Thursday, 15 February 2018

The Florida school shooting proves we need to arm every child over the age of six months for their own protection

Mark Steel in The Independent

After yet another shooting in a school in America, surely the time has come when we have to listen to the arguments of ordinary Americans and issue every child over the age of six months with a gun.

The only way to keep kids safe is to make sure they’re heavily armed as soon as they’ve developed the ability to grip. Obviously this leaves smaller babies vulnerable, so they should be given voice-activated flame-throwers that scorch anyone within 20 yards whenever there’s a gurgle.

Then the teachers can get on with the job of teaching kids how to shoot things. When a college student goes wild with a Heckler and Koch 9mm pistol, instead of telling them off like we do at the moment, they can offer advice, and say, “Watkins, WHAT have I told you about lining up your target? You did very well to murder three boys in the doorway but you completely missed Mr Nolan the caretaker.”

This shooting in Florida was the eighteenth such event in an American school this year. Soon there will be so many they won’t be news; they’ll be read out like the football results each Saturday afternoon. The announcer will say: “Here are this week’s shooting sprees in schools: Kansas 3, Wyoming 1, Montana 2, Texas FOUR.”

Then, instead of moaning about these incidents, they can be incorporated into lessons. A maths teacher might say, “This morning there were 28 of us in the classroom. Now four of us are lying in a pool of blood. Express as a fraction the amount of us who have survived.”

The National Rifle Association and opponents of gun control used to be a bit sheepish after each shooting. They’d stay quiet for a week, then mumble a statement such as, “In the light of events, maybe we shouldn’t say anything until we know the facts, as it might be that the gunshot wounds weren’t caused by a gun.”

So it’s good to see they’ve got over that timid phase, and now they respond to a massacre by saying, “Yeeeehahhhh, did you see what that dude was using? Awesome.”

Then they emphasise that a critical clause in the original constitution of their country asserts the fundamental right of every citizen to carry a gun. That makes sense, as the founders of the nation ensured the common man should have the right to oppose the tyrant, and protected the right of the colony to defend themselves against a foreign dictator, by enshrining in law the power of the governed to resist unfair governance. And that’s exactly the same as protecting the right of a bloke who sits in an attic for eight months at a time playing computer games who thinks he’s been sent to earth by the Mighty Thor to buy a semi-automatic rifle so he can blast everyone in a shoe shop in Wyoming.

Americans’ insistence about their right to own guns is sometimes difficult for outsiders to comprehend. But it’s linked to their fundamentalist Christian beliefs, and we should respect that, because when Jesus was asked what he would do if someone slapped him on the right cheek, he said, “Load my A15 semi-automatic rifle and fire at random strangers in a shopping centre in Nazareth.”

Indeed if there is a cheery side to this latest slaughter, it’s the excellent publicity it’s provided for the AR15. Because it was not only used in this shooting, but in the Sutherland Springs school shooting in Texas, and for the one in Las Vegas. So the manufacturers will rush out an advert that goes: “Hi, I’m a lunatic who eats raw squirrels and lives in a bedsit with the Devil, and when I go crazy in a school playground I always take my AR15 – it’s guaranteed to slaughter like it oughta.” Then Charlton Heston can say: “AR15: the choice of nine out of 10 fruitbat gunmen across the United States.”

The main argument we’re used to hearing from gun-toting Americans is that each new massacre proves not how dangerous guns are but how dangerous it is to not have a gun. Because the best protection against a wild gunman is a gun.

And this is true. Similarly, not many people get killed by crazy people driving their tank through a school or a shopping centre. This might be because it’s quite tricky, even in America, to buy a tank. But there is a more sensible way of looking at this, which is that if someone were to go berserk with a tank, the rest of us would have no protection. So we should immediately make it legal to possess your own personal tank.

Within a couple of years, tanks would be as easy to buy as guns are now. You could get 2 for 1 during happy hour at Hank’s Tanks, and some days you’d get one free when you bought an Aero, and before long, millions of people would have tanks so no one would need worry about tanks.

So the only problem is how to make us as safe globally from the danger of guns as they are in America. The answer must be to give other countries more guns. Trump must start giving shiploads of them to Syria and North Korea, so we can all stop worrying.

And the National Rifle Association, along with the rest of the gun lobby, will all join Isis, as the Islamic caliphate is the nearest to a society where everyone has a gun.

Then at the current rate there will soon be thousands of shooting sprees a day, until there are only three people left alive in the whole of America, each pointing guns at the heads of the other two, unable to work or hold any food, so they live by nibbling berries and never falling asleep, and at last they’ll be safe.

Sunday, 11 February 2018

The end of an era of cheap money?

Nicole Bullock, Eric Platt and Alexandra Scaggs in The Financial Time

For more than a decade, Mike Schmanske made a living trading “volatility” — betting on the size and speed of moves in the US stock market. After 2014, the market was calm for so long that he spent much of his time sailing a Swan yacht. He got his adrenalin flowing in a different way: on his first trip from Bermuda to Newport, Rhode Island, he raced a hurricane back to port and made it with 12 hours to spare. 

Now, a new bout of turbulence is pulling him back to Wall Street. A sharp outbreak of volatility has written more than $5tn off the value of global stocks in less than two weeks and Mr Schmanske is talking to his old trading buddies about getting back into the market. 

“This is the most calls I’ve taken in years,” says Mr Schmanske*, a pioneer of some of the first volatility trading products while at Barclays and now a consultant. “Things were slow. I was literally on a boat a few weeks back.” 

