In the wake of Paul Krugman's post on Wynne Godley and hydraulic modelling, I've had a number of discussions, including this one with Phil Pilkington, on the role of modelling in economics.
If you've read a few of my posts, you will know that I use models a lot. This in part a reflection of my laziness - I'm not very good at reading anyone else's stuff, if it extends to more than a page without equations in it. I've always preferred to work things out for myself - an approach that has proved very successful for me in various aspects of life. If I can't figure something out in my head, I scribble down a few diagrams or a balance sheet, and if that's not enough I build a little model.
These sort of models are intended to help me develop my own ideas about how such things work. Ideally they should be stripped of everything other than the point I want to look at - as simple as possible whilst retaining the complexity to push my understanding a bit further. The models I have included in some of my posts are examples of this. They show things where I have a sense of how it works, but I need to see it in action to really get my head round it.
The type of model is driven by the issue I am concerned with. But on the whole, I like models that I can relate to the things we observe in a real economy. I like to think that I could take any of these models and, maybe with a little tweaking, put some realistic numbers on them. I wouldn't expect to get good forecasts or anything by doing that - it would all be about understanding how it really works. Or doesn't. Sometimes the conclusion is not what you expected.
I also look at more detailed models. Again, I have on this blog some details on my UK macro model. The purpose here is different, but not a lot so. It is still about understanding. A lot of it is simply the learning that comes through construction of a model. Often simply having to organise and make sense of the data reveals important insights. Otherwise the benefit comes from running experiments with the model. With simple theoretical models, we are trying to understand a very specific mechanic. With bigger, more complete models, the purpose is more general. We are testing our intuitions, to see if everything works to together as we believe. Often, this will draw out interesting effects that would have been hard to spot otherwise. It's all about having a tool to aid our thinking - a grand version of a supply and demand diagram.
However, I think it is very important to recognise the limits to what models can do. It is easy to get seduced into thinking that a model is some kind or oracle. This is a mistake. Any model is necessarily a huge simplification. The results depend critically on the assumptions made. However complex and detailed they are, all they really reflect is the theories of the modeller.
This doesn't invalidate the benefits I have talked about, but it means we must be careful how we use them. They can help inform and quantify our judgements, but that is all. If we don't understand the results, they are useless. The model is not revealing any new truth, it is simply reflecting our own ideas, helping us to visualise how a massively complex system fits together.
I appreciate that there are economists have no interest in models. That's fine - many of them I have great respect for, and the profession benefits greatly from having people take different approaches. For me, the use of models is invaluable. One of the things that most impressed me about Wynne Godley was his ability to combine economic theory with a deep insight into the real data. His work in empirical modelling was key to that and it is the reason I do economics the way I do.