It’s often said by critics of economics that the problem is economists have physics envy: they want to describe the economy using models that are over-complicated in the mathematics, mimicking classical physics, and under-sophisticated in its understanding of how humans actually make choices. But in [amazon_link id=”1408827379″ target=”_blank” ]Forecast: What Physics, Meteorology and the Natural Sciences Can Teach Us About Economics[/amazon_link] by Mark Buchanan argues that economists haven’t been paying enough attention to physical.

[amazon_image id=”1408827379″ link=”true” target=”_blank” size=”medium” ]Forecast: What Physics, Meteorology, and the Natural Sciences Can Teach Us About Economics[/amazon_image]

He makes the argument in the context of financial economics and its discrediting by the financial crisis. I find it a wholly persuasive thesis. Rational choice theorising just cannot account for the data on financial markets – the numerous self-reinforcing large price movements without specific causes, the long persistence in the absolute size of price movements, the fractal character of the movements on annual, monthly, daily, hourly, nano-secondly timescales. However, models from statistical physics can do so. The empirics of financial markets are similar to those of earthquakes, for example, well described by power laws. Economists should be using these tools as their starting point for theorising rather than starting with theories that fit the data about as well as Cinderella’s glass slipper fits the feet of the Ugly Sisters. It astonishes me that so many economists are so resistant to believing the evidence of the data – as I wrote describing here last autumn’s ESRC symposium on macroeconomics and the reception physicist J.P.Bouchaud got from some of the other participants.

Forecast is a useful and very accessible guide to the physics models, although this is not untrodden territory in pop science. For example, Philip Ball’s [amazon_link id=”0099457865″ target=”_blank” ]Critical Mass[/amazon_link] covers it too. There were a few points when I felt it over-claimed. For example, Mr Buchanan compares events in California’s electricity market in summer 2000 to the financial market events of 1998 or 2008, when it turned out later that Enron traders were manipulating the market. From this he concludes: “Blind faith in the benefits of privatization has had negative social consequences, including the deterioration of overall social trust, the dissolution of traditional non-market relations based on social norms and the replacement of cultural incentives to ‘do a good job’ with purely monetary incentives.” This is a perfectly valid line of argument, made by many other people – [amazon_link id=”0374533652″ target=”_blank” ]Michael Sandel[/amazon_link] most prominently of late – but it is a different argument entirely from the rest of the book, and I think isn’t supported here. There are one or two other points where the book canters through a separate area – such as behavioural economics and fast versus slow thinking – interesting but not related to the main argument.

For the main point here is about the prevalence of disequilibrium in economies, and the consequent inappropriateness of equilibrium as the starting point for economic modelling; the inadequacy of comparative statics in a dynamic world; and the role of social influence in markets. There is a very interesting section on the way the ‘wisdom of crowds’ is valid for independent decisions but destroyed when people know what others think, when it is replaced by the ‘unwarranted confidence of crowds’.

The most intriguing point the book raised for me concerned the predictability of financial market prices. Markets seem to have two phases of behaviour, like water versus ice, and the transition from one to the other is particularly interesting. “When the number of participants is smaller than a certain threshold… the market always has some predictability in its movements,” Buchanan writes of some experimental research (by Yi-Cheng Zhang and Damian Challet, written up in the book [amazon_link id=”0198566409″ target=”_blank” ]Minority Games: Interacting Agents In Financial Systems[/amazon_link]). Beyond a threshold number of people, the predictability vanishes. The number is related to the amount of history participants take into account in their expectations of the future – beyond that “the space of strategies becomes effectively covered or crowded.” There will be somebody in the market who will pounce on any predictable pattern to arbitrage it, and any predictability vanishes.

Economists who have already read about complexity economics – say in Paul Ormerod’s [amazon_link id=”0571279201″ target=”_blank” ]Positive Linking[/amazon_link] or his older [amazon_link id=”0465053564″ target=”_blank” ]Butterfly Economics[/amazon_link], or Alan Kirman’s [amazon_link id=”0415594243″ target=”_blank” ]Complex Economics[/amazon_link] or Benoit Mandelbrot’s [amazon_link id=”1846682622″ target=”_blank” ]The Misbehaviour of Markets[/amazon_link] – will find much of the material in Forecast familiar. But even they will find some new insights. Economists who haven’t paid much attention to these areas should read this book and apply some of our profession’s (supposed) newly-found humility to its argument. And this is a very accessible book for non-economists (and indeed for non-physicists), who will find it interesting and wonder why on earth some economists resist learning across the disciplinary boundary.