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Archive for the ‘Technology’ Category

A radical solution to land ownership

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Farmland

What if I could offer you the following three outcomes – 1) an increase in government revenue to the extent that a Basic Income Grant (BIG) can be afforded, 2) a substantial decline in wealth inequality, and 3) a sustainable solution to the land crisis – with just one policy intervention? Fantastic, you’d say, but naïve and, frankly, absurd. There is no policy that we know of that can tackle these immense societal challenges, all in one go.

Wait, I’m not done yet, I’d answer. This policy would make it much easier to build infrastructure, get rid of derelict buildings, would ramp up GDP per capita significantly, and would foster social cohesion.

Seriously? Don’t be ridiculous, you’re dreaming, you’d respond. And to do this, I’d continue, we’d need to do two things that seem almost directly opposed to one another. We need to expand markets. You might nod in agreement, something sensible for the first time. Oh, and we must abolish private property altogether.

This, in short, is the recommendation by two economists, Erik Posner and Glen Weyl, in their new book Radical Markets. Critics seem to agree that this is something worth discussing; Kenneth Rogoff calls this ‘perhaps the most ambitious attempt to rethink democracy and markets since Milton Friedman’.

Although their ideas have huge implications for democracy and immigration too, I will focus here on their first chapter, and probably the one most relevant to South Africa currently: property. They propose a Common Ownership Self-Assessed Tax (COST) on wealth. Property, they argue (like many economists before them), are inevitably monopolistic, and monopolies create inefficiencies in the market. Their COST aims to remove these allocative and investment inefficiencies by introducing a live auction for every asset in society.

So, how does it work? Let’s take Khulekani. His young family has just expanded, and so he wants to buy a new house. He would go to a website – let’s call it UmhlabaWethu.co.za – and open a sort-of Google Maps that will allow him to see every property in South Africa, valued by the owner of the property. He can then decide to buy any property, by just clicking on the property, at the price the owner has listed. The ‘right to exclude’, one of the central tenets of private ownership, is therefore waived in this new system. Every property owned by a company or individual (or government!) must be valued and listed.

So, what prevents owners from just making excessively high valuations, making Khulekani’s attempt at buying a house impossible? Tax. In this system, each owner will pay an annual tax on the self-assessed value of their property, thereby waiving the ‘right to use’, the second central tenet of private ownership. The authors explain: ‘In the popular image of private property, all benefits from use accrue to the owner. Under a COST, on the other hand, a fraction of this use value is revealed and transferred to the public through the tax; the higher the tax, the greater the fraction of use value transferred.’

In other words, all property in South Africa would be on a permanent auction, where the current user of the property determines the price (but pay for that price in tax). It’s almost like Uber, for property.

Imagine a private investor wants to build a high-speed monorail in Cape Town. To do this at present would be almost impossible, as owners of properties on the intended route would hold out for a high price, knowing that they have monopoly bargaining power. A COST would allow an investor to go online and buy up all the properties at the listed price, combine them, and start building the monorail. (Of course, they must also value that property, and pay tax. If another investor believes they can build a more profitable monorail, they might just buy-out the original investor’s right of use.)

Or imagine that the property tax is returned to citizens as a Basic Income Grant. By the authors’ rough calculations, every US citizen from a similar system could receive $20000 annually, which for most would be far less than they would be paying in tax. By their estimates, it would only be the richest 1% property owners that would be paying more than they receive – and often a lot more. This not only reduces inequality (by 4 Gini points, according to their estimates), but it also acts as a subsidy for the poorest.

In South Africa, COST tied to a BIG could do far more to alleviate poverty and address inequality than a policy like expropriation. Unproductive land would be a direct cost to all society: higher property values paying more tax mean that more can be redistributed to everyone. As the authors note, ‘a world in which everyone benefits from the prosperity of others would likely foster higher social trust, a factor essential to the smooth operation of the market economy’.

‘The sharing of wealth would be in accord with many commonsense notions of justice. Wealth is rarely created solely by the actions of the people who are paid for it under capitalism. They normally benefit from the help of friends, colleagues, neighbours, teachers, and many other people who are not fully compensated for their contributions. A COST would better proportion the distribution of wealth o the labour that created it.’

This is a radical proposal. It might have unintended consequences that we cannot currently imagine. That’s why the authors propose a piecemeal adoption of these policies. That is a sensible approach. Experimentation will be needed, perhaps even within one municipality first.

But the radical economic transformation that COST can accomplish is a lesson in how creative thinking – and perhaps a willingness to put away our ideological differences – can help find solutions to a problem that we had thought to be insurmountable.

