Big Mac Index 2018

The Economist’s Big Mac index gives a flavour of how far currency values are out of whack. It is based on the idea of purchasing-power parity, which says exchange rates should move towards the level that would make the price of a basket of goods the same everywhere. Our basket contains only one item, but it is found in around 120 countries: a Big Mac hamburger.

If the local cost of a Big Mac converted into dollars is above $5.28, the price in America , a currency is dear; if it is below the benchmark, it is cheap. The average cost of a Big Mac in the euro area is €3.95, or $4.84 at the current exchange rate. That implies the euro is undervalued by 8.4% against the dollar.

THE Big Mac index was invented by The Economist in 1986 as a lighthearted guide to whether currencies are at their “correct” level. It is based on the theory of purchasing-power parity (PPP), the notion that in the long run exchange rates should move towards the rate that would equalise the prices of an identical basket of goods and services (in this case, a burger) in any two countries. For example, the average price of a Big Mac in America in January 2018 was $5.28; in China it was only $3.17 at market exchange rates. So the “raw” Big Mac index says that the yuan was undervalued by 40% at that time.

Burgernomics was never intended as a precise gauge of currency misalignment, merely a tool to make exchange-rate theory more digestible. Yet the Big Mac index has become a global standard, included in several economic textbooks and the subject of at least 20 academic studies. For those who take their fast food more seriously, we have also calculated a gourmet version of the index.

This adjusted index addresses the criticism that you would expect average burger prices to be cheaper in poor countries than in rich ones because labour costs are lower. PPP signals where exchange rates should be heading in the long run, as a country like China gets richer, but it says little about today’s equilibrium rate. The relationship between prices and GDP per person may be a better guide to the current fair value of a currency. The adjusted index uses the “line of best fit” between Big Mac prices and GDP per person for 48 countries (plus the euro area). The difference between the price predicted by the red line for each country, given its income per person, and its actual price gives a supersized measure of currency under- and over-valuation.

Link to the Interactive Currency-Comparison.

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What to do about China’s “sharp power”

China is manipulating decision-makers in Western democracies. The best defence is transparency

WHEN a rising power challenges an incumbent one, war often follows. That prospect, known as the Thucydides trap after the Greek historian who first described it, looms over relations between China and the West, particularly America. So, increasingly, does a more insidious confrontation. Even if China does not seek to conquer foreign lands, many people fear that it seeks to conquer foreign minds.

Australia was the first to raise a red flag about China’s tactics. On December 5th allegations that China has been interfering in Australian politics, universities and publishing led the government to propose new laws to tackle “unprecedented and increasingly sophisticated” foreign efforts to influence lawmakers (see article). This week an Australian senator resigned over accusations that, as an opposition spokesman, he took money from China and argued its corner. Britain, Canada and New Zealand are also beginning to raise the alarm. On December 10th Germany accused China of trying to groom politicians and bureaucrats. And on December 13th Congress held hearings on China’s growing influence.

This behaviour has a name—“sharp power”, coined by the National Endowment for Democracy, a Washington-based think-tank. “Soft power” harnesses the allure of culture and values to add to a country’s strength; sharp power helps authoritarian regimes coerce and manipulate opinion abroad.

The West needs to respond to China’s behaviour, but it cannot simply throw up the barricades. Unlike the old Soviet Union, China is part of the world economy. Instead, in an era when statesmanship is in short supply, the West needs to find a statesmanlike middle ground. That starts with an understanding of sharp power and how it works.

China has a history of spying on its diaspora, but the subversion has spread. In Australia and New Zealand Chinese money is alleged to have bought influence in politics, with party donations or payments to individual politicians. This week’s complaint from German intelligence said that China was using the LinkedIn business network to ensnare politicians and government officials, by having people posing as recruiters and think-tankers and offering free trips.

Bullying has also taken on a new menace. Sometimes the message is blatant, as when China punished Norway economically for awarding a Nobel peace prize to a Chinese pro-democracy activist. More often, as when critics of China are not included in speaker line-ups at conferences, or academics avoid study of topics that China deems sensitive, individual cases seem small and the role of officials is hard to prove. But the effect can be grave. Western professors have been pressed to recant. Foreign researchers may lose access to Chinese archives. Policymakers may find that China experts in their own countries are too ill-informed to help them.