The catalyst for the volatility surge came at 8:30am last Friday when the US government employment report showed a surprisingly strong rise in wages, prompting bond yields to shoot upwards and the price of those bonds to fall. Within hours, the losses in the $14tn Treasury market had spread to stocks, setting the stage for Wall Street’s worst week in two years.** By Thursday, US equities had entered what is known as a correction — a fall of at least 10 per cent. Many investors who had piled into esoteric instruments that enable them to bet on continued calm in the market had been wiped out. 

The ructions over the past week have attracted so much attention because they strike at the question that has haunted markets for the past two years — what happens when the economy returns to normal? Since the financial crisis, markets have been boosted by an unprecedented mixture of ultra-low interest rates and asset-buying by central banks in a bid to fend off the threat of deflation. But with global growth robust and inflation beginning to re-appear, central banks are pulling back. 

The question investors are trying to answer is how much of the sharp drop in share prices is due to a technical reaction driven by a much-hyped niche in the market that bets on volatility, versus part of a broader adjustment to a different economic reality. 

“The system has changed,” says Jean Ergas, head strategist at Tigress Partners, who said the market had made more of a “rethink” than a correction. “This is the unwinding of a massive carry trade, in which people borrowed at zero per cent and put money into stocks for a yield of 2 per cent.” 

The year began on a euphoric note as a large cut in US corporate tax prompted investors to mark up their expectations for earnings growth. The economy was already humming around the world for the first time since the financial crisis. 

At its peak on January 26, the market values of S&P 500 companies had surged by $5tn from a year earlier, while global stocks were up by nearly $14tn. The gains lured small investors into the market, with more than $350bn pumped into equity funds in the year, according to fund tracker EPFR Global. 

But cracks had already appeared in the bond market. Investors were starting to make noise and demand higher yields. Bill Gross and Jeffrey Gundlach — two well-known money managers in fixed-income markets — both declared last month a new era after a 36-year “bull market” in bonds, which had seen yields driven steadily lower. 

It was against that backdrop that markets reacted to last Friday’s news of a 2.9 per cent rise in US wages — not dramatic in a different era but still the largest year-on-year rise since the financial crisis. Inflation fears rose. Investors began marking up the odds that the Federal Reserve could tighten policy by a full percentage point this year, more aggressively than previously thought. Robust growth in Europe and Japan also raised the question of when the European Central Bank and Bank of Japan would begin to remove crisis-era stimulus. 

“Inflation fears running back into the market and hitting basically all assets in a market that had run up significantly is a pretty plausible, simple story,” says Clifford Asness, co-founder of AQR Capital Management. “You do not have to go looking for Alger Hiss in this pumpkin.” 

By the end of last Friday, yields on benchmark 10-year US Treasuries had hurdled above 2.8 per cent for the first time in nearly four years. For the year, yields had risen more than 40 basis points, increasing the appeal of bonds relative to stocks. The Dow Jones Industrial Average lost 666 points — an unsettling omen for religiously minded traders. 

“Optimism over synchronised global growth and supportive macro conditions led to outsized gains in equity markets to start the year,” says Craig Burelle, macro strategies research analyst at Loomis Sayles. “But more recently, some investors worried the economic momentum was too much of a good thing, and optimism gave way to concerns about the future path of inflation and interest rates.” 

Before long, the anxiety had gone global. On Sunday evening, many Americans were watching the Philadelphia Eagles upset the New England Patriots in the Super Bowl: at the same time, Asian markets were opening on Monday with a spike in bond yields. 

“On any other Sunday night you might have been more anxious about what you were seeing,” says Matt Cheslock, a trader at Virtu and a 25-year veteran of the New York Stock Exchange. “The game provided a nice distraction.” 

Monday morning in the US added a new source of uncertainty with the swearing in of Jay Powell as the chairman of the Federal Reserve, bringing a relatively little-known face to lead the central bank. For much of the day, Wall Street avoided serious losses. Then, a big drop seemed to come out of nowhere. About an hour before the closing bell, the Dow slumped more than 800 points in 10 minutes. 

“The adrenalin kicks in,” says Mr Cheslock. “Everyone gets sharper. The complacency is long gone.” 

Customers rushed to log into their accounts at Vanguard, TD Ameritrade, T Rowe Price and Charles Schwab, straining websites. Some were unable to place orders. 

“As the volatility picks up and the indices plummet the rumours start to swell,” says Michael Arone, chief investment strategist at State Street Global Advisors. “Folks are wondering the classic Warren Buffett line about when the tide goes out, you see who is not wearing swimming trunks.” 

Over the past week, the investors who have been left most exposed are those who had made bets on subdued volatility. As share prices slumped, Wall Street’s “fear gauge” — the widely watched Cboe Vix volatility index — spiked. 

Trading strategies that profited from the calm in markets during 2017 quickly unravelled. Two exchange-traded products that enabled investors to bet on low volatility lost nearly all their value on Monday. 

After the bell on Monday, the Vix continued to rise and shares in vehicles related to Vix also fell. 

On Tuesday morning, Nomura, the Japanese bank, said in Tokyo that it would pull a product that was pegged to S&P 500 volatility. Within half an hour, the Nikkei 225 had fallen 2.5 per cent, which, in turn, prompted a bout of selling in bitcoin. The digital currency — worth more than $19,000 as recently as December — dropped below $6,000 just after 2:45am in New York, as traders in London and Frankfurt were getting to their desks. Stock markets in both countries would open 3.5 per cent lower. 

As US investors slept, the turbulence continued. At 4am in New York, a number of exchange traded products related to volatility were halted. By 7:11am, more than two hours before the US open, the Vix volatility index shot above 50 — only the second time it has done so since 2010. The turbulence forced bankers to postpone a number of bond sales planned for the day. Then Credit Suisse said it would close an exchange traded note, known by the ticker XIV — which is designed to move in the exact opposite direction to the Vix each day, and had thus collapsed as volatility rose. 

