Yesterday I was named Economics Commentator of the Year. That feels jolly grown up, especially given the splendid people on the short-list and the list of previous winners. I’ll enjoy it, though! (A list of other comment award winners is here.)
Articles published in November, 2014
A housing boom is the economic equivalent of a tapeworm infection
Buying a house is not just a big deal, it’s the biggest. Marriage and children may bring more happiness – or misery, if you’re unlucky – but few of us will ever sign a bigger cheque than the one that buys that big pile of bricks, mortar and dry rot.
It would be nice to report that buyers and sellers are paragons of rationality, and the housing market itself a well-oiled machine that makes a sterling contribution to the working of the broader economy. None of that is true. House buyers are delusional, the housing market is broken and a housing boom is the economic equivalent of a tapeworm infection.
As a sample of the madness, consider the popular concept of “affordability”. This idea is pushed by the UK’s Financial Conduct Authority and seems simple common sense: affordability asks whether potential buyers have enough income to meet their mortgage repayments. That question is reasonable, of course – but it is only a first step, because it ignores inflation.
To see the problem, contrast today’s low-inflation economies with the high inflation of the 1970s and 1980s. Back then, paying off your mortgage was a sprint: a few years during which prices and wages were increasing in double digits, while you struggled with mortgage rates of 10 per cent and more. After five years of that, inflation had eroded the value of the debt and mortgage repayments shrank dramatically in real terms.
Today, a mortgage is a marathon. Interest rates are low, so repayments seem affordable. Yet with inflation low and wages stagnant, they’ll never become more affordable. Low inflation means that a 30-year mortgage really is a 30-year mortgage rather than five years of hell followed by an extended payment holiday. The previous generation’s rules of thumb no longer apply.
Because you are a sophisticated reader of the Financial Times you have, no doubt, figured all this out for yourself. Most house buyers have not. Nor are they being warned. I checked a couple of the most prominent online “affordability” calculators. Inflation simply wasn’t mentioned, even though in the long run it will affect affordability more than anything else.
This isn’t the only behavioural oddity when it comes to housing markets. Another problem is what psychologists call “loss aversion” – a disproportionate anxiety about losing money relative to an arbitrary baseline. I’ve written before about a study of the Boston housing crash two decades ago, conducted by David Genesove and Christopher Mayer. They found that people who bought early and saw prices rise and then fall were realistic in the price they demanded when selling up. People who had bought late and risked losing money tended to make aggressive price demands and failed to find buyers. Rather than feeling they had lost the game, they preferred not to play at all.
The housing market also interacts with the wider economy in strange ways. A study by Indraneel Chakraborty, Itay Goldstein and Andrew MacKinlay concludes that booming housing markets attract bankers like jam attracts flies, sucking money away from commercial and industrial loans. Why back a company when you can lend somebody half a million to buy a house that is rapidly appreciating in value? Housing booms therefore mean less investment by companies.
. . .
House prices have even driven the most famous economic finding of recent years: Thomas Piketty’s conclusion (in joint work with Gabriel Zucman) that “capital is back” in developed economies. Piketty and Zucman have found that relative to income, the total value of capital such as farmland, factories, office buildings and housing is returning to the dizzy levels of the late 19th century.
But as Piketty and Zucman point out, this trend is almost entirely thanks to a boom in the price of houses. Much depends, then, on whether the boom in house prices is a sentiment-driven bubble or reflects some real shift in value. One way to shed light on this question is to ask whether rents in developed countries have boomed in the same way as prices. They haven’t: research by Etienne Wasmer and three of his colleagues at Sciences Po shows that if we measure the value of houses using rents, there’s no boom in the capital stock.
The housing market then, is prone to bubbles and bouts of greed and denial, is shaped by financial rules of thumb that no longer apply, and sucks the life out of the economy. It even muddies the waters of the great economic debate of our time, about the economic significance of capital.
One final question, then: is it all a bubble? That is too deep a question for me but there is an intriguing new study by three German economists, Katharina Knoll, Moritz Schularick and Thomas Steger. They have constructed house-price indices over 14 developed economies since 1870. The pattern is striking: about 50 years ago, real prices started to climb inexorably and at an increasing rate. If this is a bubble, it’s been inflating for two generations.
