Tim Harford's Blog, page 121

Odds and ends

Review by Tim Harford

An investigation into the art of forecasting argues for a pick-and-mix approach

The Signal and the Noise: The Art and Science of Prediction, by Nate Silver, Allen Lane RRP£25/Penguin Press, RRP$27.95, 544 pages



When it comes to soothsaying, there seem to be two types of person: those who will gladly and glibly opine on anything from the chance of rain tomorrow to the chance of Mitt Romney winning the presidency, and those who think the forecasting game is all but impossible, the exclusive preserve of fools and frauds.

This state of affairs is not good enough, says Nate Silver, a statistician most celebrated for his New York Times blog, FiveThirtyEight, and its forecasts of election results in the US. While prediction is indeed a difficult affair, it is not hopeless. Thoughtful people with serious theories and mathematical nous should get involved, argues Silver in The Signal and the Noise, not only because they have a good chance of raising the bar for forecasters but because prediction is the acid test of their expertise.

Although Silver is a numbers man, and his book is seasoned with graphs, tables and the occasional equation, he advocates a pick-and-mix approach to forecasting. A statistical model may or may not beat expert judgment, and a computer may or may not out-forecast a human, but a judicious combination of approaches will generally outperform any particular method.

What works in forecasting is not always effective when it comes to writing a book. Each chapter picks a different forecasting problem, from terrorism to baseball to climate change. These individual chapters are strong, and some of them are outstanding. The analysis of the subprime crisis is as lucid as any I have read, I was hooked by his account of computer chess and the explanation of weather forecasting is a revelation.

The whole is less than the sum of the parts, alas. A chapter on poker seems to be there because Silver was once a professional poker player; the chess chapter, while brilliant, seems barely relevant. His pen portraits do not satisfy (do we care about Robert Daum, whose research is briefly cited, now that we know he is “a doctor’s doctor, with a dignified voice, a beard, and a detached sense of humor”?) and at times his efforts to document his extensive research descend into name dropping. “I was told by Tim Berners-Lee,” he writes, of some fact or other. After the first 400 pages of this kind of thing one begins to wish that Silver’s editor had been more assertive.

Despite these frustrations, there is a great deal to admire in the book. It defies easy summary but at its heart is the admonition that we should all think more like Thomas Bayes, an 18th-century minister and mathematician, nonconformist in both roles. Bayes’ theorem, published posthumously, tells us how to combine our pre-existing view of the world with new information in a rational way.

Bayes’ theorem can produce some counterintuitive results. My colleague John Kay once published a pair of columns about the classic game show “Let’s Make A Deal”, in which a grand prize lurks in one of three boxes. The contestant provisionally chooses a box; the host of the show opens a different box to reveal no prize; then the contestant must decide whether to open her chosen box, or to switch at the last minute and open the only alternative. Bayes’ theorem demonstrates quite clearly that the contestant should switch, but Kay’s postbag was testimony to the fact that few people believe this conclusion.

Silver explains Bayes’ theorem with a dark example: the attacks on the World Trade Center. When the first plane hit the tower, horrified observers instinctively updated the possibility of a terrorist attack that day from “barely thinkable” to “distinctly possible”, although at that stage an accident could not be discounted. Bayes’ theorem shows that when the second plane hit, the chance of terrorism could be updated again, from “distinctly possible” to “all but certain”.

There is no need for a mathematical analysis to tell us that, but Silver argues convincingly that Bayes’ theorem is an important reality check on our efforts to forecast the future. How, for instance, should we reconcile a large body of theory and evidence predicting global warming with the fact that there has been no warming trend over the last decade or so? Sceptics react with glee, while true believers dismiss the new information.

A better response is to use Bayes’ theorem: the lack of recent warming is evidence against recent global warming predictions, but it is weak evidence. This is because there is enough variability in global temperatures to make such an outcome unsurprising. The new information should reduce our confidence in our models of global warming – but only a little.

The same approach can be used in anything from an economic forecast to a hand of poker, and while Bayes’ theorem can be a formal affair, Bayesian reasoning also works as a rule of thumb. We tend to either dismiss new evidence, or embrace it as though nothing else matters. Bayesians try to weigh both the old hypothesis and the new evidence in a sensible way. This is good advice, and less technical than it might sound.