“People had forgotten that stocks don’t just go up,” says Adam Sender, head of Sender Company and Partners, a hedge fund. “Corrections are a normal process. This was inevitable. Interest rates rising was the trigger, but short-volatility was the fuel.” 

The volatility subsided amid a Tuesday afternoon rally in New York, and world stock markets survived much of the next day without incident. But then at 1pm on Wednesday in New York, signs of nervousness re-emerged. Demand at the auction of US Treasury bonds was weak, a signal that investors were worried about inflation and a rising budget deficit, and would therefore only buy at higher yields. Stocks ended the day in the red, and when investors in Tokyo returned on Thursday, prices dropped quickly. Heavier selling ensued on Wall Street. By Friday morning, the main indices in the US, Germany and Japan were all down more than 10 per cent from their January highs. When trading finally closed for the week after another rollercoaster day, US losses were shaved to about 9 per cent. 

For some, the shock created by the collapse of the volatility products has been salutary. “It’s always good to be reminded of these things with accidents that aren’t of systemic importance to the entire economy,” says Victor Haghani, founder of London’s Elm Partners and an alumnus of Long-Term Capital Management. “It’s a gentle reminder from the market.” 

However, many investors believe the questions raised over the past week go well beyond the products connected to the Vix index. “We’ve gone from a market used to playing checkers — rising earnings, low rates equals higher prices — to being forced to compete in grandmaster three-dimensional chess: worries over growth versus rates, equity valuations, and the strength of the dollar, and now market structure concerns,” says Nicholas Colas, cofounder of DataTrek, a New York research group. 

While some investors talked of a buying opportunity, believing that faster economic growth and a modest uptick in inflation represent a positive backdrop for equities, many headed for the exits. Investors pulled more than $30bn from stock funds in the week to Wednesday, the largest week of withdrawals since EPFR began tracking the data at the turn of the century. 

The slump in share prices put the White House on the defensive, given that President Donald Trump has taken pride in the stock gains under his administration. “In the ‘old days,’ when good news was reported, the Stock Market would go up. Today, when good news is reported, the Stock Market goes down,” he tweeted on Wednesday. “Big mistake, and we have so much good (great) news about the economy!” 

Others were less confident. “This is not yet a major earthquake,” said Lawrence Summers, US Treasury secretary under President Bill Clinton. “Whether it’s an early tremor or a random fluctuation remains to be seen. I’m nervous and will stay nervous. [It is] far from clear that good growth and stable finance are compatible.” 

Some strategists expect the recent declines to lead to further selling, as computer-driven funds that target volatility are forced to shed more equities. Analysts put the amount of automatic selling from the recent turmoil at about $200bn, and more could be on the way unless markets simmer down. 

Jonathan Lavine, co-managing partner of Bain Capital, says a drop in share prices was not a surprise in itself. “It was the ferocity of the move, not triggered by any material news and propelled by a small corner of financial markets,” he says. “You have to ask yourself what would happen in the event of real bad news.”

Thursday, 8 February 2018

A simple guide to statistics in the age of deception

Tim Harford in The Financial Times

Image result for statistics

“The best financial advice for most people would fit on an index card.” That’s the gist of an offhand comment in 2013 by Harold Pollack, a professor at the University of Chicago. Pollack’s bluff was duly called, and he quickly rushed off to find an index card and scribble some bullet points — with respectable results. 

When I heard about Pollack’s notion — he elaborated upon it in a 2016 book — I asked myself: would this work for statistics, too? There are some obvious parallels. In each case, common sense goes a surprisingly long way; in each case, dizzying numbers and impenetrable jargon loom; in each case, there are stubborn technical details that matter; and, in each case, there are people with a sharp incentive to lead us astray. 

The case for everyday practical numeracy has never been more urgent. Statistical claims fill our newspapers and social media feeds, unfiltered by expert judgment and often designed as a political weapon. We do not necessarily trust the experts — or more precisely, we may have our own distinctive view of who counts as an expert and who does not.  

Nor are we passive consumers of statistical propaganda; we are the medium through which the propaganda spreads. We are arbiters of what others will see: what we retweet, like or share online determines whether a claim goes viral or vanishes. If we fall for lies, we become unwittingly complicit in deceiving others. On the bright side, we have more tools than ever to help weigh up what we see before we share it — if we are able and willing to use them. 

In the hope that someone might use it, I set out to write my own postcard-sized citizens’ guide to statistics. Here’s what I learnt. 

Professor Pollack’s index card includes advice such as “Save 20 per cent of your money” and “Pay your credit card in full every month”. The author Michael Pollan offers dietary advice in even pithier form: “Eat Food. Not Too Much. Mostly Plants.” Quite so, but I still want a cheeseburger.  

However good the advice Pollack and Pollan offer, it’s not always easy to take. The problem is not necessarily ignorance. Few people think that Coca-Cola is a healthy drink, or believe that credit cards let you borrow cheaply. Yet many of us fall into some form of temptation or other. That is partly because slick marketers are focused on selling us high-fructose corn syrup and easy credit. And it is partly because we are human beings with human frailties. 

With this in mind, my statistical postcard begins with advice about emotion rather than logic. When you encounter a new statistical claim, observe your feelings. Yes, it sounds like a line from Star Wars, but we rarely believe anything because we’re compelled to do so by pure deduction or irrefutable evidence. We have feelings about many of the claims we might read — anything from “inequality is rising” to “chocolate prevents dementia”. If we don’t notice and pay attention to those feelings, we’re off to a shaky start. 

What sort of feelings? Defensiveness. Triumphalism. Righteous anger. Evangelical fervour. Or, when it comes to chocolate and dementia, relief. It’s fine to have an emotional response to a chart or shocking statistic — but we should not ignore that emotion, or be led astray by it. 

