Tim Harford The Undercover Economist

Undercover EconomistUndercover Economist

My weekly column in the FT Magazine on Saturday’s, explaining the economic ideas around us every day. This column was inspired by my book and began in 2005.

Undercover Economist

The lost leisure time of our lives

‘Keynes was right to predict that we would be working less but overestimated for how long that trend would continue’

Three hours a day is quite enough,” wrote John Maynard Keynes in his 1930 essay Economic Possibilities for our Grandchildren. The essay continues to tantalise its readers today, thanks in part to a forecast that is looking magnificently right — that in advanced economies people could be up to eight times better off in 2030 than in 1930 — coupled with a forecast that is looking spectacularly wrong, that we would be working 15-hour weeks.

In 2008, economists Lorenzo Pecchi and Gustavo Piga edited a book in which celebrated economists pondered Keynes’s essay. One contributor, Benjamin Friedman of Harvard University, has recently revisited the question of what Keynes got wrong, and produced a thought-provoking answer.

First, it is worth teasing out the nature and extent of Keynes’s error. He was right to predict that we would be working less. We enter the workforce later, after long and not-always-arduous courses of study. We enjoy longer retirements. The work week itself is getting shorter. In non-agricultural employment in the US, the week was 69 hours in 1830 — the equivalent of working 11 hours a day but only three hours on Sundays. By 1930, a full-time work week was 47 hours; each decade, American workers were working two hours less every week.

But Keynes overestimated how rapidly and for how long that trend would continue. By 1970 the work week was down to 39 hours. If the work week had continued to shrink, we would be working 30-hour weeks by now, and perhaps 25-hour weeks by 2030. But by around 1970, the slacking-off stopped. Why?

One natural response is that people are never satisfied: perhaps their desire to consume can be inflamed by advertisers; perhaps it is just that one must always have a better car, a sharper suit, and a more tasteful kitchen than the neighbours. Since the neighbours are also getting richer, nothing about this process allows anyone to take time off.

No doubt there is much in this. But Friedman takes a different angle. Rather than asking how Keynes could have been so right about income but so wrong about leisure, Friedman points out that Keynes might not have been quite so on the mark about income as we usually assume. For while the US economy grew briskly until the crisis of 2007, median household incomes started stagnating long before then — around 1970, in fact.

The gap between the growth of the economy and the growth of median household incomes is explained by a patchwork of factors, including a change in the nature of households themselves, with more income being diverted to healthcare costs, and an increasing share of income accruing to the highest earners. In short, perhaps progress towards the 15-hour work week has stalled because the typical US household’s income has stalled too. Household incomes started to stagnate at the same time as the work week stopped shrinking.

This idea makes good sense but it does not explain what is happening to higher earners. Since their incomes have not stagnated — far from it — one might expect them to be taking some of the benefits of very high hourly earnings in the form of shorter days and longer weekends. Not so. According to research published by economists Mark Aguiar and Erik Hurst in 2006 — a nice snapshot of life before the great recession — higher earners were enjoying less leisure.

So the puzzle has taken a different shape. Ordinary people have been enjoying some measure of both the income gains and the leisure gains that Keynes predicted — but rather less of both than we might have hoped.

The economic elites, meanwhile, continue to embody a paradox: all the income gains that Keynes expected and more, but limited leisure.

The likely reason for that is that, in many careers, it’s hard to break through to the top echelons without putting in long hours. It is not easy to make it to the C-suite on a 20-hour week, no matter how talented one is. And because the income distribution is highly skewed, the stakes are high: working 70 hours a week like it’s 1830 all over again may put you on track for a six-figure bonus, while working 35 hours a week may put you on track for the scrapheap.

The consequences of all this can emerge in unexpected places. As a recent research paper by economists Lena Edlund, Cecilia Machado and Maria Micaela Sviatschi points out, urban centres in the US were undesirable places to live in the late 1970s and early 1980s. People paid a premium to live in the suburbs and commuted in to the city centres to work. The situation is now reversed. Why? The answer, suggest Edlund and her colleagues, is that affluent people don’t have time to commute any more. They’ll pay more for cramped city-centre apartments if by doing so they can save time.

If there is a limited supply of city-centre apartments, and your affluent colleagues are snapping them up, what on earth can you do? Work harder. Homes such as Keynes’s elegant town house in Bloomsbury now cost millions of pounds. Three hours a day is not remotely enough.

Written for and first published at ft.com.

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Undercover Economist

How to make good guesses

‘Would you say that someone reading the FT is more likely to have a PhD or to have no college degree at all?’

What’s the likelihood that the British economy will fall into recession this year? Well, I’ve no idea — but I have a new way to guess.

Before I reveal what this is, here’s a totally different question. Imagine that you see someone reading the Financial Times. Would you say that this individual, clearly a person of discernment, is more likely to have a PhD or to have no college degree at all?

The obvious response is that the FT reader has a PhD. Surely people with PhDs better exemplify the FT reader than people with no degree at all, at least on average — they tend to read more and to be more prosperous.

But the obvious response is too hasty. First, we should ask how many people have PhDs and how many people have no college degree at all? In the UK, more than 75 per cent of adults have no degree but the chance that a randomly chosen person has a PhD is probably less than 1 per cent.

