risk management Uncertainty

Confidence and causality

Ok, it’s a bit trite, but human behaviour is really important, and a good understanding of human behaviour is a goal for people in many different fields. Marketing, education and social policy all seek to influence our behaviour in different ways and for different purposes — that’s surely what the whole Nudge thing is all about, for a start. Economists have traditionally taken a pretty simplistic view: homo economicus seems to have a very narrow view of the utility function he (and it is often he) is trying to maximise.

Psychologists have known for some time that real life just isn’t that simple. Daniel Kahneman and Amos Tversky first published some of their work on how people make “irrational” economic choices in the early 1970s, and since then the idea of irrationality has been widely accepted. It’s now well known that we have many behavioural biases: the trouble is, what do we do with the knowledge? It’s difficult to incorporate it into economic or financial models (or indeed other behavioural models): it’s often possible to model one or two biases, but not the whole raft. Which means that models that rely, directly or indirectly, on assumptions about peoples’ behaviour can be spectacularly unreliable.

Kahneman, who won the 2002 Nobel Memorial Prize in Economics (Tversky died in 1996) has written in a recent article about the dangers of over confidence (it’s well worth a read). One thing that comes out of it for me is how much people want to be able to ascribe causality: saying that variations are just random variations, rather than being because of people’s skill at picking investments, or some environmental or social effect on bowel cancer, is not a common reaction, and indeed is often resisted.

It’s something we should think about when judging how much reliance to place on the results of our models. When I build a model, I naturally think I’ve done a good job, and I’m confident that  it’s useful. And if, in due course, it turns out to make reasonable predictions, I’m positive that it’s because of my skill in building it. But, just by chance, my model is likely to be right some of the time anyway. It may never be right again.