There are certain claims that we rush to tell the world, others that we use to rally like-minded people, still others we refuse to believe. Our belief or disbelief in these claims is part of who we feel we are. “We all process information consistent with our tribe,” says Dan Kahan, professor of law and psychology at Yale University. 

In 2005, Charles Taber and Milton Lodge, political scientists at Stony Brook University, New York, conducted experiments in which subjects were invited to study arguments around hot political issues. Subjects showed a clear confirmation bias: they sought out testimony from like-minded organisations. For example, subjects who opposed gun control would tend to start by reading the views of the National Rifle Association. Subjects also showed a disconfirmation bias: when the researchers presented them with certain arguments and invited comment, the subjects would quickly accept arguments with which they agreed, but devote considerable effort to disparage opposing arguments.  

Expertise is no defence against this emotional reaction; in fact, Taber and Lodge found that better-informed experimental subjects showed stronger biases. The more they knew, the more cognitive weapons they could aim at their opponents. “So convenient a thing it is to be a reasonable creature,” commented Benjamin Franklin, “since it enables one to find or make a reason for everything one has a mind to do.” 

This is why it’s important to face up to our feelings before we even begin to process a statistical claim. If we don’t at least acknowledge that we may be bringing some emotional baggage along with us, we have little chance of discerning what’s true. As the physicist Richard Feynman once commented, “You must not fool yourself — and you are the easiest person to fool.” 

The second crucial piece of advice is to understand the claim. That seems obvious. But all too often we leap to disbelieve or believe (and repeat) a claim without pausing to ask whether we really understand what the claim is. To quote Douglas Adams’s philosophical supercomputer, Deep Thought, “Once you know what the question actually is, you’ll know what the answer means.” 

For example, take the widely accepted claim that “inequality is rising”. It seems uncontroversial, and urgent. But what does it mean? Racial inequality? Gender inequality? Inequality of opportunity, of consumption, of education attainment, of wealth? Within countries or across the globe? 

Even given a narrower claim, “inequality of income before taxes is rising” (and you should be asking yourself, since when?), there are several different ways to measure this. One approach is to compare the income of people at the 90th percentile and the 10th percentile, but that tells us nothing about the super-rich, nor the ordinary people in the middle. An alternative is to examine the income share of the top 1 per cent — but this approach has the opposite weakness, telling us nothing about how the poorest fare relative to the majority.  

There is no single right answer — nor should we assume that all the measures tell a similar story. In fact, there are many true statements that one can make about inequality. It may be worth figuring out which one is being made before retweeting it. 

Perhaps it is not surprising that a concept such as inequality turns out to have hidden depths. But the same holds true of more tangible subjects, such as “a nurse”. Are midwives nurses? Health visitors? Should two nurses working half-time count as one nurse? Claims over the staffing of the UK’s National Health Service have turned on such details. 

All this can seem like pedantry — or worse, a cynical attempt to muddy the waters and suggest that you can prove anything with statistics. But there is little point in trying to evaluate whether a claim is true if one is unclear what the claim even means. 

Imagine a study showing that kids who play violent video games are more likely to be violent in reality. Rebecca Goldin, a mathematician and director of the statistical literacy project STATS, points out that we should ask questions about concepts such as “play”, “violent video games” and “violent in reality”. Is Space Invaders a violent game? It involves shooting things, after all. And are we measuring a response to a questionnaire after 20 minutes’ play in a laboratory, or murderous tendencies in people who play 30 hours a week? “Many studies won’t measure violence,” says Goldin. “They’ll measure something else such as aggressive behaviour.” Just like “inequality” or “nurse”, these seemingly common sense words hide a lot of wiggle room. 

Two particular obstacles to our understanding are worth exploring in a little more detail. One is the question of causation. “Taller children have a higher reading age,” goes the headline. This may summarise the results of a careful study about nutrition and cognition. Or it may simply reflect the obvious point that eight-year-olds read better than four-year-olds — and are taller. Causation is philosophically and technically a knotty business but, for the casual consumer of statistics, the question is not so complicated: just ask whether a causal claim is being made, and whether it might be justified. 

Returning to this study about violence and video games, we should ask: is this a causal relationship, tested in experimental conditions? Or is this a broad correlation, perhaps because the kind of thing that leads kids to violence also leads kids to violent video games? Without clarity on this point, we don’t really have anything but an empty headline.  

We should never forget, either, that all statistics are a summary of a more complicated truth. For example, what’s happening to wages? With tens of millions of wage packets being paid every month, we can only ever summarise — but which summary? The average wage can be skewed by a small number of fat cats. The median wage tells us about the centre of the distribution but ignores everything else. 

Or we might look at the median increase in wages, which isn’t the same thing as the increase in the median wage — not at all. In a situation where the lowest and highest wages are increasing while the middle sags, it’s quite possible for the median pay rise to be healthy while median pay falls.  

Sir Andrew Dilnot, former chair of the UK Statistics Authority, warns that an average can never convey the whole of a complex story. “It’s like trying to see what’s in a room by peering through the keyhole,” he tells me.  

In short, “you need to ask yourself what’s being left out,” says Mona Chalabi, data editor for The Guardian US. That applies to the obvious tricks, such as a vertical axis that’s been truncated to make small changes look big. But it also applies to the less obvious stuff — for example, why does a graph comparing the wages of African-Americans with those of white people not also include data on Hispanic or Asian-Americans? There is no shame in leaving something out. No chart, table or tweet can contain everything. But what is missing can matter. 

Channel the spirit of film noir: get the backstory. Of all the statistical claims in the world, this particular stat fatale appeared in your newspaper or social media feed, dressed to impress. Why? Where did it come from? Why are you seeing it?  