It only takes a small proportion of non-graduates to read the FT before they’ll outnumber the PhD readers. This fact should loom large in our guess, but it does not.

Logically, one should combine the two pieces of information, the fact that PhDs are rare with the fact that FT readers tend to be well educated. There is a mathematical rule for doing this perfectly (it’s called Bayes’ rule) but numerous psychological experiments suggest that it never occurs to most of us to try. It’s not that we combine the two pieces of information imperfectly; it’s that we ignore one of them completely.

The number that gets ignored (in this example, the rarity of PhDs) is called the “base rate”, and the fallacy I’ve described, base rate neglect, has been known to psychologists since the 1950s.

Why does it happen? The fathers of behavioural economics, Daniel Kahneman and Amos Tversky, argued that people judge such questions by their representativeness: the FT reader seems more representative of PhDs than of non-graduates. Tversky’s student, Maya Bar-Hillel, hypothesised that people seize on the most relevant piece of information: the sighting of the FT seems relevant, the base rate does not. Social psychologists Richard Nisbett and Eugene Borgida have suggested that the base rate seems “pallid and abstract”, and is discarded in favour of the vivid image of a person reading the pink ’un. But whether the explanation is representativeness, relevance, vividness or something else, we often ignore base rates, and we shouldn’t.

At a recent Financial Times event, psychologist and forecasting expert Philip Tetlock explained that good forecasters pay close attention to base rates. Whether one is forecasting whether a marriage will last, or a dictator will be toppled, or a company will go bankrupt, Tetlock argues that it’s a good idea to start with the base rate. How many marriages last? How many dictators are toppled? How many companies go bankrupt? Of course, one may have excellent reasons to depart from the base rate as a forecast but the base rate should be the beginning of the journey.

On this basis, my guess is that there is a 10 per cent chance that the UK will begin a recession in 2016. How so? Simple: in the past 70 years there have been seven recessions, so the base rate is 10 per cent.

Base rates are not just a forecasting aid. They’re vital in clearly understanding and communicating all manner of risks. We routinely hear claims of the form that eating two rashers of bacon a day raises the risk of bowel cancer by 18 per cent. But without a base rate (how common is bowel cancer?) this information is not very useful. As it happens, in the UK, bowel cancer affects six out of 100 people; a bacon-rich diet would cause one additional case of bowel cancer per 100 people.

Thinking about base rates is particularly important when we’re considering screening programmes or other diagnostic tests, including DNA tests for criminal cases.

Imagine a blood test for a dangerous disease that is 75 per cent accurate: if an infected person takes the test, it will detect the infection 75 per cent of the time but it will also give a false positive 25 per cent of the time for an uninfected person. Now, let’s say that a random person takes the test and seems to be infected. What is the chance that he really does have the disease? The intuitive answer is 75 per cent. But the correct answer is: we don’t know, because we don’t know the base rate.

Once we know the base rate we can express the problem intuitively and solve it. Let’s say 100 people are tested and four of them are actually infected. Then three will have a (correct) positive test, but of the 96 uninfected people, 24 (25 per cent) will have a false positive test. Most of the positive test results, then, are false.

It’s easy to leap to conclusions about probability, but we should all form the habit of taking a step back instead. We should try to find out the base rate, or at least to guess what it might be. Without it, we’re building our analysis on empty foundations.

Written for and first published at ft.com.

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The consequences of cheap oil

‘When oil prices are high, people may get out of their cars and walk, cycle or get public transport’

After years in which $100 oil was the norm, the price of Brent crude is now around a third of that. Assume for a moment that Russia and Saudi Arabia fail in their efforts to get the price back up. Will $30 oil change the world? The answer is yes, of course. Everything is connected to everything else in economics, and that is particularly true when it comes to oil. For all the talk of the weightless economy, we’re not quite so post-industrial as to be able to ignore the cost of energy. Because oil is versatile and easy to transport, it remains the lubricant for the world’s energy system.

The rule of thumb has always been that while low oil prices are bad for the planet, they’re good for the economy. Last year a report from PwC estimated that a permanent fall in the price of oil by $50 would boost the size of the UK economy by about 1 per cent over five years, since the benefits — to most sectors but particularly to heavy industry, agriculture and air travel — would outweigh the costs to the oil production industry itself.

That represents the conventional wisdom, as well as historical experience. Oil was cheap throughout America’s halcyon years of the 1950s and 1960s; the oil shocks of the 1970s came alongside serious economic pain. The boom of the 1990s was usually credited to the world wide web but oil prices were very low and they soared to record levels in the run-up to the great recession. We can debate how important the oil price fluctuations were but the link between good times and cheap oil is not a coincidence.

Here’s a piece of back-of-the-envelope economics. The world consumes nearly 100 million barrels a day of oil, which is $10bn a day — or $3.5tn a year — at the $100 price to which we’ve become accustomed. A sustained collapse in the oil price would slice more than $2tn off that bill — set against a world economic output of around $80tn, that’s far from trivial. It is a huge transfer from the wallets of oil producers to those of oil consumers.