Despite its flaws, The Signal and the Noise is a book worth reading. It says something new in a crowded field, it is fun to read, and it’s full of facts you will remember. There is some noise here, but Silver has also produced a signal that is a pleasure to follow.

Also published at ft.com.

There are many ways to price by gender

‘From December 21 . . .  insurers must apply an EU-wide ban on the use of gender to price products, such as motor insurance and annuities.’

Financial Times

He: And not before time. It’s outrageous that I have to pay more for my car insurance than you do. I’m a perfectly safe driver.

She: Of course you are, dear. But you also drive a lot more than I do, which is not unusual for men. Since you drive more miles you are exposing yourself to the risk of more accidents.

He: Am I? Oh.

She: This is one of the reasons that men have more accidents than women. Another, of course, is that some young men are aggressive, overconfident idiots. But in any case you should probably put the money you save into your pension pot because you’re going to need it when you get stuck with the low annuity rates we women have had to put up with.

He: But my life expectancy is shorter. I deserve much higher annuity rates. That’s outrageous.

She: So you’re outraged that discrimination against you hasn’t ended earlier, and equally outraged that discrimination in your favour isn’t going to continue for ever?

He: Hmph. I read Lex when this gender-neutral insurance idea was first floated. Lex said it was “philosophically ignorant”.

She: I hadn’t realised Lex was such a philosopher. But the ruling does raise some interesting questions about the nature of what makes discrimination so objectionable.

He: It does? I mean . . . yes, it does!

She: For example, imagine that black customers were charged more in restaurants. A disgraceful idea, I’m sure you’ll agree.

He: Absolutely. Disgraceful.

She: But why is it disgraceful? Is it because black people are perfectly good restaurant customers and don’t deserve to be charged more?

He: Yes. That’s it.

She: Or is the problem that it’s just wrong to lump people into a category such as “male” or “black”? That people should be treated as individuals rather than defined by their membership of some group?

He: Er, yes – you’ve hit the nail on the head there.

She: Or are we just intellectually lazy, culturally conditioned to break out in a cold sweat if somebody talks about racial discrimination, but complacent about discrimination against men or women?

He: Um, I think . . . 

She: Because that brilliant philosopher Lex seemed to think that gender discrimination was fine but racial discrimination was “plainly unfair”.

He: [Opens mouth, shuts it again.]

She: It will be interesting to see what happens to insurance pricing, though.

He: It’s obvious what will happen. Women will pay more for car insurance but men will pay no less; men will get smaller annuities but women won’t benefit.

She: That’s possible, but that would mean corporate profit margins going through the roof. I expect insurers would be keen to grab market share under those circumstances, which will mean premiums falling again. I’d guess that the new gender-neutral pricing will settle near the average of the old rates. That is, until the behavioural response sets in.

He: What behavioural response?

She: It will be a lot cheaper for young men to get car insurance, so expect to see more boy racers on the road. And women may well be more tempted to get their own pensions.

He: But in the end, we’ll all get used to this brave new egalitarian world.

She: We might not get too comfortable. Insurers will start looking at other correlates of risk. The obvious one is how far people drive: men tend to drive more than women. Then there are issues such as the choice of a sports car rather than a people carrier. Such distinctions may carry more weight in determining your premium than they do now. As for annuities, if they can’t pay any attention to your sex they might start paying more attention to your cholesterol.

He: I can see that this might get very intrusive.

She: It might. Or it might get very clumsy. Mortgage lenders used to be accused of using geography as a way of discriminating against minorities in the US, since ethnicity and postcode can be closely correlated. There are modern analogies: since women are on average smaller than men, perhaps in the future premiums will be proportionate to height. Stranger things have happened.

Also published at ft.com.

So many numbers, so little time

The world’s complexity is a symptom of economic success, but it can pose serious risks

The world is a complicated place. When the design student Thomas Thwaites decided to reverse-engineer a toaster, he discovered that it comprised 400 components; when Eric Beinhocker, then of the McKinsey Global Institute, tried to estimate the number of products and services available in a big urban economy such as London, he estimated that it was about tens of billions; the Bank for International Settlements reported that at the start of the credit crunch in 2007, the face value of outstanding derivative contracts was more than one quadrillion dollars.

This complexity is a symptom of economic success. But it can pose serious risks, especially when dealing with “tightly coupled” systems, from a web of financial contracts to a nuclear reactor.