Sometimes the answer is little short of a conspiracy: a PR company wanted to sell ice cream, so paid a penny-ante academic to put together the “equation for the perfect summer afternoon”, pushed out a press release on a quiet news day, and won attention in a media environment hungry for clicks. Or a political donor slung a couple of million dollars at an ideologically sympathetic think-tank in the hope of manufacturing some talking points. 

Just as often, the answer is innocent but unedifying: publication bias. A study confirming what we already knew — smoking causes cancer — is unlikely to make news. But a study with a surprising result — maybe smoking doesn’t cause cancer after all — is worth a headline. The new study may have been rigorously conducted but is probably wrong: one must weigh it up against decades of contrary evidence. 

Publication bias is a big problem in academia. The surprising results get published, the follow-up studies finding no effect tend to appear in lesser journals if they appear at all. It is an even bigger problem in the media — and perhaps bigger yet in social media. Increasingly, we see a statistical claim because people like us thought it was worth a Like on Facebook. 

David Spiegelhalter, president of the Royal Statistical Society, proposes what he calls the “Groucho principle”. Groucho Marx famously resigned from a club — if they’d accept him as a member, he reasoned, it couldn’t be much of a club. Spiegelhalter feels the same about many statistical claims that reach the headlines or the social media feed. He explains, “If it’s surprising or counter-intuitive enough to have been drawn to my attention, it is probably wrong.”  

OK. You’ve noted your own emotions, checked the backstory and understood the claim being made. Now you need to put things in perspective. A few months ago, a horrified citizen asked me on Twitter whether it could be true that in the UK, seven million disposable coffee cups were thrown away every day.  

I didn’t have an answer. (A quick internet search reveals countless repetitions of the claim, but no obvious source.) But I did have an alternative question: is that a big number? The population of the UK is 65 million. If one person in 10 used a disposable cup each day, that would do the job.  

Many numbers mean little until we can compare them with a more familiar quantity. It is much more informative to know how many coffee cups a typical person discards than to know how many are thrown away by an entire country. And more useful still to know whether the cups are recycled (usually not, alas) or what proportion of the country’s waste stream is disposable coffee cups (not much, is my guess, but I may be wrong).  

So we should ask: how big is the number compared with other things I might intuitively understand? How big is it compared with last year, or five years ago, or 30? It’s worth a look at the historical trend, if the data are available.  

Finally, beware “statistical significance”. There are various technical objections to the term, some of which are important. But the simplest point to appreciate is that a number can be “statistically significant” while being of no practical importance. Particularly in the age of big data, it’s possible for an effect to clear this technical hurdle of statistical significance while being tiny. 

One study was able to demonstrate that unborn children exposed to a heatwave while in the womb went on to earn less as adults. The finding was statistically significant. But the impact was trivial: $30 in lost income per year. Just because a finding is statistically robust does not mean it matters; the word “significance” obscures that. 

In an age of computer-generated images of data clouds, some of the most charming data visualisations are hand-drawn doodles by the likes of Mona Chalabi and the cartoonist Randall Munroe. But there is more to these pictures than charm: Chalabi uses the wobble of her pen to remind us that most statistics have a margin of error. A computer plot can confer the illusion of precision on what may be a highly uncertain situation. 

“It is better to be vaguely right than exactly wrong,” wrote Carveth Read in Logic (1898), and excessive precision can lead people astray. On the eve of the US presidential election in 2016, the political forecasting website FiveThirtyEight gave Donald Trump a 28.6 per cent chance of winning. In some ways that is impressive, because other forecasting models gave Trump barely any chance at all. But how could anyone justify the decimal point on such a forecast? No wonder many people missed the basic message, which was that Trump had a decent shot. “One in four” would have been a much more intuitive guide to the vagaries of forecasting.

Exaggerated precision has another cost: it makes numbers needlessly cumbersome to remember and to handle. So, embrace imprecision. The budget of the NHS in the UK is about £10bn a month. The national income of the United States is about $20tn a year. One can be much more precise about these things, but carrying the approximate numbers around in my head lets me judge pretty quickly when — say — a £50m spending boost or a $20bn tax cut is noteworthy, or a rounding error. 

My favourite rule of thumb is that since there are 65 million people in the UK and people tend to live a bit longer than 65, the size of a typical cohort — everyone retiring or leaving school in a given year — will be nearly a million people. Yes, it’s a rough estimate — but vaguely right is often good enough. 

Be curious. Curiosity is bad for cats, but good for stats. Curiosity is a cardinal virtue because it encourages us to work a little harder to understand what we are being told, and to enjoy the surprises along the way.  

This is partly because almost any statistical statement raises questions: who claims this? Why? What does this number mean? What’s missing? We have to be willing — in the words of UK statistical regulator Ed Humpherson — to “go another click”. If a statistic is worth sharing, isn’t it worth understanding first? The digital age is full of informational snares — but it also makes it easier to look a little deeper before our minds snap shut on an answer.  

While curiosity gives us the motivation to ask another question or go another click, it gives us something else, too: a willingness to change our minds. For many of the statistical claims that matter, we have already reached a conclusion. We already know what our tribe of right-thinking people believe about Brexit, gun control, vaccinations, climate change, inequality or nationalisation — and so it is natural to interpret any statistical claim as either a banner to wave, or a threat to avoid.  

Curiosity can put us into a better frame of mind to engage with statistical surprises. If we treat them as mysteries to be resolved, we are more likely to spot statistical foul play, but we are also more open-minded when faced with rigorous new evidence. 

In research with Asheley Landrum, Katie Carpenter, Laura Helft and Kathleen Hall Jamieson, Dan Kahan has discovered that people who are intrinsically curious about science — they exist across the political spectrum — tend to be less polarised in their response to questions about politically sensitive topics. We need to treat surprises as a mystery rather than a threat.  

