Keynes and American Economic Thought" Book Launch: A New Dawn or a Walking Dead Scenario?

To all you people obsessed with models and theorems: honestly, just give it a rest. When are economists finally going to realize that there isn't some magic little formula that can account for how humans actually act? One day everyone is going to react one way, and the next day they’ll flip entirely. You can't just look at what happened yesterday and assume you know what someone is going to do tomorrow.

Economists rely too much on their models 😁

Luck isn't part of the equation when you're trying to force math where it doesn't belong. I had a friend in management at a major US bank—brilliant guy, arguably the best physicist in the country—who walked away from the industry during the 2007/08 crash after seeing how things actually worked. His parting shot? He told me, "I prefer the Austrian school."

He’d probably lose his mind if he knew I was sharing bits of our private correspondence, but here are a few snippets to illustrate my point.

"...what I like about them (referring to the Austrians) is that they don't overdo the math and statistics. Personally, I find the heavy math approach useful because it creates a hierarchy. It's easy to install someone in a high position just because they can handle complex formulas. They can basically tell you, 'Here is Equation 113a; the vector gradient is anti-correlated with the eigenvalues of the risk matrix BI-I, which justifies the bailout—now deal with it.' But if we're being honest, I agree with them: you can't solve everything with equations. I've read endless papers in physics, math, biology, and even economics—I've even authored a few myself—and I've seen a massive overreliance on models and stats..."

"...saying 'no equations' doesn't mean zero math, but people often try to introduce formalisms that have no chance of working. They build models based on assumptions that kill 50% of reality, and then the results end up being incredibly sensitive to those flaws. Having sat in on numerous board meetings and watched senior management in action, I don't have to guess how things work. I was there doing the work."

....That’s why I prefer the Austrian approach over these self-important modelers; I could outwork any of them. Look at physics: you get actual, useful results there. But you can't do that in this field because a model has to be perfect to be taken seriously. Well, no pain, no gain. I attended a couple of economics conferences recently and met a modeler from the Federal Reserve. He had this inflation model for the US, complete with some charts and graphs. After his presentation, I asked him about the predictive statistics. He looked at me and said, "Oh, we don't look at it that way; we were just fitting it to past data." So, they basically built a model with five or six parameters, slapped it onto historical data, and called it a paper. I could churn out twelve of those a month. In physics, that wouldn't even qualify as a paper. In this field, they'd sell it as a breakthrough.

Bradley Walker88 said:Economists rely too much on their models 😁

Luck isn't part of the equation when you're trying to force math where it doesn't belong. I had a friend in management at a major US bank—brilliant guy, arguably the best physicist in the country—who walked away from the industry during the 2007/08 crash after seeing how things actually worked. His parting shot? He told me, "I prefer the Austrian school."

He’d probably lose his mind if he knew I was sharing bits of our private correspondence, but here are a few snippets to illustrate my point.

"...what I like about them (referring to the Austrians) is that they don't overdo the math and statistics. Personally, I find the heavy math approach useful because it creates a hierarchy. It's easy to install someone in a high position just because they can handle complex formulas. They can basically tell you, 'Here is Equation 113a; the vector gradient is anti-correlated with the eigenvalues of the risk matrix BI-I, which justifies the bailout—now deal with it.' But if we're being honest, I agree with them: you can't solve everything with equations. I've read endless papers in physics, math, biology, and even economics—I've even authored a few myself—and I've seen a massive overreliance on models and stats..."

"...saying 'no equations' doesn't mean zero math, but people often try to introduce formalisms that have no chance of working. They build models based on assumptions that kill 50% of reality, and then the results end up being incredibly sensitive to those flaws. Having sat in on numerous board meetings and watched senior management in action, I don't have to guess how things work. I was there doing the work."

....That’s why I prefer the Austrian approach over these self-important modelers; I could outwork any of them. Look at physics: you get actual, useful results there. But you can't do that in this field because a model has to be perfect to be taken seriously. Well, no pain, no gain. I attended a couple of economics conferences recently and met a modeler from the Federal Reserve. He had this inflation model for the US, complete with some charts and graphs. After his presentation, I asked him about the predictive statistics. He looked at me and said, "Oh, we don't look at it that way; we were just fitting it to past data." So, they basically built a model with five or six parameters, slapped it onto historical data, and called it a paper. I could churn out twelve of those a month. In physics, that wouldn't even qualify as a paper. In this field, they'd sell it as a breakthrough.

