Showing posts with label non-ergodic stochastic systems. Show all posts
Showing posts with label non-ergodic stochastic systems. Show all posts

Tuesday, October 4, 2011

How Can Government Overcome Uncertainty?

S. D. Parsons poses the following question:
“Post Keynesian economists can, with considerable justification, criticize the view in some Austrian circles that it is possible to emphasize both uncertainty and market coordination. However, it would also seem that the Post Keynesian emphasis on uncertainty raises problems for the argument that governments can resolve coordination problems. ... Keynes may well have correctly identified problems of market coordination when he wrote, and correctly identified policy instruments to resolve them. However, given uncertainty, the past is a fickle guide to the future and, given transmutation, the world is now a different place. In conclusion, Post Keynesians have a valid point when they argue that an emphasis on economic uncertainty raises problems for the assumption that market coordination can occur in the absence of governmental intervention. However, it can also be argued that the emphasis on uncertainty raises problems for the assumption that market coordination can occur through government intervention.” (Parsons 2003: 9).
It is not, however, difficult to answer these charges.

When you introduce an intervention to influence the state of a nonergodic stochastic system, that process and outcome is not in the same ontological category or status as the future of that system, without intervention. The past data from which one draws inferences about what the intervention will do consist of examples of past such interventions, ideally of the same type. For example, there is no doubt that induction from past data will not be a reliable method to predict the future value of certain shares on the stock market or the future value of the whole market itself measured by some index, but predicting what happens when an entity with the power to influence certain shares or the whole system is a different matter. If the Treasury bought up the stock of a certain promising company, making the shares scarce when demand is high, announcing it will even support the value of the shares, we can make a empirical prediction about the outcome, which can be falsified. How? I have already addressed the question of the epistemological justification for such things and even Keynesian stimulus (and other government interventions) here:
“Risk and Uncertainty in Post Keynesian Economics,” December 8, 2010.
The problem revolves around whether induction can be rationally justified. If one thinks that induction can be defended rationally, then inductive arguments using past empirical evidence can be used to provide justification for policy interventions. Induction can be reliable when used outside of nonergodic stochastic systems or events. If one thinks that induction has no rational justification, then Karl Popper’s falsificationism by hypothetico-deduction can be used to test predictive hypotheses about what will happened in the future under government intervention. In the absence of falsification, we have empirical support for such polices.

Fundamentally, if Austrians or neoclassicals think that they can evade their own such epistemological problems, they are deeply mistaken. How, for example, does the Austrian praxeologist justify his belief that that the axiom of disutility of labour will continue to be true in the future? Mises explicitly tells us that this axiom is “not of a categorial and aprioristic character”, but “experience teaches that there is disutility of labor” (Mises 1998: 65). In other words, it is a synthetic proposition and its truth is only known a posteriori. Praxeologists require either induction or Popper’s falsificationism by hypothetico-deduction using empirical evidence to justify their belief in its truth now and for the future.

The concept of radical uncertainty in the Post Keynesian or Knightian sense applies to non-ergodic, stochastic systems. But human life does not just consist only of non-ergodic systems. The economic system we know as capitalism, where most commodities are produced by decentralised investment decision-making by millions of agents and consumption by other agents with shifting subjective utilities, is not the only institution of modern life. We have government and quasi-government entities, private non-profit organisations, private voluntary organisations, and at the basic level families.

The free market itself has attempted to overcome uncertainty by certain institutions. Government interventions in economies are merely a much more powerful and more effective instrument for reducing uncertainty than what has emerged on the market.

Its many institutions that exist alongside and influence modern capitalism (such as law courts that enforce contracts, buffer stocks, and even central banks) have developed precisely to deal with uncertainty, as “outside” entities capable of reducing uncertainty by interventions designed to influence the state of the system. Law and order is a basic human institution without which commerce would be impossible. It has been enforced through the ages essentially by governments, not by private enterprise. When, for example, the trade of the Roman Republic was threatened by pirates in the east Mediterranean, it was the state that ended that threat and allowed commerce to resume with confidence. Indeed, some conventions or institutions that reduce uncertainty (for example, forward/future markets for commodities, and even money) are so deeply ingrained that we think of them now as a fundamental part of capitalism. A futures market was developed to reduce uncertainty for producers of commodities, often primary commodities. There is a great deal of evidence that standardised coinage in Western European civilisation was essentially the invention of the state. Indeed, the state had a great role in monetising economies.

Central banks developed in the 19th and 20th centuries precisely because business and financial interests wanted a system that would reduce the uncertainty caused by liquidity crises and financial panics, because they were frightened by the potentially disastrous consequences of unregulated financial markets and banking systems.

It is interesting that the Austrian Ludwig Lachmann’s view that institutions have an important part to play in free market systems is similar to the view I have had described above. It is important to note the logical consequences these ideas had for Lachmann as well:
“Because of his focus on uncertainty, Lachmann came to doubt that, in a laissez-faire society, entrepreneurs would be able to achieve any consistent meshing of their plans. The economy, instead of possessing a tendency toward equilibrium, was instead likely to careen out of control at any time. Lachmann thought that the government had a role to play in stabilizing the economic system and increasing the coordination of entrepreneurial plans. We call his position ‘intervention for stability.’” (Callahan 2004: 293).
While I doubt whether Lachmann’s interventions would have been anything but minimal by Post Keynesian standards, nevertheless his intellectual journey is actually a lesson for his fellow Austrians: once they take fundamental uncertainty and subjective expectations seriously they would find themselves forced to much the same conclusions that he eventually drew.