Isaac Asimov is thought to have said, “The most exciting phrase in science isn’t ‘Eureka!’, but ‘That’s funny…’” The quip points to an important truth: if we treat the open question as more interesting than the neat answer, we’re on the road to becoming wiser.  

In the end, my postcard has 50-ish words and six commandments. Simple enough, I hope, for someone who is willing to make an honest effort to evaluate — even briefly — the statistical claims that appear in front of them. That willingness, I fear, is what is most in question.  

“Hey, Bill, Bill, am I gonna check every statistic?” said Donald Trump, then presidential candidate, when challenged by Bill O’Reilly about a grotesque lie that he had retweeted about African-Americans and homicides. And Trump had a point — sort of. He should, of course, have got someone to check a statistic before lending his megaphone to a false and racist claim. We all know by now that he simply does not care. 

But Trump’s excuse will have struck a chord with many, even those who are aghast at his contempt for accuracy (and much else). He recognised that we are all human. We don’t check everything; we can’t. Even if we had all the technical expertise in the world, there is no way that we would have the time. 

My aim is more modest. I want to encourage us all to make the effort a little more often: to be open-minded rather than defensive; to ask simple questions about what things mean, where they come from and whether they would matter if they were true. And, above all, to show enough curiosity about the world to want to know the answers to some of these questions — not to win arguments, but because the world is a fascinating place. 

Tuesday, 6 February 2018

Blockchain explainer: a revolution only in its infancy

Hannah Murphy and Philip Stafford in The Financial Times

The word blockchain has been the equivalent of financial fairy dust in recent weeks, adding tens of millions of dollars to the market value of companies, including former camera pioneer Kodak Eastman, that have announced a project involving the technology or simply added it to their names. 

However, technologists and executives warn that blockchain technology is still developing and the high-profile name changes and often giddy reaction in the stock market are far removed from the real-world experiments. 

What is a blockchain? 

It is an electronic database of transactions, whereby new deals are added to the chain and then stamped and protected with a mathematical equation. 

The database is shared among hundreds of other computers, or “nodes” on the network, to make it virtually impossible for one agent to change it. These nodes use their computing power and compete to verify and decode the latest transaction. This is then appended as a “block” to the chain. Its ability to offer a verifiable, immutable and public record is what attracts many advocates. 

“It can do for the nearly free and frictionless transfer of assets what the internet did for the nearly free and frictionless transfer of information,” says Jonathan Johnson, an executive at, an online retailer that accepts payment in virtual currencies. 

How is it being used? 

Its chief use is as the system behind most of the hundreds upon hundreds of virtual coins that are being created, stored and traded online — of which bitcoin is the best-known. Estonia uses distributed ledgers for the public to follow court, legal and democratic procedures. 

But interest in its potential is far greater, generating great discussion at the recent World Economic Forum in Davos. 

Some countries, such as Russia and China, are interested in creating their own virtual currencies. Sectors from pharmaceuticals to shipping and agriculture are looking at it as a way to streamline record-keeping and improve inventory management through tracking systems. 

Financial markets are among the most enthusiastic adopters. Equity funding into companies building on blockchain technology hit $1bn last year, across 215 deals, according to data from CB Insights, a research group. 

Ventures such as the bank-backed R3 consortium have raised more than $100m. Crédit Agricole, the French lender, on Thursday took a small equity stake in Setl, the UK blockchain technology developer. 

Many institutions — including bulge bracket banks and fund managers — hope that a real-time ledger could automate their creaky and expensive back office systems, saving them millions. 

Several test cases are planned, such as the effort by Australia’s stock exchange to replace its system for clearing and settling trades with blockchain. CLS, the world’s largest currency settlement service, is drawing up plans. Setl has more than 20 institutions on its Iznes record-keeping platform for European funds. 

“People who are working with us trust us. We’re seen as a really specialist market,” says Peter Randall, chief executive of Setl. 

What are its limitations? 

Development is slow while institutions become accustomed to blockchain technology’s biggest features — that the records are public but the owner of the digital currency is anonymous and therefore untraceable

Many are creating their own “permissioned” distributed ledgers, where only those with authorisation can access the network. Some are exploring ways to build privacy options into the technology — for example, the ability to mask certain parts of the data such as trade or customer information. 

“Right now any kind of corporate blockchain initiative is using multiple platforms and coins and building their own proprietary technology on top of it,” says Jalak Jobanputra, founder of New-York based venture capital fund Future/Perfect Ventures. “There isn’t anything off the shelf right now that works for these consortia.” 

It has also been held back by the troubled reputation of its associated asset, bitcoin. The anonymity afforded to bitcoin users means it has been used to enable money laundering and organised crime. 

Some experts have questioned whether the technology can be scaled to process thousands of deals and payments per second that other electronic systems routinely handle. As the market develops watchdogs are also weighing up new specific regulations targeting the technology. “There is a lot of focus on the potential conflict between blockchain and data protection laws,” says Sue McLean, a partner in Baker MacKenzie’s IT and commercial practice division. 

Does the future of cryptocurrencies impact the future of the blockchain? 

The current hype around blockchain is partly because of its link to the mania in cryptocurrencies. More than 1,500 have been launched, eight times the number of recognised government-backed currencies, according to 

Initial coin offerings (ICOs) — in which blockchain-based start-ups issue their own digital “coins” — have created more incentives for the public to get involved in a nascent market. CB Insights estimates blockchain start-ups using ICO funding pulled in five times as much as equity funding last year, across 800 deals. 

But critics say none of the future uses of blockchain technology would make the cryptocurrencies more valuable. 

Steven Wieting, global chief investment strategist at Citi Private Bank, says the interest is a further indication of a “bull market psychology” in broader global markets. 

