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How finance evolves

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Evolve

Why is it that stock markets tend to be depressed during winter months? Or that investors with too little emotional response (or too much) tend to be less profitable than those with just the right amount of emotion? Or that traders tend to make more money on days when their levels of testosterone are higher than average?

In a fascinating new book, Andrew Lo builds on the corpus of behavioural science research to outline a new theory of financial markets. His basic point: homo economicus is dead. The hyper-rational human that always optimized every decision, most famously portrayed in the Efficient Markets Hypothesis of Eugene Fama that has ruled the field of finance at least since the 1980s, does not exist. His new book, Adaptive Markets: Financial Evolution at the Speed of Thought, explicates his Adaptive Markets Hypothesis, first proposed in 2004 as a substitute for the Efficient Markets Hypothesis.

In short, the Adaptive Markets Hypothesis accepts that humans are biological beings, and that our biology limits our ability to optimize every decision as the Efficient Markets Hypothesis predicts. Most importantly, though, our ‘irrationality’ is not random. This means that we consistently make the same ‘mistakes’, something that behavioural scientists have known for quite some time. One of these mistakes, for example, is that we often link events together because they happen to occur close to each other. As Lo puts it: ‘We humans are not so much the “rational animal” as we are the rationalizing animal. We interpret the world not in terms of objects and events, but in sequences of objects and events, preferably leading to some conclusion, as they do in a story.’

Telling stories is one way we try to make sense of the world, even if those stories are sometimes false. We do this because, given the environments that we encountered, this was the most evolutionary successful behaviour. But that has consequences: If our environment change, our biological decision-making processes might not be equipped to deal with the new environment. In Lo’s words: ‘“Rational” responses by homo sapiens to physical threats on the plains of the African savannah may not be effective in dealing with financial threats on the floor of the New York Stock Exchange’.

Often the real world is not very different from the survival-of-the-fittest world our ancestors encountered on the African plains. Many times, humans do optimize their behaviour. This is why the Efficient Markets Hypothesis could hold for so long, treating ‘irrational’ behaviour as random outliers that will be averaged out in the marketplace. But as Low demonstrates in countless examples, often humans (and by implication traders) behave ‘predictably irrational’, reacting to fear systematically different than to reward, for example, and opening opportunities for windfall profits on the financial markets. That is why some famous investors, accounting for these predictably irrational heuristics of humans, can be consistently successful.

The good news, though, is that we are not like other animals. We do not have to wait for evolution to take its course, molding us to our environment through natural selection. We have the ability to learn and adjust through trial and error. High-frequency trading is a great example: speed is everything in financial markets, and automated trading programmes have replaced specialist human traders who are just too slow to recognize and respond to the predictably irrational human errors. But even this is changing, as Lo explains: ‘At first, these high-frequency traders made windfall profits, since human specialists were sluggish and inefficient in comparison. However, there ultimately came a point where high-frequency traders were mainly competing with each other. To succeed in this financial arms race, high-frequency trading firms had to invest in faster and more expensive hardware. At the same time, however, these firms were scouring the market for any trace of “juice” that might be left. In a very short amount of time, high-frequency trading was pushing against its natural evolutionary limits. It had unexpectedly become a mature industry, with low margins on trades and low overall profits.’ High-frequency trading is now on the decline, as more and more exchanges start implementing ‘no high-frequency trading zones’. The environment is changing, and those high-frequency traders that do not adapt, will perish.

The book presents not only a fascinating new theory that can explain why some investors continue to be successful despite the prediction of the Efficient Markets Hypothesis, but it also situates this theory within the context of broader developments in finance. We learn why the Efficient Markets Hypothesis was so appealing, why earlier attempts to use evolutionary thinking in finance never caught on, and what this new theory might say about the future of finance. It also has a cautionary word about how we train the next generation of finance gurus: ‘For the mathematically trained economist, it’s sometimes difficult to think in evolutionary or ecological terms, but sooner or later, this way of thinking will be domesticated (another biological metaphor), and will become another standard tool for economists to use, just as molecular biologists use it today.’

