Tuesday, January 17, 2017

A good series on macro and microfoundations

Brad DeLong linked to (what I think is) the third in a series of posts at Mean Squared Errors. At least I think they make a fine series:

  1. Houdini's Straightjacket
  2. The Microfoundations Hoax
  3. The Next New Macro

The story might be profitably read in reverse order as well. The main ideas are that microfoundations were adopted in a panic, essentially take the form of a straitjacket that the modern economist frees herself from in clever papers, and are largely useless at constraining the form of macroeconomic theories.

I actually used the straitjacket metaphor before myself. In fact, I've talked about a lot of the ideas mentioned in the three posts, which is why I found JEC (the blog's author) to be a kindred spirit [1]. However, JEC is a much better writer than I am. And because of that, I wanted to steal (with credit!) a series of things I wish I had said myself.

First, there's a great passage in The Microfoundations Hoax that I'd like to quote at length:
So when critics denigrated the [macroeconomic] models of the early '70's as "ad hoc," they had a pretty serious point. 
But what was the solution to all of this ad hoc-ery?  Where were we to look for the all-important virtue of discipline?   Ideally, in social science as in physical science, the source of discipline is data.  If you want to tell the difference between a true theory and a false one, you ask reality to settle the question.  But that was the heart of the problem: with so little data, all the models looked equally good in-sample, and no model looked especially good out-of-sample.  Discipline, if there was to be any, would have to come from theory instead.  And "microfoundations" was put forward as one form of theoretical discipline. 
The idea certainly sounded good: rather than simply making up relationships between aggregate variables like interest rates, output, unemployment, and inflation, we should show how those relationships arise from the behavior of individuals.  Or, failing that, we should at least restrict the relationships in our macro models to those which are consistent with our understanding of individual behavior.  For surely our standard assumptions about individual behavior (basically: people do the best they can under the circumstances they find themselves in) must imply restrictions on how the system behaves in the aggregate. 
Sadly, this intellectual bet was lost even before it was placed.  If we take Lucas (1976) as the beginning of the microfoundations movement, we may note with some puzzlement that the premise was mathematically proven false two years earlier, in Debreu (1974) and Mantel (1974).
Emphasis in the original. When I started this blog, I was seeking exactly the discipline JEC is talking about:
Put simply: there is limited empirical information to choose between alternatives. My plan is to produce an economic framework that captures at least a rich subset of the phenomena in a sufficiently rigorous way that it could be used to eliminate alternatives.
In a sense, that defines what I (and other physicists) mean by framework: a system or theory (in this case mathematical) that organizes empirical successes. Instead of human behavior, I started to build that framework out of information theory based on the least controversial formulation of economics: a large set of demand events matches up with a large set of supply events on average (therefore in "equilibrium", the information content of the two distributions are proportional to each other).

I'd like to paraphrase JEC above to describe the mission of the information equilibrium framework:
... rather than simply making up relationships between aggregate variables like interest rates, output, unemployment, and inflation, we should show how those relationships are consistent with information theory given any possible model of individual behavior.
In The Next New Macro, JEC shares my call for empirical success:
The fact is that, right now, we do not know the way forward, and no approach, no matter how promising (or how congenial to our pre-conceptions and policy preferences) should be allowed to dominate the field until it has proven itself empirically successful.
And I think JEC captures my feelings about a lot of economics:
You can't just say, "I feel in my heart that A, B, and C cause D, so here's a regression," and claim to be doing social science.  And when you're constantly saying, "Did I say 'B'?  I meant X!  A, X, and C cause D.  Also, maybe the log of B.  Here's another regression!" your credibility does not improve.
Now I'm not necessarily as uncharitable in this case. One of the key things you do in science is posit things like "A, B, and C cause D" and then look at the data. As I put in this post, I'd like to formalize this process:
In a sense, I wanted to try to get away from the typical econoblogosphere (and sometimes even academic economics) BS where someone says "X depends on Y" and someone else (such as myself) would say "that doesn't work empirically in magnitude and/or direction over time" and that someone would come back with other factors A, B and C that are involved at different times. I wanted a world where someone asks: is X ⇄ Y? And then looks at the data and says yes or no.
The series is a fun read. you should check it out.


Update 18 January 2017

I wanted to add a bit to one of the quotes. Paraphrasing JEC again in addition to the original statement, you can't just say, "I feel in my heart that A, B, and C cause D" and then not compare to data and claim to be doing social science either.



[1] Not to imply JEC would agree with what I've done; he or she might look at it with the same derision as he or she looks at microfoundations.

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