Economists are known for attempting to treat economics like a genuine science. But upon closer inspection, it becomes obvious that their methods are quite outdated as a consequence. Most of today's economists are providing an extremely naive understanding of our economy, the worse damaging societies ability to improve people's lives.
In this episode, I'll use Eric Fein Hawker's book, The Origin of Wealth, Evolution, Complexity and the radical remaking of economics to anchor my conversation around how today's economists conveniently misunderstand our world. I'm Sean mcclure. You're listening to non trivial. There are two ways to try and understand something you can attempt to reverse engineer the thing learning about its components, seeing if you can piece together the causal chains that produce what you observe.
The other way is to view the thing as a whole and notice only its high level behavior, its attitudes, wants and needs. Now, while the former sounds more scientific the most. It's an approach that has had its time as I discuss often on nontrivial, such reductionism is as outdated as it is tempting to reverse engineer. A thing is to see its components. But it's not to see how those components produce the outputs we observe reductionism is mathematically convenient.
But in all, but the simplest systems, it does not map to the reality that appears before us. Almost all relevant and interesting phenomena produce their behaviors via emergent mechanisms that do not expose causal paths back to their origins. Particle physics. Aside, I argue that science should be casting its views towards the whole, not the pieces. Economics has always had a kind of jealousy of genuine science, right? Much of its history is loaded with attempts to make it look more rigorous.
This effort has brought economics into the world of reductionism as is the case with all social researchers. And as always the inevitable outcome of these efforts has plagued the field with misconceptions, bad momentum and downright untruths. Now, this is not some passive comment about an unchangeable reality as much as it is a call for action. Today's economic models are both deeply flawed and consequential. People's lives are impacted by really bad models.
The economy is another phenomenon like any other. It contains matter, energy and information and it's just subject to the laws of thermodynamics. While an individual's contributions to an economy has little meaning. For most of us, the statistical high level properties of such a social system are both fascinating and important. So if we want to truly understand the economy, we must first accept that we never will in the reverse engineering sense.
But we can understand the economy as a holistic complex system with well-defined behaviors, something worthy of modeling appropriately. So I'm gonna begin our economics talk as many others do with Adam Smith rightly considered the father of modern economics, maybe not. So modern Smith is uh you know, he was concerned primarily with the creation and allocation of wealth in society, right?
Value creation came about whenever someone could use the resource Earth provides to create something people want the best possible allocation of wealth. According to Smith comes about when everyone maximizes their self-interest.
So this is when people usually like to reference the 1987 film Wall Street and its antihero Gordon Gekko played by Michael Douglas Gordon's famous line quote, unquote, greed is good is an apparent testament to Adam Smith's self-interest mechanism, but framing self interest in terms of something pejorative like greed is shortsighted. Self-interest is not good or bad. It just is in reality, localized self-interest often leads to better outcomes for the whole.
Remember what the small things are doing is not the same as what the big thing is doing. Smith's original ideas come to us via moral philosophy. Since understanding how to create and allocate wealth should help us create societies that are most just for the most people. But such hand wavy ideas lack the kind of rigor we see in quote unquote true sciences right after the age of Adam Smith came, you know, major advances in the physical sciences, particularly physics and chemistry.
Now this is an age when smart looking equations and diagrams littered the chalkboards of academia showcasing explicit interactions and enabling the kind of bold predictions we now read about in the histories of science. This was a time when the original insights of thermodynamics began to bear fruit. Tinkerers were discovering new ways to harness combustion, bringing forward a new age of machines and human transportation.
So eventually such trial and error discoveries were formulated into theories regarding the behavior of gasses, we have pressure volume temperature and those could all be described using the language of physics with its four specters and corresponding equation. And so as anyone might ponder if economics were to be taken seriously as something beyond the moral philosophies of people like Adam Smith, then shouldn't it be more akin to a genuine science for something to be taken seriously?
It needs all those force vectors and fancy equations. It needs to be mathematical along comes Leon Varis and a few others like William Stanley Jevans who decided they could take what was happening in the physical sciences and apply the same ideas to the field of economics. I mean, after all, an economy is a group of individuals interacting in various ways akin to gas molecules colliding leading to some interesting and consequential behavior.
Now, I've talked about the problem of physics envy before, right. Physics appears rigorous and quote unquote smart because its chalkboards are loaded with formula, detailing the mechanisms behind the phenomena of interest. But the only reason this happens in physics is because almost all of its phenomena are well simple. They deal with simple systems, simple systems don't have causal opacity. In other words, one can reverse engineer a simple phenomena to see how things add up.
Even if the phenomena are complex, the physicists task is to strip away that complexity and expose the components. So those who choose to deal with components will always get to use more math because one can express the pieces and their supposed interactions with symbols. So when every day people cast their gazes upon such formula, they're usually pretty impressed, right? Although they usually don't understand, you know what the heck they're looking at.
This has always been the downside of math though not the fault of math math looks rigorous regardless of how well it maps to reality. And so it was with Leon Boris who couldn't resist using the notions of counterbalancing forces to model the economy, applying such ideas to the concept of supply and demand. So since gas molecules interact and settle into equilibrium temperatures, so too, could people be thought of as agents that drive the market to an equilibrium price and quantity level?
Now first blush, this doesn't seem so bad. Thermodynamics is fundamental to understanding nature and not just in the physical sciences. I mean, most real world phenomena are based on collections of agents interacting in complex ways thinking of such phenomena as systems means using the statisticss of ensembles to predict their outputs, that's thermodynamics. But a major consequence of thinking of the economy as a system akin to a gas assumes the economy regularly settles into an equilibrium.
Specifically, the uh you know, so-called forces of supply and demand are assumed to counterbalance each other and settle just as a gas eventually settles into a uniform stable state. But markets are never truly in equilibrium, right? I mean, supply never really equals demand. We know this because the economy is actually operated around disequilibrium. I mean, think about it, the economy runs on stocks of inventory order backlogs and slack production capacity.