Just like the finance industry employed mathematically-inclined engineers and physicists in the last few decades, perhaps biology will be the training-of-choice for the next generation of investment firms. Perhaps. What we do know is that the environment is changing, and that means that traders will have to adapt too if they are to survive, and thrive. As Lo explains: ‘An evolutionarily successful adaptation doesn’t have to be the best; it only needs to be better than the rest.’ Let the games begin!

*An edited version of this first appeared in Finweek magazine of 7 September 2017.

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Why #DataMustFall

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ZimBoth the Independent Communications Authority of South Africa (Icasa) and the Competition Commission are concerned about South Africa’s high data costs. It is about time. Of the 48 African countries ranked by ResearchICTAfrica.net for the first quarter of 2017, South Africa was the 22nd most expensive in which to buy 1GB data. All of South Africa’s main competitors on the continent, including Egypt (1st), Ghana (4th), Nigeria (8th) and Kenya (15th) ranked higher. Our poorest neighbour – Mozambique – ranked second, with US$ 2.27 for 1GB in contrast to our US$7.49.

Consumers have known this for some time. Last year, radio personality Thabo “Tbo Touch” Molefe started a Twitter campaign – #DataMustFall – that went viral. He was subsequently invited to address the parliamentary Portfolio Committee on Telecommunications and Postal Services about the high cost of broadband in South Africa. Said Molefe at the time: “The power of data gives access to education, mentorship, skills training, financial assistance, job searching and recruit.”

Molefe is correct. There is now ample evidence globally to show that internet access at affordable prices is correlated to better job market opportunities. This is especially true in South Africa, where the employment rate is seven percentage points higher in areas connected to the internet than those with no connection. The problem is that economists have struggled to show that this relationship is causal: areas with internet connectivity usually have all the other amenities that are associated with better job market prospects. It then becomes an empirical question of how to separate the effect of internet connectivity from things like education, infrastructure and wealth that also affect job market prospects?

A new NBER Working Paper by Jonas Hjort of Columbia University and Jonas Poulson of Harvard University offers an answer. The two authors exploit the gradual arrival of 10 submarine Internet cables from Europe in cities on Africa’s coast in the late 2000s and early 2010s to identify whether the higher speeds and cheaper data costs created new jobs. First, they show that the arrival of the cables did, in fact, increase average internet speeds and the expansion of the network. They then compare the changes in employment patterns in cities and towns with a bigger versus a smaller increase in access to fast Internet. “In each of three different datasets that together cover 12 African countries with a combined population of roughly half a billion people, we find a significant relative increase—of 4.2 to 10 percent—in the employment rate in connected areas when fast Internet becomes available.” Just as Molefe said: faster and cheaper internet creates jobs!

As with any economic change, there are both winners and losers. Hjort and Poulson show that the faster, cheaper internet reduces employment in unskilled jobs, but “enables a bigger increase in employment in higher-skill occupations”. In other words, just as automation does in the developed world, faster internet in Africa results in a change in the type of skills required. One might expect the consequence to be deeper levels of inequality. Not true, says the authors, especially in South Africa. Faster, cheaper internet enables South African workers of low and intermediate educational attainment “to shift into higher-skill jobs to a greater extent than highly educated workers”. The net effect is that fast internet lowers employment inequality across the educational attainment range in South Africa.

So what types of jobs were created by the arrival of the submarine cables? The authors find that “new and new types” of jobs were created via the “extensive margin” (meaning: new users) and “intensive margin” (meaning: different use of the internet by existing users). Using detailed firm level data, they show that, in South Africa, new firms are established, notably in sectors that benefit from ICT. In Ethiopia, by contrast, existing firms improve their productivity. In other African countries like Ghana, Kenya and Nigeria, firms with access to the faster, cheaper internet export much more, perhaps, the authors suggest, because “website communication with clients become easier”.