*An edited version of this article originally appeared in the 13 September edition of finweek.

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The formula for success

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The world of work is changing. Skills that were valuable only a decade or two ago seem less valuable nowadays, displaced by newer trends and technologies. Every few weeks a news article report on the threat of automation, and how it will destroy millions of jobs, including yours. A YouTube video of a robot jumping over obstacles confirms that the inevitable is only a few months away.

The answer, many seem to think, is to become like computers. Students, in South Africa and elsewhere, are encouraged to pursue STEM – science, technology, engineering and mathematics – careers. Humanities degrees or those in the social sciences, in contrast, are often considered less prestigious. We know that the best-paying jobs are still those where a decent amount of math is required. In South Africa, this is of particular concern, as the gender and racial composition of those enrolling for STEM degrees differ significantly from those enrolling for degrees in the humanities, exacerbating inequality.

Occupations

But the story is more complicated than that. A new paper by David Deming, published in the Quarterly Journal of Economics (QJE), suggests that, at least in the United States, STEM graduates are not doing very well. In fact, between 2000 and 2012, STEM jobs shrank by 0.1 percentage points, after growing by 1.3 percentage points in the previous two decades. In contrast, all other ‘cognitive occupations’, jobs like managers, teachers, nurses, physicians, lawyers and economists , grew by 2.9 percentage points between 2000 and 2012, faster than the 2 percentage points in the previous decade. The figure below demonstrates this clearly: only 36% of STEM occupational categories had positive growth, compared to 85% of other professional occupations.

The reason for this, Deming argues, is that managers, teachers and physicians all require significant interpersonal skills. And because of the technological change – the same technological change we all fear! – these social skills are increasingly in demand. Deming explains: ‘The skills and tasks that cannot be substituted away by automation are generally complemented by it, and social interaction has, at least so far, proven difficult to automate. Our ability to read and react to others is based on tacit knowledge, and computers are still very poor substitutes for tasks where programmers don’t know “the rules”.’

Using a wide variety of sources, Deming finds that jobs that require high levels of both cognitive and social skills have fared particularly well, while high math, low social skill jobs (including many STEM occupations) have fared especially poorly. ‘Social skills were a much stronger predictor of employment and wages for young adults age 25 to 33 in the mid-2000s, compared to the 1980s and the 1990s.’ There is a revolution in the job market underway that no-one is talking about.

CyanideHappiness

Where do these social skills come from? Deming speculates that much of it is formed during early childhood development, although this is difficult to prove. The latest research that have followed children from a young age into adulthood have found strong correlations between kids’ socioemotional skills in kindergarten and adult outcomes such as employment and earnings.

The demand for social skills may also have implications for gender imbalances in the workplace. Women often choose careers that require more social interaction. If these jobs are in greater demand, with faster earnings increases, the gender gap may close quicker.

The optimism about the closing of the gender gap, though, is pegged by another study published in the same journal, by authors Matthew Wiswall and Basit Zafar. They test a group of New York University students about their preferences for flexible hours when they enter the job market, and find that students are willing to give up 2.8% of their annual earnings for a job with a centage point lower probability of job dismissal. They also find that students are willing to give up 5.1% of their salary to have a job that offers the option of working part-time hours. But there is a large gender difference: female students have a much higher average preference for flexible hours – 7.3% – compared to men – 1.1%. What the authors then do is to track the students after they graduate, and record their actual earnings four years later. Wiswall and Zafar find that those students with a high preference for work flexibility do actually end up in occupations with greater flexibility. But because women already prefer more flexible work even before they’ve started working, they also tend to earn less once they’ve entered the labour market, choosing jobs with lower pay and greater flexibility. At least a quarter of the gender gap in the labour market, the authors argue, can be explained by just these differences in preference.

These studies show how our social skills and preferences affect our labour market outcomes. Policies that aim to address labour market distortions, like race or gender gaps, should know that the roots of the problem may lie in preferences and skills moulded in the early years of development.

That is not to say that nothing can be done: for those going to university this year, perhaps one thing to keep in mind is that your future earnings depend not only on attending math class, but also on developing your social skills. Here’s one formula to remember: Math + beer = success.

>>> An edited version of this article originally appeared in the 1 February 2018 edition of finweek.

Written by Johan Fourie

March 13, 2018 at 08:00

Thuma Mina

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Ramaphosa

Today is a good day to be South African. Cyril Ramaphosa, one day after being sworn in as South Africa’s fifth democratic president, delivered a State of the Nation address last night that reminded us who we can be. Over the last nine years, we had become conditioned to the mediocrity of Jacob Zuma, had set the bar so low that our optimism of a better tomorrow had withered away. With one speech, Ramaphosa allayed the melancholy. Rise, South Africa, he said, and rebuild the dream of a prosperous and just society.