So physicists are basically the scapegoats for everything wrong with economics. 😁
Ever since Debre, they’ve stormed into the field and tried to math everything into submission. They lean on these massive assumptions just because actual data is hard to come by. Take Black-Scholes—it relies heavily on a normal probability density function, even though we all know the real-world data being modeled is anything but normally distributed. Look at Lehman Brothers; they went under because a Monte Carlo simulation missed the mark.

By the way, there's a huge difference between models meant for forecasting and those meant to explain relationships. People still misuse them just to churn out papers, even when the results make zero sense intuitively...

Professor Planck, of Berlin, the famous originator of the Quantum Theory, once remarked to me that in early life he had thought of studying economics, but had found it too difficult! Planck could easily master The whole corpus of mathematical Economics in a few Days. He did not mean that! But The amalgam of logic and intuition and The wide knowledge of facts, most of which are not precise, which is required for economic interpretation in its highest form is, quite truly, overwhelmingly difficult for those whose gift mainly consists in the power to imagine and pursue to their furthest points the implications and prior conditions of comparatively simple facts which are known with a high degree of precision.

Bottom line: it's a complex system. And as for forecasting... that's a nightmare even when humans aren't part of the equation. Imagine trying to calculate exactly where and when a single leaf will hit the ground in autumn. 😉
Don't throw the models out entirely, but you have to understand them. No matter how much math you know, you need enough common sense to say "WTF" when MATLAB spits out something totally insane.

Check this out, caught my eye earlier:

"Lovrinović warns that in the US, the Federal Reserve was basically the first line of defense against the crisis, noting that one of the core duties of monetary authorities during a crisis is to ensure the government has the funds needed to invest back into production. In America, however, laws prevent the Federal Reserve from lending money directly to the government."

So, what exactly is the government supposed to be producing?

social cases.

ruggeddriver70 said:Check this out, caught my eye earlier:

"Lovrinović warns that in the US, the Federal Reserve was basically the first line of defense against the crisis, noting that one of the core duties of monetary authorities during a crisis is to ensure the government has the funds needed to invest back into production. In America, however, laws prevent the Federal Reserve from lending money directly to the government."

So, what exactly is the government supposed to be producing?

Maybe various capital goods that actually provide a lasting positive multiplier effect for the economy—projects that aren't just corrupt or amateurish, which I guess an American textbook on stupidity could write an entire volume about. We need things that don't just create a tiny spike before crashing (I touched on this briefly in Miami... check out slide 15 of this presentation). Since most of these are imports anyway, there wouldn't even be any domestic production involved.
Roha already went over how monetary policy needs to be countercyclical from the start of the crisis until now, but since monetary and fiscal policies move in tandem, they won't just be shouting into the void...😁
As for the state getting direct credit from the Federal Reserve—God forbid. It’s probably for the best they fought to keep that decade-old law in place. Just imagine if inflation were allowed to run wild like that...
Besides, comparing the Federal Reserve to the local central bank, or the US economy to the American one, is absolute nonsense. The same goes for claims regarding "monetary sovereignty." That's basically like asking for "globalization sovereignty," or something along those lines.

I don't know about you guys, but to me, it’s crystal clear that there are two fundamentally different types of economic theory out there. Control and peasant-led movements.It really comes down to two fundamentally different types of people. The controllers and the peasants..

Controllers. They want to use their theories to control the working class because they honestly believe people are complete idiots. In their minds, if they didn't step in with constant oversight, everyone would just descend into pure chaos—turning into a disorganized mess that ruins everything. They think that without their guidance, we’d hit a point where productivity collapses entirely, leading to widespread famine because nobody would be left actually doing the work. So, they frame themselves as the saviors. They act like they're the only thing standing between us and total self-destruction, preventing society from spiraling into nothingness. Thank God we have these controllers and their little models, right? Because if it weren't for them, the world probably wouldn't even exist by now.

Peasants Some people have their own theory, and it’s pretty straightforward: just leave me alone. Don't mess with me, don't hover, and stay out of my way. Let me live my life. Get your theories and your complex models away from me. Honestly, just get lost and let me be. I want to work on what I want, when I feel like it—even when I think I’m doing something great, and especially when I know I'm absolutely screwing up. That’s my theory. It’s pure, simple, and honest. Just good old-fashioned common sense.