We rely on regulators to keep us safe in the face of this complexity, but regulations have themselves become more complex. The original US constitution was less than 5,000 words long; the Acquis Communautaire, the body of EU law to which new countries must sign up, is about 35 million words in English. This difference surely reflects the gap between the 18th century and the 21st more than any peculiarly Eurocratic love of the baroque. After all, the famous Glass-Steagall Act of 1933 was 37 pages long but the recent Dodd-Frank Act, also designed as a response to a great financial crisis, is 848 pages long despite delegating many details to regulators. Andy Haldane of the Bank of England estimated that the eventual Dodd-Frank rules would top out at about 30,000 pages.

This looks like bureaucracy gone mad, yet it also looks inevitable given the complexity of the economy. But perhaps it is not.

First, economic complexity may not be causing the regulatory complexity: in the financial industry, the causation often runs the other way. The first credit default swap, for example, was designed in response to regulations on minimum levels of bank risk capital. The boom in elaborately repackaged sub-prime mortgages was fuelled by the fact that the repackaged products were risky – and thus promised higher returns – but ticked the regulatory box that said “safe”. Complex rules invite complex rule-bending.

Second, complex rules may be a very poor response to complex situations. This is an argument made both by Haldane and by Andrew Zolli and Ann Marie Healy in their recent book, Resilience, and they draw on different traditions.

Haldane cites work on decision-making by the psychologist Gerd Gigerenzer. Gigerenzer has found that in many different cases, simple rules of thumb outperform complex statistical rules unless huge amounts of data are available. With less data, the clever number-crunching “over-fits”, finding meaningful patterns in what is, in fact, random noise.

This may be true in financial regulation, too. Haldane looks at the largest 100 or so banks before the crisis and finds that, with hindsight, simple rules such as “highly leveraged firms are in danger” had 10 times the power to predict a future bail out than the sophisticated risk-weighting systems the regulators were actually using – although if simpler regulations were introduced, this pattern might disappear.

Zolli, meanwhile, turns to systems theory to argue that thickets of regulations and safety measures nudge us towards “robust-yet-fragile” systems, which are extremely safe in the face of predictable risks, yet crumble completely when something unexpected comes along.

Haldane and Zolli both say it is time for regulators to aim for a simpler financial system as a goal worth pursuing in its own right. And both recognise that if we want simpler banks, simpler bank regulations would be a promising place to start.

Also published at ft.com.

Where maths ends, computers begin

Machines have finally made their mark on economic theory with their use in agent-based modelling and simulations

Computers have transformed economic analysis. Data can be analysed in ways that would have astonished earlier generations of economists. But computers have made less of an impact on economic theory. The typical economic model describes a small number of decision makers whose thought processes (which may or may not be rational) can be boiled down to solving a fairly simple piece of maths.

Macroeconomics is similar, with each decision maker billed as a “representative agent”. The behaviour of all consumers can be summarised by figuring out what a typical consumer would do. Some objections to this approach are obvious, but it has not been easy to find an alternative. In recent years, though, computers have begun to change that, and make their mark on economic theory at last.

Perhaps the most ambitious use of computers is in agent-based modelling. Rather than letting one agent represent all consumers, you create a computer model with lots of agents. Computers aren’t strictly necessary: the most famous agent-based model, created by the great Thomas Schelling, used coins and a chessboard. But the model was highly stylised, with about 40 agents. Modern computers could in principle model every single person in the economy.

Econo-physicist Doyne Farmer, computer scientist Robert Axtell, macroeconomist Peter Howitt and microeconomist John Geanakoplos have been trying to create such a model. “We’re trying to get a simulation of the economy that’s faithful to the economy,” says Farmer. “Where you see macroeconomics emerging from the microscopic interactions of individuals.”

The early fruits of this project include a model of the housing bubble in Washington DC. The advantage of studying housing is that a good deal of information is publicly available both about the price history of each house, and about the characteristics of the people doing the buying and selling. The agent-based model can thus be carefully calibrated. The conclusion: the bubble wasn’t driven by low interest rates but by increasing loan-to-value ratios – an important finding for central banks looking to prevent future bubbles.

A less flashy use of computers is to run simulations to estimate an individual’s best course of action in an uncertain world. Consider this question: if you opened your mail this morning to discover that someone had sent a cheque for £10,000 – a tax refund, perhaps – how quickly should you spend it? The answer can’t be solved mathematically because so much of it depends on unknowns, such as future income. Yet we need to know how people will behave because the relationship between consumption and different sorts of income is fundamental to understanding how the economy works.