Such large swings in purchasing power always used to boost economic growth, because while producers were saving the profits from high prices, consumers tended to spend the windfall from low ones. One of the concerns about today’s low prices is that the positions may be reversing: the big winners, American consumers, are using the spare cash to pay off debts; meanwhile, losers such as Russia and Saudi Arabia are cutting back sharply on investment and public spending. If carried to extremes, that would mean a good old-fashioned Keynesian slowdown in a world economy trying to spend less and save more; the more likely result of which is that lower oil prices fail to give us the boost we hope for.

It is intriguing to contemplate some of the less obvious effects. Charles Courtemanche, a health economist at Georgia State University, has found a correlation between low gasoline prices and high obesity rates in the United States. That is partly because, when oil prices are high, people may get out of their cars and walk, cycle or get public transport. Cheap gasoline, on the other hand, puts disposable income into the pockets of families who are likely to spend it on eating out. Low oil prices may make us fat.

Another depressing possibility is that low oil prices will slow down the rate of innovation in the clean energy sector. The cheaper the oil, the less incentive there is to invent ways of saving it. There is clear evidence for this over the very long run. As recently as the late 1700s, British potters were using wasteful Bronze Age technology for their kilns. The reason? Energy was cheap. Wages, in contrast, were expensive — which is why the industrial revolution was all about saving labour, not saving energy.

More recently, David Popp, an economist at Syracuse University, looked at the impact of the oil price shocks of the 1970s. He found that inventors emerged from the woodwork to file oil-saving patents in fields from heat pumps to solar panels.

It is always possible that the oil price collapse will do little to affect some of the big technological shifts in the energy market. The scale of oil production from hydraulic fracturing (fracking) in the US may be curtailed but a huge technological leap has already happened. As the chief economist of BP, Spencer Dale, recently commented, fracking is starting to look less like the huge, long-term oil-drilling projects of the past, and more like manufacturing: cheap, lean, replicable and scalable. Low oil prices cannot undo that and the efficiencies may well continue. We can hope for ever-cheaper solar power too: photovoltaic cells do not compete closely with oil, and we may continue to see more and more installations and lower and lower prices.

That said, when fossil fuels are cheap, people will find ways to burn them, and that’s gloomy news for our prospects of curtailing climate change. We can’t rely on high oil and coal prices to discourage consumption: the world needs — as it has needed for decades — a credible, internationally co-ordinated tax on carbon.

Written for and first published at ft.com.

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Undercover Economist

Online dating? Swipe left

‘It is crazy to believe someone’s eye colour, height, hobbies and musical tastes are a basis for a lasting relationship’

Online dating promised so much. “This is one of the biggest problems that humans face and one of the first times in human history there was some innovation,” says Michael Norton, a psychologist at Harvard Business School.

Finding the right partner, whether for life or for Saturday night, is so important to so many people that you would think we might have cracked it by now. By assembling a vast array of date-worthy people in a searchable format, online dating seems like it should be a huge improvement on the old-fashioned methods of meeting people at work, through friends, or in bars and nightclubs. But it’s not clear that the innovation of online dating is helping very much.

A simple survey that Norton conducted with two other behavioural scientists, Jeana Frost and Dan Ariely, revealed that people were unhappy with their online dating experience in three obvious ways. The first was that the “online” bit of the dating was about as much fun as booking a dentist’s appointment. The second was that it took for ever — the typical survey respondent spent 12 hours a week browsing through profiles and sending and receiving messages, yielding less than two hours of offline interaction. Now, 106 minutes are plenty for certain kinds of offline interaction but, however people were spending their time together, they didn’t seem satisfied. This was the third problem: people tended to have high expectations before the dates they had arranged online but felt disenchanted afterwards. To adapt a Woody Allen joke: not only are the dates terrible but there are so few of them.

Given that online dating tends to be tedious, time-consuming and fruitless, it is no surprise that we seem hungry for a better way. Most approaches to online dating have tried to exploit one of the two obvious advantages of computers: speed and data-processing power. Apps such as Grindr and Tinder allow people to skim quickly through profiles based on some very simple criteria. (Are they hot? Are they available right now?) That is, of course, fine for a one-night stand but less promising for a more committed relationship.

The alternative, embraced by more traditional matchmaking sites such as Match.com and OkCupid, is to use the power of data to find the perfect partner. We badly want to believe that after giving a website a list of our preferences, hobbies and answers to questions such as, “Do you prefer the people in your life to be simple or complex?”, a clever algorithm will produce a pleasing result.

Because these pleasing results seem elusive, wishful thinking has gone into overdrive. We hold out hope that if only we could be cleverer, the algorithms would deliver the desired effect. For example, Amy Webb’s TED talk “How I Hacked Online Dating” has been watched more than four million times since it was posted in 2013.

In a similar vein, Wired magazine introduced us to Chris McKinlay, “the math genius who hacked OkCupid” and managed to meet the woman of his dreams after cleverly reverse-engineering the website’s algorithms. The brilliance of McKinlay’s achievement is somewhat diminished by the revelation that he had to work his way through unsuccessful dates with 87 women before his “genius” paid dividends.

This should hardly be a surprise. Imagine looking at the anonymised dating profiles of 10 close friends and comparing them with the profiles of 10 mere acquaintances. Using the profile descriptions alone, could you pick out the people you really like? The answer, says Dan Ariely, is no. “It’s terrible. It’s basically random.”