At least dinner-party guests across London will continue to have something to bore each other about. Not that anybody will be able to afford a dining room.
Written for and first published at ft.com.
‘What else might influence portfolio returns? There is literally no limit to the number of variables’
Discomfiting news: most of those financial strategies that claim to beat the market don’t. Even more surprising, many of the financial research papers that claim to have found patterns in financial markets haven’t.
Don’t take my word for it: this is the conclusion of three US-based academics, Campbell Harvey, Yan Liu and Heqing Zhu. What is particularly striking about the way they’ve lobbed a hand grenade into the finance research literature is that Campbell Harvey isn’t some heterodox radical. He’s the former editor of the leading journal in the field, The Journal of Finance.
What’s going on?
Much financial research attempts to figure out what explains the investment returns on financial portfolios. At a first pass, returns follow a random-walk hypothesis. This insight is a century old and we owe it to the mathematician Louis Bachelier. The basic reasoning is that any successful forecast of price movements would be self-defeating: if it was obvious the price would rise tomorrow, then the price would instead rise today. Therefore, there can be no successful forecast of price movements.
A second pass at the problem, courtesy of several researchers in the 1960s, gives us the capital asset pricing model: riskier portfolios will probably offer higher returns. And it seems that they do.
Then, in 1992, Eugene Fama (more recently a Nobel Memorial Prize winner) and Kenneth French found that the returns on a portfolio of shares were explained by three factors: exposure to the market as a whole, exposure to small company stocks, and exposure to “value stocks”.
This is progress of sorts – but it’s also a can of worms. What else might influence portfolio returns? There is literally no limit to the number of different variables that could be examined, because variables can always be transformed or combined with each other, for instance as ratios or rates of change.
In principle, economic logic might limit the number of combinations to be examined – but in practice both academics and quantitatively minded investment managers have been known to throw in all sorts of possibilities just to see what happens. Why not, for example, use the cube of the market capitalisation of the shares? There’s no economic logic behind that variable – at least, none that I can see – but that hasn’t stopped the quants stirring such things into the mix.
The issue here is what we might call the “jelly bean problem”, after a cartoon by nerd hero Randall Munroe. The cartoon shows scientists testing whether jelly beans cause acne, applying a commonly used statistical test. The test is to assume that jelly beans don’t cause acne, then rethink that assumption if the observed correlation between jelly beans and acne has less than a 5 per cent probability of occurring by chance. The scientists test purple, brown, pink, blue, teal, salmon, red, turquoise, magenta, yellow, grey, tan, cyan, green, mauve, beige, lilac, black, peach and orange jelly beans. It turns out that the green ones are correlated with acne!
This is, of course, no way to perform a statistical analysis. If 20 statistical patterns are analysed and there’s no genuine causal relationship in any of them, we’d still expect one of them to look strikingly correlated. (How strikingly? Well, about 19-1 against.)
The finance literature has looked at far more than 20 possibilities. Harvey, Liu and Zhu scrutinise 316 different factors that have been explored by a selection of reputable research studies, of which 296 are statistically significant by conventional standards. That’s just a subset of the factors that have been examined in minor journals, or not published at all because the results were too boring.
For example, a paper might try to explain stock market returns as a function of media coverage of companies; of corporate debt; of momentum in previous returns; or of the volume of trades.
With 316 factors – and probably many more – under investigation, using a 5 per cent significance standard is absurd. Harvey and his colleagues suggest that after trying to correct for the jelly bean problem (more technically known as the multiple-comparisons problem), more than half the 296 statistically significant variables might have to be discarded. They suggest higher and more discerning statistical hurdles in future, not to mention a more explicit role for variables with some theory behind them, rather than variables that have happened to stick after the entire statistical fruit salad has been hurled at the wall.
None of this should astonish us. In 2005 an epidemiologist called John Ioannidis published a research paper that has become famous. It has the self-explanatory title “Why Most Published Research Findings Are False”. The reason is partly the multiple comparisons problem, and partly publication bias: a tendency on the part of researchers and journal editors alike to publish surprising findings and leave dull ones to languish in desk drawers.