Keynesian ideas suggest people will spend such windfalls quickly. Milton Friedman tackled the question in 1957 and developed the idea of “permanent income”, smoothing out windfalls. But if you use traditional mathematical methods to model Friedman’s ideas, you’ll conclude that individuals will spend only 5 per cent or so of the windfall, while Friedman reckoned it was more like a third.

The difference lies in dealing with the uncertainties of life. The economist Christopher Carroll has found that computer simulations can encompass this uncertainty, and produce very similar answers to Friedman’s educated guess.

This is promising yet awkward for economics. Computer simulations cannot be checked, and unless traditional methods are completely superseded, there is bound to be an awkward gap between where the optimising mathematics ends, and the computer simulations begin. The future of economics may depend on finding ways to bridge that gap.

Also published at ft.com.

Off the rails when the figures don’t add up

‘Three officials at the Department for Transport were suspended on Wednesday after the award of a new contract to run the West Coast mainline rail franchise was cancelled because of “technical flaws” in the bidding process.’

FT.com, October 3

What are these “technical flaws”?



Good question. The way this works is that companies bid for the right to operate train services on particular routes. These rights are lucrative, which is why the government sells them at auction.

How hard can it be to compare two bids and see which one is larger? This is the kind of maths question we ask four-year-olds.



There are complications that put this way beyond the grasp of a four-year-old and into the intellectual realm of, say, a competent first-year undergraduate in economics or accounting. One is that the government can’t sell the rights to the highest bidder, because it needs to consider whether the trains will actually run. The East Coast mainline had to be nationalised three years ago when the winner walked away from the franchise.

The second problem is that the government doesn’t get the money straight away and must consider how to compare cash immediately with cash promised in a decade’s time. In the contest between Virgin Trains and FirstGroup, the latter offered more cash but a lot of that was due well into the future. FirstGroup was awarded the West Coast contract on that basis but the Department for Transport has now thought better of that decision.

It still doesn’t sound that hard.



No. Admittedly there are some profound issues about how to think about uncertain future events. But the department mandarins do not appear to have fallen down any deep philosophical rabbit holes. It sounds as though they either ignored the issue entirely or botched it on a basic level. The transport secretary said the problem was “the way in which inflation and passenger numbers were taken into account”, which if true is fairly elemental.

Aren’t such basic errors unforgivable?



There’s a more worrying question: given how complicated the modern world is, aren’t such basic errors inevitable? This seems to have been a howler, but large spreadsheets are ubiquitous and their size makes it almost impossible to eliminate errors. The Office for National Statistics misreported gross domestic product last year thanks to such an error.

Doesn’t this tell us more about civil servants than spreadsheets?



These are particularly egregious errors, but the private sector is hardly immune. For instance, in 2003 Fannie Mae made a spreadsheet error that led to it misstating its results by more than $1bn.

That’s really not the worst screw-up to affect Fannie Mae.



True, the credit crunch was worse. But there were some mathematical errors involved in that, too: the infamous “Gaussian copula” was an attempt to figure out how to account for correlations between assets, such as different subprime mortgages. Unfortunately, correlations are slippery and if you bet a few hundred billion dollars that they are going to behave themselves, you have a problem.



The whole thing was a slow-motion car crash.

Or a slow-motion air crash? An Air Canada flight ran out of fuel in mid-air in 1983. It was a pounds-or-kilograms thing. Luckily the captain was a glider pilot and managed to land the jet without killing anybody.

You’re starting to make me nervous.

Denial isn’t helpful. We need to accept modern life is full of mathematical, spreadsheet and programming errors. Two famous “man versus machine” matches were affected by such errors. Marion Tinsley, the greatest draughts player in history, was persuaded to accept a draw in one match in 1992 when his silicon foe, Chinook, announced the game was drawn according to its endgame database. It later transpired the database was corrupted and Chinook had no idea what it was doing. Garry Kasparov beat Deep Blue in a game in 1997, but misinterpreted a bizarre move by the computer as an effort to avoid “mate in 20” – suggesting the machine had a terrifying ability to look ahead. In fact, Deep Blue typically looked ahead six to eight moves. The random move was just that: random, the response to a software bug. Mr Kasparov’s confidence was shattered; he should have considered the possibility that even Deep Blue suffers from the occasional “technical flaw”.