It requires action, and he has many plans. A smaller and more efficient government, support for entrepreneurs, investment in innovation, welcoming tourists, broader ownership of agriculture. But success will not depend on him alone. It cannot. In what reminded me of Kennedy’s ‘ask not what your country can do for you, ask what you can do for your country’, Ramaphosa told South Africans to take responsibility for the future they want: In the words of Hugh Masekela, thuma mina (Send Me).

We are at a moment in the history of our nation when the people, through their determination, have started to turn the country around.

We can envisage the triumph over poverty, we can see the end of the battle against AIDS.

Now is the time to lend a hand.

Now is the time for each of us to say ‘send me’.

Now is the time for all of us to work together, in honour of Nelson Mandela, to build a new, better South Africa for all.

Much work must be done. Not everything promised can surely be delivered. But the tide has turned. Today is a good day to be South African.

Written by Johan Fourie

February 17, 2018 at 10:01

The compelling case for technological optimism

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PortableComputers

In September last year, I visited the Computer History Museum in Mountain View, California. The museum is dedicated to preserving and presenting all aspects of the computer revolution, from its roots in the twentieth century to self-driving cars today. What is remarkable is to observe, while walking through the more than 90000 objects on display, the profound change in technology over the last three decades. The mobile computing display, I thought, summarised this change best, showing the first laptop computers of the 1980s (see image above) to a modern-day iPhone. But what also became clear from the exhibitions was that those ‘in the know’ at the start of the revolution were right about the transformational impact of computers, but almost certainly wrong about the way it would affect us.

We are now at the cusp of another revolution. Artificial intelligence, led by remarkable innovations in machine learning technology, is making rapid progress. It is already all around us. The image-recognition software of Facebook, the voice recognition of Apple’s Siri and, probably most ambitiously, the self-driving ability of Tesla’s electric cars all rely on machine learning. And computer scientists are finding more applications every day, from financial markets – Michael Jordaan recently announced a machine learning unit trust – to court judgements – a team of economists and computer scientists have shown that the quality of New York verdicts can be significantly improved with machine learning technology.  Ask any technology optimist, and they will tell you the next few years will see the release of new applications that we currently cannot even imagine.

But there is a paradox. Just as machine learning technology is taking off, a new NBER Working Paper by three economists, Erik Brynjolfsson, Chad Syverson and Daniel Rock affiliated to MIT and Chicago, show something peculiar: a decline in labour productivity over the last decade. Across both the developed and developing world, growth in labour productivity, meaning the amount of output per worker, is falling. Whereas one would expect that rapid improvements in technology would boost total factor productivity, boosting investment and raising the ability of workers to build more stuff faster, we observe slower growth, and in some countries even stagnation.

TrendGrowthRates

This has led some to be more pessimistic about the prospects of artificial intelligence, and in technological innovation more generally. Robert Gordon, in his ‘The Rise and Fall of American Growth’, argue that, despite an upward shift in productivity between 1995 and 2004, American productivity is on a long-run decline. Other notable economists, including Nicholas Bloom and William Nordhaus, are somewhat pessimistic about the ability of long-run productivity growth to return to earlier levels. Even the Congressional Budget Office in the US has reduced its 110-year labour productivity forecast, from 1.8 to 1.5%. On 10 years, that is equivalent to a decline of $600 billion in 2017.

How is it possible, to paraphrase Robert Solow in 1987, that we see machine learning applications everywhere but in the productivity statistics? The simplest explanation, of course, is that our optimism is misplaced. Has Siri or Facebook’s image recognition software really made us that more productive? Some technologies never live up to the hype. Peter Thiel famously quipped: ‘We wanted flying cars, instead we got 140 characters’.

Brynjolfsson and co-authors, though, make a compelling case for technological optimism, offering three reasons for why ‘even a modest number of currently existing technologies could combine to substantially raise productivity growth and societal welfare’. One reason for the apparent paradox, the authors argue, is the mismeasurement of output and productivity. The slowdown in productivity of productivity in the last decade may simply be an illusion, as most new technologies – think of Google Maps’ accuracy in estimating our arrival time – involve no monetary cost. Even though these ‘free’ technologies significantly improve our living standards, they are not picked up by traditional estimates of GDP and productivity. A second reason is that the benefits of the AI revolution are concentrated, with little improvement in productivity for the median worker. Google (now Alphabet), Apple, and Facebook have seen their market share increase rapidly in comparison to other large industries. Where AI was adopted outside ICT, these were often in zero-sum industries, like finance or advertising. A third, and perhaps most likely, reason is that it takes a considerable time to be able to sufficiently harness new technologies. This is especially true, the authors argue, ‘for those major new technologies that ultimately have an important effect on aggregate statistics and welfare’, also known as general purpose technologies (GPT).

