FlyingcarMy favourite programme on South African TV in the 1990s was Beyond 2000, a programme which showcased technologies that would (apparently) revolutionise living in the future. For a teenager, this was the stuff of dreams. The futuristic end to the opening (watch it here) showed cities with flying cars and infinitely high skyscrapers. How many of these ideas materialised? As Peter Thiel, founder of eBay, famously quipped about the technological inventions since the year 2000: ‘We wanted flying cars, instead we got 140 characters’.

There is little doubt that technological improvements causes higher productivity (making more stuff with fewer inputs) which in turn underpins economic growth. Economists like to think about two types of productivity: labour productivity is about making workers more productive through adding physical or human capital, usually measured as the amount of goods and services produced with one hour of labour. Total factor productivity, or TFP, is the increase in productivity that are not accounted for by increases in labour or capital, i.e. technological improvements. Another way to think of it is what I’ve called Nashuanomics: saving you time, saving you money. Any technological innovation that does these two things, improves productivity, increases growth, causing greater prosperity.

Economists measure the improvements in technology through TFP. One would expect that periods of rapid technological progress, like during the Industrial Revolution or the discovery of electricity, would cause large increases in TFP growth. But this is the conundrum: As Paul David has argued in several papers, there is not necessarily a clear link between new inventions of what he calls ‘general purpose technologies’ and our measures of total factor productivity. This is for the obvious reason that it takes time for new technologies to permeate society. Electricity, for example, took more than two decades before only half of all US factories had access to it. David finds similar results for the dynamo. While computers (and the internet) spread rapidly to households across the developed world, it had delayed effects on standard measures of total factor productivity. Which gave rise to Robert Solow’s quip: “We see computers everywhere but in the productivity statistics”.

Others counter by saying that we measure TFP inaccurately, that we cannot account for improvements in quality or utility. So a more intuitive question, perhaps, is to ask how the technologies of the last decade has allowed us to save time and money? The largest technological breakthroughs of the last decade that have affected our lives are arguably smart phones and tablets, and social media. Smart phones now offer access to email everywhere and a level of communication and interaction that was not possible before. Not only have access spread, costs have come down too. But how large have these gains been? Facebook and Twitter boosts networking and communication. But by how much? There are certainly large savings that accrue from using a typewriter to using Microsoft Word, but are we saving anything by shifting from Word 2007 to Word 2010 to Word 2013? And Angry Birds? A 2011 study reported that the world plays 5 million hours of Angry Birds per day.

Perhaps the software advancements over the last few years allow us to be more productive, but that that productivity allow for more leisure. As a student in my class recently remarked: Economists can now run regressions much faster than we could in the 1990s, but that just gives us more time to play around on Facebook. Is this evidence of a backward bending labour supply curve?

Of course, if we really want to see the new technologies in the productivity statistics, these technologies must infiltrate most of society. There are not many economists that run regressions in South Africa, which means that the savings from developments in Stata will be limited to a lucky(?) few. Technological improvements in mobile technology, instead, may have a far more dramatic impact. There are now 6 mobile phones for every 5 people in South Africa, which means that everyone has access to this time and cost-saving technology. (Even though mobiles reduce the costs of communication, I suspect the poor spend a larger part of their budget on phones than in the past, substituting lower utility leisure. This is just a conjecture though.) How can the poorest of the poor save time and money? Women in rural areas spend several hours a day collecting water. A simple technology – a tap – may save countless hours of labour. (Here one must tread carefully: women also use these hours away from the home to interact socially with other women. A tap in the home may save hours of hard work, but also isolate women and reduce their power within the household.) By asking the simple question – ‘What goods and services could we provide that will save the most time and money? – Nashuanomics is a great shorthand for government officials to think about the public provision of infrastructure.

And, finally, there is the constant fear that we’ve reached the end of new technologies. I’ve written about this before. As long as Nashuanomics exists though – as long as there are still savings in time and money possible – we haven’t seen the end of technological improvements. Predicting these new technologies is probably a futile exercise. One possibility is that they will be in those areas where the largest savings in time and money is possible. According to Andrew Kerr of UCT, a black commuter in South Africa spends on average 96 minutes of his day commuting. White South Africans spend 60 minutes. (This compares to 37 minutes in the EU and 49 in Europe). A better designed transport network or new technologies (trains or self-drive cars, which allows one to work will driving) would result in massive productivity (and utility, because who likes sitting in traffic?) gains in South Africa.

Flying cars are probably unrealistic. But spreading existing technologies to a greater proportion of the South African population could make a telling contribution to higher productivity, incomes, and quality of life.