Also published at ft.com.

The unpalatable business of spam

A new article provides a fascinating overview on the dynamics of unsolicited email and the fight to keep it at bay

A couple try to get cooked breakfasts at a greasy spoon, but their attempts to order are frustrated. The menu largely consists of Spam, and in any case the conversation – and indeed, the following sketch – is swamped by a crowd of Vikings singing “Spam, Spam, Spam, Spam”. A typical Monty Python skit, really.

Unsolicited email, often selling fake pills or watches, has a similar ability to drown out sensible communication, which may be why the name “spam” stuck, despite the initial protestations of the trademark owners, Hormel Foods.

Spam email rarely reaches my inbox these days, but this isn’t because spam itself is a thing of the past. Most emails “out there” are spam, but the vast majority are intercepted at some point.

So where do these emails come from? How? Who pays for them? And who pays for our defences against them? A new article by Justin Rao and David Reiley in the Journal of Economic Perspectives provides a fascinating overview.

It would be easy to block spam sent from a single fixed source, so spam emails are sent by “botnets”, swarms of home computers that have fallen prey to viruses and been co-opted by the spammers. These botnets are rented by merchants, who use a bewildering variety of aliases. One group of researchers identified 30 pharmaceutical merchants who, between them, were using almost 1,000 different “store front” web-page styles, more than 50,000 domain names and almost 350 million distinct URLs.

But who buys these products, typically shipping from China or India, from such obviously shady sources? Almost nobody. Rao and Reiley estimate that the hit rate is about one sale per 10 million emails sent – but then sending 10 million emails might only cost $50 or $60, so the spam continues.

If it’s clear who benefits from sending spam, it’s less clear who pays to block it. One case is instructive: when the vast Rustock botnet was shut down last spring, Microsoft and Pfizer (manufacturer of the genuine Viagra) took leading roles and Microsoft offered a $250,000 reward. This single episode reduced the proportion of spam email from almost 90 per cent to 75 per cent, creating large spillover benefits.

This seems typical: the big beasts of the internet have the incentive to fight spam, and it’s striking that the big three webmail providers with the resources to keep spam at bay – Google, Microsoft and Yahoo – have seen their market share rise from under 60 per cent to over 80 per cent since 2006. (Rao and Reiley wrote their working paper at Yahoo before moving to Microsoft and Google respectively.)

Economists often talk about “negative externalities” – private activities that produce public costs. Driving a car might produce a social cost of about 10 pence for every pound of private benefit, which is why economists advocate fuel duty and congestion charges. But the externality ratio for spam is about a thousand times higher – perhaps £100 per pound of private benefit. Vast resources are devoted to blocking spam, or deleting it when it gets through, but the actual benefit to the spammers is relatively tiny. Rao and Reiley reckon that even car theft has a lower externality ratio – at least the thief gets a car.

All this put me in mind of two immigration lawyers, Laurence Canter and Martha Siegel, often credited with being the first spammers back in 1994. Canter and Siegel defended their unsolicited bulletin board advertising: it was a matter of free speech, they said, and then published a book called How to Make a Fortune on the Information Superhighway. In the end, the real fortunes are being made by the likes of Amazon and Google. Spam is a small industry; annual revenues are about what Apple makes in a single day. Alas, it is a small industry with a long shadow.

Also published at ft.com.

Time for Dad to move to the garden shed

“Parents in work should be able to use pension savings to help their children buy a first property, according to proposals from Nick Clegg.”

– Financial Times

Dad?



Yes, darling?

Do you love me?



Of course I do; why do you ask such a thing?

Do you love me enough to use your pension to guarantee my mortgage with Barry?



[There is an awkward cough and a rustling of a newspaper.]

Dad, Nick Clegg says that you should be able to help me get on the housing ladder.



Nick Clegg should be old enough to remember that sometimes it’s more of a housing snake.

You’re always warning of a house price crash, Dad – but we’ve had the crisis and prices have fallen. Isn’t it time to buy?



Possibly, possibly not. For first-time buyers I seem to recall that prices relative to income are still well above the levels of the last bubble, at the end of the 1980s. I wouldn’t be so sure that a house is a one-way bet.

It may not be a one-way bet but it’s a bet I can’t take without your help.



What do you want me to do again?