To ensure China’s rise is peaceful, the West needs to make room for China’s ambition. But that does not mean anything goes. Open societies ignore China’s sharp power at their peril.

Part of their defence should be practical. Counter-intelligence, the law and an independent media are the best protection against subversion. All three need Chinese speakers who grasp the connection between politics and commerce in China. The Chinese Communist Party suppresses free expression, open debate and independent thought to cement its control. Merely shedding light on its sharp tactics—and shaming kowtowers—would go a long way towards blunting them.

Read the complete article on The Economist magazine web site.

A prosecutor of Klansmen captures Jeff Sessions’s old seat, as the Republicans’ Senate majority shrinks

Roy Moore watching results

INITIALLY the mood at Doug Jones’s election-night party was genial but uneasy. Guests knew Mr Jones was closer to winning one of Alabama’s Senate seats than any Democrat in a quarter-century; they also knew that Mr Trump won the state by 28 points, and the last two Republican Senate candidates won 63.9% and 97.3% of the vote. So they smiled, and made all the right hopeful noises, but around the corners of their eyes you could see them bracing for disappointment.

Mr Jones’s victory was narrow—he took 49.9% of the vote to Mr Moore’s 48.4%, with the remaining 1.7% going to write-in votes—but decisive. He flipped every one of the counties that Mr Trump won by 10 points or less last year, banking large numbers of votes in the counties housing Alabama’s five biggest cities, and running up sizable margins in Alabama’s majority African-American “black belt”.  Mr Moore, meanwhile, underperformed Mr Trump’s results from November 2016 in every one of Alabama’s 67 counties, faring especially poorly in those with large numbers of educated voters.

At a rally in south-eastern Alabama the night before the election, Steve Bannon, Mr Trump’s former chief strategist and the architect of his presidential campaign, headlined a motley crew of far-right Republicans who offered a cavalcade of bilious, resentment-filled speeches promoting Mr Moore while pandering to Alabamians’ prickliness. “Nobody comes down here and tells Alabamians what to do,” said Mr Bannon, a Virginian, speaking after a Texan and several Midwesterners. Other speakers attacked George Soros, Islam and “the lynch-mob media”. No name got longer and more sustained boos than Mr Shelby’s. Two days before the election he went on a prominent talk show just to say, “I wouldn’t vote for Roy Moore…The state of Alabama deserves better.” Mr Moore’s wife defended her husband against charges of bigotry by revealing that “one of our attorneys is a Jew.”

White evangelicals—Mr Moore’s core supporters—comprised a smaller share of the electorate this year than in past elections. Some of them stayed home, or even voted for Mr Jones, despite vehemently disagreeing with his pro-choice position on abortion. Rushton Mellen Waltchack, a Christian and lifelong Republican from Birmingham, compared Mr Moore to “a televangelist who falls from grace,” and said she could not bring herself to vote for him. “He makes statements that to me don’t represent Jesus in the Bible…What does it say about us as a party if we continue to choose policy over character?”

Read the complete article on The Economist magazine web site.

Donald Trump’s big test in 2018 – The Economist video

The ninth in The Economist series of films previewing some of the big themes of 2018 considers America’s mid-term elections. A bad result for Donald Trump could lead to his impeachment. Can he unite and rally Republican voters?

How bookmakers deal with winning customers

888, an online betting firm, was fined a record £7.8m ($10.3m) in August after more than 7,000 customers who had chosen to ban themselves from their betting accounts were allowed to retain access. Yet away from the regulator’s gaze, bookies often stand accused of the opposite excess: being too prompt to shun winning customers. Successful bettors complain that their accounts get closed down for what are sometimes described as business decisions. Others say their wagers get capped overnight to minuscule amounts. The move may be unpopular with punters, but in most parts of the world it is legal.

