Bretton Woods: Modelling and Economics
September 30, 2011 Leave a comment
The institute for new economic thinking has a video on modelling and economics. It is considerably more interesting that it might have been before the financial crises beginning 2007. I make a few points from a mathematical perspective.
- There is a tendency to apply a ‘canned’ model, varying a few parameters, rather then to engage in genuine modelling. The difference makes a difference. In the run-up to the crises of 2007 on there was wide-spread agreement on key aspects of economic theory and some fixed models became to be treated as ‘fact’. In this sense, modelling had stopped. So maybe proper modeling in economics would be a useful innovation? 😉
- Milton Friedman distinguishes between models that predict well short-term) and those that have ‘realistic’ micro-features. One should also be concerned about the typical behaviours of the model.
- One particularly needs, as Keynes did, to distinguish between short-run and long-run models.
- Models that are solely judged by their ability to predict short-run events will tend to forget about significant events (e.g. crises) that occur over a longer time-frame, and to fall into the habit of extrapolating from current trends, rather than seeking to model potential changes to the status quo.
- Again, as Keynes pointed out, in complex situations one often cannot predict the long-run future, but only anticipate potential failure modes (scenarios).
- A single model is at best a possible model. There will always be alternatives (scenarios). One at least needs a representative set of credible models if one is to rely on them.
- As Keynes said, there is a reflexive relationship between one’s long-run model and what actually happens. Crises mitigated are less likely to happen. A belief in the inevitable stability of the status quo increases the likelihood of a failure.
- Generally, as Keynes said, the economic system works because people expect it to work. We are part of the system to be modelled.
- It is better for a model to be imprecise but reliable than to be precisely wrong. This particularly applies to assumptions about human behaviour.
- It may be better for a model to have some challenging gaps than to fill those gaps with myths.
Part 2 ‘Progress in Economics’ gives the impression that understanding crises is what is most needed, whereas much of the modelling video used language that seems more appropriate to adding epicycles to our models of the new status quo – if we ever have one.