I need you to guarantee my mortgage using the lump sum from your pension.



I see. That’s nice, darling. Isn’t that a bit risky for me?

No, it’s just to tick the boxes for the bank. I’ll pay the mortgage and you won’t have to pay anything.



I seem to remember that’s what everybody told AIG before it blew up. You basically want me to write a credit default swap on your mortgage and you’re assuring me there’s no risk. I’m afraid Barry has always seemed distinctly subprime to me.

That’s so rude, Daddy! Barry has a good steady job.



I wasn’t talking about his creditworthiness, my dear, but since we’re on the subject: there’s no such thing as a steady job in this day and age. There is always a risk that something will go wrong, and you, Nick Clegg and your bank would prefer that the risk landed on me.

But Dad, it’s such an imaginative policy: the older generation, who’ve benefited from rising house prices, have an opportunity to help out their kids, who have been shut out of the market by the same trend.



Nonsense. For a start, it’s not the older generation. It’s a very particular subset of people: people who aren’t old enough legally to draw money from their pension pot but are just about to be; who also have pension pots well above the national average; and who despite this don’t have spare cash to help out their children. I’d be surprised if more than a few thousand people take this up.

That’s a shame.



No, that’s a relief. The more people get involved in this the more instances we’ll have of parental pensions being poleaxed by their children’s financial misfortunes, which is hardly going to spread domestic peace and love. And it won’t help any more people get on the housing ladder, as you so strangely put it.

Why won’t it?



Because the only thing that will get more people on the housing ladder is more houses, something which this country has had a great deal of trouble accepting for some reason. If you don’t do anything to boost the rate of housebuilding, but you give financial help to one segment of the population – whether it’s key workers, or the children of moderately prosperous 54-year-olds – then you will simply pump up the price of houses until somebody else who would have been able to afford a house now cannot. This financial engineering can redistribute money and housing but it won’t create new houses. I realise higher prices might encourage more housebuilding but even that seems rather doubtful these days.

How can the older generation help the younger generation buy houses, then?



The main thing they could do is sell the houses they currently own and move somewhere smaller. Why on earth that would be preferable to simply building some more houses – in a recession, with the construction industry dragging down economic growth – is beyond me. But it would at least free up some housing stock.

Daddy, you’re an angel. I’ll get the garden shed all pimped out for you, and Barry and I should be able to help you move there by the end of next week.

Also published at ft.com.

Don’t take growth for granted

One economist believes modern inventions are puny compared to earlier innovations. Does this mean that human progress has hit a dead end?

The summer’s most talked about working paper in economics is by Robert Gordon, and it is simply titled “Is US Economic Growth Over?” And well he might ask: GDP per capita, the most obvious measure of economic growth, is lower today than it was when the financial crisis began in 2007.

The western world’s failure to recover from the crisis surely explains why Gordon’s gloomy thesis is getting so much attention, but, in fact, he takes great pains to avoid drawing conclusions from any short-term difficulties – even if the short term has now lasted more than half a decade.

Gordon has been arguing since the days of the dotcom mania that the information revolution looks rather puny compared with earlier waves of innovation, such as the internal combustion engine, indoor plumbing, electrification and the telephone – all of which took hold from about 1850 to 1900. This claim was plausible then and it’s plausible now. (Would you rather give up the smartphone, Facebook and broadband – or hot running water and your flush toilet?)

Let’s take this line of argument further. Economic growth is a modern invention: 20th-century growth rates were far higher than those in the 19th century, and pre-1750 growth rates were almost imperceptible by modern standards. Many have seen this as an encouraging trend, but Gordon draws a different lesson: growth is a recent phenomenon, so why assume that it will last?

If Gordon is right to claim that modern inventions are less impressive than those of the late 19th century, we would expect to see slow growth in US real GDP per capita. And, indeed, growth has been slowing since the 1960s, even setting the current recession to one side. (World GDP per capita growth, by contrast, has been just fine, as others close the gap on the US.)

All these observations raise uncomfortable questions. But for some answers, we need to ponder the likely forces at play. Both Gordon and Tyler Cowen, author of The Great Stagnation, point out that some easy gains – such as sending children to secondary school or allowing women to have careers – can only be enjoyed once. Important inventions, too – such as the car, the washing machine and the lavatory – admit only gradual improvement after the first few decades.

