I didn’t want to talk about this book before I had finished it: I somehow think Noah’s contrary approach has its shortcomings! The first and most important thing to say is this is a great book. Not because it gave me some huge new insight or knowledge, although I did learn quite a bit about other parts of economics, but because it had a way of putting things which was illuminating and eminently sensible. Illuminating is I think the right word: seeing my own subject in a new light, which is something that has not happened to me for a long time. There was nothing I could think of where I disagreed (which given the book’s wide scope is quite something), and plenty where the inner blogger in me said I wish I’d written that.
So who should read it? To be honest I cannot think of anyone who should not, as I think most of the material could be understood by interested non-economists. His writing style is enviable - it seems so effortless! (That’s me as blogger again.) The people who should especially read it are those who interact with economics or economists and are either unclear or distrustful about what economists are about (other social scientists particularly).
The first part of the book sets out a way of thinking about economics, and in particular to the models that economists could not live without. The key idea is that there are many valid models, and the goal is to know when they are applicable to the problem in hand. This idea has already attracted some attention, including Noah Smith’s post I linked to earlier.
I must admit when I first read it I thought well of course, doesn’t everyone understand that? I remember way back when I did my undergraduate degree, hearing a lecture from a young David Newbury I think, who said the days of big models (models of everything) were over in economics, and that today economists focused more on small but focused models, looking at particular problems or issues. But then as I read on I began to realise that I typically did not employ this knowledge into how I discuss the subject, which is exactly what Rodrik does.
One area of economics that you might think this would not apply is macro, but it does. It is routine, for example, to split issues up by time: the famous short, medium and long run. A New Keynesian model is not going to tell you much about long run growth, but a Solow growth model does not tell you much about involuntary unemployment. The point here is not that an all encompassing model could not be built - it could, and sometimes individuals or institutions try to do that - but if it was it would be unwieldy, and we would want to break it up in our minds to understand how it works. (I used a related idea of ‘theoretical deconstruction’ in an EJ paper some time ago.) An important point that follows from that is that although we work with different models, it is important that we know how they interconnect, or at least how they relate to each other.
Rodrik spends a good part of the book describing how you ‘navigate among models’. He warns that these methods are as much a craft as a science. Many have picked up on that, presuming that this is something that a proper science would not do. But as I have often said, the best analogies for economics are with medicine rather than physics. When a doctor diagnoses an illness based on symptoms, they could also be said to be using craft rather than science.
Let me give you a simple example from macro. How do we know if most economic cycles are described by Real Business Cycles (RBC) or Keynesian dynamics. One big clue is layoffs: if employment is falling because workers are choosing not to work we could have an RBC mechanism, but if workers are being laid off (and are deeply unhappy about it) this is more characteristic of a Keynesian downturn. This simple test beats any amount of formal econometric comparison. Craft maybe, but not a very difficult craft in this case.
Lots of people get hung up on the assumptions behind models: are they true or false, etc. An analogy I had not seen before but which I think is very illuminating is with experiments. Models are like experiments. Experiments are designed to abstract from all kinds of features of the real world, to focus on a particular process or mechanism (or set of the same). The assumptions of models are designed to do the same thing.
Although I found that Rodrik’s discussion of how you select the right model familiar and sensible, it remains vague in the philosophical sense, as Emrah Aydinonat points out. But he also finds them instructive, so they are a work in progress that hopefully philosophers and economists can interact on. (It is worth passing on a point which Aydinonat makes, which is that unlike many economists who write about methodology, Rodrik has read the relevant literature!) Thinking about alternative models that differ in their applicability to particular problems is certainly a more insightful approach than the kind of Popperian stuff that most economists remember.
If this makes the book sound like a philosophical tome, that is quite wrong. It is a very readable account of how economists do what they do: the philosophical grounding is there but it is not intrusive, and instead the book focuses on practical examples. What Rodrik then does with this perspective of many models is to think about a lot of the issues outsiders have about economists: how ideological are they, for example. Towards the end he discusses what went wrong in the financial crisis. Once again the perspective is illuminating: there were for sure models that said a crisis should not happen, but also plenty of models around at the time that explained pretty well why it could. The mistake many economists made was to choose the wrong models, and he discusses why that might have happened. This perspective shows why a simple ‘the crisis shows economics must be flawed’ misses the point.
Hopefully that is enough to make you read this book.