You develop financial structures where any drop in income or a rise in interest rates will transform some firms to Ponzi financing. And I said, well, did you predict the global financial crisis? And he said, no. And I said, well, on your own definition, you're an idiot. Why shouldn't I model the Wallace insisting of people like you, the influential contrarian economist, Steve Keane, brilliant economist that criticizes much of modern economic. The research fellow at the Institute for Strategy, resilience and Security at University College in London. He's someone that each and every one of us has to listen to, whether we agree or disagree. Steve Keen. So in the previous lectures I've led up to the point of saying we have to an analyze the economy as a complex system, and that of course wins what is a complex system and intriguingly enough, I hadn't actually provided a definition. The definition I came up with there is that a, a complex system that often a very simple system, so to complex text does not mean complicated. And that's an important point I try to illustrate. In today's lecture, the center, you're in a complex system. Uh, you are not dealing with the system, which in which equilibrium tells you anything other than the broad characteristics of the system. It certainly doesn't tell you where the system is going to be, uh, and you can't understand it by reductionism. You can't reduce the active component s and then understand them. But I wanna start by giving a simulation of the very first. Discovered model of complex system that honor belongs to the remarkable, one of the great mathematicians for royal, a French mathematician. And he proved the existence of, of what we now call complexity. When he proved the, solved the three body problem, by proving it couldn't be solved, the idea was forgotten until Lorenz rediscovered it by accident. Uh, in the 1960s working on meteorology, he wanted to illustrate to his fellow. Um, meteorologists. They, they were, they were using two sorts of things, most, mostly at the time. He wrote this paper, either linear models of the weather or their models, which had pattern matching. Now, what he did to make his point was he took those, whoever took those equations, produced into three very simple first order differential equations, and this is what they looked like. Now, Lorenz expected something interesting out of this, but he didn't know, so he wrote a. Math, a computer program probably in Fortran to simulate it. And the machine that it reduced that did the simulation work, did six decimal places of internal accuracy. That's to be compared to modern computers, which really opened about F 25 or 30 or more decimal places. What he got was a column of numbers printed, the four decimal places, because that was the printer. So he gave them back to the technician who entered the numbers and said, redo it, starting from this number. And when he simulated it, this is what he got. Of course, no, no one, not as, not a pretty, uh, graph here. Of course that a set of numbers, but. Identical for quite some time, and then suddenly started and ultimately were completely unrelated to each other. There were complex, a periodic cycles added, added deterministic system, and hence, the title they gave to the paper was simply unbelievable given the understanding we had before then that such things were possible. But he showed that it was there. We have, you know, this just three, three equations. Three variables and off we go. And absolutely nothing happens because they've started the model in equilibrium. And then you can see that all three variables are propelled away from the equilibrium, but they don't get propelled into outer space. They start to cycle. And that's where the concept of strange tractor came from. The key features there, uh, first of all, non-line interactions there. So those are your non-linearities. Uh, the system is extremely simple. Just those three variables and three parameters, but all three libria are unstable, but the system doesn't break down. That's completely unlike what neoclassical economists think. Still about the nature of unstable, the equilibrium. So you got a periodic cycles coming. A cycle is different. Now, this is something which before Lorenzo's work, and unfortunately still after it, 'cause economists don't read outside their own literature. The general expectation of economists was once we thought about this thing, the complex were complicated. Because physical systems were simple, they wouldn't have complex outcomes, but pen and social systems are complicated, so they would have complex outcomes. Now, what Lorenza showing instead is the complexity of this even in simple systems and also the coroll of that is some of what we see is the complicated behavior of capitalism may also have equally simple foundations. And as soon as you've got them, you're in a complex world and that is you. You're in a complex world because nothing. Is linear. So a straight line, for example, you draw a straight line, no, you have, and it's non-linear because you didn't draw it from one side of the universe to the other. So the fact that it stops at some point isn't nonlinearity. Uh, and then interactions are also normally non-linear, but there's multiplicative interactions everywhere in macroeconomics. If you work out the wage bill, you're trying to work out aggregate profit, then it's gonna be profit of all the companies, which is additive. Minus wages for all the employees, which is multiplicative in the sense that you've got both the, uh, number of employees, which is a function of economic activity and the wage rate, which is a function of economic activity. So you put the two together and you've got two, two variables multiplied by each other. Trying for debt level is also the level of private debt divided by GDP, that's another nonlinearity. Okay? So they