It is crazy to believe that someone’s eye colour and height, or even hobbies and musical tastes, are a basis for a lasting relationship. But that is the belief that algorithmic matching encourages. Online dating is built on a Google-esque trawl through a database because that’s the obvious and easy way to make it work.

Is there a better way? Perhaps. Jeana Frost’s PhD research explored an alternative approach to online dating. Why not, she asked, make online dating a bit less like searching and a bit more like an actual date? She created a virtual image gallery in which people had a virtual date, represented by simple geometric avatars with speech bubbles. The images — from Lisa and Jessica Simpson to George Bush and John Kerry — were conversation starters. People enjoyed these virtual dates and, when they later met in person, the virtual date seems to have worked well as an icebreaker.

Virtual dating has not taken off commercially, says Norton, in part because companies have tried too hard to make it realistic, and have fallen into the “uncanny valley” of the not-quite-human. I suspect, but cannot prove, that virtual spaces such as World of Warcraft are perfectly good places to meet a soulmate, assuming your soulmate happens to like orc-bashing. Perhaps mainstream virtual dating is just waiting for the right design to emerge.

Or perhaps the problem is deeper: online dating services prosper if they keep us coming back for more. Setting someone up with a romantic partner for life is no way to win a repeat customer.

Written for and first published at ft.com.

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How to keep your gym habit

‘Might a commitment strategy allow you to pay yourself to go to the gym?’

How are those resolutions going? Still going to the gym? If not, you’re not alone.

Let’s think about incentives. If some benevolent patron had paid you a modest sum — a few pounds a day, perhaps — for keeping your resolution throughout January, would that have helped you keep fit now that January is behind us?

The answer is far from clear. An optimistic view is that by paying you to look after yourself in January, your mysterious patron would have encouraged you to form good habits for the rest of the year. The most obvious case would be if you were trying to give up cigarettes; paying you to get through the worst of the withdrawal period might help a lot. Perhaps diet and exercise would be similarly habit-forming.

Yet some psychologists would argue that the payment is worse than useless, because payments can chip away at our intrinsic motivation to exercise. Once we start paying people to go to the gym or to lose weight, the theory goes, their inbuilt desire to do such things will be corroded. When the payments stop, things will be worse than if they had never started.

The idea that external rewards might crowd out intrinsic motivation is called overjustification. In a celebrated study in 1973 conducted by Mark Lepper, David Greene and Richard Nisbett, some pre-school children were promised sparkly certificates as a reward for drawing with special felt-tip pens. Others were given no such promise. When the special pens were reintroduced to the nursery classrooms a week or so later, without any reward on offer, the researchers found that the children who had previously been promised certificates for their earlier drawing now spent half as much time with the pens as their peers. Only suckers draw for free.

There’s a big difference between exercising and colouring, however: while many children like felt-tips, many adults do not like exercising. A payment can hardly crowd out your intrinsic motivation if you don’t have any intrinsic motivation in the first place. Systematic reviews of the overjustification effect suggest that incentives do no harm for activities that people find unappealing anyway.

So perhaps the idea of paying people to exercise is worth thinking about after all. In 2009, two behavioural economists, Gary Charness and Uri Gneezy, published the results of a pair of experiments in which they tried it. Some of their experimental subjects were paid $100 to go to the gym eight times in a month, while those in two alternative treatment groups were either paid $25 for going just once, or weren’t asked to go to the gym at all.

The results were a triumph for the habit-formation view. The payments worked even after they had stopped. In one study, the subjects were exercising twice as often seven weeks after the bonus payments stopped than before they started; in the other, the increase was threefold 13 weeks after payments had stopped. People who were already regular gym-goers didn’t change their behaviour — so there was no crowding-out — but there was a surge in exercise from people who hadn’t previously done much. A later study by Dan Acland and Matthew Levy found a similar habit-forming effect among students, although, alas, the good habits often failed to survive the winter vacation. In other experiments, incentive payments have been shown to be modestly successful at helping smokers to give up.

There is much to be said for a benign patron who pays you to stay healthy while you form good habits. But where might such a person be found? Take a look in the mirror — your patron might be you.

Inspired by the ideas of Nobel laureate Thomas Schelling, economists have become fascinated by the idea of commitment strategies, where your virtuous self takes steps to outmanoeuvre your weaker self before temptation strikes. A simple commitment strategy is to hand £500 to a trusted friend, with instructions that they are only to return the cash if you keep your resolution.

Might a commitment strategy allow you to pay yourself to go to the gym? It might indeed. Economists Heather Bower, Mark Stehr and Justin Sydnor recently published the results of a long-term experiment conducted with 1,000 employees of a Fortune 500 company. In this experiment, some employees were initially paid $10 for each visit to the company gym over a month. Some of them were then offered the opportunity to put money into a commitment savings account: if they kept exercising, the money would be returned; otherwise it would go to charity. The approach was no panacea: most people did not take up the option, and not everyone who did managed to stick to their goals. But even three years later, those who had been offered commitment accounts were 20 per cent more likely to be exercising than the control group.

That chimes with my experience. I once wrote a column about sending $1,000 to a company called Stickk, which promised to give it away if I didn’t exercise regularly. The contract was for a mere three months — and I succeeded. Eight years after my money was returned, I’m still sticking to the habit.

