The three most familiar economic statistics are all measures of change: inflation, the growth of gross domestic product, and the daily rise or fall in the price of shares. Even so, they do not begin to capture the mad churn of the economy: the growth and bankruptcy of companies; the millions of sackings and hirings, which unemployment statistics barely summarise; the movement of goods and services around the world and the ebb and flow of consumer fads. Under the circumstances, it is strange that economists do not have a satisfactory way of talking about change; yet we do not.
As any undergraduate student of economics knows, both microeconomists and macroeconomists tend to describe change in the same way that an advertisement for washing powder does: “before” and “after”. When oil cost $20 a barrel the economy looked like this; now oil costs $100 a barrel, the economy looks like that. Quite how the process of change occurred – or how quickly – is a problem glossed over in the textbooks and most journals.
That is worrying. Perhaps it does not even make sense to compare two static “before” and “after” states; perhaps “during” is everything. In fairness, economists are not blind to this problem. Back in 1923 John Maynard Keynes warned that “Economists set themselves too easy, too useless a task if in tempestuous seasons they can only tell us that when the storm is long past the ocean is flat again.” He was not the only one with reservations. Yet identifying the problem is easier than solving it, at least using the mathematical tools with which economists are familiar.
Several popular books have argued that economists could learn about dynamics from approaches developed in the sciences. Malcolm Gladwell, a journalist, wrote an entire book – The Tipping Point – devoted to the idea that innovations, fashions and other ideas spread through society in much the same way as a disease does. Philip Ball, a science writer, attacked economics more directly in his book, Critical Mass, arguing that economists should learn from physicists’ understanding of dynamic processes, such as phase transitions. (An example of a phase transition is when cold water suddenly turns to ice. It turns out that, for example, traffic flows can exhibit phase transitions.) Still others advise economists to look to models of evolutionary dynamics.
This is all sage advice, but the details matter. Duncan Watts, who studies dynamic processes on networks, has discovered that neither Ball nor Gladwell has the whole story. Ideas can spread through an economy like a disease or like a phase transition – it all depends on how the social networks along which the ideas flow are connected.
In The Tipping Point, Gladwell focused attention on highly connected individuals – the “connectors” or the “influencers” – who were able to spread anything from a fashion trend to a new software release. He was influenced by epidemiologists who already knew that diseases often spread through such “connectors”. But Watts points out that ideas can flow along many more connections than diseases do. That implies that the epidemiological model does not apply, and a new trend will either ripple through the economy like a near-instantaneous phase transition, or it will ripple nowhere at all because it never gets started. And in either case, the “connectors” will be irrelevant, because we’re all so interconnected anyway.
My guess is that it is just a matter of time before economists embrace methods from other disciplines in an effort to understand dynamic processes better than we do.
But it would be a shame if we looked only to physicists, chemists and biologists for advice; something would be missing if we did. Duncan Watts, after all, is a sociologist.
Also published at ft.com.