There are market makers who continually attempt to smooth the dis equilibria that regularly occur. This can all be thought of as delays in an otherwise instantaneous process, something we'll get out, you know, more into in a bit but hold on despite some deep discrepancies between the borrowed equations of all rests and what we see in real economies isn't science about approximation. I mean, after all, we know that all models are wrong, right?
The problem is the connection between economic models and reality. And I don't just mean in the sense of how good or not the models are. I mean, the way policymakers use whatever academics tell them itself an awful policy. Traditional economics rooted in the models of Aris has had a major impact on public policy, business and finance policymakers such as central bankers presidential advisers and finance ministers regularly rely on these models.
In addition, these models are used to inform decisions in the business world related to stockholders as well as competitive strategy. In fact, trillions of dollars are traded every day in the markets using calculations that come to us from the gas molecules approach of traditional economics. These models are the basis of the interventions we take in attempting to control our economy. Traditional economic models are fundamentally flawed for reasons we will get into.
But the answer cannot be to not intervene at all unless we you know, all choose to just subscribe to anarchy. I guess a complete lack of regulation and government intervention would likely prove problematic. So the question is, is there another option while regular listeners are non-trivial already know this answer at least at a high level, right? It makes little sense to model something that is obviously complex like the economy in terms of basic physical forces.
This causes problems in all of the areas where physics envy leads to misplaced concreteness. Now this came to a head during a meeting in Santa Fe between economists and physicists in the late eighties. The Santa Fe Institute SF I is an independent nonprofit theoretical research institute located in Santa Fe, New Mexico and is dedicated to the multidisciplinary study of the fundamental principles of complex adaptive systems. This includes physical computational biological and social systems.
Basically, the SF I was formed to bring about a focus on complex systems, something that was severely lacking in mainstream science at the time. Arguably still the case.
Now, the meeting between the economists and physicists helped promote the kind of interdisciplinary research that was gaining steam in the late eighties, disparate intellectual fields could share their ideas on concepts and models, letting others know how they chose to model their phenomena of interest, cross pollination, cross pollination of concepts and approaches is always a good idea, right? Solutions to problems never belong to a particular field.
But in this instance, as the physicists and economists share their methods, something became quite apparent. Economists were using extremely outdated methods to model the economy. You didn't need to be an economist to know this since their methods were all borrowed from physics to begin with. But the methods they were using were the origin original ones from Varu. And there had been entire revolutions in science since those methods were used.
One of the physicists famous uh famously commented that the field of economics reminded him of Cuba and their outmoded cars unaware of just how behind the times they were due to their isolation, right? In the case of economists, it was isolation from the rest of the scientific community. So the ideas of forces leading to equilibria were extremely limited compared to the kind of methods developed since the two major revolutions in science, quantum mechanics and relativity.
But it wasn't just isolation that kept economists tethered to outdated methods. I mean, after all, it's not like that, it's not like no economist had ever heard of the advances in science and some of them likely had degrees in science themselves before focusing on economics. The real reason for remaining fixed on outdated methods in economics was and is convenience. Once you decide your system of interest can be modeled as an equilibrium, the math becomes quite basic.
The math gets easy because almost all the realistic complexity of the system has been artificially removed by the insistence on extreme assumptions. The assumptions made by traditional economics can be summarized as follows. People will always do what's in their economic self-interest and do so in fantastically complex and calculating ways.
Now I'm gonna spend some more time discussing what this means and and more importantly, the consequences of such assumptions and how those you know, impact economic models and reality or at least our perception of it. But even a casual glance at such an assumption would make most people wince think about the kind of economic decisions real people make, they purchase products and services, they buy homes, et cetera.
Traditional economics assumes that when people are making these purchases, they somehow take into account inflation rates and estimates of future government spending the trade deficit and so on in their daily decision making. These kinds of assumptions are the only way one can model an economy as a system that settles into a nice equilibrium. People have to have access to perfect information instantaneously and make perfectly rational decisions with that information.
If they didn't, the system wouldn't be an equilibrium since differences in the use of information like different access times or irrational decision making would be akin to forces in the system that don't counterbalance each other. Traditional economics assumes that there are incredibly smart people in unbelievably simple world when in fact, it's the precise opposite. Think of the gas molecules metaphor instead of perfectly identical balls or molecules elastically bouncing into each other.
Imagine balls that are in elastic with delays in when they bounce and by how much some balls don't bounce at all while others pick up speed midway through their travels, such a system would never be at rest. It would exist as some asymmetric collection of particles with a rich variety of behaviors. By the time the Santa Fe meeting took place in the late eighties, right? It had been 100 years since Varis published his seminal work on general equilibrium theory.
What started as physics envy with Varis was now something even worse since it was now. The physicists were pointing out how outdated the economists models were. It's like economics was jealous of physics', old girlfriend who they weren't even dating anymore. Move on the overarching theme here is how traditional economics disregards time, traditional economic models, trade time for mathematical convenience to understand why this is a problem.
Let's turn to the age old joke about an old and young economist, an old economist and a young economist are walking down the street. The younger economist says, hey, look a $20 bill and while the older and supposedly wiser economist doesn't even look down and just simply says nonsense, if there had been a $20 bill, someone would have picked it up by. Now. This is the idea behind the efficient market hypothesis, right? That says that asset prices reflect all available information.
Colloquially, this means transactions happen immediately in any financial system. But this is a drastic assumption that anyone should realize strays from reality. This is because there must be a finite amount of time that passes for any transaction to occur. It takes time for someone to discover the $20 bill, perhaps quite a bit of time. There are likely multiple bills on the ground at any given time with a wide variation of pickup times.
There's little reason to believe things happen instantaneously in the market. This would be price discrepancies could be arbitrage, arbitraged away instantly, which is not actually what we see opportunities, take time to be discovered, they come and go, they may or may not be worth using. And there are likely a variety of barriers to the transaction. These barriers to instantaneous mean there is little reason to expect an economy to be in equilibrium.