Written for and first published at ft.com.

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Hidden truths behind China’s smokescreen

‘When countries become richer, do they pollute their environment more or less?’

The pictures from Beijing tell their own story: pollution there is catastrophic. Bad news for residents, and awkward for me too. Just over a decade ago, I wrote a book, The Undercover Economist, which among many other things cheerfully asserted that particulate air pollution in urban China was sharply falling as the country grew richer. It’s a claim I believed at the time (based on well-regarded research in the 2002 Journal of Economic Perspectives) but with each new report of smog over China, I felt a nagging sense that I had led readers astray. I figured it was time to do some more research and to set the record straight.

There is a broader question here. When countries become richer, do they pollute their environment more or less? For a while it seemed obvious that pollution and riches went hand in hand: industrialised nations spewed out more of everything.

But then the leading countries began to crack down on pollution. London no longer suffers from smog. The European Union reduced sulphur dioxide emissions by more than 80 per cent between 1990 and 2011. At the same time, the United States has reduced atmospheric lead by 98 per cent.

In the early 1990s, Princeton economists Gene Grossman and Alan Krueger coined the phrase “environmental Kuznets curve” to stand for the idea that as countries become richer, their emissions first rise but then fall, as richer citizens demand cleaner air from the governments they elect and the companies from whom they buy. There’s some evidence that this is true but it’s hard to interpret that evidence. An optimistic view is that countries reduce pollution with or without economic growth because they can use clean technologies developed elsewhere. If true, China may be able to clean up its air faster than we’d expect.

A grimmer possibility is that the richer countries aren’t really reducing pollution — they are exporting it, by banning dirty factories at home while happily buying from dirty factories abroad. On this view, China is unlikely to be able to clean its air any time soon.

How serious a problem is offshoring pollution? It’s not trivial. In 2007, Joseph Aldy of Harvard’s Kennedy School published research showing clear evidence of this pollution-export effect within the US. Richer states seemed to be emitting less carbon dioxide per person as their economies grew. Alas, Aldy concluded that the effect could be explained entirely by the rich having bought their electricity from poorer states rather than generating it at home. A more recent study (Peters, Minx, Weber and Edenhofer 2011) estimated that by 2008, developed countries were net importers from developing countries of goods whose production represented about 1.6 billion tonnes of carbon dioxide emissions, roughly 5 per cent of the global emissions total. No prizes for guessing that much of this energy-intensive manufacturing is taking place in China, alongside the production of steel, cement and coal-fired electricity for domestic use.

The dreadful air quality in Beijing, then, is no mystery. First, China is not yet rich, so it may be on the wrong side of the environmental Kuznets curve anyway, the side where pollution has not yet begun to fall. Second, China is not a democracy, and that will partially dampen the power of its citizens to demand cleaner air. Third, China is a major exporter of manufactured goods.

But as I stood ready to pen my correction, I realised something: I didn’t actually have a time series for air pollution in urban China. I could see that things were bad but not what the trend was.

“The challenge with particulates is that we keep changing what we want to measure and regulate,” Aldy told me. Researchers now track PM2.5, very fine particles thought to be particularly hazardous to health; but, in 1985, when my original data series began, nobody was collecting PM2.5 data.

So how much worse have things got in China? I called Jostein Nygard of the World Bank, who has been working on Chinese air pollution issues for more than two decades, and I was surprised at his response: in many ways, China’s urban air quality has improved.

Sulphur dioxide is down and coarser particulate matter is also down since good records began in 2000 — a fact that is explained by Chinese efforts to install sulphur scrubbers and to move large pollution sources away from the cities. “You could see the air quality improving through the 1980s and 1990s and to the 2000s,” says Nygard. PM2.5 is very bad, he says — but not necessarily worse than 10 years ago, and serious efforts are now under way to track it and reduce it.

To my surprise, not quite a correction at all, then. But if local air pollution in China is actually on an improving track, how come we see so many stories about pollution in China? One reason, of course, is that the situation remains serious. Another is that the Chinese government itself seems to be using smog alerts as a way to send a message to local power brokers that clean air is a priority. But there is also the question of what counts as news: sudden outbreaks of smog are newsworthy. Slow, steady progress is not.

Written for and first published at ft.com.

Undercover Economist

How fighting for a prize knocks down its value

‘If many people have patience to queue for scarce (and underpriced) tickets, the value on offer will be consumed by the race to grab it’

I was recently told about an airstrip near a banknote-printing facility. Every day, planes take off, bursting with cash. It used to be that if you stood in a certain field near the airstrip, you could catch the dollars as they drifted gently to the ground, or scoop armfuls of them up from the soil. On average, $1m a day fluttered down.

Word soon got around. Before long, the field was packed with bill-catchers, racing and shoulder-charging each other to get the cash. People started to bring butterfly nets. The skies were thick with quadcopters darting around to snatch the money at altitude.

If you’re wondering where this field might be, don’t. It exists only in the imagination of Stanford economist Mike Ostrovsky, reported in Al Roth’s book Who Gets What and Why. But if the field did exist, you’d have to be a hardy soul to venture there. If $1m a day was known to be at stake, the ferocious quadcopter scramble would escalate until it cost almost $1m a day to run. If it didn’t, then people would have a strong incentive to keep buying drones until it did.