Regulators, honestly, they get so caught up in their own theories that they completely miss the mark. They're just throwing around empty buzzwords and can't stand a bit of plain, old-fashioned common sense. It’s frustrating. They seem totally blind to reality. Don't they see that if we don't manage this properly, everything is going to fall apart in a single season? If they keep playing these games, who's actually going to be left to run the show and keep things moving?

It’s honestly baffling how some people react to management. Instead of just adapting, they struggle like cattle being led to slaughter. It makes no sense to me. Only someone truly out of touch would fight against a solution that’s actually trying to save them from making a complete mess of things.

And so, in an attempt to keep them under control, the regulator keeps dreaming up more and more sophisticated models—massive frameworks, bloated simulations, tiny little formulas—all just to find sneakier, quieter ways to manage the masses. It’s all part of the effort to prevent this whole thing—thank God—from turning into a complete disaster out in the fields.

Look, at the end of the day, an average Joe is still an average Joe. He might be unrefined or lacking in sophistication, but he isn't completely brainless. Eventually, there comes a defining moment where he realizes exactly who is pulling the strings behind the scenes—that shadowy controller working from the sidelines. And when that realization finally hits... man, it’s going to be intense. It’s shaping up to be a pretty long afternoon. (Just like Robbie Williams would say in his music video, "She's Madonna.")

There’s a massive, fundamental divide between the controllers and the farmers. The controllers are convinced that things will stay exactly as they are, while the farmers don't even realize yet that everything is about to change.

Which one are you?

I don't know what you're seeing, man, but usually when I run into transit inspectors, it’s just someone checking tickets on the subway—and the only other "locals" I see coming into Chicago are folks out on tractors, looking for those government subsidies being paid for right out of my pocket.

Elizabeth Harris11 said:I don't know what you're seeing, man, but usually when I run into transit inspectors, it’s just someone checking tickets on the subway—and the only other "locals" I see coming into Chicago are folks out on tractors, looking for those government subsidies being paid for right out of my pocket.

You've got a point there. That totally slipped my mind. My apologies.

brightlynx11 said:So physicists are basically the scapegoats for everything wrong with economics. 😁
Ever since Debre, they’ve stormed into the field and tried to math everything into submission. They lean on these massive assumptions just because actual data is hard to come by. Take Black-Scholes—it relies heavily on a normal probability density function, even though we all know the real-world data being modeled is anything but normally distributed. Look at Lehman Brothers; they went under because a Monte Carlo simulation missed the mark.

By the way, there's a huge difference between models meant for forecasting and those meant to explain relationships. People still misuse them just to churn out papers, even when the results make zero sense intuitively...

Professor Planck, of Berlin, the famous originator of the Quantum Theory, once remarked to me that in early life he had thought of studying economics, but had found it too difficult! Planck could easily master The whole corpus of mathematical Economics in a few Days. He did not mean that! But The amalgam of logic and intuition and The wide knowledge of facts, most of which are not precise, which is required for economic interpretation in its highest form is, quite truly, overwhelmingly difficult for those whose gift mainly consists in the power to imagine and pursue to their furthest points the implications and prior conditions of comparatively simple facts which are known with a high degree of precision.

Bottom line: it's a complex system. And as for forecasting... that's a nightmare even when humans aren't part of the equation. Imagine trying to calculate exactly where and when a single leaf will hit the ground in autumn. 😉
Don't throw the models out entirely, but you have to understand them. No matter how much math you know, you need enough common sense to say "WTF" when MATLAB spits out something totally insane.

Basically, use them only to confirm what you already know. If they don't back you up, scrap them. 😁

There’s a bigger issue here. It isn't just about technical math proficiency. You have to decide what actually warrants being formalized into math and what doesn't. Economics needs more philosophy and epistemology, not more calculus. It's no coincidence Hayek focused so much on epistemology; he saw exactly where the field got stuck.

Known knowns, unknown unknowns, unknown knowns, ...and all that jazz... 😁

I think Taleb does a killer job of breaking down these exact issues in Black Swan. Honestly, I highly recommend picking up the book. In my own experience, I see so many "models" and "theories" that look incredible on paper because they use fancy equations and gorgeous charts, but at their core, they’re just leaning heavily on a normal distribution. It only takes one unexpected outlier—a Black Swan, or those "unknown unknowns" mentioned in this video 🙂—to send the entire model or theory straight into the trash, usually while you're going bankrupt in the process (look at what happened to LTCM). But hey, I guess those people need a way to make a living too, so let them have their fun...