Technology is not just a threat to job creation – it is also an opportunity. But as the #DataMustFall movement has shown, fast internet access remains a mirage for most South Africans. That is hopefully changing. Non-profits, like Project Isizwe, want to facilitate the roll-out of free WiFi in public spaces in low income communities, as it is already doing in Tshwane. Similar initiatives are following in South Africa’s other metros. Both Google and Facebook are designing new technologies that could revolutionise connectivity for in rural areas.

Consumers are rightfully angry about the high cost of data in South Africa. Yet it is local entrepreneurs and their employees that should be most upset. As Hjort and Paulson show, cheap data will create more firms and more, better-paying jobs. “Employment responses of the magnitude we document indicate that building fast Internet infrastructure may be among the currently feasible policy options with the greatest employment-creating potential in Africa.”

Fast and cheap internet is probably the simplest way to alleviate South Africa’s high unemployment conundrum. Policy-makers should take note.

*An edited version of this first appeared in Finweek magazine of 24 August 2017.

Written by Johan Fourie

August 30, 2017 at 10:56

What explains the rise of populism?

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Donald Trump

Consider the following thought experiment: Sibusiso and Thulani each own a firm that competes with the other. In each of the following scenarios, Sibusiso’s firm outcompetes Thulani’s. Which of the four do you consider unfair competition?

  • Sibusiso works hard, saves and invests his profits, and invents new techniques and products, while Thulani’s products change little and he loses market share.
  • Sibusiso finds a higher quality input supplier in the US, which makes his products better and he therefore takes market share from Thulani.
  • Sibusiso outsources some of his services to Bangladesh, where workers work 12-hour shifts under hazardous conditions, earning very low wages.
  • Sibusiso brings Bangladeshi workers into South Africa under temporary contracts, and puts them to work at lower than minimum wages.

From an economic perspective, each of these scenarios have a similar result: there are winners as well as losers as they expand the economy. But people generally react very differently to them. Most people are happy with scenario 1 and 2: even if someone loses (Thulani and his employees), this comes through what is perceived as fair competition from Sibusiso. It is scenario 3 and 4 that creates problems: when Sibusiso ‘breaks’ local laws (even though it may be perfectly legal in the foreign country), his competitive advantage, and by implication international trade, is viewed as unfair.

In a provocative new NBER Working Paper, Harvard University economist Dani Rodrik use this example to argue that too-rapid globalisation – the increasing use of scenarios 3 and 4, of outsourcing production to the developing world or of employing immigrants – is the underlying cause for the rise of populism across the developed world. The ‘losers’ from globalisation feel that foreigners – abroad or as immigrants in their own countries – have taken unfair advantage of then, stealing their jobs. They have chosen the politics of populism as a way to ‘punish’ this rapidly globalising world.

Economists know that free trade creates both winners and losers, and that the winners almost always gain more than what the losers lose. If the winners could perfectly compensate the losers, everyone would be better off from a free-trading world.

But Rodrik argues that such compensation is not always easy, and rarely happens. Aside from Europe, where an extensive social safety net was institutionalized to support ‘losers’, most countries failed to find a way to sufficiently compensate those that suffered the consequences of open borders. Make no mistake: open borders resulted in massive global gains, notably for the poor of China and India. But in each country, as trade theory predicts, there were losers. In Rodrik’s words: “People thought they were losing ground not because they had taken an unkind draw from the lottery of market competition, but because the rules were unfair and others – financiers, large corporations, foreigners – were taking advantage of a rigged playing field.”

There are many new studies to back up this claim. In a 2016 paper, David Autor and his co-authors show, for example, that the trade shock of China joining the World Trade Organisation aggravated political polarisation in the United States: districts affected by the shock moved further to the right or left politically, depending which way they were leaning in the first place. Analysing the Brexit vote, Italo Colantone and Piero Stanig show that regions with larger import penetration from China had a higher Leave vote share. They repeat the study for fifteen European countries, showing that China’s entry into the WTO had similar political consequences across Europe. In a 2017 working paper, Luigi Guiso and his co-authors use European survey data to draw even more precise conclusions: the more individuals are exposed to competition from imports and immigrants (the higher their economic insecurity), the more they vote for populist parties.