cause very different dynamics when you're five from equilibrium compared to when you're near equilibrium. So near equilibrium, linear terms will dominate. This is gonna be shown mathematically, but far from equilibrium. The nonlinear terms dominate. And what you get out of that is interaction, uh, between those two extremes. That gives you, uh, instability near the equilibrium, but stability far from it. In other words, not stability in the sense that you don't get, uh, you know, crazy high values at various times, but you don't get values that say the system break down necessarily. I do get that in my model of a debt deflation, and that's one reason to avoid a debt deflation. You get to a corner solution you can't escape from. So what we should be doing in economics is modeling complex systems. The economists are locked in a 19th century mindset where they still expect equilibrium to be stable. Um, so when you, one of the earliest instances of this is when Harod Roy Howard, he did a lot of disturbing things to mainstream economics. Fascinating character. I should learn his baring far close, more closely than I have. He managed to disturb economists by bringing up the concept of marginal revenue, which put a big hole in the supply and demand analysis that economists were doing up until that time. When you look at, um, the model that, that, um, Ramsey wrote that all these models were based on, it's unstable. But anyway, back to back to how they reacted to this. They also have linear models. This is Olivia B. Blanchard. I had some polite exchanges with back in the post-crisis days. C C's been polite since then. Um, but they said we had a system in which cycle, they had a model where cycles were regular and essentially self-correcting. So here's Lorenzo's model with one or more of the ods turned off. So I run it and you know, you see I started from a different point, which not an equilibrium. So, so if you cut out the third dimension, you lose the interesting behavior. You can't actually see. Then I turned it on back on again and showed the same forces are still there. So you have to analyze the whole system. You can't analyze it bit by bit. And simulation as I've done there is the easiest way to see it, how it behaves. But you actually have an enormous of, um, what they call phase space around the equilibrium. So, but because of the obsession with equilibrium, they don't even want to know about, they said they impose imposed stability on an unstable equilibrium. This is where the, the God mode of neoclassical economics has come from. But what it really means is we're assuming every agent here can predict the future because they have a model in their head, which is identical to the model of just bill of the economy. And since what they do is based on the model of the economy, all the capacity of any, any outside force to change, the equilibrium outcome is removed. So this, this is the great tragedy, and I, I hope we could recruit some physicists to join us when the kind of physics began back in the, uh, early two thousands. But the physicists are stuck with their own little. Group and mainly looking at applying the techniques from nuclear physics to financial sector data. So we just don't have the development going on there. So please join us. It's just, that's one reason I'm giving these courses. One of my best mates, you, if you, any of you watched the show on the Saturday that I do with, um, Ty Canes and uh, uh, and Mike Zeki, Mike's one of my best mates in economics in general, and he talks about doing the system system dynamics. You'll take a complex system, you'll break down components of it, and what you'll do is part of the testing out component is work out its equilibrium and its own interpersonal damage, and then you slot it back into the big system. So you have to be aware of both. And what economists has done. Us presume we don't want to se equilibrium anywhere, so we assume we impose equilibrium everywhere and we're quite happy to assume that rationality means you can predict the future. Then I gave a talk in the, what they call the Western Economics Association of the United States at his conference in Brisbane, which is pretty Western, uh, one year. And I went along to it, gave my paper on Minsky's Financial Instability Hypothesis. And as I was going through explaining Minsky's financial instability hypothesis, getting more and more agitated, and he finally couldn't hold himself in the middle of my presentation, he blurts out. But, but, but, but you're assuming people are idiots. And I said, well, did you predict the global financial crisis? And he said, no. And I said. On your own definition, you're an idiot. Why shouldn't I model the water consisting of people like you? And he then chased me out of the room. I, I mean, the thing is, I, I realized how insulting this was. I said it very softly. It's twice I finished to do that when I should have said something loudly for the sheer dramatic effects. But anyway, he followed me out of the room and I just, what's the point in talking to these characters? And he shouts to me as we've gotta make some simplifying assumptions. And I said, mate, you've gotta learn the difference between a simplifying assumption and a fantasy. Maybe not a bad time to finish up. So thank you everybody. Okay, everybody, see you all. Nick, maybe tomorrow or maybe next week. Bye. If you're like many other truth seekers and wanna learn 50 years of real economics from me in only seven weeks. If you'll love my new Seven Week Rebel Economist challenge as well, to apply, go to apply dot Steve can free.com. If you qualify, you can attend my lectures, ask me questions personally every week, and make friends with a great group of like-minded people. So again, like many others, go to apply@stevekingfree.com to apply as well for the seven week Rebel Economist Challenge. Good luck.