Why on earth would you think we can't bake uncertainty right into a mathematical model? I mean, look—the entire foundation of Quantum Theory is built on exactly those kinds of models (which is why some people just hate them, but honestly, there's nothing better). It’s just like how people make "unpredictable" decisions; certain subatomic particles act like they have a mind of their own, too, where they might decide one thing with one probability and something else entirely with another. The point is, you *can* determine those probabilities if you know the initial conditions. Even if we can't pinpoint exactly what’s going to happen, we can at least map out a bunch of possible scenarios based on that uncertainty—and assign a probability to each one—so we can build a strategy accordingly. That’s literally how things are done!

And now we’ve got this situation where the hard scientists are basically spitting on the social sciences because they aren't "exact" enough—claiming they only offer "middle-range theories," as E. Pusić used to say, rather than grand, universal ones like Maxwell's theory of electromagnetism. But that doesn't mean those kinds of theories won't emerge eventually; in fact, it's impossible to reach true Artificial Intelligence without using mathematical models. If people had always thought like this: "Hey, my dear Galileo, who cares if all objects fall at the same rate due to gravity when everyone knows a rock is going to hit your head much harder than a feather," where would the natural sciences be today? Simply put, we have robust natural sciences because of that mindset, and we’ll eventually have social sciences that hold up just as well. Then we'll finally know if Keynes was an Aristotle or a Galileo—which doesn't take away from the value of an Aristotle, or even a Keynes, in the first place.

Bradley Walker88 said:Basically, use them only to confirm what you already know. If they don't back you up, scrap them. 😁

There’s a bigger issue here. It isn't just about technical math proficiency. You have to decide what actually warrants being formalized into math and what doesn't. Economics needs more philosophy and epistemology, not more calculus. It's no coincidence Hayek focused so much on epistemology; he saw exactly where the field got stuck.

Known knowns, unknown unknowns, unknown knowns, ...and all that jazz... 😁

Yep, that’s called confirmation bias for curated facts. Throw that in a journal and suddenly it’s "academic" instead of just a barroom argument. Then again, all economics is basically just a glorified fancy barroom argument. 😁

Bradley Walker88 said:Basically, use them only to confirm what you already know. If they don't back you up, scrap them. 😁

There’s a bigger issue here. It isn't just about technical math proficiency. You have to decide what actually warrants being formalized into math and what doesn't. Economics needs more philosophy and epistemology, not more calculus. It's no coincidence Hayek focused so much on epistemology; he saw exactly where the field got stuck.

Known knowns, unknown unknowns, unknown knowns, ...and all that jazz... 😁

Spot on. That’s why econ students need to grind through economic logic and philosophy alongside the math.

Solid book on the subject, great starting point.

wiredtinker12 said:Why on earth would you think we can't bake uncertainty right into a mathematical model? I mean, look—the entire foundation of Quantum Theory is built on exactly those kinds of models (which is why some people just hate them, but honestly, there's nothing better). It’s just like how people make "unpredictable" decisions; certain subatomic particles act like they have a mind of their own, too, where they might decide one thing with one probability and something else entirely with another. The point is, you *can* determine those probabilities if you know the initial conditions. Even if we can't pinpoint exactly what’s going to happen, we can at least map out a bunch of possible scenarios based on that uncertainty—and assign a probability to each one—so we can build a strategy accordingly. That’s literally how things are done!

And now we’ve got this situation where the hard scientists are basically spitting on the social sciences because they aren't "exact" enough—claiming they only offer "middle-range theories," as E. Pusić used to say, rather than grand, universal ones like Maxwell's theory of electromagnetism. But that doesn't mean those kinds of theories won't emerge eventually; in fact, it's impossible to reach true Artificial Intelligence without using mathematical models. If people had always thought like this: "Hey, my dear Galileo, who cares if all objects fall at the same rate due to gravity when everyone knows a rock is going to hit your head much harder than a feather," where would the natural sciences be today? Simply put, we have robust natural sciences because of that mindset, and we’ll eventually have social sciences that hold up just as well. Then we'll finally know if Keynes was an Aristotle or a Galileo—which doesn't take away from the value of an Aristotle, or even a Keynes, in the first place.

