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Cracks in the anti-behavioral dam?

Author(s): Noah Smith

From Noah Smith's blog:

This is purely my impression, buttressed with some anecdotes; I don't have any systematic data to back this up. But in both papers and casual discussion, I'm seeing macro people taking behavioral ideas more seriously. 

"Behavioral" is a very squishy idea, but basically I think of it as meaning "imperfect use of information". The difficulty with labeling a model "behavioral" is that we don't really know what information is available. This is why I believe there's a fundamental equivalence between behavioral and informational models - for any "informational" model where agents don't know all of the facts, there's an observationally equivalent "behavioral" model where they do observe the facts and just don't make use of them. 

But anyway, in macro, most models use Rational Expectations, so let's think of "behavioral" as just meaning "non-RE". Actually, non-RE models have been kicking around for a long time - for example, Sargent's learning models, or Mankiw and Reis' sticky information models. What seems to be changing (slightly) is that A) younger people seem to be making non-RE models, B) people are recommending non-RE models for policy analysis, and C) the departures from RE are getting more stark. 

Some recent examples I've seen are:

1. The learning approach to New Keynesian models, promulgated by Evans et al., which seems to be solidly mainstream

2. Mike Woodford's response to Neo-Fisherism, which relies crucially on a slight departure from RE

3. Xavier Gabaix's behavioral New-Keynesian model, where consumers are short-term thinkers instead of infinitely far-ahead-looking

These are all well-established people making these models - they cut their teeth on RE models for years before daring to venture out into behavioral waters. But now I'm starting to see young people doing behavioral stuff as well. A good example, sent to me by Kurt Mitman, is this paper by Kozlowski, Veldkamp, and Venkateswaran, entitled "The Tail that Wags the Economy: Belief-Driven Business Cycles and Persistent Stagnation". 

The basic idea of the paper is that instead of knowing the true PDF of macroeconomic shocks, people re-estimate the distribution every time they see a shock. Not too crazy, right? But that seemingly small departure from RE has big business-cycle implications. 

The reason is tail events. When big shocks are rare, just one of them can change people's whole understanding of how the economy works. How many events like the Great Depression have there been in American history? Really, there are only two since we started keeping national accounts. Two! In 2008 we abruptly went from "There was that one really bad depression one time" to "Whoa, this is a thing that can happen multiple times!". To think that this would have zero impact on agents' beliefs about the economy - which is exactly what RE demands we think - seems implausible. The authors write:

No one knows the true distribution of shocks to the economy. Economists typically assume that agents in their models do know this distribution as a way to discipline beliefs. But assuming that agents do the same kind of real-time estimation that an econometrician would do is equally disciplined and more plausible. For many applications, assuming full knowledge has little effect on outcomes and offers tractability. But for outcomes that are sensitive to tail probabilities, the difference between knowing these probabilities and estimating them with real-time data can be large.

Anyway, to make a long story short, this can produce long economic stagnations, like the one we just had. Taking a gander at the literature review section, I see that these authors didn't aren't the first to use this mechanism in a theory - it looks like it can be traced back to a 2007 AER paper by Lars Hansen. The other similar papers the authors cite, however, all come from 2013 or later, showing that this sort of idea has been gaining currency recently and rapidly. 

Now, Koslowski et al. do dodge one important issue: what data set do agents use to estimate the distribution of economic shocks? The data set they use goes back to Word War 2 - they don't even include the Great Depression. But even if we go back further than that, we'll miss earlier episodes like the Panic of 1873, when good national accounts just weren't kept at all. Data availability is so recent that there's almost an observational equivalence between assuming that people use all the available data, vs assuming that people overweight data from their own lifetimes.

If the authors - or some other authors - were to assume that people overweight data from their own lifetimes, as evidence from Malmendier and Nagel suggests, it would have important implications down the line. Instead of people's expectations slowly converging to RE over the decades (centuries?), people would forget the lessons of history and continue being surprised by depressions every 50 or 100 years or so. 

For now, macroeconomists don't have to worry about this question. Authors like Koslowski et al. can frame their papers as quasi-behavioral papers, where RE is limited by data availability, instead of fully behavioral papers where RE is limited by collective forgetting. So these are still only cracks in the anti-behavioral dam, not a full torrential flood.

But my question is this: What happens when people start applying this mechanism to more complicated shock processes? What if the economy has regime switches that last decades? What if there is more than one kind of rare shock (e.g. the Great Inflation of the 70s/80s)? I've seen some people try to model stuff like this, and the end result can come out looking like practically any type of non-rational expectations you can think of. Meanwhile, empirical macro people are starting to pay more attention to survey measures of expectations. And people from behavioral finance are starting to put things extrapolative expectations into macro models, to explain macro facts. And evidence like that collected by Malmendier and Nagel continues to pile up.

And I should mention casual conversation as well. More and more young macro people that I interact with, including (even especially?) those who run in "freshwater" circles, are saying that behavioral explanations will have to be part of our understanding of how consumption works. Here's an example from a recent blog comment. 

So I wouldn't be surprised to see some more cracks in the anti-behavioral dam in the years to come. Chris House, my old macro prof, proclaimed three years ago that behaviorism was a dead end and would never have a transformative impact on macro. But seeing papers like Koslowski et al.'s, I'm thinking that his prediction now looks to have been quite ill-timed.

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