Economists call such arms races the “dissipation of economic rents”. They’re frustrating, because value is being frittered away in the competition to secure them. Think of the queue around the block for scarce (and evidently underpriced) concert tickets or the riots over cheap merchandise that occasionally break out during discount sales. If a few people are particularly patient, or muscular, or skilled at piloting drones, then they will keep at least some of the value; if many people have similar patience, strength or skill then the entire value on offer will be consumed by the race to grab it.

(The airfield tussle is particularly wasteful because real resources are being devoted to grabbing banknotes that could easily and cheaply be replaced. But even if the planes were dropping something valuable, such as saffron or USB drives, the process would mean that value was wasted.)

Another example is the business of high-frequency trading in financial markets, in which algorithms try to outwit or outpace each other as they scramble for trades in a contest that is over in less than an eye-blink. Some traders have invested in microwave networks, which are faster than fibre optics, to gain edges of less than a thousandth of a second as they respond in New York to news from Chicago. The parallel with the money-field is clear enough — and, unlike the field, high-frequency traders do exist.

A microwave link to save a few microseconds is in much the same category as a faster dollar-grabbing drone, or turning up earlier for a better place in the queue at an Oxford Street store. There is a value to having a liquid market for financial assets, one in which you can quickly find some buyers to compete for whatever you might be selling. But high-frequency trading adds little to market liquidity in times of crisis; the microwave link, like the drone, adds no value to society as a whole.

Can anything be done about such rent-dissipating behaviour? One approach is to tax it. We could levy a fee on standing in queues, or on microwave transmitters, or on stock market transactions themselves. If people who queue for scarce concert tickets are all taxed $5 an hour while they queue, then the lines will be shorter. The cost of the tax should roughly be offset by the reduced waiting time, so the queueing crowd is no worse off; the government, on the other hand, has acquired revenue from nowhere. This is a rare free lunch.

Taxing transactions is also a possibility, although a more problematic one. Much of the difficulty comes not from transactions themselves but from “quote stuffing”, where high-frequency traders make and withdraw thousands of bids, probing for information without actually making transactions. And charging for quote-stuffing might not help either. Three Canadian researchers (Katya Malinova, Andreas Park and Ryan Riordan) studied the impact of a regulatory change where traders were charged for quotes, not just trades; they found that quote volume fell sharply. But the bid-ask spread, a measure of market inefficiency, rose nearly 10 per cent. And while a transaction tax or quote tax would discourage some forms of high-frequency trading, it seems to me that the incentive to build microwave links between Chicago and New York would still exist.

So an alternative is to redesign the market to make it work better. In the case of queues for tickets, charging more for the original tickets would help, and the seller could hold an auction to set the perfect price. Financial markets could also be improved by introducing an auction once a second, batching together all the offers that have been submitted during that second. That would be fast enough for any reasonable purpose — and would remove the need to spend all this money on microwave relays.

Auctions are no more of a panacea than markets themselves, but they can help. Markets do not always organise themselves. A well-designed auction can mean less effort wasted in the fight to get to the front of the queue.

Written for and first published at ft.com.

Undercover Economist

The price of being female

‘Gender-based mark-ups may not be an economy-wide phenomenon. But they seem to exist for certain products’

Does a dollar in my pocket buy more than a dollar in my wife’s? It seems so, according to a report released just before Christmas by New York City’s Department of Consumer Affairs, which was much covered in the US media. The DCA report found that men often paid less for clothes and items such as razor blades and shampoo. Even boys’ toys are cheaper than those aimed at girls. The report led with a striking example from a department store website: while a red “My 1st Scooter Sport” costs $24.99, a pink “My 1st Scooter Girls Sparkle” is twice as much. Beneath the paint job, the products appear to be identical — surely glitter cannot be that expensive?

The sparkly scooter was sold at an astonishing mark-up but it’s not a typical case. The DCA report looked at 22 bikes and scooters, finding that on average the product aimed at girls or women cost 6 per cent more. Across 800 products, the DCA found that while men sometimes paid more than women, on average women faced prices that were 7 per cent higher. Relative to profit margins this is still a large price difference but it’s a long way shy of 100 per cent.

What should we make of this? One response is that perhaps the price gap isn’t really there or at least not in any systematic way. Perhaps the DCA unwittingly cherry-picked examples. (Sports cars and hi-fi systems were not included.) Whether or not systematic gender-based pricing is widespread, it will always be easy to find examples that look sexist.

Still, other research has reached similar conclusions. For example, a study published in Gender Issues in 2011 by Megan Duesterhaus and others found that “gendered price disparities are not as widespread as . . . journalists have previously reported but it does appear that women pay more for certain goods (deodorant), services in hair salons (haircuts), and dry-cleaning of shirts”.

In the hope of getting a truly comprehensive overview, I spoke to the UK’s Office for National Statistics, which systematically collects price data to calculate inflation measures. Unfortunately, the ONS data aren’t designed to shed light on this question; they often do not distinguish between male and female products and services. The job of inflation indices, after all, is not to detect discrimination but to follow price changes over time.

