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This post is for economists and/or econ bloggers and/or people with opinions about this issue of mathematical modeling in macroeconomics. So that might be one or two of my usual readers (I won't mention what that is in percentage terms).
Noah Smith has a good post about some problems with DSGE models, particularly when they are solved using linearization methods (I like Smith's blog; I don't like his comment sections as much). He is not the only person with complaints about the workhorse approach to macroeconomic thinking. Stephen Gordon also has a very nice post, again mainly about linearized DSGE. My post is not about Smith's or Gordon's notes; it's a more general comment on this occasionally popular topic.
I don't want to wade too deeply into this debate for the following reasons:
- Much of the debate is over my head--not technically speaking, but in terms of knowing how to do science well.
- The blogosphere is a poor place to have this debate.
- Many of the people involved (but not Smith or Gordon) probably don't know enough about DSGE models to draw useful conclusions (i.e., if you don't know how to build or solve one, you may be unable to make a highly productive contribution to the debate).
- Political preferences are involved, which makes it hard to tell whether methodology is really the issue.
- I don't have a strong enough opinion to justify dragging myself and charitable readers through the weeds, aside from thinking that DSGE models are useful tools.
- I think linearized models are harder to defend than those with global solutions.
But here's what I will say:
- Not all DSGE models are solved with linearization. Yes, the New Keynesian ones typically are, and those are the ones informing policy the most--and there aren't a lot of great ways around that. But lots of DSGE models can be solved globally without using Taylor-type approximations, in which case approximation error is far smaller (and is basically determined by Curse of Dimensionality and/or numerical precision issues).
- I don't like it when people act like we face a big choice between using DSGE or doing empirical work. That's a false dilemma. First, why not do both? Second, that distinction does not always exist. This deserves its own post, but for now: DSGE models are just systems of equations, and they can be estimated; and it's not obvious to me that estimating a DSGE system is any more silly than assuming the world resembles the atheoretic linear functional form we use in purely empirical work. I think we all know that there is no such thing as simply "letting the data speak."
- In this debate, and in debates about formal modeling in general, some critics tend to make the mistake of thinking that a modeler believes that the assumptions and simplifications of the model are true in the real world. They also like to accuse macroeconomists of thinking they are physicists. Those are straw men. Take your straw man and go home.
- We must get econ pundits to understand that we're all using models, including non-economist bloggers, even if they're not written down as mathematical expressions. Writing a model down in its entirety so that its assumptions are made explicit and its internal workings can be examined by anyone is an act of intellectual humility. It is baffling to me that people who write down their models formally so we can all argue about them are supposedly worse and more arrogant than those who think they can identify a narrative model's assumptions and keep it internally consistent.
- There are limits to what the "credibility revolution" techniques from applied micro can do for macro. There is little or no clean identification to be had at the aggregate level, and extrapolating empirical results from small regions to the aggregate level can be misleading. These approaches can definitely shed light on macro topics (the excellent Mian and Sufi papers come to mind), but I think it's a mistake to assume that they are sufficient for all macro questions.
- In typical empirical work and heuristic/narrative theorizing, it's really difficult to avoid partial equilibrium reasoning. A DSGE model, even a very simple one, has more moving parts than my mind alone can keep track of, and it forces agents to obey resource constraints in a way that is really difficult without formality. You don't have to believe literally in "general equilibrium" to appreciate how GE models allow you to think about feedback mechanisms.
A recent example: Last week, I was messing with an augmented version of this DSGE model (in my version, there is also a corporate sector and some other stuff). Households choose whether to be workers or entrepreneurs. I was messing with the parameter that governs entrepreneurial productivity (specifically, the scale parameter of the Pareto TFP process). I noticed that sometimes when I increase that parameter and solve the model, the share of households that choose to be entrepreneurs fell. My initial expectation was that increasing how much entrepreneurs can produce with a given level of inputs would make entrepreneurship more enticing (relative to earning a wage) and cause more people to do it. But that's partial equilibrium reasoning. I pushed on the model a little and figured out that it depends on the wealth distribution and capital intensity. Roughly speaking, if entrepreneurs consume most of their new income (rather than saving it), and if production is more capital intensive, entrepreneurship will rise: higher TFP raises capital demand, and people don't save enough to mitigate the upward pressure on the interest rate; and wages and interest rates move in opposite directions when production is Cobb-Douglas-esque, so worker income falls while entrepreneurial income rises. On the other hand, if people save most of their new income and production is less capital intensive, the supply of savings can rise enough to mitigate upward pressure on the interest rate (and downward pressure on the wage). It is possible for wages to rise enough to induce some people to abandon entrepreneurship and become workers.
A lot of people would have seen that coming, and I probably would have if I'd thought it through carefully. But there were other things on my mind. The point is that the model forced me to consider the implications of my ideas and to recognize how conditions in one part of the economy affect things that happen elsewhere. This kind of discipline is important when arguing about the potential effects of this or that policy.
I think most people, including me, are used to thinking in partial equilibrium. DSGE models, at the very least, can force us to think a little more broadly.
I don't see why we can't allow for a wide range of methodological approaches in economics, and even in macroeconomics. I suspect that part of the problem is that recent events have raised everyone's level of interest in macroeconomics. People working in other economics fields, along with a lot of noneconomists, want to get in on the action and be part of the conversation. That's a good thing. But some of them can look a bit like Monday Morning Quarterbacks, making big claims about the failure of the field and recommending all sorts of changes to the standard toolkit as if macro can be approached in the same way as their home field. I think it would be a bad idea to discard the DSGE framework, even as I also think that drill-down empirical work is increasingly important (and possible) in macroeconomics (as should be evident by my other posts).
I also suspect that, for a few people, antipathy towards workhorse macro models is driven by politics. This debate often arises in the context of discussions about fiscal multipliers (ha!) or optimal tax policy, and it sometimes appears that people who don't like the political implications of a paper respond to it by rejecting the entire modeling approach. If that's going on, well, we shouldn't let it affect real economics work.