Doyne Farmer

Now, so in complexity economics, we do things completely differently. So it's really throwing out stuff that's been in economics since the 19th century. And we say, well, let's assume we have some agents. Let's give them some ways of making decisions that could be very simple or more complicated, but we're not assuming optimality. So information flows in.

Now, so in complexity economics, we do things completely differently. So it's really throwing out stuff that's been in economics since the 19th century. And we say, well, let's assume we have some agents. Let's give them some ways of making decisions that could be very simple or more complicated, but we're not assuming optimality. So information flows in.

The agents use their rules to make decisions, which might be learning algorithms or they might just be simple heuristics like buy undervalued assets or imitate the best. Look around and see who's doing the best. Imitate them. Or it might be trial and error. Try something. If it works, keep doing it. Doesn't work, try something else. Simple stuff. And so they make their decisions.

The agents use their rules to make decisions, which might be learning algorithms or they might just be simple heuristics like buy undervalued assets or imitate the best. Look around and see who's doing the best. Imitate them. Or it might be trial and error. Try something. If it works, keep doing it. Doesn't work, try something else. Simple stuff. And so they make their decisions.

We then calculate the economic consequences of the decisions. That generates new information. In addition, new information may flow in from the outside. And then we repeat the process. And we just go around and around that loop. We may arrive at an equilibrium where supply equals demand or agents decisions get locked in.

We then calculate the economic consequences of the decisions. That generates new information. In addition, new information may flow in from the outside. And then we repeat the process. And we just go around and around that loop. We may arrive at an equilibrium where supply equals demand or agents decisions get locked in.

If so, that's what we would regard as complex system scientists as an emergent property or we might not. And actually oftentimes we don't. And I think that's one of the important strengths of this formalism that we more naturally capture dynamics And endogenous dynamics, that is dynamics that arises from within.

If so, that's what we would regard as complex system scientists as an emergent property or we might not. And actually oftentimes we don't. And I think that's one of the important strengths of this formalism that we more naturally capture dynamics And endogenous dynamics, that is dynamics that arises from within.

Things like business cycles, where if you take, say, the financial crisis of 2008, the so-called great financial crisis, I think it's pretty clear it's an endogenous crisis. It wasn't like a meteor hit the earth and that caused the crisis or that people suddenly changed. It was that we introduced new types of technologies

Things like business cycles, where if you take, say, the financial crisis of 2008, the so-called great financial crisis, I think it's pretty clear it's an endogenous crisis. It wasn't like a meteor hit the earth and that caused the crisis or that people suddenly changed. It was that we introduced new types of technologies

Financial instruments, mortgage-backed securities, housing market got overpriced, it crashed. All these things happened from within the economy. In a mainstream model, you can't get that to happen. And so you just don't get, it's very, you can get endogenous dynamics, but you have to push the economy into extreme, you have to make what seem like unreasonable assumptions in order to get there.

Financial instruments, mortgage-backed securities, housing market got overpriced, it crashed. All these things happened from within the economy. In a mainstream model, you can't get that to happen. And so you just don't get, it's very, you can get endogenous dynamics, but you have to push the economy into extreme, you have to make what seem like unreasonable assumptions in order to get there.

There's actually something called a turnpike theorem that says things are just gonna settle into a fixed point unless certain conditions are satisfied, like very myopic reasoning, et cetera. But if under normal reasonable conditions, You know, it's like a turnpike. You look down the road. You see where things are going. You make corrections as needed because you can see everything well ahead.

There's actually something called a turnpike theorem that says things are just gonna settle into a fixed point unless certain conditions are satisfied, like very myopic reasoning, et cetera. But if under normal reasonable conditions, You know, it's like a turnpike. You look down the road. You see where things are going. You make corrections as needed because you can see everything well ahead.

And so you're not steering wildly. Now, in the book, I show several examples where behavioral errors, bounded rationality, making mistakes we should expect people should make, lead to endogenous dynamics. And, you know, the analogy I make is that the economy is more like a drunk driver on a mountain road, you know, swerving and not quite always doing what he or she is supposed to do.

And so you're not steering wildly. Now, in the book, I show several examples where behavioral errors, bounded rationality, making mistakes we should expect people should make, lead to endogenous dynamics. And, you know, the analogy I make is that the economy is more like a drunk driver on a mountain road, you know, swerving and not quite always doing what he or she is supposed to do.

So maybe one more thing. Sure. So it gets me back to what caused the whole digression. The part that economists, I think, will all agree on is when you're computing optimal strategies for each agent, you're deducing those strategies, you can't make things very complicated. Once the system gets nonlinear, once you have more than a dozen agents, you can't solve the equations anymore.

So maybe one more thing. Sure. So it gets me back to what caused the whole digression. The part that economists, I think, will all agree on is when you're computing optimal strategies for each agent, you're deducing those strategies, you can't make things very complicated. Once the system gets nonlinear, once you have more than a dozen agents, you can't solve the equations anymore.

And so you have to keep the models simple. You're just forced to do that. You're also writing down equations. You have to write down everything in equations. In an agent-based model, those constraints don't exist. We have models, we've run simulations with millions of agents making decisions. And there's just a lot more room to put in institutional structure, heterogeneity, real world stuff.

And so you have to keep the models simple. You're just forced to do that. You're also writing down equations. You have to write down everything in equations. In an agent-based model, those constraints don't exist. We have models, we've run simulations with millions of agents making decisions. And there's just a lot more room to put in institutional structure, heterogeneity, real world stuff.