To summarise: because there were uncompensated losers from global free trade, argues Rodrik, there were political consequences. Rodrik then constructs a model to explain this populist rise on both the left and the right. According to the model, there are three different groups in society: the elite, the majority, and the minority. Says Rodrik: “The elite are separated from the rest of society by their wealth. The minority is separated by particular identity markers (ethnicity, religion, immigrant status). Hence there are two cleavages: an ethno-national/cultural cleavage and an income/social class cleavage. An important implication of this reasoning is that even when the underlying shock is fundamentally economic the political manifestations can be cultural and nativist. What may look like a racist or xenophobic backlash may have its roots in economic anxieties and dislocations.”

Populists who emphasize the identity cleavage target foreigners or minorities, and this produces right-wing populism. Those who emphasize the income cleavage target the wealthy and large corporations, producing left-wing populism. The large numbers of immigrants into Western Europe has resulted in the rise of right-wing populists, for example, while Latin America, because of large disparities between rich and poor, has seen more left-wing populism. The United States, argues Rodrik, falls somewhere in the middle – with Donald Trump on the right and Bernie Sanders on the left.

These findings have important implications for South Africa too. South Africa joined the WTO in 1995 and liberalised our complicated tariff schedule, opening our borders to foreign competition. There were many winners from cheaper imports, notably consumers, but some firms and industries struggled, leading to job losses, often concentrated in certain regions. And although South Africa rolled out an impressively comprehensive social safety net for a middle-income country, they could not compensate all the losers, especially as the global financial crisis hit in 2007 and unemployment began to worsen. It is not entirely coincidental that the first large-scale xenophobic attacks on foreigners happened in 2008 (what Rodrik would call right-wing populism) and that the ANC shifted left with the election of Jacob Zuma as South African president in 2009.

Even if globalisation creates more winners than losers, the losers, like Thulani and his employees, may feel that the system is rigged, and retaliate by voting for more populist parties. As South Africa stumbles into another recession, this may have profound consequences for the ANC’s December elective conference – and the national election in 2019.

*An edited version of this first appeared in Finweek magazine of 10 August 2017.

Written by Johan Fourie

August 14, 2017 at 16:47

How do we build a prosperous, decolonized South Africa?

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boys-plowing

I recently attended an academic conference at the University of the Free State on the topic ‘Decolonizing Africa’. Much of the debate was, understandably, about the past: about the lingering effects of the (Atlantic) slave trade, European colonization that included the imposition of largely artificial borders, and the post-colonial failures of independent Africa. But at the final keynote, delivered by Prof Alois Mlambo of the University of Pretoria, the discussion turned to the future. How do we build a prosperous, decolonized South Africa?

One unescapably emotive topic is land reform. The expropriation and dispossession of land in South Africa is the root, many agreed, of the severe levels of inequality that plague the region. But how to correct this past injustice was not so easy; in the audience, too, were several Zimbabwean scholars quite critical of that country’s land reform programme. Over lunch, one Zimbabwean student told me the tragic story of his grandfather, a former farm worker on a white farm turned successful tobacco farmer after land reform, only to lose his land because he was considered ‘too successful’ by the ruling ZANU-PF party. The farm is now dormant.

Getting land reform right is fraught with difficulty. Not everyone that suffered land expropriation wants to return to farming – by far the largest number of recipients of successful land claims in South Africa choose the cash instead of the land. (This is often ignored by politicians and commentators when simply taking the hectares transferred as measure of land reform success.)  And even when recipients choose to return to the land, they often struggle to support themselves because of the small size of land allocated, or a lack of capital investment, or a lack of technical or management skills. There are also political consequences: because land recipients, like those in Zimbabwe, often do not receive title deed to the land they are given, they become ensnared by the political party that gave them the land. Why do people still vote for ZANU-PF despite the state of the economy? Because they worry a vote for the opposition means that they might lose their land. Most worryingly, it is often the original farm workers who lose the most, like the Zimbabwean student’s grandfather.