In fact, Yale economist Herbert Scarf actually calculated how long it would take an economy to reach equilibrium. And he came up with the answer 4.5 quintillion years. It turns out that the time to equilibrium scales exponentially with the number of products and services in the economy to the power of four. In other words, the bouncing balls with all their differences would take a near infinite amount of time to finally settle into the uniform stable state of the traditional economics worldview.
What is obvious is that traditional economics is founded on extremely convenient mathematics and overly simplistic assumptions about how economies work. And this is all consequential. The economy is central to how we participate in the world, create value for others, feel fulfilled and define our futures now to be fair. The predictions of traditional economics are not totally off the mark.
Supply does roughly equal demand and prices do sometimes converge the markets can act as though they are in a kind of equilibrium. So what's the problem? Why can't we just use traditional economics as a rough guide to making decisions regarding public policy, business and finance? Why can't central bankers, presidential advisers, finance ministers and businesses use traditional models to generally inform policies and set strategic or business strategies rather?
Doesn't it make sense to just use a model that works most of the time? The question we have to ask is what happens when the model is wrong in equilibrium systems. The answer is relatively inconsequential. A wrong model means once in a while we miss the mark. But the system can still be expected to return to whatever our model usually predicts. But in complex systems, this is not true, not true at all. When complexity goes wrong, relative to a model's predictions, the consequences can be drastic.
And this is because complex systems have almost all of their outcomes dictated by rare events. The stock market crash in 1929 took out thousands of investors in one day. The crash on September 29th, 2008 was the largest point drop in history prior to COVID wiping out years worth of wealth in one shot. Remember we talked about before when Terra luna collapsed in May 2022 it wiped out almost $45 billion of market capitalization over the course of a single week.
If almost all the wealth gained over years or even decades can be wiped out in a single day, then you're not existing in the kind of simple equilibrium system of traditional economics. You're existing in a system that is extremely fat tailed as they say, which means the events that dictate what the market does are both extremely rare and impactful.
And this isn't just markets systems in nature exhibit the same behavior because they too are complex avalanches will accumulate over time until a single event wipes out the mass of snow using models that work most of the time is exceedingly dangerous and complex systems. If the model doesn't account for those rare events, those rare events are everything. The core problem with models in traditional economics is they'd only work in well behaved markets and economies.
Ok. They only work in well behaved markets and economies and better, more appropriate models are needed. If we are to gain understanding of the economy and enable the policies that you know, actually align with real world complexity. We need the kind of methods used to model complex systems. The starting point for such an exercise is to show economists that their use of thermodynamics while itself a sound idea is lacking a critical ingredient.
Now I mentioned Vares towards the beginning, he was instrumental in mathematical the field of economics and as a result misapplying basic physics to model a complex phenomenon. But his use of thermodynamics was not a bad idea. Anyone interested in understanding non-trivial systems at a rigorous level should be using a thermodynamic and information theoretic description of that system.
As I mentioned previously, social systems are not abstract mathematical constructs, they are real physical systems, social systems have matter, energy and information and are thus subject to the laws of thermodynamics. Ba Vares only relied on the first law of thermodynamics which is energy is neither created nor destroyed in his defense. That's all he had.
But we now know just how critical the second law of thermodynamics entropy and closed systems always increases is to understanding complex systems. The second law of thermodynamics. The first law says that if energy is conserved, the system is guaranteed to reach equilibrium. So think of a ball rolling down, let's say, rolling down the inside of a wooden bowl, ok? A ball as that ball rolls, it dissipates heats and it accomplishes, you know, some kind of work giving away its energy.
Eventually the ball settles to the bottom of the ball, right the back and forth. Rolling of a ball until it finally stops is a good way to think about a system reaching equilibrium. Only if energy is added from the outside such as shaking the bowl, can we kick the system out of equilibrium? So thinking of the economy in this way means the notion of value is a fixed quantity.
It's merely converted from one form to another just as energy is a fixed quantity is converted from potential to kinetic energy. In our bowl example, in a traditional economy, the earth's resources are converted into goods exchange for money exchange back for goods and consumed. In this scenario, new wealth is never actually created instead, finite resources are merely real allocated. Recall, Smith's view of morality being anchored on the concept of allocation of wealth.
The above situation that I just talked about is still taught in economics textbooks today, but it's completely devoid of the extremely important second law of thermodynamics which states that entropy enclosed systems always increases. Now, entropy is just a measure of disorder, a randomness in a system if disorder keeps increasing, then nothing of value can ever be created. Since only low entropy, non random things do useful stuff. Life itself is not possible with pure randomness.
Since large ordered molecules are required for life, life exists quote unquote despite the second law of thermodynamics, because earth is an open system, open systems allow energy matter and information to enter into the system which permits entropy to be lowered locally at the expense of increased entropy everywhere else. In other words, the second law of thermodynamics can still hold even though you are locally in your own little area, decreasing entropy.
Recall my episode on technology as humanity where I frame technological innovation in terms of local entropy reduction order is organization, structure and function which is opposite the natural tendency towards randomness or chaos. Something called the Singer's paradox. The evolution of biological systems occurs in the direction of increased complexity. Survival is the adaptation of species to their environment.
So as to minimize entropy production, the creation of large complex molecules which enables life and all its complexity happens because the sun continually pumps energy into the system, allowing low entropy things to be created at the cost of increased heat and disorder somewhere else on and beyond earth. The critical point here is that open systems are not in equilibrium. Imagine hot and cold, hot and cold gas molecules in a container and they're separated by a wall in the middle.
You got hot gas on the left, you got cold gas on the right. Now, if we remove the wall, separating the hot and cold gasses, we expect them to mix until there was a single uniform gas at a single temperature. This is equilibrium. This is the most disordered a system can have the gasses prior to mixing were in a more ordered state. The gas example is a closed system. If the economy was a closed system, its defining characteristic will be a trend toward a trend towards less order.