There are two reasons why it takes long for GPTs to be seen in the statistics. It takes time to build up the stock necessary to have an impact on the aggregate statistics. While mobile phones are everywhere, the applications that benefit from machine learning are still only a small part of our daily lives. Second, it takes time to identify the complementary technologies and make these investments. ‘While the fundamental importance of the core invention and its potential for society might be clearly recognizable at the outset, the myriad necessary co-inventions, obstacles and adjustments needed along the way await discovery over time, and the required path may be lengthy and arduous. Never mistake a clear view for a short distance.’

As Brynjolfsson and friends argue, even if we do not see AI technology in the productivity statistics yet, it is too early to be pessimistic. The high valuations of AI companies suggest that investors believe there is real value in those companies, and it is likely that the effects on living standards may be even larger than the benefits that investors hope to capture.

Machine learning technology, in particular, will shape our lives in many ways. But much like those looking towards the future in the early 1990s and wondering how computers may affect our lives, we have little idea of the applications and complementary innovations that will determine the Googles and Facebooks of the next decade. Let the Machine (Learning) Age begin!

An edited version of this article originally appeared in the 30 November 2017 edition of finweek.

The politics of infrastructure

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Cape Town railway historic

What type of infrastructure would be best for South Africa’s future? The answer, of course, depends on your point of view. If you live and work in Gauteng, your answer might well be to expand the Gautrain network. Or if you reside in Cape Town, you might prefer investments in desalinization plants. Your occupation may also be relevant. If you’re a miner, you are unlikely to support the expansion of renewable energies. A trained software engineer? Well, you’re likely to support large investments in telecommunications infrastructure.

An important – but often underappreciated – role of government is to choose the type of infrastructure that is destined to shape the country’s future development path. This choice is never neutral though: for every decision, there are winners and losers. Choose to build a new coal-fired power plant? That will benefit coal mine owners and workers, while the users of electricity, were the costs of alternative sources to fall rapidly, will pay. Choose to build a high-speed train network across the country (a hyperloop, perhaps!), then users of this network, likely to be high- or middle-income South Africans, will benefit, while long-distance bus services, taxi operators and rental cars will pay. The government’s job, in theory at least, is to choose the projects that will maximize the benefits and minimize the costs.

But things are never that simple. A research paper that will soon appear in the European Review of Economic History, written by Alfonso Herranz-Loncan and myself, investigate the infrastructure in the Cape Colony built during the second half of the nineteenth century. Before the discovery of diamonds in 1867, the few railways that existed (in and around Cape Town) were privately-owned and largely unprofitable. But the discovery of diamonds and the rush to the mines meant the demand for fast, affordable inland transport increased exponentially. The Cape government had to react.

They did. They bought the few existing lines, and then began to the process of connecting Cape Town to Kimberley, finally achieved in 1885. The connection to the booming diamond region brought huge economic benefits: we estimate that the railway may account for 22-25 percent of the increase in income per capita in the Cape during the diamond-mining period (1873-1905). This is a massive share for a single investment and a clear indicator of the transformative power of railways during the first era of globalisation.

But these benefits were not equally shared by everyone. Surprisingly, the government itself earned a meager 3.7% average return on its capital. Had a private firm built the railways, far fewer branch lines would probably have been built. As Stellenbosch PhD student Abel Gwaindepi now shows, the government incurred huge debt to build this infrastructure, and although the government did benefit through customs duties and other tariffs, the main beneficiaries were the owners of the diamond fields. The railway link between Cape Town and Kimberley could now transport the machinery and foodstuffs required to feed the growing Kimberley population. Western Cape wheat farmers, who supplied the mines with food, was another group of beneficiaries. It is not entirely coincidental that it was also these two groups – mine owners and Western Cape farmers – who had formed a political alliance in Cape parliament.

Of course, it was not only mine owners and Cape farmers that benefited. As detailed reports of passengers show, Cape Colony residents from all walks of life used the railways. But, ultimately, it was tax payers who had to foot the debt that were incurred, and often these tax payers were spread across the entire colony (far from the direct benefits of the railways) – and after unification in 1910, the rest of the country. And the location of the railways meant that those with less political influence – like Basotho farmers, who were of course producing wheat much closer to the diamond fields – lost out. Here is one missionary report from 1886, the year after the railway line was completed: ‘Basutoland, we must admit, is a poor country… Last year’s abundant harvest has found no outlet for, since the building of the railway, colonial, and foreign wheat have competed disastrously with the local produce.’