The core issue here is that people treat uncertainty (risk) as a mere statistical value. Most people building math models just assume everything follows a normal distribution. They think "risk" is just anything sitting more than three standard deviations away from the mean. Fine, that works if you're dealing with a bell curve. But there are plenty of events and phenomena out there that don't follow a normal distribution at all, where you can't just slap a simple model on them—or if you do, the model itself shifts unpredictably.

Maybe I'm talking nonsense. I haven't graduated from the University of Chicago or the University of Pennsylvania, or any of those Ivy League schools...

Yeah, basically you have to account for the possibility that your statistics are just plain wrong—that your sample size is garbage, your data is thin and sketchy, or you’ve messed up the entire distribution... 🙄

You can't just lean on stats alone; you've got to bring in some common sense and actual intuition. The real question is which one ends up winning out. It’s not exactly rocket science to try and prove something that’s obvious to anyone with eyes, but I think that's kind of the point—using a model to smash through the biases of "common sense" or intuition to find some fresh insight that actually lets you make a better prediction. Or, conversely, using common sense to toss a model aside because it just doesn't apply to specific, real-world conditions. So, either way, you need a bit of basic logic and a much broader perspective than what you'd find in the mathematics and natural sciences. Math isn't enough on its own. But then again, you can't go without it either, because if you do, you just fall into this "scholastic," oversimplified pattern that you're stuck in—you lose the ability to break out of it.

When you’re relying on a model to tell you exactly how much risk you’re taking, don’t forget to factor in one very specific variable: the risk that the model itself is dead wrong. 😬

Mises's core argument against trying to define economic laws through math is pretty simple: human action belongs to a fundamentally different category of phenomena than physical objects reacting to force.

The people obsessed with using mathematical models in economics just can't accept this as truth.

Mainstream economic theory focuses entirely on answering one question: "What should we do to make the community's economy better?" In this view, "abundance" is strictly limited to material things like houses, cars, or cash.

Alternative economic theory asks a different question: "What allows an individual to gain freedom and live their life exactly how they want to achieve better economic outcomes?" To this school of thought, abundance includes anything a person might find worth spending their limited resources on—whether that’s material goods (houses, cars, money) or non-material things (friendship, peace of mind, love, esotericism, metaphysics, or even a moment of nirvana).

It’s easy to see why mainstream theory tries to reduce everything to math: they believe nothing exists beyond matter, so they don't bother looking any deeper.

Alternative economic theory doesn't claim there's some mystical force governing economic relations; it just refuses to take a hardline stance on whether such a thing exists. Its role is simply to identify the patterns that emerge within the economic interactions of individuals and groups, without passing judgment on their value.

That doesn't mean human action shouldn't be subject to moral judgment; it just means that economic science isn't tasked with doing it.

Gregory Nelson6 said:Mises's core argument against trying to define economic laws through math is pretty simple: human action belongs to a fundamentally different category of phenomena than physical objects reacting to force.

The people obsessed with using mathematical models in economics just can't accept this as truth.

Mainstream economic theory focuses entirely on answering one question: "What should we do to make the community's economy better?" In this view, "abundance" is strictly limited to material things like houses, cars, or cash.

Alternative economic theory asks a different question: "What allows an individual to gain freedom and live their life exactly how they want to achieve better economic outcomes?" To this school of thought, abundance includes anything a person might find worth spending their limited resources on—whether that’s material goods (houses, cars, money) or non-material things (friendship, peace of mind, love, esotericism, metaphysics, or even a moment of nirvana).

It’s easy to see why mainstream theory tries to reduce everything to math: they believe nothing exists beyond matter, so they don't bother looking any deeper.

Alternative economic theory doesn't claim there's some mystical force governing economic relations; it just refuses to take a hardline stance on whether such a thing exists. Its role is simply to identify the patterns that emerge within the economic interactions of individuals and groups, without passing judgment on their value.

That doesn't mean human action shouldn't be subject to moral judgment; it just means that economic science isn't tasked with doing it.

