My argument is that the it’s irrelevant whether the presuppositions can be known with certainty. You can attach a probability estimate to them, allowing for the uncertainty of your missing variables, discount the evidence from experimental and behavioral economics accordingly, and update your priors accordingly. If your unconditional probability assignment is such that the uncertainty influenced by those missing variables discounts all such evidence by 100%, I really want you to show your work.
Austrians recognize that there is an unquantifiable variable in economics, namely human action, which heavily influences economic outcomes. You want to insert an arbitrary (estimated) variable value, i.e. probability estimate, in a model to account for something that Mises claims cannot be accounted for based on experience and historical fact.
Since you seem to believe that the variable value can be known and quantified for modeling purposes, what is it? What are the attributes of the variable collection which represent human action in economics?
Mises claims that human action is present, significant and cannot be measured. Are you claiming human action is absent, insignificant or measurable?
If you can set up the conditions to prove your case experimentally, then you have an argument.
How are your assumptions, i.e. probability estimates, inserted in a model going to provide feedback that will enable a valid update of the priors? Is that not circular reasoning?
If the claims made by Mises and the Austrians went no farther than to say human action cannot be measured and therefore nothing in economics can be measured, you would have an argument simply because their thinking would be inadequate. This is not the case.
To the contrary, Mises thinking regarding economic calculation in the socialist commonwealth clearly shows that human action coupled with ownership is a required component of a healthy and sustainable economy. Human action is necessary and yet cannot be measured or predicted, except that people are going to act in such a way as to satisfy their own self interest, which is conditional and subjective.
If experience and fact can be used to account for human action in economics, then Mises claims are false.
If they cannot, why discount his theory because he acknowledges a real-world constraint using a presuppositional argument?
If human action could not be predicted, the results of experiments into the Allais Paradox, preference reversal, conjunction fallacy, and on and on, should be a random walk. Since they’re not, human action can be to some measure predicted. If an Austrian believes all such research should be discounted by 100%, I’m taking issue with whatever prior gives that result.
And no, using priors in the way I described is not circular reasoning. Recall Bayes’ Rule for updating on evidence: P(H|E) = P(H)P(E|H)/P(E)
To be as clear as possible, let’s use the following example. We want to test the hypothesis “People act rationally and self-interested.” As a definition for rationality, let’s say people’s STABLE preferences disallow intransitivity.
Say I start with a prior for the hypothesis, P(H)=0.9. The likelihood that we see experimental evidence of intransitive preferences given this hypothesis must be fairly low, but there could always be experimental error, so P(E|H)=0.05. This estimate is where my priors come in as I described above. If I think it’s equally likely for an experiment to show evidence of intransitivity as transitivity, even given my hypothesis, P(E|H)=0.5.
I discount by my estimate that there will be experimental evidence of intransitive preferences regardless. P(E) = P(H1)P(E|H1) + P(H2)P(E|H2). Given P(Intransitivity results | People are rational) = 0.05, P(Intransitivity | People are irrational) = 0.95, we have, for the case of the believer P(E) = 0.05 0.9+0.1 0.95 = 0.14 and, for the case of the skeptic, 0.5 0.9+0.1 0.5 = 0.5. So, for the believer, evidence of intransitivity gives 0.90.05/0.14 = 0.32, and for the case of the skeptic, 0.9 0.5/0.5 = 0.9, ie, no updating.
Mises argues that we can never have any evidence of intransitive preferences because preferences are not stable. Thus, the preference reversal evident in choosing Gamble 1 in Part 1 and Gamble 2 in Part 2 of the Allais Paradox can never be evidence of intransitive preferences. But, I argue that if we show, in study after study, across the majority of people, that the preference for Gamble 1A and Gamble 2B is stable over time—seconds, weeks, months, years, lifetimes even!--that we should discount the skeptic argument P(Intransitivity results | People are rational) from 0.5 to something lower, akin to P(E|H) = 0.05.
But that’s not where it begins. I’m saying that experimental evidence of such preference stability should change your probability estimate of P(Preferences are stable) from 0.5 (This variable is mystical, completely unknown, sublime and unknowable even to a superintelligent AI with the capability of doing a nanosweep of your entire noggin) to something much higher, like 0.9 (I am pretty damn sure this preference is stable because the evidence says so and evolutionary psychology suggests it’s universal). Even if you want to leave it highly unknown, P=0.51, this will change your update according to the evidence. So it’s not circular reasoning. It’s using priors/updates on one hypothesis (preferences are stable) to update on another hypothesis (people are sometimes irrational).
