Monday, 20 November 2017

The rise of dynamic and personalised pricing

Tim Walker in The Guardian

You wait 24 hours to book that flight, only to find it’s gone up by £100. You wait until Black Friday to buy that leather jacket and, sure enough, it’s been marked down. Today’s consumers are getting comfortable with the idea that prices online can fluctuate, not just at sale time, but several times over the course of a single day. Anyone who has booked a holiday on the internet is familiar with the concept, if not with its name. It’s known as dynamic pricing: when the cost of goods or services ebbs and flows in response to the slightest shifts in supply and demand, be it fresh croissants in the morning, a bargain TV or an Uber during a late-night “surge”.

Sports teams, entertainment venues and theme parks have started to use dynamic pricing methods, too, taking their cues from airlines and hotels to calibrate a range of ticketing deals that ensure they fill as many seats as possible. Last month, Regal, the US cinema chain, announced it would trial a form of dynamic ticket pricing at many of its multiplexes in 2018, in the hope of boosting its box office revenue. Digonex, one of the leading dynamic ticketing firms in the US, has consulted for Derby County and Manchester City football clubs in the UK. “In five years, dynamic pricing will be common practice in the attractions space,” says the company’s CEO, Greg Loewen. “The same goes for many other industries: movies, parking, tour operators.” Amazon, the world’s largest online retailer, tweaks countless prices every day. Savvy shoppers have learned to wait for bargains with the help of other sites such as, which analyses Amazon price drops and lists the biggest. On a single day on last week, those included a Samsung Galaxy S7 phone, down 14% from £510.29 to £439, and a pack of six 300g jars of Ovaltine, down 33% from £17.94 to £12.

Physical retailers can’t match the agility of their online rivals, not least because changing prices requires altering labels. But “smart shelves” – already common in European supermarkets – are coming to the UK, with digital price displays that allow retailers to offer deals at different times of day, along with information about the products. Sainsbury’s, Morrisons and Tesco have all trialled electronic pricing systems in select stores. Marks & Spencer conducted an electronic pricing experiment last year, selling sandwiches more cheaply during the morning rush hour to encourage commuters to buy their lunch early.

Toby Pickard, senior innovations and trends analyst at the grocery research firm IGD, says this new technology will benefit retailers by enabling them “to gain more data about the products they sell; for example, they can closely gauge how prices fluctuating throughout the day may alter shoppers’ purchasing habits, or if on-shelf digital product reviews increase sales.” IGD’s research suggests there is an appetite for this sort of tech from consumers, too. For example, says Pickard: “Four in 10 shoppers say they are interested in being alerted to offers on their phone while in-store.”

FacebookTwitterPinterest M&S experimented with pricing to encourage commuters to buy their lunch early. Photograph: Luke Johnson/Commissioned for The Guardian

Earlier this year, the Luxembourg-based computer firm SES took a majority stake in the Irish software firm MarketHub. Together, they are bringing data analysis and smart-shelf-style systems to some 14,000 stores in 54 countries including the UK. MarketHub says two Spar stores in London have succeeded in raising revenue and decreasing waste since introducing its technology. For the firm’s CEO Roy Horgan, though, there’s a big difference between what MarketHub offers and dynamic pricing per se. “I don’t see dynamic pricing happening in major retailers,” he says. “Supermarkets have huge, complicated logistics systems. They can’t react in real time to what’s going in their stores the way Amazon can. [Physical retailers] want to discount, to have more relevant deals, fewer promotions, better value and more customer loyalty. That’s not about changing the price of individual products, it’s more about changing deals.”

As examples, Horgan suggests offering cheap lunch deals in the morning (à la M&S), so that workers don’t have to queue up at lunchtime, or guiding shoppers with limited budgets to discounted ingredients for an evening meal. “That’s not dynamic pricing,” he says. “It’s just agile retail.”

A recent survey of US consumers by Retail Systems Research (RSR) found that 71% didn’t care for the idea of dynamic pricing, though millennials were more amenable to the concept, with 14% of younger shoppers saying they “loved” it. Perhaps that ought not to be surprising, given the younger generation’s greater familiarity with browsing for bargains online.

“Consumers always love it when they can get a great deal, and dynamic pricing isn’t just about raising prices – it often leads to lowering them,” says Loewen. “In general, we have found that when prices are transparent to consumers and they understand the ‘rules of the game’, they adapt to dynamic pricing fairly seamlessly and even embrace it.”

