The human brain is wired to recognize patterns, which it then organizes into higher level models and theories and beliefs, which in turn it uses to explain the past and present, and to predict the future. Models offer the consolation of rationality and understanding, which provide a sense of control. All of this is foundational to classical economic theory, which assumes we approach commerce equipped with an internal rational scale that weighs supply and demand, cost and benefit, and that we then act according to our assessment of what we give for what we get back. This assumption of an internal calculus has caused mathematical modeling to reign supreme in the practice of economics.
The trouble is, humans aren’t as innately calculating as classical economics would like to believe — so says David Graeber, professor of anthropology at the London School of Economics, in his new book Bullshit Jobs: :
“According to classical economic theory, homo oeconomicus, or “economic man” — that is, the model human being that lies behind every predication made by the discipline — is assumed to be motivated by a calculus of costs and benefits.
“All the mathematical equations by which economists bedazzle their clients, or the public, are founded on one simple assumption: that everyone, left to his own devices, will choose the course of action that provides the most of what he wants for the least expenditure of resources and effort.
“It is the simplicity of the formula that makes the equations possible: if one were to admit that humans have complicated emotions, there would be too many factors to take into account, it would be impossible to weigh them, and predictions would not be made.
“Therefore, while an economist will say that while of course everyone is aware that human beings are not really selfish, calculating machine, assuming they are makes it possible to explain
“This is a reasonable statement as far as it goes. The problem is there are many dimensions of human life where the assumption clearly doesn’t hold. — and some of them are precisely in the domain of what we like to call the economy.”
Economics’ reliance on mathematics has been a topic of lively debate for a long time:
“The trouble… is that measurement and mathematics do not guarantee the status of science – they guarantee only the semblance of science. When the presumptions or conclusions of a scientific theory are absurd or simply false, the theory ought to be questioned and, eventually, rejected. The discipline of economics, however, is presently so blinkered by the talismanic authority of mathematics that theories go overvalued and unchecked.
“In 1886, an article in Science accused economics of misusing the language of the physical sciences to conceal ‘emptiness behind a breastwork of mathematical formulas’. More recently, Deirdre N McCloskey’s The Rhetoric of Economics(1998) and Robert H Nelson’s Economics as Religion (2001) both argued that mathematics in economic theory serves, in McCloskey’s words, primarily to deliver the message ‘Look at how very scientific I am.’
“After the Great Recession, the failure of economic science to protect our economy was once again impossible to ignore. In 2009, the Nobel Laureate Paul Krugman tried to explain it in The New York Times with a version of the mathiness diagnosis. ‘As I see it,’ he wrote, ‘the economics profession went astray because economists, as a group, mistook beauty, clad in impressive-looking mathematics, for truth.’ Krugman named economists’ ‘desire… to show off their mathematical prowess’ as the ‘central cause of the profession’s failure’.
“The result is people… who trust the mathematical exactitude of theories without considering their performance – that is, who confuse math with science, rationality with reality.
“There is no longer any excuse for making the same mistake with economic theory. For more than a century, the public has been warned, and the way forward is clear. It’s time to stop wasting our money and recognise the high priests for what they really are: gifted social scientists who excel at producing mathematical explanations of economies, but who fail, like astrologers before them, at prophecy.”
Economists may bristle at being compared to astrologers, but as we have seen, their skill at prediction seems about comparable.
In the coming weeks we’ll look at other models emerging from the digital revolution, consider what they can tell us that classical economic theory can’t, and how they are affecting the world of work.