As with a gas example, we would see less complexity over time, we would expect entropy to move our world from a rich featured environment to a featureless nothingness. If we stopped the inflow of food, oil and information and entropy would be unopposed, our economy would drift towards a kind of equilibrium and death as Eric Weinhauer suggests in the origin of wealth, one could argue that countries like North Korea suffer misery and starvation due to their isolation, lack of inflow.
Whereas vibrant economies like that in the US fare much better usually since they exist far from equilibrium. Because there's this constant inflow existing in a state far from equilibrium is another hallmark of complex systems. And it leads to the kinds of properties we see in our economy, specifically systems that exist far from equilibrium exhibit exponential growth, radical collapse and oscillations.
These are the signatures of so-called complex adaptive systems and also the distinctive behaviors of our economy wrestling. Economic theory, solely on the first law of thermodynamics is mathematically convenient, but it leaves out critical realistic behaviors that must be accounted for the reality is that the economy is best viewed as an open disequilibrium system. And more specifically a complex adaptive system, our economy creates novelty value.
As time progresses, our economy shows signs of self organization structure and increased complexity. So for truly going to understand the economy, we have to move away from simple force vectors and equilibria and instead comprehend how complex behaviors emerge from a collection of people who create and reallocate value. Joshua Epstein and Robert Axtell are researchers who wanted to see if they could grow an economy from scratch.
Now to to achieve such a task, you you have to rely on computer simulation, right? For obvious reasons, Epstein and Axtel called their pet economy. Sugar scape says the thing of value in their fictional world was sugar of the programmed kind.
Sugar scape has a physical space and that the agents in this world can move north, south east and west and the terrain, quote unquote, varied by virtue of quote unquote mountains and quote unquote valleys as well as fertile areas where there were lots of sugar and then desert areas where there was little sugar. Now the agents in their simulation represent people trading goods, 250 agents were randomly added to sugar scape.
And since they were both desert and fertile areas, some were born into sugar wealth and others were not. Each agent was also given a genetic endowment quote unquote for vision and metabolism such that certain agents could see more steps ahead and utilize the sugar more effectively. Now, when Eps and Axel first let their program run the behavior on the board looked like chaos agents randomly bumping into each other, collecting and consuming sugar. But eventually order starts to emerge.
The emergence of structure is something we see in complex systems. And Epstein Axel sugar scape is a simulation of a complex system. One behavior that emerges is the rich get richer pattern which I discussed in my episode called wealth, the middle class and the shape of networks. In that episode. If you remember, we looked at how the preferential attachment mechanism leads to wealth disparity in real economies.
Any simulation that models market dynamics accurately should thus also show a concentration of wealth, which is what Epstein and Axel saw. Now what's important to realize is that the concentration of wealth and sugar scape was not due to genetic endowments nor did it matter where the agents started on the board and agents circumstances had no bearing on who found themselves in the top echelon of sugar scape society. We'll touch on this in a little more detail later.
Now, as I've discussed before, the skewed distribution of wealth is an emergent property of complex systems. In the case of sugar scape, it arose from some intricate combination of the environment, the agents and their interactions. There is no causal story that can be traced back to how such things emerge. They are an invariant reoccurring property of vibrant economies. Eps and axel even made further additions to add realism.
They added quote unquote sex to sugar skate by allowing agents to reproduce and pass on their characteristics. This led to the least fit members dying off because they ran out of sugar. The most of it having more offspring and population swings, we have like cycles of feast and famine and an even wider gap between the rich and the poor. So far, this was all modeled with you know, agents as pure hunter gatherers, right, collecting, consuming whatever they found on the landscape.
But then the researchers, the researchers added a second commodity which they called spice. So in addition to fertile sugar mountains, there was now also spice mountains and they also made it possible for the agents to trade. This was modeled as straightforward bartering.
Meaning if one agent had a lot of spice and needed sugar, another agent faced the reverse situation, then both agents could improve their circumstances by trading and agreeing on some price know that there is no know that there is no money in sugar scape, right? So quote unquote price just simply means the relative value of sugar to spice and vice versa. So if you run the program with those above editions, it initially led to uh you know what traditional economists would predict.
In other words, everyone can trade and overall everyone is better off. More specifically, Epstein and Axel were able to reproduce supply and demand curves. And the result was the classic textbook, downward sloping, demand and upward sloping supply. Now keep in mind that the researchers did not explicitly program anything about supply and demand into their model. This is a pattern that emerged purely as a bottom up phenomenon.
It comes about only via agent, agent and agent environment interactions. So to a first approximation, things seem to agree with traditional economics though, right? I mean, we've talked about supply and demand curves being there. You've got agents trading, we've got everybody kind of seeming to better their position or some people better their position. And you and you've got the wealth, you know, disparity that we see in economics.
But if you have a closer examination into this experiment, it shows that the prices and quantities traded never settled on the traditionally predicted equilibrium point, this would be at the intersection of the supply and demand curves, right? Instead prices fluctuated in the vicinity of that equilibrium point. Now at this 0.1 might say, OK, yeah, but the deviation from the exact equilibrium point that would just be noise, right?
But this argument doesn't hold because there was no noise added to the model. All of the agents interactions were perfectly deterministic only the initial addition of agents to the board had any kind of random component to it. So what's happening, the proper interpretation of these results is that prices move dynamically around a so-called a tractor but do not settle into an equilibrium.
This means the so-called law of supply and demand as per traditional economics is merely a loose approximation. In addition, the so-called law of one price breaks down since sugar space sugar scapes already showed wide variances in price. Now, another tenet of traditional economics is that markets should have so-called Rito optimal. That just means there's no reallocation of resources that can make someone better off without making someone else worse off.
But in the sugar scape simulation, it was shown that the market operates at less than Rito optimal. In other words, there always existed trades that could have made agents better off but did not happen. So if there existed trades that could have made Asians better off, why were they not executed? The reason is that trades are separated in time and space.