Simon Read, a money and personal finance writer, says: “If you’re desperate for an item and it’s the last available, you are likely to pay a premium when dynamic pricing comes into play.” But dynamic pricing can also play to the consumer’s benefit, he explains.

“The truth is that retailers want to flog their wares at whatever price they can get. If you want to take advantage of dynamic pricing, you’ll need to find out when retailers are desperate to sell. In bricks-and-mortar stores that means shopping at quiet times – in the morning – or waiting until closing time when grocers need to clear their shelves.” If you’re shopping online, Read says, research the normal price of an item before buying it, so as not to be caught out. “It’s also a good idea to leave things in your shopping basket at most online retailers rather than buying immediately. After a day or two, you will often get an email offering a decent reduction.”

Those consumers who are suspicious of dynamic pricing may also be confusing it with (the far more controversial) personalised pricing, whereby specific customers are asked to pay different amounts for the same product, tailored to what the retailer thinks they can and will spend – using personal data points that might one day include, for instance, our credit rating. In 2014, the US Department of Transportation approved a system allowing airlines and travel companies to collect passengers’ data to present them with “personalised offerings” based on their address, their marital status, their birthday and their travel history. It’s not hard to imagine that the fares you are offered might be higher than for others if, say, you live in an affluent postcode and your husband’s birthday is coming up.

 Airlines use dynamic pricing on flight tickets. Photograph: Easyjet

In 2012, the travel site Orbitz was found to be adjusting its prices for users of Apple Mac computers, after finding that they were prepared to spend up to 30% more on hotel rooms than other customers. That same year, the Wall Street Journal revealed that the Staples website offered products at different pricesdepending on the user’s proximity to rival stores. In 2014, a study conducted by Northeastern University in Boston found that several major e-commerce sites such as Home Depot and Walmart were manipulating prices based on the browsing history of individual customers. “Most people assume the internet is a neutral environment like the high street, where the price you see is the same as the one everyone else sees,” says Ariel Ezrachi, director of the University of Oxford Centre for Competition Law and Policy. “But on the high street you’re anonymous; online, the seller has information about you, and about your other buying options.”

Dynamic pricing, says Ezrachi, is simply a way for businesses to respond nimbly to market trends, and thus is within the bounds of what consumers already accept as market dynamics. “Personalised pricing is much more problematic. It’s based on asymmetricity of information; it’s only possible because the shopper doesn’t know what information the seller has about them, and because the seller is able to create an environment where the shopper believes they are seeing the market price.”

The ethics of pricing based on an individual’s personal data are vexed: some consumers will find it manipulative and insist on its regulation; others may feel it’s fair – socially beneficial, even – to charge wealthy customers more for a product or service. “You will find people arguing in different directions,” Ezrachi says. Loyalty cards have long enabled supermarkets and other major retailers to offer personalised offers based on the spending habits of repeat customers. B&Q has tested electronic price tags that display different prices to different customers using information gleaned from their phones (the company made clear that their intention was to “reward regular customers with discounts”, not to raise the price for more profligate shoppers). In the US, Coca-Cola and Albertsons supermarkets have experimented with targeting shoppers in-store by sending personalised offers to their phones when they approach the soft drinks aisle in an Albertsons store.

Horgan resists the idea that supermarkets will embrace personalised pricing. “In the airline industry, we have more freedom, information and choice on airlines than we’ve ever had before, and that is all dynamic-pricing led. But nobody’s loyal to Ryanair; they’re loyal to the deal. Retail is different,” he says. “If I have five pounds in my pocket and a family of four to feed, I want to know I can generate a recipe that is nutritious for them, and I want an app that can navigate me around the store to find a deal on [the necessary ingredients]. To me, that is personalised retail. But any [bricks and mortar] retailer who charges different prices to different people for the same product is an idiot. They’re only going to lose loyalty.”

Loewen agrees that personalised pricing carries as many dangers as opportunities for retailers. “Consumers are more empowered and informed than ever before, and any pricing strategy that seeks to fool or mislead them is unlikely to be successful for long,” he says. Nevertheless, in the dawning era of dynamic pricing, personalised pricing and agile retailing, the days of fixed prices seem to be coming to an end. And although the technology may be more advanced, in some ways dynamic pricing is simply a return to the days long before supermarkets, when traders would judge how high or low a price to haggle from a customer based on factors as simple as the sound of their accent, or the cut of their cloak.