“This is evident in the very mild impact that negative events have had in market pricing. The willingness of so many to speculate in cryptocurrencies, an unproven financial innovation separate from the underlying blockchain technology, may be a symptom,” he says.

The myth of post-truth

The assumption is that my truth is as good as your truth, and hence all truths are immaterial and irrelevant. Such extreme relativism is a problem

Tabish Khair in The Hindu

It has been remarked that ‘post-truth’ is very different from similar terms with the prefix post-, such as postcolonialism and postmodernism. No one who uses postcolonialism or postmodernism argues that colonialism and modernism are no longer relevant. However, the assumption behind ‘post-truth’ is that the concept of truth is no longer relevant.

Why is there no post-falsehood?

The philosophical (or, in my view, anti-philosophical) aspects of ‘post-truth’ cannot be covered in a column — they would require a voluminous thesis. However, it is worth asking: why do we not talk of ‘post-falsehood’? After all, the opposite of truth is not post-truth but falsehood. In that case, if we can have an age of post-truth, we should be able to talk of an age of post-falsehood too. Having gone past truth, we should also be able to go past its opposite: falsehood. This, however, is not the case.

Partly, this has to do with the nature of truth and how we have understood it across cultures. Truth is seen as singular and fixed: it is generally felt that there can be only one truth, while there may be many falsehoods. Hence, we feel that to go past truth is to go past a singularity, but to go past falsehood might well mean to choose among multiple falsehoods.

There is another reason why ‘post-falsehood’ does not exist: strangely enough, it would come to mean ‘truth’. We instinctively feel that to go beyond generic falsehood is also to reach truth. That is because the positivity of truth cannot exist without the negativity of falsehood. The essential lie of ‘post-truth’ is exactly this: it is supposed not to suggest falsehood. But if there is no falsehood on the other side of truth, then there is no truth either. ‘Post-truth’ dismisses the very possibility of truth — and, by that act, it dismisses the existence of falsehood.

In short, it dismisses critical and scientific thinking, which are based not on eternal truth, which is religion’s penchant, but on a methodical and endless elimination of falsehoods. This is essentially what Karl Popper meant when he stressed that a scientific statement needs to be falsifiable.

It is nevertheless interesting to stand the matter on its head and pose this question: if we cannot talk of ‘post-falsehood’, surely the fact that we are talking of ‘post-truth’ means that there is actually a difference between truth and falsehood? And if that is the case, then, by definition, we can never have an age of ‘post-truth’ — in the sense of equating truths and falsehoods.

Truths are contextual

On the other hand, belief in a singular, unchanging truth is also what has led to the mistaken notion of an age of ‘post-truth’. That is so because the idea of one eternally fixed truth has been radically shaken over the past few centuries in different ways, most of which do not lead to extreme relativism but instead to a kind of contextualisation. However, this necessary shaking of given and fixed truths can be and is often converted into an extreme relativism by the loudly ignorant — a relativism in which all truths seem relative to you as an observer, and not to the complex context of the observation. This slippage inevitably leads to talk of post-truth, especially in fields outside the hard sciences.

In fact, truths are contextual — not relativist — in hard science too: the ‘truth’ of subatomic particles exists in the context of atoms, and the ‘truth’ of planetary systems in our universe exists in that context. These are not necessarily exclusive contexts, but only a seriously confused student would expect the rules that obtain within an atom to be the same as the rules that apply to our planetary system. This is what I mean by contextualisation.

Relativism, on the other hand, or at least extreme relativism (for many versions of what is called ‘relativism’ are basically contextualisation), extracts the observer from the context and makes the observer’s version paramount.

This is what lies at the core of ‘post-truth.’ The assumption is that my truth is as good as your truth, and hence all truths are immaterial and irrelevant. Need I note the problem of such extreme relativism, for it puts the observer outside a context, a context that can be and should be used to determine the ‘truth’ of his or her observations. Truths might not be eternally fixed, but we do get closer to what is true by comparing and contrasting our versions of it: to you it might be superman, to me it is a bird, but enough and better sightings will ascertain that it is actually a plane.

Hence, while one can argue about the details of evolution, the fact that both human beings and apes evolved from a common ancestor is more true than the claim that human beings were directly handcrafted by a god. There is overwhelming evidence of the former, and it can be dismissed only by stubborn acts of belief (or disbelief).
However, one should not oppose the myth of post-truth by returning to older and faulty myths of fixed, eternal truths. This too would block the necessary and fledgling project of critical inquiry. We need to maintain a balance between the dismissal of the difference between truth and falsehood and blind acceptance of given truths. The future of humanity depends on our precarious ability to maintain this delicate balance.

Wednesday, 31 January 2018

Numbers aren't neutral

A S Paneerselvan in The Hindu

Analysing data without providing sufficient context is dangerous

An inherent challenge in journalism is to meet deadlines without compromising on quality, while sticking to the word limit. However, brevity takes a toll when it comes to reporting on surveys, indexes, and big data. Let me examine three sets of stories which were based on surveys and carried prominently by this newspaper, to understand the limits of presenting data without providing comprehensive context.

Three reports

The Annual Status of Education Report (ASER), Oxfam’s report titled ‘Reward Work, Not Wealth’, and the World Bank’s ease of doing business (EoDB) rankings have been widely reported, commented on, and editorialised. In most cases, the numbers and rankings were presented as neutral evaluations; they were not seen as data originating from institutions that have political underpinnings. Data become meaningful only when the methodology of data collection is spelt out in clear terms.

Every time I read surveys, indexes, and big data, I look for at least three basic parameters to understand the numbers: the sample size, the sample questionnaire, and the methodology. The sample size used indicates the robustness of the study, the questionnaire reveals whether there are leading questions, and the methodology reveals the rigour in the study. As a reporter, there were instances where I failed to mention these details in my resolve to stick to the word limit. Those were my mistakes.

