Economics needs a scientific revolution

So says Jean-Philippe Bouchaut in a Nature (subscription) essay:

Compared with physics, it seems fair to say that the quantitative success of the economic sciences has been disappointing…Of course, to paraphrase Isaac Newton, modelling the madness of people is more difficult than modelling the motion of planets. But statistical regularities should emerge in the behaviour of large populations, just as the law of ideal gases emerges from the chaotic motion of individual molecules. To me, the crucial difference between modelling in physics and in economics lies rather in how the fields treat the relative role of concepts, equations and empirical data.

Classical economics is built on very strong assumptions that quickly become axioms: the rationality of economic agents (the premise that every economic agent, be that a person or a company, acts to maximize his profits), the ‘invisible hand’ (that agents, in the pursuit of their own profit, are led to do what is best for society as a whole) and market efficiency (that market prices faithfully reflect all known information about assets), for example.

…

Physicists, on the other hand, have learned to be suspicious of axioms. If empirical observation is incompatible with a model, the model must be trashed or amended, even if it is conceptually beautiful or mathematically convenient. So many accepted ideas have been proven wrong in the history of physics that physicists have grown to be critical and queasy about their own models.

…

The supposed omniscience and perfect efficacy of a free market stems from economic work done in the 1950s and 1960s, which with hindsight looks more like propaganda against communism than plausible science. In reality, markets are not efficient, humans tend to be over-focused in the short-term and blind in the long-term, and errors get amplified, ultimately leading to collective irrationality, panic and crashes. Free markets are wild markets.

…

Reliance on models based on incorrect axioms has clear and large effects. The Black–Scholes model, for example, which was invented in 1973 to price options, is still used extensively. But it assumes that the probability of extreme price changes is negligible, when in reality, stock prices are much jerkier than this. Twenty years ago, unwarranted use of the model spiralled into the worldwide October 1987 crash; the Dow Jones index dropped 23% in a single day, dwarfing recent market hiccups. Ironically, it was the very use of a crash-free model that helped to trigger a crash.

…

Surprisingly, classical economics has no framework through which to understand ‘wild’ markets, even though their existence is so obvious to the layman. Physics, on the other hand, has developed several models that explain how small perturbations can lead to wild effects. The theory of complexity shows that although a system may have an optimum state, it is sometimes so hard to identify that the system never settles there. This optimum state is not only elusive, it is also hyper-fragile to small changes in the environment, and therefore often irrelevant to understanding what is going on.

…

The prerequisites for more stability in the long run are the development of a more pragmatic and realistic representation of what is going on in financial markets, and to focus on data, which should always supersede perfect equations and aesthetic axioms.