Harvey and his colleagues have shown that the Ioannidis critique applies in the finance research literature too. No doubt it applies far more strongly in the advertisements we’re shown for financial products. We should have always been on the lookout for intriguing patterns in the data. But if we’re not careful, our analysis will produce plenty of flukes. And in finance, flukes are just as marketable as the truth.
Written for and first published at ft.com.
Class matters far less than it used to in the 19th century. Citizenship matters far more
I’ve been a lucky boy. I could start with the “boy” fact. We men enjoy all sorts of privileges, many of them quite subtle these days, but well worth having. I’m white. I’m an Oxford graduate and I am the son of Oxbridge graduates. All those are things that I have in common with my fellow columnist Simon Kuper, who recently admitted that he didn’t feel he’d earned his vantage point “on the lower slopes of the establishment”.
I don’t feel able to comment objectively on that, although we could ask another colleague, Gillian Tett. She’s female and – in a particularly cruel twist – she wasn’t educated at Oxford but at Cambridge. That’s real diversity right there.
All these accidents of birth are important. But there’s a more important one: citizenship. Gillian, Simon and I are all British citizens. Financially speaking, this is a greater privilege than all the others combined.
Imagine lining up everyone in the world from the poorest to the richest, each standing beside a pile of money that represents his or her annual income. The world is a very unequal place: those in the top 1 per cent have vastly more than those in the bottom 1 per cent – you need about $35,000 after taxes to make that cut-off and be one of the 70 million richest people in the world. If that seems low, it’s $140,000 after taxes for a family of four – and it is also about 100 times more than the world’s poorest people have.
What determines who is at the richer end of that curve is, mostly, living in a rich country. Branko Milanovic, a visiting presidential professor at City University New York and author of The Haves and the Have-Nots, calculates that about 80 per cent of global inequality is the result of inequality between rich nations and poor nations. Only 20 per cent is the result of inequality between rich and poor within nations. The Oxford thing matters, of course. But what matters much more is that I was born in England rather than Bangladesh or Uganda. (Just to complicate matters, Simon Kuper was born in Uganda. He may refer to himself as “default man” but his life defies easy categorisation.)
That might seem obvious but it’s often ignored in the conversations we have about inequality. And things used to be very different. In 1820, the UK had about three times the per capita income of countries such as China and India, and perhaps four times that of the poorest countries. The gap between rich countries and the rest has since grown. Today the US has about five times the per capita income of China, 10 times that of India and 50 times that of the poorest countries. (These gaps could be made to look even bigger by not adjusting for lower prices in China and India.) Being a citizen of the US, the EU or Japan is an extraordinary economic privilege, one of a dramatically different scale than in the 19th century.
Privilege back then used to be far more about class than nationality. Consider the early 19th century world of Jane Austen’s Pride and Prejudice. Elizabeth Bennet’s financial future depends totally on her social position and, therefore, if and whom she marries. Elizabeth’s family’s income is £430 per capita. She can increase that more than tenfold by marrying Mr Darcy and snagging half of his £10,000 a year (this income, by the way, put Mr Darcy in the top 0.1 per cent of earners). But if her father dies before she marries, Elizabeth may end up with £40 a year, still twice the average income in England.
Milanovic shows that when we swap in data from 2004, all the gaps shrink dramatically. Mr Darcy’s income as one of the 0.1 per cent is £400,000; Elizabeth Bennet’s fallback is £23,000 a year. Marriage in the early 19th century would have increased her income more than 100 times; in the early 21st century, the ratio has shrunk to 17 times.
This is a curious state of affairs. Class matters far less than it used to in the 19th century. Citizenship matters far more. Yet when we worry about inequality, it’s not citizenship that obsesses us. Thomas Piketty’s famous book, Capital in the 21st Century, consciously echoes Karl Marx. Click over to the “Top Incomes Database”, a wonderful resource produced by Piketty, Tony Atkinson and others, and you’ll need to specify which country you’d like to analyse. The entire project accepts the nation state as the unit of analysis.
Meanwhile, many people want to limit migration – the single easiest way for poor people to improve their life chances – and view growth in India and China not as dramatic progress in reducing both poverty and global inequality, but as a sinister development.
It would be unfair to say that Simon Kuper and Thomas Piketty have missed the point. Domestic inequality does matter. It matters because we have political institutions capable of addressing it. It matters because it’s obvious from day to day. And it matters because over the past few decades domestic inequality has started to grow again, just as global inequality has started to shrink.