This is not to say that some form of wealth redistribution is not imperative. But whereas land (and the minerals it contained) was clearly the most productive resource when it was expropriated in the nineteenth century (which is the reason it was expropriated), a valid question is whether it still is the most productive. Of course, people value land not only for its economic uses: there are a myriad of historic, cultural and religious reasons why the land of your ancestors are treasured. But as a redistributive policy aimed at creating a more equitable society, is land reform the best way to create prosperity for those who suffered historical injustice?

Think of the fastest growing companies globally: which of them still rely predominantly on land ownership? AirBnB is a great example: it is the world’s largest accommodation service, without owning any property! For AirBnB and the myriad other unicorns that have created incredible wealth for their founders and shareholders, it is not land or physical property that creates wealth, but science and technology. (Even farmers know this: that is why they are investing in science to improve their crops and in technology to mechanize production.)

In the twenty-first century, land is what you buy with your wealth, and not the reason for your wealth. A quip about Stellenbosch wine farmers summarize this well: How do you make R1 million farming in Stellenbosch? You spend R2 million.

Prof Mlambo remarked that India and China, both with a history of colonisation, is not growing at above 5% because they have redistributed land. They have prospered because they embraced science and technology. Consider this: in the 2015/2016 academic year, 328,547 Chinese students studied in the United States; only 1,813 South African students did. (If you account for population size, 7 times more Chinese than South Africans students study in the US.) Take South Korea, a country with roughly the same population size as South Africa: 61,007 South Koreans traveled to study in the US in 2015/2016, 33 times more than South Africa.

So how would a redistribution policy look that takes science and technology seriously? I don’t have the answers, but here are some suggestions. Most of us would agree that education is key, but the South African education system has not made much progress in the last decade and it is unlikely to do so in the next. Redistribution must start at the first year of life. Publicly funded but privately run nurseries will remove the gap between the rich and poor that has already emerged when kids arrive at school. For primary and secondary education, a voucher system that incentivize private schools for the poor is an option. At tertiary level, we need more and better-funded universities, notably in science and technology. (It would help to send more of our smartest students abroad to study at the frontiers of science – they will return with new ideas and networks to propel our industries forward.) Visas for and recruitment of skilled immigrants can boost research and entrepreneurship. Improve free wifi access and invest in renewable energies. The private sector, because that is where most innovation occur, can be incentivized through appropriate legislation to offer shares to workers – or to those living in communities where they operate. There are a myriad of innovative possibilities.

If Zimbabwe has taught us anything, it is that politics may triumph over economic logic. Land reform in Zimbabwe was not an economic strategy in as much as it was a strategy to keep the ruling party in power. It has had severe economic consequences, as anyone visiting Zimbabwe today can attest. The real radical economic transformations of our age – just in my lifetime, the Chinese has managed to reduce the share of people living in absolute poverty from 88% to less than 2% – have not come from redistributing an unproductive twenty-first century resource. It has instead been the result of investments in science and technology. Any attempt to redistribute with the purpose of building a more prosperous society should take this as the point of departure.

*An edited version of this first appeared in Finweek magazine of 29 June 2017.

How social status drives our consumption – and inequality

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louis-vuitton

A couple of years ago I attended a focus group for Finweek. The magazine was rebranding and it had invited a diversity of people to comment on the content it should offer. The conversation turned to investment options for young professionals: should young people invest their monthly savings in a new property, or stocks, or something else? The facilitator asked the thoughts of a young woman that had been quiet for most of the meeting. Her answer, and its consequences for many young South Africans like her, stunned me: I invest in expensive clothes, because I have to signal to a potential husband that I am wealthy. In other words: I buy brand names, because I want to improve my social status.

Economists have known since Adam Smith already that people buy luxury goods not only for the value they derive from consuming it, but because these goods offer something else: social status. Conspicuous consumption, as economist Thorstein Veblen coined our affinity for status goods, has helped explain economic phenomenon like our excessive expenditure on weddings or the difference between black and white incomes in America.