So it is hard to be sure that gender-based mark-ups are an economy-wide phenomenon. But they may be. And they certainly seem to exist for particular kinds of product. Why? No single theory will suffice. Car insurers and nightclub owners both want to charge more to men, but not for the same reason.

Broadly, there are two types of explanation. One is that higher prices reflect higher costs. Maybe men’s haircuts typically require less time and skill than women’s haircuts. It’s said that women’s blouses cost more to clean and iron at a dry-cleaner’s because they are delicate and need to be pressed by hand. Still: why not charge by the hour to provide a haircut? Or charge for hand-pressed clothes, regardless of gender? Restaurants do not charge men more on the grounds that they usually eat more; instead, they charge by the dish. I can only speculate as to why hairdressers act differently.

The alternative explanation is that companies are making fatter margins on women’s products and services. Economists call this “price discrimination”, and it would suggest that women pay more than men if and when they are less sensitive to prices. Perhaps manufacturers and retailers have found that if they try to raise the price of razor blades or shampoo, men will shop elsewhere or skimp on the product, while women will willingly pay the higher price.

This female insensitivity to price — if it really exists — might be driven by all kinds of things. Perhaps women tend to be busier and have less time to shop around. Or perhaps they care more about quality when it comes to deodorant or shampoo, whereas men just want something cheap.

 . . . 

But even if women are potentially willing to pay extortionate rates for certain kinds of goods, it doesn’t mean that companies can exploit that willingness. A lot of the businesses most regularly accused of sexist pricing — hairdressers, dry cleaners and nail salons — operate in the face of almost unlimited potential competition. If all of them are operating on razor-thin margins for men and fat margins for women, shouldn’t they be desperately trying to win female customers away from each other? This competitive pressure will constrain attempts to discriminate on price. It is the big brands — such as Ferrari, Hermès and perhaps Gillette — who have the power to charge different mark-ups to different customers.

As soon as a company acquires some market power, it will try to give spendthrift customers an opportunity to display their spendthriftiness by offering costly variants on basic products. Publishers ask double for a book with hard covers; coffee chains charge a lot for squirting flavoured syrup in your latte. We can hardly be surprised if some of these special variants look pink and sparkly. And as consumers, male or female, our only resort is to keep searching for the products without those frills, literal or otherwise.

Written for and first published at ft.com.

Undercover Economist

Why predictions are a lot like Pringles

‘Nobody thinks that there’s any great virtue in forecasts but we find them hard to resist’

In mid-December, Phil McNulty, the BBC’s chief football writer, offered us his predictions for the rest of the English Premier League season. My interest in football is limited but I found McNulty’s efforts fascinating. Even the most sceptical about football can learn a great deal from the episode.

A brief piece of context for those sceptics. Chelsea, the champions, had just played Leicester City, a team that had been relegation favourites just a few months before. Leicester won the game. This result would have been surprising had it not been set against the even more surprising pattern of the season. Champions Chelsea had slumped towards the bottom of the league after producing an unprecedentedly appalling run of form; Leicester, meanwhile, were top of the table. Nobody was shocked to see them vanquish Chelsea but it felt like a significant moment nonetheless.

What of McNulty? At the beginning of the season, he had predicted that Chelsea would be champions again, while Leicester would finish in the bottom three and be relegated from the Premier League. Both of those outcomes are now inconceivable. After admitting that his initial prediction had been about as wrong as it is possible to be, McNulty proposed a new set of predictions.

Those predictions were . . . but wait. Why on earth should you care? McNulty knows a great deal about football — far more than I do — but he had conclusively proved that he can’t see into the future. And yet he felt bold enough to offer another forecast, which many sports fans read with great interest.

This is a common pattern in football and beyond: pundits make forecasts, their audience consume those forecasts with relish, the forecasts are proved wrong, nobody is very surprised, and the cycle begins again. Why?

Part of the explanation is wishful thinking: we like to believe that the world runs on rails, and to trust in experts who claim to have decoded the timetable and can therefore explain what is going to happen, when, and why. Forecasters with a record of some success — such as data-driven political and sports analyst Nate Silver — soon find themselves saddled with unrealistic expectations.

Silver correctly predicted the fine details of the 2012 presidential election but he is happy to admit three things: that US elections are data-rich environments and much more predictable than most; that he had some luck; and that the bar for forecasting success had been set very low by partisan pundits much more interested in cheerleading than accuracy.

Sure enough, when Silver and his colleague Ben Lauderdale tried to predict last year’s UK election result, their performance was woeful. This was partly because the seat-by-seat polling data are far less detailed than in the US and partly because Silver’s good luck didn’t last.

We would be wise to have more realistic expectations, even of careful data-driven forecasters such as Silver. But perhaps our expectations are irrelevant. Even when we know that the forecasts are useless, when the pundits have no track record, when the events in question have always been unpredictable (the stock market; geopolitical shocks; recessions), we remain hungry for opinions about the future.

The truth is that forecasts are like Pringles — nobody thinks that there’s any great virtue in them but, offered with the fleeting pleasure of consuming them, we find it hard to resist. I am not sure quite why this should be so, but I have a couple of theories.

Possibility one is that the moment we hear a forecast, we imagine it happening. It then becomes a believable outcome and one that is easy to call to mind in the future. The scenario that we imagine looms large in our minds; other scenarios, equally plausible, fade to the background. As a result, we can be sceptical of forecasts in general yet still hooked by a particular one.