So even though trade can lift all boats, so to speak, making society richer as a whole, it also widens the gap between the rich and poor as discussed by Eric Weinhauer in the origin of wealth. New theory should always reproduce the successes of old theories and in addition, add new insight, something that we call the correspondence principle. Now we have seen that models based on complexity such uh such as sugar scape, they do reproduce many of the elements of traditional economics, right?
Supply and demand worked in an approximate fashion and there were indeed significant societal gains from trade. But what's critical is that Sugar scape was able to reproduce these results without the unrealistic assumptions of traditional economics, the agents of Sugar scape were not programmed to have superhuman powers of rationality. There were no pre-existing social structures or economic institutions critically. It did not assume that everything happens instantaneously.
Sugar scape spontaneously evolved the complex order structure and diversity seen in real vibrant economies. It even showed what could be interpreted as quote unquote tribes, market towns, trading routes and capital markets. Again, none of these were programmed into the system. Just simple starting rules and the constitution to let the program run on its own. The economy is a dynamic system. It changes with time, prices move up and down people's wages, change organizations enter and exit markets.
While all these facts sound obvious. None of this dynamism is taken into account by traditional models. The only way traditional economics recognizes the dynamism of real world economies is by treating things like price movements, disruptive innovation, political events and shifts in consumer taste as exogenous, meaning something that originates outside the system that cannot be predicted and modeled things like weather events or catastrophes that supposedly come from nowhere.
Next time you hear a politician or one of their economists say we couldn't have seen this coming. It's likely because they are relying on outdated models from traditional economics. After all, most people tend to misuse the term Black Swan. The dynamism of markets should be expected to emerge from the structure of the economy itself. Whereas the static equilibrium world of traditional economics can only treat dynamic behavior as exogenous complexity.
Economics shows us that the ups and downs pulses collapses and swaying trends of the market are just the type of behavior that usually emerge in complex systems. If your model is to reproduce a realistic approximation of the economy, it should encompass and reproduce its core behaviors. Not shuffle them off as inconvenient and uncontrollable variables.
Models of complexity can reproduce price swings, changes in consumer taste and economic collapses since these are what arise naturally under complexity, although we don't normally call them by these names. In scientific vernacular, we call them positive feedback loops, negative feedback loops, time delays and non linearity. So to begin modeling the economy properly, we must map the parlance of money and markets onto the vernacular of complexity.
Economists often think about market mechanisms in terms of so-called stocks and flows. A stock is anything that can be accumulated like total money supply or the number of people employed. Whereas the flow is the rate at which a stock changes. So a central bank increasing or decreasing money supply companies hiring or firing employees.
The stocks and flows of an economy are connected to each other in intricate ways imagine employment falling than a policymaker cutting interest rates to encourage borrowing, increasing the amount of money available for investment, which would then be used by businesses to invest in more productive capacity, leading to more demand for employees which would raise the stock of employment and finally affect future interest rate policy.
Something to notice about this economic scenario that I just outlined is how the output feeds back into the input. We started with cuts to the interest rates from falling employment which were once again influenced by its own produced effect, increased employment. This is how feedback systems work. Positive feedback occurs when the situation is reinforcing. Hence, the word positive doesn't necessarily mean good.
A common example of a positive feedback loop is when someone holds a microphone too close to a speaker, something called the Larsen effect. If this isn't intuitive enough, uh imagine learning to play golf at the beginning, it's not that enjoyable because you're not good at it, but the more you play, the better you get, which makes it more enjoyable, which makes you play more and so on. That would be a positive feedback loop downward. Economic spirals are caused by positive feedback loops.
Imagine a drop in consumer confidence leading to decreased spending leading to decreased production, leading to decreased uh or sorry, leading to unemployment, which leads to even lower consumer confidence. And thus, as per the output to input characteristic of feedback loops, a further drop in spending. This pattern can spiral all the way down into a recession. Positive feedback loops reinforce accelerate or amplify whatever is happening.
Importantly, systems that exhibit positive feedback loops can show exponential growth, exponential collapse or oscillations. With increasing amplitude sound familiar markets can turn explosively upward, drastically downward or fluctuate over long periods of time. This is an example of the kind of behaviors that we see in the economy being explained, not as exogenous factors, but as internal endogenous dynamics within the system itself.
The opposite of positive feedback is negative feedback which leads to a dampening cycle instead of a reinforcing one. So think of a system that pushes in the opposite direction of some initial direction, bringing things back to a more stable state. So a common example is a thermostat, it regulates temperature via negative feedback, negative feedback loops produce dampening cycles, right?
Think of negative feedback as bringing systems back to equilibrium as they oscillate with decreasing amplitude over time. In other words, they peter out perhaps a more intuitive example. My wife and I just experienced this as we approached a crosswalk the other day, deciding whether or not to cross comes down to looking at the countdown on the wa sign, right? So if the numbers are low, then the decision becomes more questionable. Like will we make it?
Well, I noticed, well, I thought I noticed her slowing down which made me slow down, which made her notice me slow down. Which made her slow down and so on. We eventually both stopped and laughed because neither one of us had decided to slow down. So we experienced this dampening cycle if you will, where our motion petered out until we stopped. Not because anyone decided to not cross or to slow down. But rather because we got caught in a negative feedback loop.
Many processes and biological systems use this kind of negative feedback to maintain a desirable state. So examples would include homeostatic situations such as uh you know, thermal regulation, blood sugar regulation or osmo regulation. Things like that dynamic systems also have time delays. We talked about time delays a little bit already, Eric Weinhauer in the origin of wealth. He uses the challenge of finding the right shower temperature as an example.
So think about how you uh you know, tend to overshoot the cold and hot settings in a shower, you go back and forth until you finally get the temperature to where you want, right? What we struggle with is because of the delay in response between the water temperature and our actions. Obviously, the longer the delay, the more difficult it will be to control the shower temperature. Well, similarly, the economy is filled with these kinds of delays. We call that joke about the $20 bill.