If you’re arguing that we should remain radically uncertain even in the face of such evidence, I want to know the priors you assign. Saying “it’s unknown” isn’t enough. How unknown is it? I have trouble believing it’s really a 50⁄50 split. Are we really equally likely to see most people choose Gamble1A and Gamble 2B in every experimental study with highly statistically significant results across times and cultures as we are to see a random walk? If so, how come we never see random walks?
Human action can indeed be to some measure predicted.
For instance, if I conducted an experiment with 100 people wherein I presented each person with the opportunity to place their bare hand on a red hot burner on a stove, including leaving it there for one minute, I predict 100% would say no. I could even model that experiment.
However, this kind and degree of predictability is meaningless in the context of economic modeling.
What if the person who is being presented with the choice in the Allais Paradox just lost their mother to death, as well as losing their job in the same week? How does this affect the model? What does that research show?
How does one account for decisions made without adequate consideration, or when the decision maker doesn’t understand the problem? What about the follow on effects of choices made in the past which encumber via contract, or cause emotional or financial pain, such that the decision is not rational or the risk assessment is distorted? Or the reverse when the rewards have been great in the past?
How many life choices exist in such pristine, simple and clear conditions as the Allais Paradox?
Are not our choices, responsibilities, assets, liabilities, obligations, future earnings, job markets, work relationships, preferences, skills, talents, capital, regulatory environments, choices of other people, comparative advantages, currency fluctuation, taxation, inflation, religious beliefs, IQ, education, weather, genetics, resource allocation, scarcity, social stability, time constraints, competing demands, influence of peers, influence of media, family relationships, beliefs about the future, and more, all knit into each decision made?
Are you really claiming that the minor complexities presented in such a simple model as the Allais Paradox rise to the level of mathematically illuminating, for the purpose of useful economic modeling, the myriad decisions inherent in daily life? After all, everything in life depends, at some significant level, on exchange of productivity, which is generated as a result of the decisions of life.
My point is that the models relating to human action which are herein employed as proofs, are not sufficiently complex to be useful or meaningful in economic modeling.
You criticize the Austrian school on the basis of presuppositions which are designed to note the limits of our ability to construct theories or predict future events. At the same time, all that is offered to suggest we are not limited are simplistic and wholly inadequate models which do nothing to solve the problem. As long as Mises claims we can’t know or test these things and no one else shows that we can, I have to agree with Mises.
Besides, if these things were knowable, Mises would never have accepted stopping at this level. He would have anticipated and likely discovered and modeled the information so as to press another layer deeper, in hopes of gaining a greater mastery of the subject.
Everyone who is doing economics is working on the assumption that there are some useful regularities about human behaviour. None claim a model that perfectly predicts the behaviour of every individual. What distinction are you drawing here between the regularities that the Austrians assume about human behaviour, and the regularities that other economists assume?
Austrians believe that modeling for purposes of prediction is fruitless. Modeling for the purpose of control is unethical and oppressive because property rights are violated.
Other economists believe they can successfully model and manage an economy. They deal in numbers without taking into consideration human action at a level that has explanatory power. Monetarists, Keynesians, etc. ignore human action and generally treat the notion as unimportant. Austrians claim human action cannot be modeled, but knowledge of human action is required in order to model.
Austrians, for example, are able to model the effects of unrealistically cheap money, which is the source of malinvestment which leads to a boom bust cycle. We are experiencing the bust now.
With Austrians, things that can be modeled are modeled. Things that cannot be modeled or achieved are accepted, rather than, like the Keynesians, arrogantly claiming knowledge which is proven wrong time and time again.
Every time we have a bust, we are first told it should never have happened because after the last bust the bankers were given the tools necessary to prevent the bust. Then we are told that they just need a few more tools in their bag in order to fix the problem and ensure it never happens again. Then it happens again, each time bringing us nearer to the hyperinflation of 1920s Germany or today’s Zimbabwe.
The economists which claim to be able to manage our economy for our good are either liars or incompetents or both. And we are supposed to accept their critique of the Austrian baseline?
Claiming the presuppositions are wrong is fine, if one can show that these need not be presuppositions because they can indeed be measured and worked into a predictive model… This proof I have not observed in a research model, let alone in the applied science, which we live with daily.
