Doyne Farmer
speaker
145 appearances
1 recordings
1 series
first heard Oct 2024
last heard Oct 2024
Doyne Farmer’s voice in public audio — every appearance, attributed to the second.
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Let me just put an asterisk by this. There are special cases where that doesn't, where you get dynamics. But they're really special cases. If you look at the workhorse models used by the Federal Reserve or any of the people who are actually using models to make decisions about the economy, they're still actually using rational expectations.
And those models settle into fixed points absent external stimuli.
They even have names like real business cycles. Okay. But when you look at them, they don't make business cycles unless they're getting kicked. So I find the name a misnomer. Got it. They're not endogenous business cycles.
Yeah. Well, that's one of the things. But unlike in physics, where the work you're talking about builds out of the classical work, the methods used are similar to those used in traditional equilibrium statistical mechanics, here we throw the whole thing out and start over.
And that's actually the source of the tension within the academic community and why this kind of, this way of doing things is so strongly opposed by the mainstream academic economists.
Yeah. Again, I'm trying to be nice to the economists. They were doing the best they could. But, you know, yeah, I think there were two key things that happened. One is, I think the 2008 crisis was substantially a non-equilibrium event. Things got out of whack. We weren't sitting at the equilibrium we've been at. Why? Because we were dealing with
financial instruments we didn't properly understand, and they had side effects that we really didn't understand. There were a few people like Robert Shiller who anticipated the housing bubble, that the housing bubble would pop, but almost nobody anticipated was how enormous the side effects on the real economy would be.
And that was because mortgage-backed securities, almost everybody globally was holding them. Foreign institutions were holding US mortgage-backed securities because they were the hot new thing, great investment, low risk, high return, hooray, hooray. But what they didn't realize is when the housing bubble popped, that meant that all those mortgage-backed securities got enormously
their valuations dropped very low, which meant that all these financial institutions holding them were stressed, which meant that they were not in shape to lend money anymore, which meant nobody was lending money to the businesses in the real economy that needed it to construct new buildings and do all the things that we do in the real economy, and the real economy got whacked really hard.
I would argue it was all an out of equilibrium event, endogenously driven.
Oh, that totally makes sense. It's true. As a physicist, you will appreciate it because it says that The economy doesn't seem to be time reversible. If I look at time series, just from looking at the time series, I can tell which way time is flowing. Now, of course, the other significant thing that happens is the economy tends to grow.
It's not that it can't shrink, but the US economy has been going up at 2% per year on average most of the time since the Revolutionary War. So that's another time asymmetry. But yeah, markets go down easier than they go up.
Right, right. You know, since we're talking about the endogenous-exogenous distinction, I should say disequilibrium models are also really useful when the shocks come from outside. And the good example of that would be COVID. Now, that was clearly outside, right? I mean, at least from the point of view of the economy, having a virus suddenly cause people to not go to work is an outside shock.
That was a very sharp and sudden outside shock. And we built a model in a crash program as the pandemic was starting and actually used it to advise the British government about the economic consequences of different forms of lockdowns. And that model was very, very explicitly disequilibrium. I mean, it worked in a very simple way. We said,
An industry can't make its product if there's no demand for the product, if it doesn't have the inputs it needs for the product, and if it doesn't have the labor it needs.
And so just using that basic observation, the longer story for how we managed to guess how big the shocks were going to be and which industries would get shocked, that had to do with our knowledge of occupational labor and beautiful data set put together by the Bureau of Labor Statistics. But that contained information like how close together do people work in different occupations?
Yeah.
So from that, we can infer who would be able to go to work and who wouldn't. And but we initialized the model in the steady state it was in before the pandemic started. And then we hit it with the shocks. And using the rule I said, we could see those shocks reverberating around the economy because every day we'd update the model. We'd say, oh, does this industry have labor? Does it have inputs?
Does it have demand? And if it didn't have some of those, we would reduce its output. So it was a very dynamic output that changed through time. For example, some of the industries were running out of inputs a month or two after the lockdown started. So it didn't, the consequences weren't necessarily felt immediately.
And then once they ran out of, once they reduced production, if they were upstream in the economy, meaning like producing natural resources or stuff that lots of other industries use, then that would propagate, as they say, downstream and hit the other industries. So there were complicated dynamic effects. And mainstream models don't work that way. They assume equilibrium from the get go.
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