Operators say scrutinising winners is necessary to help prevent fraud. Competition in the gambling industry increased with the arrival of online betting, prompting bookmakers to offer odds on markets they did not previously cover. In some, such as Eastern European football leagues, low wages and late payments make fertile ground for match-fixing. A winning streak at the windows can signal foul play. Most often, however, efforts to spot savvy customers are not rooted in a desire to thwart dodgy schemes. Rather, they are part of what industry insiders call “risk management”: to remain profitable, bookies seek to cap potential losses. As one betting consultant puts it, “Bookmakers close unprofitable accounts, just as insurance companies will not cover houses that are prone to flooding.” Betting outlets get to know their customers by gleaning information online, tracking web habits and checking whether punters visit odds-comparison sites. Profiling has also been made easier by the tightening of anti-money laundering regulations, which require online punters to provide detailed information when opening accounts.

Professional gamblers rarely do business with high-street bookmakers. They often place their trades on betting exchanges like Betfair or Smarkets, which do not restrict winning customers (though Betfair charges a premium to some of its most successful users). Alternatively they work with those bookmakers who use successful gamblers to improve the efficiency of their betting markets, and make most of their money on commission. These profess not to limit winning accounts and accept much bigger bets (Pinnacle, an influential bookie, often has a $1m limit for major events). Betting professionals also sneak in big trades via brokers, like Gambit Research, a British operation that uses technology to place multiple smaller bets with a range of bookmakers. Asian agents, in particular, have made their names in that trade: many are able to channel sizeable bets to local bookies anonymously. Unlike the sports they love, the games played by professional gamblers and bookmakers are kept out of the spotlight.

Sources: The Economist magazine web site.

 

Active fund managers have had a good 12 months, but a terrible ten years

coin flip

When it comes to choosing an index-tracking, or passive fund management, investment a lot of people choose a manager who tries to beat the market by picking the best stocks, because that sounds like a great idea.

The tricky bit is finding the right manager. The temptation is to look at past performance but fund managers rarely beat the market for long.

The average fund manager is always going to struggle to beat the market (this is a separate argument from whether markets are “efficient”). That is because the index reflects the performance of the average investor before costs. In a world dominated by professional fund managers, there aren’t enough amateurs for the professionals to beat. Even the hedge funds, those supposed “masters of the universe”, haven’t been able to do it; Warren Buffett looks set to win a $1m bet on the issue.

The table, from Standard & Poor’s, shows how many European-domiciled funds (investing in a wide range of markets) have managed to beat the market over one, three, five and 10 years. Eight out of 19 categories managed the feat over one year, but that drops to four categories over three years, three over five years and none over 10 years. In most categories over 10 years, you had a less than one-in-five chance of finding a fund that beat the market.

The Economist fund table

So why do so many people think they can pick a winner? The answer may be found in a new paper from James White, Jeff Rosenbluth and Victor Haghani of Elm Partners that shows people find it very difficult to tell skill from luck. Suppose you have two coins, one fair and the other biased 60% in favour of heads. How many parallel tosses would you need to be 95% certain (statistically speaking) of identifying the rigged coin? They asked 700 financial professionals the question and their median guess was 40. The actual answer is 143.  If you widen the experiment to three coins, the number rises to 220.

The authors then use a thought experiment, which assumes that 15% of fund managers can generate a post-fee return of 1% a year relative to the market while the other 85% lose 1%. They put 1% of the portfolio a year into each fund and then shift more to the winners each year, based on the probability that they can continue to outperform. Even after 10 years, the expected return on this portfolio is -0.6% a year, relative to the index.

Read the complete article on The Economist web site.

What machines can tell from your face

machine facial recognition on punzhu puzzles

We are now living our lives in the age of facial recognition, and each new technology comes with its own pro’s and con’s.

THE human face is a remarkable piece of work. The astonishing variety of facial features helps people recognise each other and is crucial to the formation of complex societies. So is the face’s ability to send emotional signals, whether through an involuntary blush or the artifice of a false smile. People spend much of their waking lives, in the office and the courtroom as well as the bar and the bedroom, reading faces, for signs of attraction, hostility, trust and deceit. They also spend plenty of time trying to dissimulate.