Models are used for prediction in all sorts of domains. Each of us has a mental model (or “theory of mind”) of how others behave to a significant degree of accuracy. Economics often covers situations well outside the range of the evolutionary adaptive era for which our intuitive mental models don’t work as well. If modeling were truly useless, it wouldn’t matter if it was used “for the purpose of control” because it wouldn’t get you anywhere.
I wish Matthew Mueller’s Post-Austrian Economics blog was still up, because he made a good point about the unfortunate entanglement of austrian economics with political libertarianism since Rothbard. This results in some of its adherents viewing people who think their method is flawed as political enemies. For the record, I still read sites like mises.org & Lew Rockwell (though to a lesser extent recently due to all the competing distractions on the internet and my banning from the comments section of the former) and appreciate the work they do in bringing economics to a wider audience even if they can exhibit the flaws they point out in Rand’s circle.
There is a difference between modeling and manipulating.
To model, is to create a framework that describes something.
To manipulate is to choose one or more elements among the known attributes of the model which can be controlled and then use that to coercively accomplish goals; then set the model up to “show good things are happening” based on the all wise management of the modeled system by the managers.
You note “a significant degree of accuracy”. The point is that the degree of accuracy that can be attained is insufficient for the purpose.
Austrians believe that modeling for purposes of prediction is fruitless.
So if someone does successfully make a prediction about human behaviour, for example that a price increase will reduce sales, that falsifies the entire edifice of Austrian economics?
That is not an economic model or prediction of utility for the purpose. It will remain to be understood what happens to all other prices and production when this single adjustment is made. In addition, the question arises why the price is being adjusted. For example, what decisions were made and what conditions changed, either actually or by way of changes in understanding, which caused the prices to change?
Besides, your example is in reference to the law of supply and demand.
I would be cautious saying “Modeling for the purpose of control is unethical and oppressive because property rights are violated” purely because I wouldn’t want people to get the idea that Austrian Economists consider economics as normative. Austrian Economics may point out that the economic calculation problem shows that central planning is impossible, but it’s libertarian political philosophy that talks about things being ‘ethical’ or ‘unethical’. I think it’s important to keep the distinction between economics and political philosophy very clear.
Thanks nateemmons. I appreciate the distinction being made.
My reason for mixing is the centrality of private property and the consequent violation of property rights, using the standard of theft or fraud, that follows manipulation of currency, favored business license or heavy taxation for the purpose of redistribution. My interest in the school of thought is less theoretical and more practical application; i.e. how the body of knowledge affects the decisions by government that we then have to live with.
The problem I have here is the ganging up on the Austrian school in general because of a methodology used at the base of the theory. Mises said certain things cannot be done; he didn’t say don’t do them. If someone believes his presuppositions are wrong then simply prove it by doing what he claimed cannot be done.
To criticize Mises presuppositions is to claim a different set of presuppositions; i.e. we can experimentally measure the concept labeled human action and that there is nothing meaningful about human action that is antecedent to the study of history. I would say to the one making the claim, if this is the presupposition you would have us accept, please show your work.
If there was ever a Popperian refutation of the econometric/quant modelling of human behaviour we are surely living through that now.
No matter how many people know that water is H2O, it will not affect the fact. Once we have people telling us they can plug in probabilities for human actions, we have the start of monumental folly.
Every wise investor understands what Soros calls reflexivity. There is a role for math clearly but I find this post obsession about what to me seem fairly dull objections to the Austrian school miss their larger picture which seems to me overwhelmingly supported by current market experience.
It should not be a surprise to note that some of the most successful money managers/traders I work with have a strong Austrian bias, at least in the understanding of the monetary system and its systemic flaws and the predictable response of government… all using shiny models of course. Ahem.
I believe Mises said that socialism would fail at a time when the left (I do not imply Mises was thus on the right) was wowed over the success of Russia etc. and logically his theory would suggest money would be debased over time and that wealth would increasingly, and unjustly flow in Cantillon fashion to the earlier recipients of new money. Well, that to me means bankers, property developers, lawyers etc and this is so.
Today we are seeing rates near zero and government supporting long bonds and it is no surprise, to an Austrian trader, that we are seeing enormous trading profits in these areas of investment banks. This is an example of the Cantillon effect.
I would recommend we take the powerful parts from the Austrian theory and use them in real life. They surely work but it is also true that many who call themselves Austrians are of a ‘perma-bear’ disposition so be careful who you listen to. Look for form.