The ASER study covering specific districts in States is about children’s schooling status. It attempts to measure children’s abilities with regard to basic reading and writing. It is a significant study as it gives us an insight into some of the problems with our educational system. However, we must be aware of the fact that these figures are restricted only to the districts in which the survey was conducted. It cannot be extrapolated as a State-wide sample, nor is it fair to rank States based on how specific districts fare in the study. A news item, “Report highlights India’s digital divide” (Jan. 19, 2018), conflated these figures.

For instance, the district surveyed in Kerala was Ernakulam, which is an urban district; in West Bengal it was South 24 Parganas, a complex district that stretches from metropolitan Kolkata to remote villages at the mouth of the Bay of Bengal. How can we compare these two districts with Odisha’s Khordha, Jharkhand’s Purbi Singhbhum and Bihar’s Muzaffarpur? It could be irresistible for a reporter, who accessed the data, to paint a larger picture based on these specific numbers. But we may not learn anything when we compare oranges and apples.

Questionable methodology

Oxfam, in the ‘Reward Work, Not Wealth’ report, used a methodology that has been questioned by many economists. Inequality is calculated on the basis of “net assets”. The economists point out that in this method, the poorest are not those living with very little resources, but young professionals who own no assets and with a high educational loan. Inequality is the elephant in the room which we cannot ignore. But Oxfam’s figures seem to mimic the huge notional loss figures put out by the Comptroller and Auditor General of India. Readers should know that Oxfam’s study has drawn its figures from disparate sources such as the Global Wealth Report by Credit Suisse, the Forbes’ billionaires list, adjusting last year’s figure using the average annual U.S. Consumer Price Index inflation rate from the U.S. Bureau of Labour Statistics, the World Bank’s household survey data, and an online survey in 10 countries.

When the World Bank announced the EoDB index last year, there was euphoria in India. However, this newspaper’s editorial “Moving up” (Nov. 2, 2017), which looked at India’s surge in the latest World Bank ranking from the 130th position to the 100th in a year, cautioned and asked the government, which has great orators in its ranks, to be a better listener. In hindsight, this position was vindicated when the World Bank’s chief economist, Paul Romer, said that he could no longer defend the integrity of changes made to the methodology and that the Bank would recalculate the national rankings of business competitiveness going back to at least four years. Readers would have appreciated the FAQ section (“Recalculating ease of doing business”, Jan. 25) that explained this controversy in some detail, had it looked at India’s ranking using the old methodology.

Lessons from the IPL Auction 2018

Suresh Menon in The Hindu

Image result for ipl auction 2018

Both Neville Cardus and C.L.R. James asked whether cricket is an art, and answered in different ways. Cardus compared cricket to music while for James it belonged alongside theatre, opera and dance. Thus, art, yes, but the performing arts, and for what happens on the field.

It is now safe to say that cricket belongs to the visual and plastic arts — painting and sculpture — but not for what happens on the field. The IPL auction has added another dimension with the question: what is the value of a player? Is he like a Jeff Koons or an M.F. Hussain?

Is Jayadev Unadkat worth ₹11.5 crores? Is Hashim Amla not worth anything at all? The comparison with art is inevitable. A painting is worth exactly what someone is prepared to pay for it. In his book The Value of Art: Money, Power, Beauty, the art dealer Michael Findlay gives a more sophisticated explanation.

“The commercial value of art,” he says, “is based on collective intentionality. Human stipulation and declaration create and sustain the commercial value.” Replace “art” with “cricketer” and that still holds. If, based on sports metrics and private algorithms, Mumbai Indians think Krunal Pandya is worth ₹8.8 crores, you cannot argue.

On a weekend when every Test-playing country was engaged in an international, the focus was on a hotel ballroom in Bangalore. You can read all kinds of meaning into this. “It will be a distraction,” South Africa’s captain Faf du Plessis had said earlier. Kamlesh Nagarkoti, at the Under-19 World Cup in New Zealand said, “I went and sat inside the washroom even as my bidding was going on.” It went on and on and didn’t stop till it had reached ₹3.2 crores.

It was possible to switch channels between the auction and the incredible Indian performance at the Johannesburg Test. Virat Kohli certainly wasn’t distracted — his ₹17 crores was already in the bank. It would be interesting to discover which event garnered the more eyeballs; that should tell us the direction the sport is taking. In The Australian, Gideon Haigh wrote a piece headlined: IPL auction now the real centre of world cricket.

A union minister tweeted that most players didn’t deserve half the amounts they were bought for. Politicians are allergic to such transparent contract negotiations. However, what he and others find difficult to deal with is the fact that the market decides value. And the market can be cruel and ageist, often casually dispensing with high-performing players of the past. It is influenced by the ego of the bidder too. Monetary value is not always the same as cricketing worth.

Part of the confusion is caused by top players going unsold. In the recent Test, Amla and Ishant Sharma put in inspiring performances, yet find themselves with no role in the IPL. The way to reconcile this is to acknowledge that IPL and Test cricket are as different from each other — tactically, physically, psychologically, emotionally — as soccer and cricket or kabaddi and tennis. They just happen to use the same equipment.

It took the franchises some time to realise this. The inaugural auction had nothing to go by and established Test players were most sought after. Royal Challengers had Rahul Dravid, Jacques Kallis, Wasim Jaffer, Shivnarine Chanderpaul. Today they would have to depend on pity-selection by friends in the franchises, if at all. Cricket has changed, the IPL most of all, and auctions, even if not fully professional yet are headed in that direction. Data is king. How good are you between overs 11 and 16, for example?