But honestly, what even is the foundation of morality? For all we know, what we call "morals" might just be one long, repeated game that happened to hit an equilibrium at certain points—though there's absolutely no guarantee it won't be totally disrupted down the road by things like technological breakthroughs or shifts in society, right? In that sense, Game Theory actually goes way beyond standard economics; it acts as this unique bridge for behavioral sciences, linking them back to biology through evolutionary game theory, heading toward what Herbert Gintis calls "sociological game theory." In that framework, people aren't just these perfectly rational, selfish robots—because let's face it, that's just not how reality works. Humans are capable of altruism and all sorts of other behaviors that you simply can't explain away using nothing but pure rationality and egoism. At the start of his preface, Gintis quotes John Maynard Smith: "The mathematics and natural sciences are sterile, yet natural science without mathematics is muddled." Economics sits right in that sweet spot between the natural and social sciences, so it really ought to be the first among the social sciences to actually get a better handle on aligning theory with experimentation—because right now, the field feels like it hasn't moved much compared to how the natural sciences stood 300 years ago. Some theories align pretty well with "experimentation" (meaning the data, whatever form it takes), while others... well, others are just straight-up alchemy.

wiredtinker12 said:Why on earth would you think we can't bake uncertainty right into a mathematical model? I mean, look—the entire foundation of Quantum Theory is built on exactly those kinds of models (which is why some people just hate them, but honestly, there's nothing better). It’s just like how people make "unpredictable" decisions; certain subatomic particles act like they have a mind of their own, too, where they might decide one thing with one probability and something else entirely with another. The point is, you *can* determine those probabilities if you know the initial conditions. Even if we can't pinpoint exactly what’s going to happen, we can at least map out a bunch of possible scenarios based on that uncertainty—and assign a probability to each one—so we can build a strategy accordingly. That’s literally how things are done!

And now we’ve got this situation where the hard scientists are basically spitting on the social sciences because they aren't "exact" enough—claiming they only offer "middle-range theories," as E. Pusić used to say, rather than grand, universal ones like Maxwell's theory of electromagnetism. But that doesn't mean those kinds of theories won't emerge eventually; in fact, it's impossible to reach true Artificial Intelligence without using mathematical models. If people had always thought like this: "Hey, my dear Galileo, who cares if all objects fall at the same rate due to gravity when everyone knows a rock is going to hit your head much harder than a feather," where would the natural sciences be today? Simply put, we have robust natural sciences because of that mindset, and we’ll eventually have social sciences that hold up just as well. Then we'll finally know if Keynes was an Aristotle or a Galileo—which doesn't take away from the value of an Aristotle, or even a Keynes, in the first place.

Probability doesn't capture all "knowledge." Throwing in a probability and a standard deviation doesn't account for total uncertainty. These models completely ignore human action and consciousness. People aren't marbles or subatomic particles.
How do you model something when you don't even realize what you don't know? And the worst part is trying to deal with the things you don't even realize you *do* know. 😁

wiredtinker12 said:But honestly, what even is the foundation of morality? For all we know, what we call "morals" might just be one long, repeated game that happened to hit an equilibrium at certain points—though there's absolutely no guarantee it won't be totally disrupted down the road by things like technological breakthroughs or shifts in society, right? In that sense, Game Theory actually goes way beyond standard economics; it acts as this unique bridge for behavioral sciences, linking them back to biology through evolutionary game theory, heading toward what Herbert Gintis calls "sociological game theory." In that framework, people aren't just these perfectly rational, selfish robots—because let's face it, that's just not how reality works. Humans are capable of altruism and all sorts of other behaviors that you simply can't explain away using nothing but pure rationality and egoism. At the start of his preface, Gintis quotes John Maynard Smith: "The mathematics and natural sciences are sterile, yet natural science without mathematics is muddled." Economics sits right in that sweet spot between the natural and social sciences, so it really ought to be the first among the social sciences to actually get a better handle on aligning theory with experimentation—because right now, the field feels like it hasn't moved much compared to how the natural sciences stood 300 years ago. Some theories align pretty well with "experimentation" (meaning the data, whatever form it takes), while others... well, others are just straight-up alchemy.

The foundation of morality lies within the individual mind. Alternative economic theory suggests that humans are fundamentally more unpredictable than any physical particle. To be more precise, we are dealing with two entirely different classes of phenomena that are so distinct that the laws governing one cannot be applied to explain the other, and vice versa.

Of course, mainstream economic theory disagrees with this premise. In fact, they fight against it, trying desperately to prove it wrong.

The beauty of Mises's economic theory is that he doesn't try to dictate which specific laws govern human action compared to material particles. He simply insists that those laws are fundamentally different and rejects any attempt to use mathematical models to explain human behavior.

I’d go a step further: I think the sole mission of Mises and the Austrian School of Economics is to deny, dismantle, and essentially destroy any possibility of using math to explain human choice. Their entire effort is focused on showing that you can only truly begin to understand human behavior once you completely abandon trying to view it through the lens of the natural sciences.