Sunday, 19 November 2017

This is redistribution for Zimbabwe’s elite, not revolution in a ruined nation

Jason Burke in The Guardian

Drive any distance anywhere in Zimbabwe beyond the upmarket Borrowdale neighbourhood in Harare, where Robert Mugabe and his wife Grace are detained in their sprawling mansion, and the scale of the challenges facing what was once one of the wealthiest countries in Africa is evident.

In the capital, the roads are potholed, outside they are cracked and crumbling. Banks are so short of cash that people wait hours to withdraw even tiny sums. The only jobs are in government service, yet salaries are rarely paid. The best and the brightest have long fled abroad. Warehouses are empty, fields lie fallow. The busiest store in rural villages is the “bottle shop”, selling dirt-cheap spirits.

Zimbabwe has famously abundant natural resources but resuscitating the economy after 20 years of disastrous mismanagement and wholesale looting by corrupt officials is a major undertaking. The banking system needs to be rebooted, faith restored in the national currency and government finances somehow replenished. The vast debts incurred by Mugabe’s regime need to be rescheduled or waived and new funding arranged to rebuild the country’s shattered infrastructure.

Investors have long been interested in Zimbabwe but put off by the significant risk that any funds will be stolen or any successful venture appropriated. Can they now be sure that will not happen? Old habits die hard.

The ruling Zanu-PF party and allies in the military launched their takeover to purge an ambitious faction that threatened their position, not because they wanted to see structural reform that would shut down their own lucrative rackets and rent-seeking.

There are immediate practical problems, too. The police are seen as creatures of Mugabe by the military and allies, but someone needs to patrol the streets. There is the fate of Comrade Bob and Grace, when they are no longer president and first lady, to decide. There is a government to form, possible elections to hold.

It is this political process that poses the greatest challenge. The people of Zimbabwe have high hopes of a new democratic era. But the ousting of Mugabe was a redistribution of power within the ruling elite of Zimbabwe, not a people’s revolution.

Emmerson Mnangagwa, the ousted vice-president, who is most likely to succeed Mugabe when he finally leaves power, is no committed democrat. He was Mugabe’s chief enforcer, with a long history of human rights abuse. Mnangagwa, 75, will need to make some concessions to public opinion within Zimbabwe and the hopes of the international community, not least to get the donor and diaspora money the country so desperately needs. However, he will seek to do this while reinforcing, not weakening, the grip of the party.

But how long will Zimbabweans tolerate the rule of a clique of septuagenarian veterans of an armed struggle that took place before most of the population was born?

A similar question has been asked elsewhere in Africa over recent decades. It is being asked today in neighbouring South Africa, where the lustre of the African National Congress has steadily diminished over its 23 years in power.

The eventual demise of parties like Zanu-PF is inevitable. But so, too, is the trauma that accompanies their passing.

Saturday, 18 November 2017

Subramanian Swamy on his legal journey

Income inequality in India

Varsha Kulkarni and Raghav Gaiha in The Hindu

With the Gujarat State elections barely a few weeks away, the debate on the Indian economy has become increasingly polarised. While the official view of demonetisation unleashed in November 2016 elevates it to a moral and ethical imperative, the chaos caused by the goods and services tax (GST) launched on July 1, 2017, is dismissed as a short-run transitional hiccup. Both policies, it is asserted, are guaranteed to yield long-term benefits, unmindful of large-scale hardships, loss of livelihoods, closure of small and medium enterprises and slowdown of agriculture. Critics of course reject these claims lock, stock and barrel. Lack of robust evidence is as much a problem for the official proponents of these policies as it is for the critics. Hence the debate continues unabated with frequent hostile overtones.

Tracking income inequality

Beneath the debate are deep questions of inequality and its association with poverty. Thomas Piketty produced a monumental treatise, Capital in the Twenty-First Century, demonstrating that rising income inequality is a by-product of growth in the developed world. More recently, Lucas Chancel and Piketty (2017), in ‘Indian income inequality, 1922-2014: From British Raj to Billionaire Raj?’, offer a rich and unique description of evolution of income inequality in terms of income shares and incomes in the bottom 50%, the middle 40% and top 10% (as well as top 1%, 0.1%, and 0.001%), combining household survey data, tax returns and other specialised surveys.