My argument is that the it’s irrelevant whether the presuppositions can be known with certainty. You can attach a probability estimate to them, allowing for the uncertainty of your missing variables, discount the evidence from experimental and behavioral economics accordingly, and update your priors accordingly. If your unconditional probability assignment is such that the uncertainty influenced by those missing variables discounts all such evidence by 100%, I really want you to show your work.
Austrians recognize that there is an unquantifiable variable in economics, namely human action, which heavily influences economic outcomes. You want to insert an arbitrary (estimated) variable value, i.e. probability estimate, in a model to account for something that Mises claims cannot be accounted for based on experience and historical fact.
Since you seem to believe that the variable value can be known and quantified for modeling purposes, what is it? What are the attributes of the variable collection which represent human action in economics?
Mises claims that human action is present, significant and cannot be measured. Are you claiming human action is absent, insignificant or measurable?
If you can set up the conditions to prove your case experimentally, then you have an argument.
How are your assumptions, i.e. probability estimates, inserted in a model going to provide feedback that will enable a valid update of the priors? Is that not circular reasoning?
If the claims made by Mises and the Austrians went no farther than to say human action cannot be measured and therefore nothing in economics can be measured, you would have an argument simply because their thinking would be inadequate. This is not the case.
To the contrary, Mises thinking regarding economic calculation in the socialist commonwealth clearly shows that human action coupled with ownership is a required component of a healthy and sustainable economy. Human action is necessary and yet cannot be measured or predicted, except that people are going to act in such a way as to satisfy their own self interest, which is conditional and subjective.
If experience and fact can be used to account for human action in economics, then Mises claims are false.
If they cannot, why discount his theory because he acknowledges a real-world constraint using a presuppositional argument?
If human action could not be predicted, the results of experiments into the Allais Paradox, preference reversal, conjunction fallacy, and on and on, should be a random walk. Since they’re not, human action can be to some measure predicted. If an Austrian believes all such research should be discounted by 100%, I’m taking issue with whatever prior gives that result.
And no, using priors in the way I described is not circular reasoning. Recall Bayes’ Rule for updating on evidence: P(H|E) = P(H)P(E|H)/P(E)
To be as clear as possible, let’s use the following example. We want to test the hypothesis “People act rationally and self-interested.” As a definition for rationality, let’s say people’s STABLE preferences disallow intransitivity.
Say I start with a prior for the hypothesis, P(H)=0.9. The likelihood that we see experimental evidence of intransitive preferences given this hypothesis must be fairly low, but there could always be experimental error, so P(E|H)=0.05. This estimate is where my priors come in as I described above. If I think it’s equally likely for an experiment to show evidence of intransitivity as transitivity, even given my hypothesis, P(E|H)=0.5.
I discount by my estimate that there will be experimental evidence of intransitive preferences regardless. P(E) = P(H1)P(E|H1) + P(H2)P(E|H2). Given P(Intransitivity results | People are rational) = 0.05, P(Intransitivity | People are irrational) = 0.95, we have, for the case of the believer P(E) = 0.05 0.9+0.1 0.95 = 0.14 and, for the case of the skeptic, 0.5 0.9+0.1 0.5 = 0.5. So, for the believer, evidence of intransitivity gives 0.90.05/0.14 = 0.32, and for the case of the skeptic, 0.9 0.5/0.5 = 0.9, ie, no updating.
Mises argues that we can never have any evidence of intransitive preferences because preferences are not stable. Thus, the preference reversal evident in choosing Gamble 1 in Part 1 and Gamble 2 in Part 2 of the Allais Paradox can never be evidence of intransitive preferences. But, I argue that if we show, in study after study, across the majority of people, that the preference for Gamble 1A and Gamble 2B is stable over time—seconds, weeks, months, years, lifetimes even!--that we should discount the skeptic argument P(Intransitivity results | People are rational) from 0.5 to something lower, akin to P(E|H) = 0.05.
But that’s not where it begins. I’m saying that experimental evidence of such preference stability should change your probability estimate of P(Preferences are stable) from 0.5 (This variable is mystical, completely unknown, sublime and unknowable even to a superintelligent AI with the capability of doing a nanosweep of your entire noggin) to something much higher, like 0.9 (I am pretty damn sure this preference is stable because the evidence says so and evolutionary psychology suggests it’s universal). Even if you want to leave it highly unknown, P=0.51, this will change your update according to the evidence. So it’s not circular reasoning. It’s using priors/updates on one hypothesis (preferences are stable) to update on another hypothesis (people are sometimes irrational).
