When the Bank of England invited me to give a talk at their workshop on macroeconomics, I wasn't sure if they wanted me to provoke (i.e. troll) them with the kind of skeptical stuff I usually write on this blog, or to talk about my own research on artificial markets and expectations. So I did both…. I'd reproduce part of my talk in a blog post - the part where I talked about DSGE models. (In other words, the provocative part.)… To be "DSGE" your model probably has to have things like infinitely far-sighted rational expectations, rapid clearing of goods markets, certain simple types of agent aggregation, etc…. As of 2013, the most "mainstream" DSGE models of the business cycle are "New Keynesian" models. The most important of these is the Smets-Wouters model, which has gained a huge amount of attention, especially from central banks, for seeming to be able to forecast the macroeconomy better than certain popular alternative approaches. If you know only one DSGE model, Smets-Wouters is the one you should know.
Anyway, my talk asked the question: "What can you do with a DSGE model?" Most people who evaluate the DSGE paradigm don't focus on this question; they either trace the historical reasons for the adoption of DSGE (the Lucas Critique, etc.), or they discuss the ways DSGE models might be improved. Instead, in my talk, I wanted to take the perspective of an alien econ prof who showed up on Earth in 2013 and tried to evaluate what human macroeconomic theorists were doing….
Forecast the economy?… But as Rochelle Edge and Refet Gurkaynak show in their seminal 2010 paper, even the best DSGE models have very low forecasting power…. In this 2013 paper, Gurkaynak et al. test the "forecast efficiency" of DSGE models, and find that their forecasts are not optimal forecasts. Also, they find that simple univariate AR models are often significantly better at forecasting things like inflation and GDP growth than the best available DSGE models! This is not an encouraging finding for the DSGE paradigm, since AR models are just about the simplest thing you can use….
Give policy advice? This is what DSGE models are "supposed to do"…. But here's the problem: To get good policy advice, you need to know which model to use, and when…. DSGE models could offer policy advice if you used an appropriate model selection criterion, and dealt carefully with a bunch of other thorny issues, AND happened to find a model that seemed to fit the data decently well under some clearly defined set of observable conditions. But I don't think we seem to be there yet.
Map from DSGE models to policy advice? OK, so it's really hard to give definitive policy advice with DSGE models. Maybe you could instead use DSGE models as maps from policymakers' assumptions to policy advice? I.e., you could say "Hey, policymaker, if you believe A and B and C, then here are the implications for policies X and Y and Z."… There's just one problem with this. DSGE models are highly stylized, meaning that it's often not possible even to figure out whether you buy an assumption or not….
Communicate ideas? DSGE models can definitely be used as a language in which to communicate ideas about how the economy works. But they are probably not the best such language. Simpler econ models, like OLG models, or even partial-equilibrium models, are much more flexible, and can be understood much more quickly by an interlocutor. DSGE models have a ton of moving parts, and it's generally very hard to see which assumptions end up causing which results. The better a model matches data or forecasts future data, the more moving parts it will generally have. This is called the "realism-tractability tradeoff"….
So, what else would you have us do?… For communicating ideas, the most popular alternatives are simpler, OLG-type models (which are, technically, DSGE, though not what we typically call "DSGE"!), and partial-equilibrium models (suggested by Robert Solow). I've seen some people use these at seminars, especially the OLG type, so I think this alternative may be catching on. For forecasting, the common alternatives are "spreadsheet" type models (Chris Sims' dismissive term) that don't assume structural-ness…. Policy advice is the thorniest question, since you need your model to be structural. For this, the main alternative that has been put forth is called "agent-based modeling". I don't know too much about this, and the name is weird, because DSGE models are also agent-based. But basically what it seems to mean is to specify a set of microfoundations (behavioral rules for agents), and then do a big simulation. The big difference between this and DSGE is that with DSGE you can write down a set of equations that supposedly govern the macroeconomy, and with ABM you can't.
So are we wasting our time making all these DSGE models, or not? My answer is: I'm not sure. So far, we don't seem to have gotten a heck of a lot of a return from the massive amount of intellectual capital that we have invested in making, exploring, and applying these models. In principle, though, there's no reason why they can't be useful…