Some of the principal findings are: one, the share of national income accruing to the top 1% income earners is now at its highest level since the launch of the Indian Income Tax Act in 1922. The top 1% of earners captured less than 21% of total income in the late 1930s, before dropping to 6% in the early 1980s and rising to 22% today. Two, over the 1951-1980 period, the bottom 50% captured 28% of total growth and incomes of this group grew faster than the average, while the top 0.1% incomes decreased. Three, over the 1980-2014 period, the situation was reversed; the top 0.1% of earners captured a higher share of total growth than the bottom 50% (12% v. 11%), while the top 1% received a higher share of total growth than the middle 40% (29% v. 23%).

True to its modest objective, it offers a rich and insightful description of how income distribution, especially in the upper tail, and inequality have evolved.

Sharp reduction in the top marginal tax rate, and transition to a more pro-business environment had a positive impact on top incomes, in line with rent-seeking behaviour.

India’s wealth gain

According to Credit Suisse Global Wealth Report 2017, the number of millionaires in India is expected to reach 3,72,000 while the total household income is likely to grow by 7.5% annually to touch $7.1 trillion by 2022. Since 2000, wealth in India has grown at 9.2% per annum, faster than the global average of 6% even after taking into account population growth of 2.2% annually. However, not everyone has shared the rapid growth of wealth.

Our research, based on the India Human Development Survey 2005-12, focusses on a detailed disaggregation of income inequality, along the lines of Chancel and Piketty, recognising that incomes in the upper tail are under-reported; and examines the links between poverty and income inequality, especially in the upper tail, state affluence, and prices of cereals.

Our analysis points to a rise in income inequality. A high Gini coefficient of per capita income distribution, a widely used measure of income inequality, in 2005 became higher in 2012. The share of the bottom 50% fell while those of the top 5% and top 1% rose. The gap between the share of the top 1% and the bottom 50% narrowed considerably.

More glaring is the disparity in ratios of per capita income of the top 1% and bottom 50%. The ratio shot up from 27 in 2005 to 39 in 2012. Far more glaring is the disparity in the highest incomes in these percentiles. The ratio of highest income in the top 1% to that of the bottom 50% nearly doubled, from a high of 175 to 346.

All poverty indices including the head-count ratio fell but slightly.

Poverty and inequality

Higher incomes reduced poverty substantially. Inequality measured in terms of share of income of the top 10% increased poverty sharply but only in the more affluent States. Somewhat surprisingly, higher cereal prices did not have a significant positive effect on poverty. Similar results are obtained if the share of the top 10% is replaced with the Gini coefficient as a measure of inequality.

It is plausible that poverty reduction slowed in 2016-17 because of deceleration of income growth; and huge shocks of demonetisation and the GST to the informal sector have aggravated income inequality. Indeed, depending on the magnitudes of these shocks, poverty could have risen during this period.

In sum, regardless of the longer-term outlook and presumed but dubious benefits of the policy shocks, the immiseration of large segments of the Indian population was avoidable.

Friday, 17 November 2017

Are our dreams trying to tell us something – or should we sleep on it?

Oliver Burkeman in The Guardian

What are dreams for? It’s one of those bottomless questions where the answer tells you mainly about the person doing the answering. Those who pride themselves on being hard-headed and scientific will say they’re meaningless nonsense or, at best, some kind of boring but essential process for consolidating the memories of the day. Those who think of themselves as spiritual, meanwhile, will insist they’re messages from beyond. Yet the hard-headed answer isn’t much more plausible than the kooky one. If dreams are random brain-firings, how come they have coherent narratives? And if they’re just a dull retread of everyday events, how come they’re so often wildly inventive, haunting or surreal? (Don’t worry, I won’t bore you with any of my own, though the famous fact that “nothing is more boring than other people’s dreams” is, in itself, rather interesting.) As James Hollis, a Jungian psychotherapist for whom dreams are far from meaningless, writes: “Who would make this stuff up?” Night after night, you go to bed and elaborately crazy stories plant themselves in your mind through no choice of your own! Don’t tell me something intriguing isn’t going on.