However, so far economists have struggled to differentiate between our affinity for nice things (in economics jargon: our unobserved consumption utility) and our affinity for the status that those nice things signal. In other words, I might buy a Ferrari not only because I really like fast and furious cars (consumption utility), but also because I want to signal to the everyone else that I am rich (status).

A team of five economists, in a new NBER Working Paper, has now found a way to test the importance of social status. They worked with a large Indonesian bank that distribute credit cards to clients. (Indonesia is a great place for a test like this, because it is in developing economies, as Veblen theorized, where you are most likely to see conspicuous consumption. Also, Indonesia has 74 million middle-class consumers, expected to double by 2020.) They used platinum credit cards, which come with a number of benefits like a higher credit limit and discounts on luxury purchases and is typically sold to high-income individuals, in their experiment.

How do they show that social status matter? They randomly offered a fancy-looking platinum and standard-looking credit card to their customers at the same price and with the same benefits. If customers only cared about the utility of the new card (like the benefits on offer), there should be no difference in the take-up of the fancy-looking or standard-looking card. And yet, there is a 7 percentage point difference: 21% purchased the fancier card versus only 14% for the standard card. The mere fact that the fancy-looking card was associated with a higher status meant that people purchased it.

Perhaps it is not that surprising that people purchase something because it conveys an additional status element, but what is surprising about the experiment is that poorer individuals bought more of the fancy-looking card. The rich, in contrast, showed no difference in demand for the fancy or standard card. The authors ascribe this finding to the fact that “richer individuals already have ways to signal their income, while the platinum credit cards are a more powerful signaling tool for those with comparatively lower incomes”. This also explains the behaviour of the young woman in our focus group; she was more limited in her ability to show social status and thus had to resort to clothing.

In a second experiment, the authors then look at how the customers use their cards. Consistent with their theory, they find that the customers that bought the fancy-looking card (remember: it had the same privileges as the standard-looking card) used the card more often in social settings, such as spending in restaurants, bars and clubs, where the card is more visible to others. Here, too, there is somewhat of a surprise: the use of this card comes at a cost, because in 48% of the cases the customers have another card that would have given them discounts on those purchases. In other words, they chose to ignore the discount just so that they can use the fancy-looking card that gives them social status! If this is true for credit cards where there is a limited audience (only your buddies who joined you for dinner can see you paying with a fancy-looking card), imagine what people are willing to forego for luxury products with a larger audience, like clothes and cars.

The authors conduct several other experiments, all of which support the authors’ theory that social status matter in explaining our consumption behaviour. We do not only buy luxury goods because they provide us with utility; we buy them because they signal something about our social status. And because poorer individuals tend to have fewer ways of signaling social status than richer ones, they are the most eager to grasp at opportunities for showcasing their status. (That is why direct marketing is never aimed at the wealthiest individuals!)

Such findings have implications for the distribution of wealth. The choice for a young person between investing your meager savings in stocks or a new car may not only depend on the financial returns they can get, but also the psychological returns they might get from purchasing a luxury good. If poorer individuals tend to buy more luxury goods to earn social status, like the young woman in the Finweek focus group, while the rich invest in assets that yield positive financial returns (because they already have assets that give them social status), the only logical conclusion is a widening wealth gap. There is little any policy, like a purported wealth tax, can do to prevent that instinctive human yearning for status.

*An edited version of this first appeared in Finweek magazine of 15 June 2017.

Written by Johan Fourie

July 12, 2017 at 11:02

How our emotional intelligence makes us productive

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Emotional-Intelligence-1

Economists spend a lot of time investigating the factors that make people more productive. This is because more productive people – producing more, with less – is the reason we can today afford a much higher standard of living than our ancestors – in Africa, India or Europe – two centuries ago.

Many things improve our productivity. Technological improvements like a computer can allow us to use the power of machines to substitute manual labour. Education allow us to build faster and stronger computers. Both technology and education are key if we are to continue building and sharing a prosperous future.

