Here We Go Again Once More on DSGE Models

A day may come when the old guard of macroeconomics convinces this starry eyed graduate student to give up his long battle against the evils of DSGE models in macroeconomics. But it is not this day.

Shockingly, it seems like many top economists have not yet discovered my superior critique of macroeconomics (because obviously if they had they would be convinced to stop defending DSGE). Instead, we get statements like:

Macroeconomic policy questions involve trade-offs between competing forces in the economy. The problem is how to assess the strength of those forces for the particular policy question at hand. One strategy is to perform experiments on actual economies. Unfortunately, this strategy is not available to social scientists. The only place that we can do experiments is in dynamic stochastic general equilibrium (DSGE) models

That’s from the recent paper “On DSGE Models” written by three prominent DSGE modelers, Lawrence Christiano, Martin Eichenbaum, and Mathias Trabandt (who I’ll call CET). As you might suspect, I disagree. And I expect their defense will be about as effective at shifting the debate as my critique was (and since my readership can be safely rounded down to 0, that’s not a compliment). Unlike Olivier Blanchard’s recent thoughts on DSGE models, which conceded that many of the criticisms of DSGE models actually contained some truth, CET leave no room for alternatives. It’s DSGE or bust and “people who don’t like dynamic stochastic general equilibrium (DSGE) models are dilettantes.” So we’re off to a good start.

But let’s avoid the ad hominem as much as we can and get to the economics. Beyond the obviously false statement that DSGE models are the only models where we can do experiments, CET don’t offer much we haven’t heard before. Their story is by now pretty standard. They begin by admitting that yes, of course RBC models with their emphasis on technology shocks, complete markets, and policy ineffectiveness were woefully inadequate. But we’re better now! Macroeconomics has come a long way in the last 35 years! They then proceed to provide answers to the common criticisms of DSGE modeling.

Worried DSGE models don’t include a role for finance? Clearly you’ve never heard of Carlstrom and Fuerst (1997) or Bernanke et al. (1999) which include financial accelerator effects. Maybe you’re more concerned about shadow banking? Gertler and Kiyotaki (2015) have you covered. Zero lower bound? Please, Krugman had that one wrapped up all the way back in 1998. Want a role for government spending? Monetary policy? Here’s 20 models that give you the results you want.

Essentially, CET try to take everything that critics of DSGE models say is missing and show that actually many researchers do include these features. This strategy is common in any rebuttal to attacks on DSGE models. Every time somebody points out a flaw in one class of models (representative agent models, rational expectations models, models that use HP-filtered data, complete markets, etc.) they point to another group of models that purports to solve these problems. In doing so they miss the point of these critiques entirely.

The problem with DSGE models is not that they are unable to explain specific economic phenomenon. The problem is that they can explain almost any economic phenomenon you can possibly imagine and we have essentially no way to decide which models are better or worse than others except by comparing them to data that they were explicitly designed to match.  It’s true there were models written before the recession that contained features that looked a lot like those in the crisis. We just had no reason to look at those models over the hundreds of other ones that had entirely different implications.

Whatever idea you can dream up, you can almost be sure that somebody has written a DSGE model to capture it. Too much of what DSGE models end up being is mathematical justifications for ideas people have already worked out intuitively in their minds (often stripped of much of the nuance that made the idea interesting in the first place). All the DSGE model itself adds is a set of assumptions everybody knows are false that generate those intuitive results. CET do nothing to address this criticism.

Take CET’s defense of representative agent models. They say “It has been known for decades that restrictions like (1)[the standard Euler equation] can be rejected, even in representative agent models that allow for habit formation. So, why would anyone ever use the representative agent assumption? In practice analysts have used that assumption because they think that for many questions they get roughly the right answer.”

Interesting. If they already knew the right answer, what was the model for again? Everybody agrees the assumptions are completely bogus, but it gets the result we wanted so who cares? That’s really the argument they want to make here?

But this is the game we play. Despite CET’s claims to the contrary, I am almost certain that most macroeconomics papers begin with the result. Once they know what they want to prove, it becomes a matter of finagling a model that sounds somewhat like it could be related to how an actual economy works and produces the desired result (and when this task can’t be done, it becomes a “puzzle”). The recession clearly demonstrated the importance of finance on the economy? Simple. Let’s write a DSGE model where finance is important. If in the end the model actually shows that finance is unimportant rewrite it until you get the answer you want.

Almost every DSGE macroeconomics paper follows pretty much the same outline. First, they present some stylized facts from macroeconomic data. Next, they review the current literature and explain why it is unable to fit those facts. Then they introduce their new model with slightly different assumptions that can fit the facts and brag about how well the model (that they designed specifically to fit the facts) actually fits the facts.  Finally they do “experiments” using their model to show how different policies could have changed economic outcomes.

In my view, macroeconomics should be exactly the opposite. Don’t bother trying to exactly match macroeconomic aggregates for the United States economy with a model that looks nothing like the United States economy. Have a little more humility. Instead, start by getting the assumptions right. Since we will never be able to capture all of the intricacies of a true economy, the model economy should look very different from a real economy. However, if the assumptions that generate that economy are realistic, it might still provide answers that are relevant for the real world. A model that gets the facts right but the assumptions wrong probably does not.

I spent 15 posts arguing that the DSGE paradigm gets the assumptions spectacularly wrong. CET provide many examples of people using these flawed assumptions to try to give us answers to many interesting questions. They do not, however, provide any reason for us to believe those answers.

But, then again, I am but a dilettante, so you probably shouldn’t believe me either.

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