Dreams are hard to study in the lab, for the obvious reason that only you experience your own. Indeed, as the philosopher Daniel Dennett points out, you can’t even be certain you experience them, at least in the way you imagine. You “recall” them when you wake, but how do you know that memory wasn’t inserted into your mind at the moment of waking? Yet recent work by researchers including Matthew Walker, author of the new book Why We Sleep, strongly suggests dreams are a kind of “overnight therapy”: in REM sleep, we get to reprocess emotionally trying experiences, but without the presence of the anxiety-inducing neurotransmitter noradrenaline. In experiments, people exposed to emotional images reacted much more calmly to seeing them again after a good night’s dreaming. Neither dreamless sleep nor the mere passage of time duplicated that effect.

Carl Jung certainly wouldn’t have settled for that explanation, though. He argued– I’m simplifying here – that dreams were messages from the unconscious, offering, in symbolic form, insights and advice the conscious mind might have missed. That dream where you’re careening down a slope in a runaway shopping trolley towards a cliff edge: what might that be saying about how you need to change? So you wrote down a dream, then studied it, with or without a therapist, trying out different interpretations, and if one rang true – if it gave you goosebumps or triggered strong emotions – you pursued it further. What’s striking, you may have noticed, is that this approach would work even if Jung were wrong, and dreams were just random. If you treat them as potentially meaningful, retaining only those interpretations that really “click”, you’re going to end up with meaningful insights anyway. I’ve dabbled in this, and highly recommend it. To ask what your dreams might be trying to tell you is to ask deep and difficult questions you’d otherwise avoid – even if, in reality, they weren’t trying to tell you anything at all.

Yanis Varoufakis on Catalonia, Muslim Ban and a Sustainable World Order

Thursday, 16 November 2017

UK GDP - The measurement that holds economic statistics back from reality

Diane Coyle in The FT

It is faintly surprising that one of the liveliest areas of economics these days is the question of measurement, and what relation published statistics bear to what is happening in the economy. Statistics do not usually inspire excitement. 

This attention reflects the convergence of two strands of scepticism about the existing statistics, and in particular gross domestic product. One is the “productivity puzzle” and to what extent the mis-measurement of digital phenomena helps explain the slow rate of productivity growth. The other is the longstanding critique of GDP as a meaningful measure of progress, for reasons of environmental sustainability or other contributors to society’s wellbeing. 

The two converge on the distinction between the aggregate amount of marketed economic activity and total economic welfare. The conventional statement about GDP is that it is only meant to count the former, not the latter. GDP does not capture environmental factors or consider income distribution. But as long as that gap has been roughly constant, GDP growth has been a good enough measure of improvement in economic welfare. 

Perhaps the wedge between total marketed economic activity and welfare is increasing because of the pace of technological change, but statistics have never captured the human gains from advances in periods of innovation, whether in medicines or the internet. 

This case for the defence of GDP is fundamentally weak, however. It in fact includes many non-marketed activities, yet excludes other productive activity. Business and government count as “the economy” but voluntary and household activities do not. 

Postwar social changes — a rising proportion of women working outside the home, and the increased purchases of prepared foods, professional childcare, domestic appliances and so on — have flattered the official productivity statistics for decades. 

More subtly, the statistics blur the distinction between marketed economic activity and increases in economic welfare that cannot be priced by converting nominal GDP into “real” terms. 

Economists and statisticians are beginning to accept that our framework for economic statistics needs to change. Some argue for developing better “satellite” accounts, where all the interesting data about the environment or the household are collated. But why should all the pressing questions be satellites? 

GDP could certainly be improved. In one of the joint winners of the Indigo Prize essay competition, a team led by Carol Corrado and Jonathan Haskel, proposed better measurement of services and intangibles, and direct measurement of the economic welfare being created by digital goods. The other winning essay — which I co-authored with Benjamin Mitra-Kahn — proposed similar incremental changes as an interim step. 

We opted for better measurement of intangibles, adjusting for the distribution of income, and removing unproductive financial activity. The long-term recommendation was more radical: ditching GDP as the metric of progress in favour of measures of access to different kinds of assets, including financial wealth but also natural capital, intangible assets, infrastructure and human and social capital. 

This was inspired by Amartya Sen’s idea that prosperity consists in people having the capabilities needed to lead the life they would find meaningful; and by the need to get away from measuring economic progress only through the short-term flow of activity. There is no sustainability without a balance sheet. 

Perhaps neither the incremental nor the radical is the right approach. Reform will take time because there needs to be consensus about how to change; statistical standards are like technical standards. But I am now confident that in another 10 or 20 years GDP will have been dethroned.