If you’re arguing that we should remain radically uncertain even in the face of such evidence, I want to know the priors you assign. Saying “it’s unknown” isn’t enough. How unknown is it? I have trouble believing it’s really a 50⁄50 split. Are we really equally likely to see most people choose Gamble1A and Gamble 2B in every experimental study with highly statistically significant results across times and cultures as we are to see a random walk? If so, how come we never see random walks?
Human action can indeed be to some measure predicted.
For instance, if I conducted an experiment with 100 people wherein I presented each person with the opportunity to place their bare hand on a red hot burner on a stove, including leaving it there for one minute, I predict 100% would say no. I could even model that experiment.
However, this kind and degree of predictability is meaningless in the context of economic modeling.
What if the person who is being presented with the choice in the Allais Paradox just lost their mother to death, as well as losing their job in the same week? How does this affect the model? What does that research show?
How does one account for decisions made without adequate consideration, or when the decision maker doesn’t understand the problem? What about the follow on effects of choices made in the past which encumber via contract, or cause emotional or financial pain, such that the decision is not rational or the risk assessment is distorted? Or the reverse when the rewards have been great in the past?
How many life choices exist in such pristine, simple and clear conditions as the Allais Paradox?
Are not our choices, responsibilities, assets, liabilities, obligations, future earnings, job markets, work relationships, preferences, skills, talents, capital, regulatory environments, choices of other people, comparative advantages, currency fluctuation, taxation, inflation, religious beliefs, IQ, education, weather, genetics, resource allocation, scarcity, social stability, time constraints, competing demands, influence of peers, influence of media, family relationships, beliefs about the future, and more, all knit into each decision made?
Are you really claiming that the minor complexities presented in such a simple model as the Allais Paradox rise to the level of mathematically illuminating, for the purpose of useful economic modeling, the myriad decisions inherent in daily life? After all, everything in life depends, at some significant level, on exchange of productivity, which is generated as a result of the decisions of life.
My point is that the models relating to human action which are herein employed as proofs, are not sufficiently complex to be useful or meaningful in economic modeling.
You criticize the Austrian school on the basis of presuppositions which are designed to note the limits of our ability to construct theories or predict future events. At the same time, all that is offered to suggest we are not limited are simplistic and wholly inadequate models which do nothing to solve the problem. As long as Mises claims we can’t know or test these things and no one else shows that we can, I have to agree with Mises.
Besides, if these things were knowable, Mises would never have accepted stopping at this level. He would have anticipated and likely discovered and modeled the information so as to press another layer deeper, in hopes of gaining a greater mastery of the subject.
I’m having a hard time following your argument.
Everyone who is doing economics is working on the assumption that there are some useful regularities about human behaviour. None claim a model that perfectly predicts the behaviour of every individual. What distinction are you drawing here between the regularities that the Austrians assume about human behaviour, and the regularities that other economists assume?
Austrians believe that modeling for purposes of prediction is fruitless. Modeling for the purpose of control is unethical and oppressive because property rights are violated.
Other economists believe they can successfully model and manage an economy. They deal in numbers without taking into consideration human action at a level that has explanatory power. Monetarists, Keynesians, etc. ignore human action and generally treat the notion as unimportant. Austrians claim human action cannot be modeled, but knowledge of human action is required in order to model.
Austrians, for example, are able to model the effects of unrealistically cheap money, which is the source of malinvestment which leads to a boom bust cycle. We are experiencing the bust now.
With Austrians, things that can be modeled are modeled. Things that cannot be modeled or achieved are accepted, rather than, like the Keynesians, arrogantly claiming knowledge which is proven wrong time and time again.
Every time we have a bust, we are first told it should never have happened because after the last bust the bankers were given the tools necessary to prevent the bust. Then we are told that they just need a few more tools in their bag in order to fix the problem and ensure it never happens again. Then it happens again, each time bringing us nearer to the hyperinflation of 1920s Germany or today’s Zimbabwe.
The economists which claim to be able to manage our economy for our good are either liars or incompetents or both. And we are supposed to accept their critique of the Austrian baseline?
Claiming the presuppositions are wrong is fine, if one can show that these need not be presuppositions because they can indeed be measured and worked into a predictive model… This proof I have not observed in a research model, let alone in the applied science, which we live with daily.
