore evidence — even when they have helped to support the researchers who produced it. For example, when the chancellor George Osborne announced in his budget last month that all English schools were to become academies, making them independent of the local government, he did so on the basis of faith alone. The Sutton Trust, an educational charity which funds numerous research projects, warned that on the question of whether academies had fulfilled their original mission of improving failing schools in poorer areas, “our evidence suggests a mixed picture”. Researchers at the LSE’s Centre for Economic Performance had a blunter description of Osborne’s new policy: “a non-evidence based shot in the dark”.

This should be no surprise. Politicians typically use statistics like a stage magician uses smoke and mirrors. Over time, they can come to view numbers with contempt. Voters and journalists will do likewise. No wonder the Guardian gave up on the idea that political arguments might be settled by anything so mundane as evidence. The spin-doctors have poisoned the statistical well.

But despite all this despair, the facts still matter. There isn’t a policy question in the world that can be settled by statistics alone but, in almost every case, understanding the statistical background is a tremendous help. Hetan Shah, the executive director of the Royal Statistical Society, has lost count of the number of times someone has teased him with the old saying about “lies, damned lies and statistics”. He points out that while it’s easy to lie with statistics, it’s even easier to lie without them.

Perhaps the lies aren’t the real enemy here. Lies can be refuted; liars can be exposed. But bullshit? Bullshit is a stickier problem. Bullshit corrodes the very idea that the truth is out there, waiting to be discovered by a careful mind. It undermines the notion that the truth matters. As Harry Frankfurt himself wrote, the bullshitter “does not reject the authority of the truth, as the liar does, and oppose himself to it. He pays no attention to it at all. By virtue of this, bullshit is a greater enemy of the truth than lies are.”

 

Written for and first published in the FT Magazine

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20th of April, 2016HighlightsOther WritingComments off
Marginalia

Three pieces of Brexit Bullshit

A referendum on UK membership of the European Union is scheduled for June 23: dodgy statistics ahoy.

“Ten Commandments — 179 words. Gettysburg address — 286 words. US Declaration of Independence — 1,300 words. EU regulations on the sale of cabbage — 26,911 words”

Variants of this claim have been circulating online and in print. It turns out that the “cabbage memo” is a longstanding urban myth that can be traced back to the US during the second world war. Variants have been used to berate bureaucrats on both sides of the Atlantic ever since.

Part of the bullshit here is that nobody ever stops to ask how many words might be appropriate for rules on fresh produce. Red Tractor Assurance, the British farm and food standards scheme, publishes 56 different protocols on fresh produce alone. The cabbage protocol is 28 pages long; there is a separate 28-page protocol on pak choi and choi sum. None of this has anything to do with the EU.

Three million jobs depend on the EU

This claim is popular among “Remain” advocates — most famously the former deputy prime minister Nick Clegg. What makes this claim bullshit is that it could easily be true, or utterly false, and it all hangs on the definition of “depend”.

The claim is that “up to 3.2 million jobs” were directly linked to exports of goods and services to other EU countries. That number passes a quick reality check: it’s about 10 per cent of UK jobs, and UK exports to the EU are about 10 per cent of the UK economy.

But even if “up to” 3.2 million jobs depend on trade with the EU, that does not mean they depend on membership of the EU. Nobody proposes — or expects — that trade with the EU will just stop. Three million jobs might well be destroyed if continental Europe was to sink beneath the waves like Atlantis, but that is not what the referendum is about.

EU membership costs £55m a day

This one is from Ukip leader Nigel Farage, who says membership amounts to more than £20bn a year. In fact, the UK paid £14.3bn to the EU in 2014 and got £6bn back. The net membership fee, then, was £8.3bn, less than half Farage’s number.

But even the correct number is little use without context. It is, for example, just over 1 per cent of UK public spending. Not nothing, but not everything either. And non-member states such as Norway and Switzerland pay large sums to the EU to retain access to the single market, so Brexit would not make this bill disappear.

The membership fee is small relative to the plausible costs and benefits of EU membership, positive or negative. If EU membership is good for Britain then £8.3bn is cheap. And if the EU is holding Britain back, then a few billion on membership is the least of our worries.

 

Written as a sidebar for “How Politicians Poisoned Statistics“, and first published in the FT Magazine.

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16th of April, 2016MarginaliaOther WritingComments off
Other Writing

A modest proposal – let’s just abolish the Budget

Once upon a time, it made sense to have an annual Budget speech. When the central economic fact of the year was whether the harvest had failed or not, it behoved the Chancellor to declare how he planned to spend whatever he happened to have in his coffers. But a vital institution for the pre-industrial age has mutated into a mere circus for the post-industrial one. The central question that this Budget provoked in my mind was this: why on earth do we still have a Budget?

Skim through the transcript of yesterday’s speech — if you can bear to — and you’ll find that the items fall into a few categories: (1) trivial; (2) responses to silly self-imposed rules; (3) economic forecasts that will later be wrong; (4) pure rhetoric; (5) worse than useless; (6) irrelevant.

Mr Osborne opened with a list of all the ways in which the UK economy is strong, skimmed over all the ways in which it is weak, and blamed the Labour party or foreigners for everything. (Rhetoric.)

Then he ran through the latest outlook from the Office for Budget Responsibility, an institution that represents all that is best about rigorous independent economic forecasting — and is therefore bound to be wrong. (Bad forecasts.)

He admitted that he had broken his own rather odd rule about the ratio of debt to gross domestic product, before announcing that according to a different, nonsensical metric, he looked rather good. (Silly self-imposed rules.)

Mr Osborne threw the usual glitter-bomb of little presents. (Trivial.)

Consider the £19m for “community-led housing schemes” in the south-west of England. Very nice, but if every £1m of spending earned one word from the chancellor, his Budget speech would be considerably longer than War and Peace. Then there’s the donation of tampon VAT revenues to charity, the halving of the Severn Bridge toll, and a tax break for touring museum exhibitions. Isn’t it strange how the treats are emphasised and the multibillion pound cuts and tax rises are always relegated to the appendices?

Then there’s the Chancellor’s odd tradition of pencilling in an increase to fuel duty year after year and, regardless of circumstances, coming up with an excuse to cancel the increase one more time. (Worse than useless.)

We also have major reforms to the school system. (Nothing to do with the Budget.)

What are we left with? The bodged introduction of a sugar tax and yet another wheeze to reform pension saving, the Lifetime Isa. Both policies would have been far better separated from the rabbit-out-of-hat Budget show, and considered on their merits.

There have been more dramatic Budgets than this, of course, but even then the drama has too often fallen into the “worse than useless” category.

Would the country’s economic policy really be harmed if the chancellor set out his fiscal direction at the beginning of the parliament and left it unchanged unless extraordinary circumstances intervened?

We should abolish 100 per cent of Autumn Statements and 80 per cent of Budgets — that’s a fiscal rule that I could really get behind.

Written for and first published in the Financial Times.

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