But as I check off my list of privileges, I won’t forget the biggest of them all: my passport.
Also published at ft.com.
Financial price data are converted into music, the music is played to a rat, then the rat guesses whether the price will fall or rise
Eighty-five years ago, a young psychologist called BF Skinner developed what is technically called an operant conditioning chamber but is more famously known as a Skinner box, designed to contain and train laboratory animals. The simplest version rewards a rat for pressing a lever. More complex devices can play sounds, display lights and even deliver electric shocks, although Skinner himself preferred to use rewards rather than punishments.
The Skinner box acquired an unpleasant reputation: rumours circulated that Skinner raised one of his own daughters in one, that she lost her mind, that she sued him and that she killed herself before reaching middle age. None of this is true. One explanation for the rumours is that Skinner did design an air-conditioned crib for his daughter and described it with fancy technical terms such as “apparatus”. But perhaps the false ideas circulated because Skinner’s ideas of modifying behaviour with rewards in a carefully controlled environment seemed somehow manipulative and threatening. These days, of course, we call behaviour modification “nudging” and it is perfectly respectable.
I thought of all this when I discovered RatTraders.com, a website offering, in its own words, “a professional service to the financial industry; rats are being trained to become superior traders in the financial markets.”
RatTraders displays photographs and short films of rats in Skinner boxes. As the website explains, “RATTRADERS rats can be trained exclusively for any financial market segment. They outperform most human traders and represent a much more economic solution for your trading desk.”
The brains behind the project is Michael Marcovici, who has a double life: he’s both a conceptual artist and an offbeat investment guru. So is RatTraders a work of art or a business proposition? The basic conceit is that financial price data are converted into 20 seconds of piano music, the music is played to a rat, and then the rat guesses whether to bet that the price will then fall or rise. If the rat is successful, it receives food; if not, a mild shock. After weeks of training, the site says, the best rats outperform most humans.
In an online video, Marcovici deadpans to a “reporter” that “rats are much better at this because you can train a rat on a very specific thing. It will not be distracted.” The interviewer asks how much it would cost to buy one of these elite rats. “It’s hard to put a price tag on a rat. A rat will not help. Rat trading is a system,” responds Marcovici. But he adds that even the full service would be “just a fragment of what a human trader will cost”.
Just when the viewer’s credibility is strained to breaking point, Marcovici announces that investment banks have already installed trading floors full of rats in boxes. His ultimate business vision, he says, is that rats will also be trained to do marketing and general management. The comic timing is impressive. And it’s a piece of art with a message that does not need underlining.
Marcovici says that all this began as a joke. But after he had bought some rats and built a rather beautiful Skinner box, his girlfriend urged him not to get rid of the rats but to see if they actually could learn to trade gold, oil and foreign exchange. Most of them couldn’t but after five months a few of the rats were pretty good – better than tossing a coin, anyway, which is a tougher benchmark than you might think.
So should we start employing rats as traders? The idea is not totally absurd. Ben Vermaercke of the University of Leuven recently published a paper with four colleagues titled “More complex brains are not always better”. They showed that rats were better than humans at distinguishing certain kinds of striped patterns from others – the humans, it was hypothesised, were thinking too hard rather than relying on instinctive pattern recognition.
Perhaps a properly controlled scientific experiment would also find that rats make excellent foreign exchange traders. I doubt it. If rats really can make money after being played a sonified snippet of recent price history, that suggests a basic inefficiency in financial markets. If price movements were predictable in such an elementary way then profit-seeking traders, human or murine, should exploit the pattern and thereby change it. (If there are patterns in market prices, they are not simple.)
RatTraders is five years old but the project has recently enjoyed a fresh burst of media attention. Marcovici tells me that several small hedge funds promptly got in touch with him to find out more. Did he really expect serious interest in financially savvy rats?
“Yes, yes. Honestly I did,” he says. “I’ve been involved with the financial industry for some time and people try anything.”
Fair enough. Greed is a powerful motivator for humans and rats alike. But it is not always a great investment strategy. Some people wanted to believe the worst about BF Skinner. If there seems to be money to be made, others will gladly believe the best about trader rats.
Also published at ft.com.