I notice this tendency in myself whenever I hear someone opining on the stock market. As an abstract proposition I think that it’s almost impossible to predict what the stock market will do. But the moment someone starts to tell me a story about what will happen to it, I’m hypnotised.

Possibility two is that forecasts offer us a lazy way to understand a complex world. The background to the conflict in Syria is complicated. So is Chinese politics. So, too, is the evolution of the Japanese economy. Trying to understand what is going on in any of these places requires an investment of time and attention that most of us are not willing to make. Wise heads at this newspaper could explain the intricacies to you or to me for hours yet barely have begun to do the topic justice.

But a forecast? That’s different. A forecast about what will happen in Syria, China or Japan is a simple way to convey a fleeting sense of understanding. The forecast will probably be wrong. But at the instant it is consumed, it gratifies. As I say, a lot like Pringles.

Written for and first published at ft.com.

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Undercover Economist

The cost of overconfidence

‘Some companies base their business models on our tendency to overestimate our willpower’

So, how are those resolutions going? Given that the new year has scarcely begun, there is some chance that your will remains as firm as it was on New Year’s Eve: the cigarettes have not been smoked, the white wine has not been guzzled and you actually went to the gym. As we all know, however, a year is a long time to stay strong.

Companies know it too, and some base their entire business model on our tendency to overestimate our willpower, our memory or our ability to navigate small print so devious that it would make Rumpelstiltskin blush.

The most egregious example — popular in the US, blessedly less so in the UK — is the mail-in rebate, where a manufacturer or retailer will offer a discount but only after the customer fills in a form, attaches a receipt and mails the paperwork off with fingers crossed. There are a number of advantages to this — it may allow the manufacturer to gain information about customers, and produces a flattering cash flow — but surely the main reason companies use mail-in rebates is that they know some people aren’t as disciplined and organised as they think.

Scott Adams, as so often, nailed the issue in a Dilbert comic strip. Dogbert offers a product for sale for $1,000,029 with a $1,000,000 rebate. And since “all we need is one person to forget to mail in the rebate forms”, Dogbert suggests targeting “the lazy rich”.

While the mail-in rebate is a particularly naked case of exploiting inattentive consumers, there are subtler examples, such as magazine subscriptions with free trial periods followed by auto-renewals.

More subtle still are pricing schemes that exploit consumers. In a recent analysis of overconfident consumers, economist Michael D Grubb highlights the “three-part tariff”. A one-part tariff would be, for example, 2p per minute to make phone calls. A two-part tariff might be £10 a month, plus 1p a minute to make phone calls. And a three-part tariff? A tenner a month with 200 minutes of free calls, plus 10p a minute to make phone calls after the 200 minutes have been used.

The three-part tariff will be reassuringly familiar to anyone with a mobile phone contract. But look at it there on the page. It’s ridiculous, is it not? It is hard to imagine any company deploying such a convoluted offering for a product whose consumption was obvious, such as petrol — “£10 a month to use our petrol stations, the first 50 litres of petrol to be supplied at cost price, and then £5 a litre thereafter.” There are legitimate business justifications for a three-part tariff but the likeliest story is that phone companies think we are fallible. Most of us don’t have a firm grasp either of how much we talk on average or of how variable that average is. As a result, many of us pay these punitive charges more often than we expect.

At least mobile phone carriers offer an honest service behind their manipulative pricing structures. I am not sure the same can be said of bookmakers, casinos and lotteries. Some of their customers have a clear-headed view of their chances of winning — just as some customers mail back their rebates or accurately forecast their phone calls — but many must overestimate their skill or underestimate the odds against them.

Yet I wonder if any business model is more dependent on the excessive optimism of its customers than gyms that offer ongoing memberships. In a famous research paper, “Paying Not to Go to the Gym”, economists Stefano DellaVigna and Ulrike Malmendier studied almost 8,000 gym members, with data on their attendance record and on the contracts they had agreed with the gym.

There were three contractual options: pay per visit, pay monthly on an automatically renewed contract, or pay annually on a contract that is not automatically renewed. DellaVigna and Malmendier found a number of patterns that are most naturally explained by the hypothesis that we consumers are naive, weak-willed fools.

● Eighty per cent of pay-monthly customers would have paid less — often much less — had they simply paid per visit. Likely explanation: we don’t go to the gym as much as we think we will.

● Pay-monthly customers pay more than the annual customers, because they retain an option to cancel, yet these customers, in fact, tend to stay members for longer. Explanation: we think flexibility is valuable but don’t realise how lazy we are in the face of auto-renewal.

● The people who get the worst value from the gym (highest per-visit cost) also take the longest to cancel (gap between final visit and cancellation). Explanation: people who are idiots about one thing are idiots about other things too.

Taking money to provide facilities to people who do not use them is a tempting business. But gym companies must still compete with each other for our custom, even if that competitive dynamic is dysfunctional.

So, take heart: if you are a customer who mails in her rebates, who carefully rations mobile phone use or who goes to the gym five times a week, then you are likely to get an excellent deal, cross-subsidised by other customers.

And you are just such a person, aren’t you? Of course you are.

Written for and first published at ft.com

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