Models are used for prediction in all sorts of domains. Each of us has a mental model (or “theory of mind”) of how others behave to a significant degree of accuracy. Economics often covers situations well outside the range of the evolutionary adaptive era for which our intuitive mental models don’t work as well. If modeling were truly useless, it wouldn’t matter if it was used “for the purpose of control” because it wouldn’t get you anywhere.
I wish Matthew Mueller’s Post-Austrian Economics blog was still up, because he made a good point about the unfortunate entanglement of austrian economics with political libertarianism since Rothbard. This results in some of its adherents viewing people who think their method is flawed as political enemies. For the record, I still read sites like mises.org & Lew Rockwell (though to a lesser extent recently due to all the competing distractions on the internet and my banning from the comments section of the former) and appreciate the work they do in bringing economics to a wider audience even if they can exhibit the flaws they point out in Rand’s circle.
Thanks for your remarks teageegeepea.
There is a difference between modeling and manipulating.
To model, is to create a framework that describes something.
To manipulate is to choose one or more elements among the known attributes of the model which can be controlled and then use that to coercively accomplish goals; then set the model up to “show good things are happening” based on the all wise management of the modeled system by the managers.
You note “a significant degree of accuracy”. The point is that the degree of accuracy that can be attained is insufficient for the purpose.
So if someone does successfully make a prediction about human behaviour, for example that a price increase will reduce sales, that falsifies the entire edifice of Austrian economics?
That is not an economic model or prediction of utility for the purpose. It will remain to be understood what happens to all other prices and production when this single adjustment is made. In addition, the question arises why the price is being adjusted. For example, what decisions were made and what conditions changed, either actually or by way of changes in understanding, which caused the prices to change?
Besides, your example is in reference to the law of supply and demand.
I would be cautious saying “Modeling for the purpose of control is unethical and oppressive because property rights are violated” purely because I wouldn’t want people to get the idea that Austrian Economists consider economics as normative. Austrian Economics may point out that the economic calculation problem shows that central planning is impossible, but it’s libertarian political philosophy that talks about things being ‘ethical’ or ‘unethical’. I think it’s important to keep the distinction between economics and political philosophy very clear.
Thanks nateemmons. I appreciate the distinction being made.
My reason for mixing is the centrality of private property and the consequent violation of property rights, using the standard of theft or fraud, that follows manipulation of currency, favored business license or heavy taxation for the purpose of redistribution. My interest in the school of thought is less theoretical and more practical application; i.e. how the body of knowledge affects the decisions by government that we then have to live with.
The problem I have here is the ganging up on the Austrian school in general because of a methodology used at the base of the theory. Mises said certain things cannot be done; he didn’t say don’t do them. If someone believes his presuppositions are wrong then simply prove it by doing what he claimed cannot be done.
To criticize Mises presuppositions is to claim a different set of presuppositions; i.e. we can experimentally measure the concept labeled human action and that there is nothing meaningful about human action that is antecedent to the study of history. I would say to the one making the claim, if this is the presupposition you would have us accept, please show your work.
If there was ever a Popperian refutation of the econometric/quant modelling of human behaviour we are surely living through that now.
No matter how many people know that water is H2O, it will not affect the fact. Once we have people telling us they can plug in probabilities for human actions, we have the start of monumental folly.
Every wise investor understands what Soros calls reflexivity. There is a role for math clearly but I find this post obsession about what to me seem fairly dull objections to the Austrian school miss their larger picture which seems to me overwhelmingly supported by current market experience.
It should not be a surprise to note that some of the most successful money managers/traders I work with have a strong Austrian bias, at least in the understanding of the monetary system and its systemic flaws and the predictable response of government… all using shiny models of course. Ahem.
I believe Mises said that socialism would fail at a time when the left (I do not imply Mises was thus on the right) was wowed over the success of Russia etc. and logically his theory would suggest money would be debased over time and that wealth would increasingly, and unjustly flow in Cantillon fashion to the earlier recipients of new money. Well, that to me means bankers, property developers, lawyers etc and this is so.
Today we are seeing rates near zero and government supporting long bonds and it is no surprise, to an Austrian trader, that we are seeing enormous trading profits in these areas of investment banks. This is an example of the Cantillon effect.
I would recommend we take the powerful parts from the Austrian theory and use them in real life. They surely work but it is also true that many who call themselves Austrians are of a ‘perma-bear’ disposition so be careful who you listen to. Look for form.