This title harks back to one of the books that have influenced me most: Blanchard and Fischer’s Lectures on Macroeconomics. That textbook was largely in the mould of modern microfounded macroeconomics, but chapter 10 was not, and it was entitled ‘Some Useful Models’. One of their useful models is IS-LM.
The role of such models in an age where journal papers in macro theory are nearly always microfounded DSGE models is problematic. Paul Krugman has brought this issue to the forefront of debate, starting with his ‘How Did Economists Get It So Wrong?’ piece in 2009. His view has been recently stated as follows: “That doesn’t mean that you have to use Mike’s [Woodford] model or something like it every time you think about policy; by and large, ad hoc models like IS-LM are actually more useful, in my judgment. But you probably do want to double-check your logic using fancier optimization models.”
This view appears controversial. If the accepted way of doing macroeconomics in academic journals is to almost always use a ‘fancier optimisation’ model, how can something more ad hoc be more useful? Coupled with remarks like ‘the economics profession went astray because economists, as a group, mistook beauty, clad in impressive-looking mathematics, for truth’ (from the 2009 piece) this has got a lot of others, like Stephen Williamson, upset. I think there are a lot of strands here, many of which are interesting.
The issue I want to discuss now is very specific. What is the role of the ‘useful models’ that Blanchard and Fischer discuss in chapter 10? Can Krugman’s claim that they can be more useful than microfounded models ever be true? I will try to suggest that it could be, even if we accept the proposition (which I would not) that the microfoundations approach is the only valid way of doing macroeconomics. If you think this sounds like a contradiction in terms, read on. The justification I propose for useful models is not the only (and may not be the best) justification for them, but it is perhaps the one that is most easily seen from a microfoundations perspective.
First we must find a new name for these ‘useful’ models. They are sometimes described as ‘policy models’, but that is not a very good name because microfounded models are also used to analyse policy. Let me call them ‘aggregate models’. I think this term is useful, because the defining characteristic of the models I want to talk about is that they start with aggregate macro relationships. Like an IS curve. Microfounded models start with microeconomics, like an optimising representative consumer. I do not want to call aggregate models ‘ad hoc’, because the meaning of ad hoc is not well defined.
The typical structure of a microfounded model involves two stages. In the first stage the microfoundations are set out, individual optimisation problems solved, and aggregation assumptions made. We set out a particular world, perhaps a unique world, in all the detail required for the task in hand. This first stage may also include deriving an aggregate welfare function from individual utility. This leads to a set of aggregate relationships. The second stage involves using these aggregate relationships in some way – to find an optimum policy for example. In aggregate models we only have the second stage. A good paper of either type will often go further, and attempt to suggest (perhaps even show) what it is about the aggregate model that gives us the key results of the paper. Let us call this the critical features of the aggregate model.
Put this way, it looks as if microfounded models must be the superior tool – we get more information in the form of the model’s microfoundations. In particular, we establish that at least one microfounded support exists for the aggregate model we use in the second stage. If we start with an aggregate model, it is possible that no such microfounded support exists for that model. If that could be proved, the usefulness of that aggregate model is completely diminished from a microfoundations perspective. A more realistic case is if we cannot for the moment find any potential microfoundation for such an aggregate model (this is what some people mean by ad hoc), or the only microfoundation we can find is a little odd. In that case the usefulness of the aggregate model is highly questionable.
But suppose there is in fact more than one valid microfoundation for a particular aggregate model. In other words, there is not just one, but perhaps a variety of particular worlds which would lead to this set of aggregate macro relationships. (We could use an analogy, and say that these microfoundations were observationally equivalent in aggregate terms.) Furthermore, suppose that more than one of these particular worlds was a reasonable representation of reality. (Among this set of worlds, we cannot claim that one particular model represents the real world and the others do not.) It would seem to me that in this case the aggregate model derived from these different worlds has some utility beyond just one of these microfounded models. It is robust to alternative microfoundations.
In these circumstances, it would seem sensible to go straight to the aggregate model, and ignore microfoundations. Well, not quite – it would be good to have a sentence referring to the paper that shows at least one of these microfoundations. A classic example of what I have in mind here is Clarida, Gali and Gertler (1999) Journal of Economic Literature. If an aggregate model can be derived from a number of different microfoundations, then we actually appear to restrict the generality of what we are doing by choosing one derivation and then working with this particular microfounded model. I think this possibility is stronger still if we think about the critical features of an aggregate model – the things that generate the results we focus on.
I suspect it is this robustness aspect of aggregate models that makes them attractive to some macroeconomists. Why restrict yourself to one particular microfoundation – and let’s be honest, waste time going through yet another derivation of Euler equations and the like? Why not go straight to the set of aggregate relationships that contain the critical features we need for the problem at hand?
Now there is a danger in this approach. That sentence referencing the paper where the aggregate model is derived from microfoundations may not be written, and then further along the line it turns out that the aggregate model being used misses out something important because microfoundations were being ignored. Krugman acknowledges that danger in the last sentence of the quote I started with. However, it seems a little strong to suggest that to avoid such mistakes we should always do the full microfoundations thing.
So my claim is in many ways quite a weak one. Some aggregate models contain critical features that can be derived from a number of different microfoundations. In that situation, it is natural to want to work with these aggregate models, and to describe them as useful. We could even say that they are more useful, because they have a generality that would be missing if we focused on one particular microfoundation.