It takes time for someone to discover the $20 bill. The drastic assumptions in traditional economics are founded on the notion that transactions happen immediately in any financial system. But there will always be a finite amount of time that passes for any transaction to occur. Remember, the economy is in disequilibrium, right? Disequilibrium not equilibrium. I stated earlier, the economy runs on stocks of inventory order backlogs and slack production capacity.
There are delays in an otherwise continuous process. So a critical thing to realize is that these delays are actually required for an economy to run smoothly. So buffering of stocks like order backlogs allows for more continuous flows of the economy at the aggregate level. It's kind of akin to how buffering works in a streaming service like Netflix.
In order to ensure a good user experience, there must be a constant video play even when there is a momentary drop in the internet connection, right? Well, that's only possible with a backlog of preloaded content. So you can think of instantaneous actually killing many otherwise effective systems. The final behavior listed previously in our mapping of economic parlance on the complexity of vernacular is non linearity. The economy is undoubtedly a non linear system.
A non linear system is a system or a little change in the input can have a dramatic change in the output and vice versa. Well, complex systems are not just nonlinear since even static systems can actually produce curved behavior over time complex systems like the economy are more appropriately modeled as nonlinear dynamic systems. Nonlinear dynamic systems produce a wide variety of behaviors. If you want to get a sense of the various behaviors that nonlinear dynamic systems can produce.
You can look at the quintessential example of chaotic systems called the double pendulum. It's like a regular pendulum, but it's got like two pieces instead of one, you go look at animations online, look, look at the path that it traces out and it's, you know, appears very chaotic, they swing out in these, you know, mostly unpredictable patterns.
Now, while the economy has chaotic aspects to it, it's not a fully chaotic system because there are far more degrees of freedom in an economy than there are in a double pendulum degrees of freedom are just a number of independently variable factors that affect the range of states a system can exist in. So the economy is loaded with a massive number of interacting factors that come together to produce emergent behaviors.
Now, systems that have this kind of staggering number of degrees of freedom are known to exhibit complex modalities. OK. So this means that if the parameters of the system are tweaked just a little bit, then we see dramatic changes in the output. Imagine drawing out the lines on a graph as we typically do with the double pendulum. Again, go look up that animation except this time for genuinely complex systems.
OK. The be the, the the behaviors that we would see would be lines that do all kinds of different things like they would rise and then they would settle something called a fixed point detractor. The lines that produce regular oscillations like a pendulum, which we call a periodic limit cycle lines that show oscillations within oscillations like a heartbeat, something called a quasi periodic limit cycle and lines that appear random for a long time and then eventually repeat themselves.
And we'd also see instances of, you know, complete chaos, which would be something that's deterministic and never repeats, but it's still bounded. So anyways, the point is you see all kinds of different behavior in a genuinely complex system. Remember the economy has multiple stocks and flows and they in they interact in intricate ways and they will showcase positive and negative feedback loops, time delays and nonlinear dynamics.
So there's all those patterns, right, the the the economy has to be accepted as a complex dynamical system, not a basic double pendulum and most definitely not a simple equilibrium system. Now this all amounts to a core truth about non-linear dynamic systems. They have extreme sensitivity to initial conditions, non linearity cause small differences in the initial conditions to be magnified dramatically. Over time. You start a double pendulum from two slightly different starting positions.
You're gonna produce swing patterns that are widely different from one another. Real world. Economies as complex systems would manifest these path discrepancies to the extreme. This is why the economy cannot be modeled analytically. It must be treated appropriately using computing approaches similar to sugar scape, right. In other words, there are no shortcuts when it comes to modeling the economy like you would, if you could do with equilibrium theories, right, that would be a shortcut.
You have to run the program out, you have to use the computer's ability to attempt a massive number of configurations and then witness what emerges. It's important to realize that almost all systems in nature are nonlinear and dynamic. Despite the copious use and promotion of linear models and the sciences genuinely linear systems are exceedingly rare.
Any time someone starts promoting a model for something even remotely non-trivial, look for linearity and go and distributions if you see them run away and just warn others what you saw now as Eric mentions in his book, the Origins of Wealth, the mathematician Ian Stewart actually says that having a domain in physics called nonlinear systems is actually pretty silly. It's like biology, having a field called the study of non elephants.
In other words, almost everything of consequence is nonlinear and dynamic. This is why computation is a must tool if not the tool for doing science today, because only computation can allow us to see how nonlinear dynamic systems evolve. Hence experiments like sugar scape now, it's not that traditional economics hasn't recognized the existence of non linearity, but they have struggled to incorporate them in any meaningful dynamic way.
Their recourse is to either use non-linear relations, nonlinear relationships inside static models or use linear relationships inside dynamic models. But both of those make solving of the equation fairly straightforward. Yes, but there is little reason to believe that they map to reality for reasons that we just discussed. So a little bit jargony there. Hopefully you guys follow that decently. Now, what I want to talk about is kind of what all this leads to. What's kind of the take home message.
What does it mean for our everyday lives? Well, the models of traditional economics, let's kind of sum this up and just say that they should not be used to teach, advise or intervene on our economy. Although of course, they are, they certainly shouldn't be used to attempt to comprehend our economy. They're outdated, dangerously naive and propped up by the illusion of control. The economy is obviously a complex system and as such exhibits the properties we know occur in complex systems.
The overarching lesson when it comes to complexity is always the same. It isn't about control, it's about acceptance. We must accept that nature operates the way it does and look to work with nature rather than against it. So in an economic setting, this means admitting that we live in a world that does not provide many levers to manipulate the outcomes of events. The economy is not the cogs and pistons world of the industrial revolution. It is more akin to an ecosystem that presents stressor.