Technology is rapidly catching up with the human ability to read faces. In America facial recognition is used by churches to track worshippers’ attendance; in Britain, by retailers to spot past shoplifters. This year Welsh police used it to arrest a suspect outside a football game. In China it verifies the identities of ride-hailing drivers, permits tourists to enter attractions and lets people pay for things with a smile. Apple’s new iPhone is expected to use it to unlock the homescreen (see article).

Set against human skills, such applications might seem incremental. Some breakthroughs, such as flight or the internet, obviously transform human abilities; facial recognition seems merely to encode them. Although faces are peculiar to individuals, they are also public, so technology does not, at first sight, intrude on something that is private. And yet the ability to record, store and analyse images of faces cheaply, quickly and on a vast scale promises one day to bring about fundamental changes to notions of privacy, fairness and trust.

The final frontier

Start with privacy. One big difference between faces and other biometric data, such as fingerprints, is that they work at a distance. Anyone with a phone can take a picture for facial-recognition programs to use. FindFace, an app in Russia, compares snaps of strangers with pictures on VKontakte, a social network, and can identify people with a 70% accuracy rate. Facebook’s bank of facial images cannot be scraped by others, but the Silicon Valley giant could obtain pictures of visitors to a car showroom, say, and later use facial recognition to serve them ads for cars. Even if private firms are unable to join the dots between images and identity, the state often can. China’s government keeps a record of its citizens’ faces; photographs of half of America’s adult population are stored in databases that can be used by the FBI. Law-enforcement agencies now have a powerful weapon in their ability to track criminals, but at enormous potential cost to citizens’ privacy.

The face is not just a name-tag. It displays a lot of other information—and machines can read that, too. Again, that promises benefits. Some firms are analysing faces to provide automated diagnoses of rare genetic conditions, such as Hajdu-Cheney syndrome, far earlier than would otherwise be possible. Systems that measure emotion may give autistic people a grasp of social signals they find elusive. But the technology also threatens. Researchers at Stanford University have demonstrated that, when shown pictures of one gay man, and one straight man, the algorithm could attribute their sexuality correctly 81% of the time. Humans managed only 61% (see article). In countries where homosexuality is a crime, software which promises to infer sexuality from a face is an alarming prospect.

Keys, wallet, balaclava

Less violent forms of discrimination could also become common. Employers can already act on their prejudices to deny people a job. But facial recognition could make such bias routine, enabling firms to filter all job applications for ethnicity and signs of intelligence and sexuality. Nightclubs and sports grounds may face pressure to protect people by scanning entrants’ faces for the threat of violence—even though, owing to the nature of machine-learning, all facial-recognition systems inevitably deal in probabilities. Moreover, such systems may be biased against those who do not have white skin, since algorithms trained on data sets of mostly white faces do not work well with different ethnicities. Such biases have cropped up in automated assessments used to inform courts’ decisions about bail and sentencing.

Eventually, continuous facial recording and gadgets that paint computerised data onto the real world might change the texture of social interactions. Dissembling helps grease the wheels of daily life. If your partner can spot every suppressed yawn, and your boss every grimace of irritation, marriages and working relationships will be more truthful, but less harmonious. The basis of social interactions might change, too, from a set of commitments founded on trust to calculations of risk and reward derived from the information a computer attaches to someone’s face. Relationships might become more rational, but also more transactional.

In democracies, at least, legislation can help alter the balance of good and bad outcomes. European regulators have embedded a set of principles in forthcoming data-protection regulation, decreeing that biometric information, which would include “faceprints”, belongs to its owner and that its use requires consent—so that, in Europe, unlike America, Facebook could not just sell ads to those car-showroom visitors. Laws against discrimination can be applied to an employer screening candidates’ images. Suppliers of commercial face-recognition systems might submit to audits, to demonstrate that their systems are not propagating bias unintentionally. Firms that use such technologies should be held accountable.

Read the complete article on The Economist magazine web site.