Demographics and debt accumulation have both speeded up growth in the past and, as the pendulum swings back, demographics and debt repayment will reduce it in the future.

Then there are pure resource constraints. Even assuming that climate change can be managed, there are limits to the rate at which we can burn fossil fuels, grow food and mine metals. Renewable energy sources are available, but less plentifully than we might hope. If economic growth is to continue unabated, it will have to be of a more ethereal kind, with energy and resource consumption becoming ever less significant.

Despite all this, I remain an optimist. The economist Michael Kremer pointed out two decades ago that with more people around, there are simply more possible sources of new ideas, and that high populations have tended to enjoy higher economic growth per person, despite resource constraints.

My inner contrarian also tells me to ignore Robert Gordon. During the dotcom boom I cited his work to anyone who would listen, but we are all stagnationists now. And yet: innovation won’t happen by magic. I argued in my last book, Adapt, that scientific and technical progress now seem to require larger teams, more cross-disciplinary work, more money, and older, more specialised scientists. It has become an organisational challenge that we are yet to take as seriously as we should. We’ve lived with astonishing economic growth for 250 years; perhaps we are starting to take this exciting companion for granted.

Also published at ft.com.

Some public wages are more equal than others

‘Twenty-five economists have written to George Osborne, urging the chancellor not to give up on his attempts to end national pay bargaining.’

Financial Times, May 18

Beware economists writing letters, that’s what I say.

I know, but in this case they have a point. We have an odd system in this country under which people doing the same job in a different part of the country are paid very different wages. What’s stranger, this inequity isn’t the result of some unstructured, decentralised process: it’s agreed in national public sector pay negotiations.

Eh? I thought that national pay negotiations were designed to make sure that pay was the same across the country, except perhaps for London and the south-east?

I suppose it depends what you mean by “equal”. “Equal” by what measure?



“Equal” by receiving the same amount of money, of course.

Ah, I understand. By the way, I’m thinking of taking on a butler. I wondered if you might fancy doing the job for £1,000 a year.

£1000 a year? What sort of a salary is that?

It’s an excellent salary – for 1950. After all, you said that two salaries were equal if they involved payment of the same amount of money. What I’m offering you is equal to a very good salary: £1000.

But we’re not living in 1950.

I’m confused. I thought you said that two salaries were equal if they involved payment of the same amount of money. What I’m offering you is equal to a very good salary.

In 1950.

But you don’t care about such things. It’s the same amount of money: £1,000.

This is ludicrous. Things were a lot cheaper in 1950.

Of course they were, but you’ve told me that’s just not relevant to you. I disagree; I think that it makes no sense at all to talk about a salary in terms of pounds unless you take into account what those pounds can buy. You can’t eat money, after all – and you can’t live in it, either. £40,000 a year is a nice salary in Hull. It will buy very little in Chelsea. It seems to me we might want to take that into account when we consider what to pay public sector workers.



Are you saying that public sector workers are overpaid in Hull and underpaid in Chelsea?



Possibly, although an even more fundamental question is whether public services in either Hull or Chelsea are able to recruit enough good people to function properly. There’s more going on here than the cost of living – there are other factors that make a job attractive or unattractive. For instance, Hull has found it hard to recruit experienced teachers in recent years, regardless of whether a teacher’s salary goes a long way in Hull. This is yet another reason to negotiate salaries locally rather than nationally.

But if regional pay bargaining raises pay in places like Hull, won’t that merely raise the gap between the underpaid private sector and the overpaid public sector?

Hang on. “The public sector” is not a caste into which people are born. People will move in or out of public service depending on how well it is paid, among many other things. It’s not very meaningful to say that “statisticians are overpaid in Cardiff” or “nurses are underpaid in London”. Much more useful is to recognise that if nursing isn’t competitively remunerated in London then it will be hard to get good nurses. They’ll live elsewhere, or choose different careers.

That’s the theory. Is there any evidence?

There is some – for instance, a study by the economists Emma Hall, Carol Propper and John van Reenen showing that fatality rates in the NHS are higher in areas where staff are paid less relative to the private sector. That seems to be because a lot of staff in high-cost regions are either agency workers or overpromoted as a way of getting around pay constraints.

Wouldn’t cutting public sector pay in Hull merely drain money out of Hull?