The nineteenth-century Cape railways contributed significantly to economic growth, but it inadvertently also had distributional consequences: some benefited more than others, and some even suffered as a result of its construction.

The lessons for today? Politics shapes the type of infrastructure that’s built. And infrastructure shapes the direction of economic development. So the key question is this: Are we building the type of infrastructure that will put South Africa on a path of broad-based economic development, or is the choice of infrastructure determined by the self-interest of those with decision-making power, much like Cecil John Rhodes and his cronies during the late nineteenth-century?

Put differently, when we choose a new power-generating facility or national air carrier or telecommunications license, do we consider the benefits for society as a whole or the benefits for a specific interest group?

*An edited version of this first appeared in Finweek magazine of 5 October 2017.

Policy uncertainty is killing investment in what matters

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microscope

Much has already been said about South Africa’s inefficient public sector. Not only has the public sector wage bill escalated beyond the realms of the sustainable, but this has come at almost zero public sector productivity growth. In other words, we are paying more for government to do less. Add to that the poor performances of state-owned enterprises like Eskom, the SABC and most notoriously, South African Airways, and it seems that there is little more that the South African government can do to hurt the prospects for economic growth.

But there is. A new NBER working paper, published by Jose Maria Barrero, Nicholas Bloom and Ian Wright, uses new data on about 4000 US firms to investigate the sources of uncertainty in the US economy. They first distinguish between short-term and long-term uncertainty, identifying the factors that cause each type of uncertainty. They then ask how each type of uncertainty affect firms’ behaviour.

Short-term uncertainty, they find, is caused by oil price volatility. In contrast, economic variables like the oil price has less of an effect on long-term uncertainty where political risk, like policy uncertainty, has a much larger effect. The important result is that short-term and long-term uncertainty have different consequences for firm behaviour. Short-term uncertainty affects employment; long-term uncertainty affects investment in research and development.

If we assume this is true for South Africa too, how would it play out? Volatility of several macroeconomic variables, like the oil price and exchange rate, cause higher short-term uncertainty. This would likely make firms unwilling to hire new workers, or make managers unwilling to offer higher wages. These are the consequences economic commentators typically cite when referring to an unstable macroeconomic environment.

But employment and wages are not the only variables affected by uncertainty. One of the key indicators of a thriving economy is businesses’ willingness to invest in research and development. Take R&D as a percentage of GDP, shown in the Figure below. There is large variation in the share that countries spend on research and development: Israel and South Korea, for example, spend more than 4% of their GDP on R&D. South Africa spend less than 0.8%. (This figure almost reached 0.9% in the 2006-2008 period, a period not surprisingly correlated with high growth rates.)

RDspending

There is a strong positive correlation between countries that grow fast and those that invest in research and development. South Africa, unfortunately, significantly lags those countries at the technological frontier. It is important, though, to understand why this is the case. It is not only government that invests in R&D; in fact, more than half of all R&D investment in South Africa comes from the private sector.

So what will encourage businesses to invest more in R&D? Well, according to Barrero, Bloom and Wright, political risk and policy uncertainty is the biggest determinant of private sector investment in R&D. In a political environment with little policy coherence, business are unlikely to make investments where the returns can only be realized in the long-run. Even if the possible returns are substantial, a rational investment response to a murky policy environment would be to sit back and see what happens. Lower investment in R&D means falling further behind international competitors.

There are some in the South African government who realise this. Minister of Science and Technology, Naledi Pandor, has committed to doubling R&D expenditure as a percentage of GDP by 2020. This is commendable, but in the current budgetary environment, unlikely to get the support from the Minister of Finance. Other initiatives to get the private sector investing in R&D, like a refundable tax credit that will benefit small businesses, have not been implemented.

These problems are not unique to South Africa. As the authors argue: ‘Our findings are significant in the wake of recent events like Britain’s vote to leave the European Union and Donald Trump’s assumption of the US Presidency, which have generated considerable uncertainty over future economic policy around the world. As we have shown, such policy uncertainty is particularly linked with long-run uncertainty and in turn with low rates of investment and R&D that can have significant consequences for the global economic outlook in years to come.’

R&D is the bedrock of future prosperity. Political risk that leads to policy uncertainty hurts not only economic growth and employment creation, but also deters firms from investing in the one thing that can create prosperity for all. If the ruling party is serious about its slogan, it better start by enacting more coherent economic policy.

*An edited version of this first appeared in Finweek magazine of 21 September 2017.

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