(Back to the overview post)
Income growth is not a neat story, but technology pessimists would like you to think it is. Robert Gordon provides the following neat picture of ‘Growth in real GDP-per-capita, 1300-2100’ (here or unpaywalled summary, here).
The end-date alone should be enough to make us realise that this is a stylised representation, at best (and the 2008 onwards data is purely imagined, a ‘provocative fantasy’ in Gordon’s words). But even with that caveat it is a highly selective and misleading representation of growth.
In his NYT column this week, Paul Krugman has once again raised the apparent ‘growth slowdown’. In his words:
A growing number of economists, looking at the data on productivity and incomes, are wondering if the technological revolution has been greatly overhyped — and some technologists share their concern.
It’s true, a number of economists (possibly growing) definitely seem to believe this. In 2011 Tyler Cowen declared a Great Stagnation, and in 2012, Robert Gordon argued that we face six ‘headwinds’ to growth; for technologist-pessimists, Krugman quotes Peter Thiel complaining that ‘We wanted flying cars, instead we got 140 characters.’ — as if Twitter were the most impressive technology the 21st century has to offer. (‘We wanted flying cars, instead we got self-driving cars’ has less rhetorical impact.)
Like so many economic debates, I think the side you fall on has more to do with your innate disposition than a fair reading of the evidence, and so I should begin by declaring mine: I just don’t believe this hypothesis: at heart I’m a techno-optimist, and I’d need dramatic evidence to change my mind.
The economics of networks is fascinating. One recurring feature is the costly last mile. I’m borrowing this term from telecommunications, where it refers to the final part of the network, which actually reaches the consumer – e.g. the copper cables that carry your ADSL services from the exchange. Most ‘transport’ (loosely interpreted to include electricity, water, internet) benefits from economies of scale. For example, a bus fare is less than a taxi fare for the same route in part because the cost of the driver’s time is divided between 50 passengers rather than 4. For this reason, transport networks tend to be planned as (or evolve to) a branching structure – think the hub & spoke structure of US airlines – with very high capacity ‘trunk’ routes and lower capacity branches.