Let’s assume that regional pay bargaining would mean lower public sector salaries

in Hull – which is a big assumption. In the short term this would be bad for Hull, but introducing regional pay variation won’t be a short-term project. In the longer term, inequalities in the housing market would probably increase. Services in Hull – restaurants, hairdressers and the like – would suffer because public sector workers would have less money to spend. But local firms competing in national or global markets would benefit because they would have access to smarter workers for lower salaries. In the long term I suspect this would be good for the regions but I don’t think anybody can be too sure of that.



Osborne is just going to use this as an excuse to pay people less in Hull.

Don’t be ridiculous. George Osborne doesn’t need an excuse.

Also published at ft.com.

Blow the whistle and reap a web of rewards

‘The Internal Revenue Service has awarded a former UBS banker $104m for revealing a tax evasion scheme that cost the US government billions of dollars in taxes and resulted in criminal charges against Swiss banks and top executives.’

Financial Times, September 12

This is “Tarantula”?

Yes, this is “Tarantula”.

Who calls him “Tarantula”?

Well, a chap called Bradley Birkenfeld phoned the Financial Times five years ago with the opening line, “My name is Tarantula. That is not my real name.”

No kidding. Did he also confirm that his real name was not Muppet, Loony or Blowhard?

You’re just grumpy because he’s sitting on $104m. Not bad for a guy who just got out of prison for helping a billionaire to evade tax. But that’s his reward for handing over information to the US authorities about how his former employer, UBS, helped US citizens avoid tax using Swiss bank accounts.

Very nice – but isn’t it a bit crass to give the guy more than $100m?

That’s a fascinating question. You could break it down into two parts. The first is whether we need whistleblowers. The second is whether whistleblowers need to score the equivalent of a lottery jackpot or three before they will speak up.



Whistleblowing feels antediluvian somehow; shouldn’t we be looking to auditors and regulators to spot wrongdoing?

There’s a study of this by Alexander Dyck, Adair Morse and Luigi Zingales. They looked at more than 200 alleged corporate frauds – stealing money from investors rather than tax evasion – and asked how the allegations initially came to light. It’s the job of auditors and financial regulators to spot this stuff, but they rarely do. And shareholders and bondholders have a big financial incentive to discover fraud, but again this doesn’t happen much. It turns out many frauds are uncovered by employees. That makes sense: regulators and auditors are presented with carefully cooked books, but employees are at the coal face and they see the messy details of what is happening. There is no single way in which frauds are uncovered, but whistleblowers are more important than most.

But do we need to pay them so much cash?

Prof Dyck and his colleagues also looked at this. At the time, by far the largest whistleblowing payments were in the healthcare industry, because that was the industry in which the US government was most likely to be the victim of fraud. Under so-called qui tam rules, whistleblowers are due a fat slice of any government money recovered. Whistleblowers were three times more likely to speak out in the health sector, and since the average payout to whistleblowers in successful qui tam cases was almost $50m, that is not surprising.

Why are such large incentives needed?

Perhaps there are cheaper ways to encourage whistleblowing, but it’s clear that it is a hazardous business. Many people who claim to be whistleblowers have had a rough ride.



Such as?

Mr Birkenfeld claimed his life was in danger and he went to jail. Paul Moore, risk manager at HBOS, was sacked. Cheryl Eckard, who identified manufacturing problems at GlaxoSmithKline, lost her job. Ray Dirks, an analyst who uncovered the Equity Funding fraud in the 1970s, was censured by the Securities and Exchange Commission for spreading inside information. Andrew Siemaszko was an engineer at the Davis-Besse reactor when serious corrosion was discovered. Defenders claim he was trying to blow the whistle on safety problems, but he was convicted of lying to the Nuclear Regulatory Commission.



But there are two sides to these stories, aren’t there? I mean, do whistleblowers lose their jobs because they speak out or do they speak out because they lose their jobs?

It’s true many whistleblowers are ambiguous figures. Some have a grudge, while others are culpable and simply trying to reduce their own punishment. But whatever the merits of individual cases, you can see why a potential whistleblower might ask whether the game is worth playing. The chance of $100m might well tip the balance.

Perhaps we should just rely on public-spiritedness.

Fat chance: thanks to the Dodd-Frank act, it should be much more lucrative to blow the whistle on Wall Street in future. That seems sensible. Whenever we’re dealing with complex, fast-moving systems, it’s vital to have early warning of trouble ahead – and that means rewarding whistleblowers.

Also published at ft.com.