We must adapt to adaptation does not happen by finding root causes and applying specific changes to control outcomes. It works by embracing variation selection and replication in an effort to produce something that survives. It works by a high level process that doesn't naively reach into the internals of a system of all the properties we looked at exponential growth radical collapse oscillations, positive and negative feedback loops, time delays, non linearity and fat tailed events.
What they all have in common is they emerge. If we set up computational experiments like sugar scape, we can reproduce economic behaviors without programming them into the experiment. They all arise from basic local decisions of the agents involved. This means that whatever we see in our economy, whether it's wealth disparity, disruptive innovation, stock market collapses, et cetera. These are all inevitable behaviors that exist because complex systems produce these kinds of outfits to survive.
Recall my episode on things only look crazy when you stand too close, right? Where I discussed the the, you know, the idea of the cost of complexity, the mechanisms that make complex environments tractable are not free. They come with events and behaviors that humans tend to deem as quote unquote bad. Remember the uh the ant mill or the ant, you know the death spiral go check out that episode.
So we have to accept these behaviors as being there for a reason without knowing the reason we must resist the scient that plagues today's elitist and naive view that we can control nature. So let's get more specific. Let's use an example. Take wealth inequality. Now this is a perfect example of the postmodern belief that we can intervene in an otherwise natural process and create better outcomes for everyone.
This belief is founded on the notion that there are levers, we can pull to outsmart nature as though social engineering hasn't shown us enough disasters, rest assured forcing equal outcome is fully unscientific and guaranteed to fragile any system In the long run, this is baked right into the probabilistic foundations of how networks function. Wealth inequality is a fully inevitable outcome of complexity. Reflecting the Perrino asymmetries we see in complex networks.
Recall my episode on wealth, the middle class and the shape of networks remember that we looked at these asymmetries as they relate to enterprises and their labor. But this doesn't mean there are no solutions to wealth inequality. Complexity doesn't mean throwing your hands up in epistemic resignation, admitting defeat to nature, resigning oneself to whatever station in life one was assigned. Recall the sugar scape ex uh experiment. Remember the agents roamed around a grid.
They looked to improve the situation by acquiring quote-unquote sugar. Now some agents were born close to the sugar mountains and some were even given genetic advantages such as better vision and or increased virility. Most people might assume that the results of such an experiment would produce one of two outcomes. One that the random movement of agents would result in everyone equally finding enough sugar to prosper or two.
A wealth disparity would appear from the advantages given to those born close to the mountains and, or having genetic advantages. But neither of these were the result, there was indeed a wealth disparity which as I just discussed should be fully expected. But those who benefited the most came from all walks of life. It didn't matter where they started on the board or what supposed advantages they were given.
In the end, it was a random mix of agents in the peak of the wealth disparity distribution. So what sugar scape and other models of complexity show us is that while the asymmetries in the economy are a natural and inevitable outgrowth of complex systems, this does not mean only certain individuals must succeed. In other words, accepting wealth and equality is not the same as accepting that only certain people will be prosperous. Now, let's get into this and understand this.
This is because natural networks are not static things. They are dynamic. The nodes that attract the most connections are not the same agent over the long run, different agents come in and out of the wealth distribution's peak, but the peak remains. In other words, it's not the people in society that are invariant. It's the asymmetry itself that is invariant models of complexity have a way of showing us how complexity is supposed to behave.
This is because the models used in complexity don't rely on explicit programming. Beyond basic scaffolding, this means there's much less chance for naive intervention to artificially control how systems evolve. Beyond a few high level constraints and assumptions models of complexity are let loose allowing the computer to run millions of iterations and converge on a result over time. As long as the local interactions of the agents are kept basic and the computer allowed to run many iterations.
The results in computer simulation should be considered a much closer approximation to how nature evolves over time. Compared to some analytical model with predestined outputs designed by people. The behaviors that emerge in sugar scape like different agents prospering at different times are thus arguably the kind of properties we should expect in a healthy economy.
But long term income statistics show this isn't the case, especially in the United States, the biggest economy in the world currently. Whereas models like sugar scape show different agents coming in and out of the wealth peak. The US is much stickier. Social mobility appears quite restricted in the US. Studies show that mobility opportunities are different for poor and wealthy Children. For example, parental incomes and their choices of home locations.
While rearing Children are known to be major factors in wealth disparity. A 2012 pew economic mobility project study found that 43% of Children born into the bottom quintile. In other words, the bottom 20% remain in that bottom quintile as adults. Similarly, 40% of Children raised in the top quintile, which would be the top 20% will remain there as adults. The so-called American dream is a strong narrative in the US.
Apparently, only 32% of Americans agree with a statement that forces beyond their personal control, determine their success. But the American dream is just that it's a dream and it's one that is almost guaranteed statistically to not become a reality for an American citizen. Social mobility is largely anchored on educational opportunities. Certain individuals are granted.
We know that with a degree in hand, these individuals can seek out better jobs, make better money and place themselves into a higher social class. Education is undeniably a leading factor in one's ability to move up the ladder in society. And there in lies the problem. In my opinion, it's the grossly exaggerated importance that society, especially Americans place on institutional intelligence that is largely to blame for the lack of social mobility.
Americans have equated one's education to their intelligence. They have created an entire economy that uses higher education as the gateway to opportunity. The more schooling you have the quote unquote smarter. You are the better the school you went to the quote unquote, smarter you are. Here's the issue. Once you institutionalize intelligence, you do two things, one you make it. So one's current economic standing often via their parents dictates the ability to enter the economy.
In other words, only some can afford education and two you ensure that only certain people who excel at a very narrow definition of smart are given the opportunities. This is what I call bad momentum. By encouraging this narrative around institutional intelligence. We artificially intervene in an otherwise natural process. We prop up patterns that are not as nature intended. This will always in the long run produce bad outcomes.