But it is not only technology and education that improve our living standards. There are formal and informal institutions – things like the criminal-justice system, property right regimes and the political system – that create the incentives for us to invest in technology and education. And there are the even less tangible things, like the way we make decisions (often referred to as ‘culture’), or our personalities. Economists are only now beginning to explore the roots of these ‘soft’ determinants.

Psychologists have known for long that our personality affect the way we make decisions. One example: Whether we apply for that senior position may depend on whether we exhibit the leadership qualities that is required to lead a large team. But what determines whether we have those leadership abilities? Is it nature or nurture?

One option is to look at siblings. If genetic traits (nature) were the only source of leadership qualities, then almost all the variation we find in society would be between families. In other words, there should be little variation between brothers, for example, as they have a lot of genetic overlap.

This is not the case, however, at least according to a recent NBER Working Paper written by three economists, Sandra Black, Björn Öckert and Erik Gröngqvist. Almost a third of total variation in personality traits, they note, are within the family. So, if it is not only nature that determine much of your personality, where do these within-family differences come from?

One possibility, they argue, is birth-order. Using a very rich Swedish dataset, the authors find that first-born children are ‘advantaged’ when measured on their ‘emotional stability, persistence, social outgoingness, willingness to assume responsibility and ability to take initiative’. Note: these are non-cognitive abilities, i.e. there is little difference in terms of a first-born and a third-born’s innate ability to do math, for example. It is on the softer abilities, instead, that first-borns clearly outperform their lower-ranked siblings: third-born children, for example, have non-cognitive abilities that are 0.2 standard deviations below first-born children.

These non-cognitive abilities matter. Controlling for many things, they show that first-born children are almost 30% more likely to be Top Managers compared to third-borns. This is because managerial positions, they argue, tend to require all Big Five domains of personality: openness to experience, conscientiousness, extraversion, agreeableness, and emotional stability.

But why does birth-order matter? The authors argue for largely three possible reasons. First, biology. Successive children may have less of the stereotypical male behavioural traits due to the mother’s immunization to the H-Y antigen. But this seems unlikely to explain most of the variation, as the authors also find that birth order patterns vary depending on the sex composition of the older children: third-born sons perform worse on non-cognitive tests when their older siblings are male compared to when they are female.

This suggests that it has something to do with how parents allocate their time and resources, especially in the early years. ‘First-born children have the full attention of parents, but as families grow the family environment is diluted and parental resources become scarcer’, the authors argue. Parents may also have incentives for more strict parenting practices towards the first born to ensure a reputation for “toughness” necessary to induce effort among later born children.

Thirdly, children may also act strategically in competing for parental resources. Siblings compete for possession of property and access to the mother. Older siblings, research shows, tend to take a more dominant role in conflict and have more elaborate conflict strategies. To minimise conflict, parents tend to invest more in the dominant, older sibling.

Using a novel approach, the authors can identify which of these effects is largest. They find that biological factors only explain a small part, and may actually benefit later-born children. It is however in the behaviour of parents that there are distinct differences between first- and later-born children: they find that later-born children spend substantially less time on homework and more time watching TV. Parents are also less likely to discuss school work with later-born children, suggesting that it is the parents that lower their investment which explains the large gap in non-cognitive skills.

What the authors do not do is to link their results with the general improvement in living standards over the last two centuries. We are becoming ‘better angels of our nature’ because we grow up in smaller families with more parental attention and resources, improving our non-cognitive abilities.

It is not only the vast improvement in technology and education that has made us more productive, but also because we have become more conscientious, agreeable, responsible and willing to take the initiative. We are rich, in part, because we are more emotionally intelligent.

*An edited version of this first appeared in Finweek magazine of 1 June 2017.

Written by Johan Fourie

June 23, 2017 at 07:49

We are shopping less, but buying more

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CheckersMini

One of the things I realised soon after marriage, is that my wife and I share different strategies when it comes to grocery shopping. I like to stock up, buying bulk on the cheap, while she prefers to visit the store more frequently, acquiring only what is necessary for the next few days. This of course means that we never run out of canned beans, but often out of milk.