BIBLIOGRAPHY

Barkley Rosser, J. 2010. “How Complex are the Austrians?,” in R. Koppl, S. Horwitz, and P. Desrochers (eds), What is So Austrian About Austrian Economics?, Emerald Group Publishing Limited, Bingley, UK. 165–180.

Callahan, G. 2004. Economics for Real People: An Introduction to the Austrian School (2nd edn), Ludwig von Mises Institute, Auburn, Ala.

Parsons, S. D. 2003. “Austrian School of Economics,” in J. E. King (ed.), The Elgar Companion to Post Keynesian Economics, E. Elgar Pub., Cheltenham, UK and Northhampton, MA. 5–10.

Wednesday, March 2, 2011

Uncertainty and Non-Ergodic Stochastic Systems

The concept of uncertainty in economic life was used by Keynes in the General Theory (1936) and also in an article defending his new theory the next year (see Keynes, “The General Theory of Employment,” Quarterly Journal of Economics 51 [1937]: 209–223).

Paul Davidson notes the nature of uncertainty in the Keynesian/Knightian sense:
“Keynes’s description of uncertainty matches technically what mathematical statisticians call a nonergodic stochastic system. In a nonergodic system, one can never expect whatever data set exists today to provide a reliable guide to future outcomes. In such a world, markets cannot be efficient” (Davidson 2002: 187).

“Keynes … rejected this view that past information from economic time-series realizations provides reliable, useful data which permit stochastic predictions of the economic future. In a world where observations are drawn from a non-ergodic stochastic environment, past data cannot provide any reliable information about future probability distributions. Agents in a non-ergodic environment ‘know’ they cannot reliably know future outcomes. In an economy operating in a non-ergodic environment, therefore – our economic world – liquidity matters, money is never neutral, and neither Say’s Law nor Walras’s Law is relevant. In such a world, Keynes’s revolutionary logical analysis is relevant” (Davidson 2006: 150).
Certain types of phenomena in our universe are what mathematicians call non-ergodic stochastic systems. The concept of radical uncertainty applies to such systems, like medium term weather events, financial markets, and economies, and other natural systems studied in physics.

In these systems, past data is not a useful tool from which one can derive an objective probability score for some specific, future state of a quantitative variable in the system. Of course, such a system can still have trends, cycles and oscillations, both in the past and future. For example, stock markets certainly have cycles of bull and bear phases, but trying to predict the specific value of some stock x, say, two years from now with an objective probability score is not possible.

But the fundamental point is that it is still possible for a powerful agency or entity to reduce uncertainty in these systems, or at least in theory in some of them. It is entirely possible that in the future – with a far more advanced human civilization – we could use technology to control local, regional or perhaps even global weather.

And even today a powerful entity like the government can intervene to reduce uncertainty in the non-ergodic stochastic system we call the economy.


Is Climate a Non-Ergodic Stochastic System?

Does the earth’s climate system have the property of non-ergodicity? This question has occurred to me more than once, but I am actually unsure of the answer.

Some quick research suggests that climate models appear to make an ergodicity assumption about climate systems:
“Thus, it is perfectly valid to consider our climate a realization of a continuous stochastic process even though the time-evolution of any particular path is governed by physical laws. In order to apply this fact to our diagnostics of the observed and simulated climate we have to assume that the climate is ergodic. That is, we have to assume that every trajectory will eventually visit all parts of phase space and that sampling in time is equivalent to sampling different paths through phase space. Without this assumption about the operation of our physical system the study of the climate would be all but impossible.

The assumption of ergodicity is well founded, at least on shorter time scales, in the atmosphere and the ocean. In both media, the laws of physics describe turbulent fluids with limited predictability (ie, small perturbations grow quickly, so two paths through phase space diverge quickly) (von Storch and Zwiers 1999: 29–30).
But then what about longer time scales? If “the laws of physics describe turbulent fluids with limited predictability” on short time scales, what sort of predictability can they provide on medium or long term time scales?

Let’s assume, for the sake of argument, that long term climate is non-ergodic, in the way that a free market economy is. Does that mean all intervention would be useless and ineffective in such a system to affect the state of it? Does it mean that we are all doomed to (in a manner of speaking) live in a “free market” climate forever?

In fact, that does not follow at all. It is probably very likely that our future technology, when it becomes sophisticated and powerful enough, will be used by humans to intervene and control climate, e.g., by preventing ice ages.


BIBLIOGRAPHY

David, P. A. 2007. “Path Dependence, its Critics and the Quest for ‘Historical Economics,’” in G. M. Hodgson, The Evolution of Economic Institutions: A Critical Reader, Edward Elgar, Cheltenham. 120–144.

Davidson, P. 2002. Financial Markets, Money, and the Real World, Edward Elgar, Cheltenham.

Davidson, P. 2004. “Uncertainty and Monetary Policy,” in P. Mooslechner, H. Schuberth, and M. Schürz (eds), Economic Policy under Uncertainty: The Role of Truth and Accountability in Policy Advice, Edward Elgar, Cheltenham. 233–260.

Davidson, P. 2006. “Keynes and Money,” in P. Arestis and M. Sawyer (eds), A Handbook of Alternative Monetary Economics, Edward Elgar, Cheltenham, UK and Northampton, Mass. 139–153.

Keynes, J. M. 1937. “The General Theory of Employment,” Quarterly Journal of Economics 51 (February): 209–223.

Storch, H. von and F. W. Zwiers, 1999. Statistical Analysis in Climate Research, Cambridge University Press, Cambridge, UK and New York.