OK. But wait, but isn't like natural outgrowth of complex systems like the rich get richer mechanism, right? We talked about that before. So isn't that a natural outgrowth of these systems? The rich get richer mechanism. In other words, isn't the preferential attachment of education, an opportunity to uh an end opportunity to those with existing money and certain types of smarts. Isn't that just a reflection of this inescapable reality?
But this confuses informational asymmetry with physical asymmetry? Let me explain, think about a wave, say a big one from a tsunami, the peak of the wave is maintained for a long time, but the water molecules that form the peak are constantly changing. The peak of a proper natural wealth distribution is not a static thing. It's not formed to be the physical allotment of certain individuals.
The peak just means that the probability of finding someone with a lot of wealth is only high for a few individuals at any given time. If you could label each water molecule that makes up a wave, you would see constant mobility that maintains the peak, the dynamic nature of complex systems means agents do not stick around, they swarm in and out of locations to produce informational invariants. We call that thing a wave not physical invariants, you know what's it made of? Right?
In other words, the static look of a wave is more of an illusion caused by the constant motion of different water molecules swirling in and out of that same spot. This is the asymmetry that occurs in complex systems, not physical people and organizations, but concentration of wealth itself as a concept whose form is defined by highly mobile and varying individuals.
Institutionalized intelligence is both expensive and as a deeply flawed notion of what constitutes quote unquote smart, this bakes in bad momentum because money must be available to would be students at the time they get accepted into institutions. This makes a student's opportunity fully dependent on a family's history, not on their own ability to generate wealth since they are too young to do this and scholarships don't help.
Since their qualifier is high academic achievement, which just gets us back to filtering on individuals who already conform to a restricted low dimensional definition of intelligent. The economy cannot function as it should under the narrative of institutionalized intelligence. Such contrived gatekeeping to opportunity artificially restricts the mobility that would otherwise be available to agents inside a naturally occurring complex system.
The competition and selection of natural systems do not function via artificial constructs like educational institutions. They function by competing and cooperating for the creation of genuine wealth. Nature does not need some false narrative to filter an agent's movement into the possibility space of our economy and doing so will cripple the adaptive ability of our economy in the long run.
One might attempt to use my argument to support their claims that things like, you know, equity policies like affirmative action are therefore good. I mean, after all the bad momentum I speak of is a kind of systemic obstacle to a properly functioning system. Why not remove the bad momentum by taking it away from the privileged but establishing better representation inside the peak of a wealth distribution would do nothing to improve mobility.
It would only momentarily change who gets to be in the peak. This is still a naive intervention and would fragile the system in the long run. We know this because we know how complex systems evolve. And we know that the economy is a complex system. Mobility means mobility. It doesn't mean changing who gets to sit in the king's chair even perfect representation has nothing to do with mobility.
If one family from every culture sits at the peak, it will be those families who pass on their privilege with almost everyone in the population, regardless of culture left out giving the current underrepresented among us, you know, better access to academic opportunities cannot solve the problem because it does not solve the core issue, institutionalized intelligence. It is the equating of education to capability that must be destroyed.
Now, I've talked about the pseudoscience of IQ elsewhere to be clear. My take has absolutely nothing to do with race and everything to do with the statistical and scientific laws baked into such studies, equating human intelligence to some standardized test scores wholly circular, performing better within the confines of institutionalized intelligence guarantees you will be given better opportunities in life.
There's a little mystery around the so-called predictive power of IQ and job success when our modern economy only grants opportunities to extremely scholastic individuals. So just keep in mind that good representation will arise naturally in complex systems because variation is a core ingredient in how nature solves problems. So just kind of just wrap the whole thing up, look the models of traditional economics with their convenient reliance on ideas like equilibrium and force vectors.
These keep society bound to the illusion of control. They encourage social engineering because they tell us there are deterministic levers we can pull to control outcomes. Anything beyond what these models predict, which is much of the economy are deemed exogenous and uncontrollable. We use simplistic models as gatekeepers to opportunity because they creep into how we filter individuals in society. This is not some progressive opinion. This is factually how complex systems work.
Economists have a massive influence on how government and businesses function. A lack of social mobility is. But one example of the kinds of problems caused by outdated thinking, we cannot tout the virtues of meritocracy. When our opportunities are fully dependent on some outdated credentialed form of perceived competence. So what can we do? We can embrace realistic but not always convenient models of complexity.
We can appreciate how nature actually works and form our policies and actions around this understanding. You know, one aspect we would have to accept is the intermittent form of an individual's wealth and opportunity. As with water molecules moving in and out to form a wave, people should only be expected to run into wealth for short periods of time. Now, this is very different than how our economy thinks of economic stability and health, right? We seek jobs that pay good ongoing salaries.
We are given lines of credit and mortgages. If we can demonstrate continuing income and payments on debt over time at the individual level, we are expected to land an opportunity which provides us enduring and growing economic status. But added to the list of complex behaviors, I already mentioned, intermittency is a fundamental modality nature tends to produce its behaviors in fitful, infrequent and occasional bursts.
There is a strong argument to suggest that it is more natural for people to run into their economic opportunities once in a while rather than land, a good job maintained until retirement.
This is in line with one of the consequences of fat tail distributions I discussed previously complex systems have almost all their outcomes dictated by rare events, having an economy where an individual's wealth is largely determined by a few instances of economic success may be the most natural economy of all after all. Do we really need to make good money continuously or do we just need a few windfalls to bring about prosperity in our lives?
Does the same company need to be around for more than 10 to 15 years for the individual? This suggests entrepreneurism is a better path than traditional employment for organizations that suggests companies shouldn't be allowed to become artificially too big for too long practices like VC funding and lobbying. Maybe other sources of stifled mobility are we destined to be self-made?
Intermittent heroes of our own economic journeys will antitrust laws make a comeback to keep competition more natural or will the illusion of stability from misplaced models keep us bound to naive notions of wealth at the expense of almost everyone in society. Will the false levers of traditional economics prove too tempting for society to even try time will tell as always. Thanks for listening. Until next time.