Such choices are at the heart of economics. Understanding how, why and when a buyer chooses a product or service is often the difference between a thriving and failing business. That is why every successful firm, from banks to health insurance to mobile communications companies, spend considerable resources these days analysing ‘Big Data’ to understand and ‘nudge’ the behaviour of their customers.

Even general retail, a sector often caricatured as unaffected by technological change, now has to adjust to the new technological possibilities, like sensing technologies that track the movement of customers as they browse a store. Not only can technology help retailers to optimise store lay-out, but, with a little leap of the imagination, they can have advertising that can recommend new products when a new customer walks past based on the content of their previous purchases, of their existing basket or of the purchases of their friends that is connected to them on social media. (Imagine buying shampoo, and being prompted: Your friend, Herman, purchased Organics in this store five days ago.) And then there is a plethora of other technologies that are likely to revolutionise the shopper’s experience, from mobile payments (in South Africa: wiCode or SnapScan), to digital receipts (another South African upstart: Pocketslip), to online shopping.

There is no doubt that these new technologies will shape the way we make decisions about what, how and where to buy our groceries, but technology is not the only thing that affects our spending behaviour. A new NBER Working Paper by three authors affiliated to US universities, identifies an interesting trend in the US over the last four decades: the rise of spending inequality, or a widening gap between how much different households spend when they go shopping.

We usually measure inequality by comparing peoples’ incomes. But presumably we are also interested in how people spend their incomes: are there huge differences between how much some households spend vis-à-vis others, and do these differences change over time? In fact, it seems like this is indeed the case: the difference in household spending patterns in the US seem to be on the increase. Some families seem to be spending a lot more than others.

One suggestion for the rise in income inequality is the impact of technology. But this is where the authors find an interesting result: the reason for the rise in spending inequality, they argue, is not because of growing differences in consumption caused by greater levels of income inequality (i.e. the rich still consume more than the poor, but this gap is not increasing), but instead because Americans go shopping less frequently. They explain it as follows: if a household starts buying groceries once a month instead of once a week, their consumption may not change (they stockpile to smooth their consumption), but the measured spending inequality will change because some households in surveys will appear as if they spend a lot, while others will appear as if they spend nothing. This difference was less dramatic when households went shopping every week, and so it appears as if inequality is on the rise.

Using various datasets, the authors find two distinct trends to support this theory: first, the number of shopping trips that Americans make has been steadily falling since 1980. In contrast, the average expenditure per trip has been steadily rising. Americans are making fewer, but larger, shopping trips on average. Second, the quantity of goods Americans buy have been rising, while the amount of time spent shopping has declined. All of this, the authors conclude, points to higher levels of stockpiling by Americans.

What explains this changing behaviour? Surprisingly, it is not technology innovation, which is often considered the source of most disruption. Instead, the authors show, the increasing stockpiling is a result of the emergence of warehouse stores, like Costco, that sell larger quantities of goods at lower unit prices. “As these stores have expanded throughout the country since the 1980s, it has become easier for households to stock up in ways that were not feasible in the past, consistent with the decreased frequency of shopping that we observe.”

Technological improvements like mobile payments, digital receipts and online shopping is aimed at reducing transaction costs, making it easier and cheaper for consumers to do their grocery shopping. Such lower costs should result in a higher frequency of shopping. And yet, the trends, at least for the US, point in exactly the opposite direction: fewer visits to the supermarket, with consumers preferring to buy in bulk and on the cheap.

Perhaps South African consumers behave differently. Perhaps the digital revolution will reverse these trends quickly; once your fridge can order canned beans automatically from the local supermarket when supplies run low, we won’t need to buy in bulk. But any retailer worth their salt would do well to be aware that the promise of technology can often overshadow deeper forces pulling in the other direction. Technology reduces transaction costs, but the benefits of buying bulk seem to outweigh the costs. Now to convince my wife.

*An edited version of this first appeared in Finweek magazine of 18 May.

Written by Johan Fourie

June 13, 2017 at 05:48