[This post is addressed to fringe economists and others who have broken with ever-more dysfunctional mainstream neoclassical economics, but who still search for a replacement paradigm.]

[2 Aug:  Posted on Real-World Economics Review Blog.]

The need for a new conception of economics is widely acknowledged in the wake of the global financial crisis[1], at least outside of diehard neoclassical circles.  However a common perception seems to be that no adequate and coherent general conception is in sight, though many loosely related or unrelated heterodoxies vie for attention, as noted by the Editor of Real World Economic Review blog.  I argue here that when the subject is approached from the point of view of dynamical systems a broad new framework becomes evident.  Furthermore, once the nature of the beast is identified, some fundamental conclusions can immediately be drawn.

To a natural scientist experienced in thinking about dynamical systems, the neoclassical claim of equilibrium is laughable.  Several kinds of instabilities can be readily identified, and mechanisms promoting instability are also readily apparent.  The observable pervasiveness of instability leads to the identification of the kind of system we are dealing with.

Financial market crashes are an obvious case of instability.  The so-called business cycle, of which crashes are a part, also strongly suggests destabilising mechanisms are at work.  The rapid growth to dominance of one or a few firms in new-technology areas is an obvious form of instability at the micro level.  Minsky’s financial instability hypothesis is also clearly describing an instability, at the macro level.  One might suspect that the long-term tendency of economies to grow exponentially is a result of an underlying instability, rather than just a result of policy, particularly given the tendency of shrinkage sometimes to be uncontrollably rapid.  A different kind of instability is evident in the pervasive tendency of income distribution to become extremely uneven – the rich get richer.

Several mechanisms that drive instabilities are also readily identifiable, and some are widely remarked upon.  Perhaps the one with the most direct implication, though it does not seem to be the most remarked, is economies of scale, or more rigorously increasing returns to scale.  The existence of economies of scale are well known in manufacturing, but they actually pervade the economy, operating strongly in service industries and in management and other components of business[2].  Economies of scale commonly enable early entrants into a new market segment to grow exponentially until they gain an unassailable dominance, Microsoft being a classic example.

Exponential growth is a signature of instability.  It is caused by positive internal feedback:  in the case of economies of scale, the larger the firm the greater the profit margin, which allows the firm to grow even larger, and so on.

Another readily evident cause of instability is herding behaviour.  This is exhibited by financial market players and is also behind fashion and fads.  It is a manifestation of our social behaviour, something not possessed by homo economicus.  It is every marketer’s dream to induce the customer base to grow exponentially through the operation of our social responses.

Incomplete or delayed information can also lead to instability.  Physicists and engineers know that a dynamical system in which negative (damping) feedback is weakened or delayed can lead to the system becoming oscillatory or unstable.  Good and complete information is fundamental to the proper functioning of markets, since they underlie the evaluations that are needed to determine reliable prices.  Information thus contributes to a negative feedback that tends to stabilise the economic system, and delaying or losing information can allow instability to develop.  Currency traders, for example, can have only a minute fraction of the information relevant to their cavalier activities.

The charging of interest on new money is like a private tax that pumps wealth from the less wealthy to the very wealthy.  There are other such wealth pumps, among them being the easier access the wealthy have to credit, to political influence, to participation in financial market gambling, and so on.  These mechanisms operate to destabilise the distribution of income and exaggerate its extremes.

There are surely many other sources of instability in our complex modern economies, but these examples should convey the pervasiveness of instability, and the folly of the neoclassical theory, which excludes most of them a priori.

Systems in which internal feedbacks operate are forms of dynamical system, and typically are self-organising systems.  Positive feedbacks can cause the system to encounter external limits, and internal relationships then typically become nonlinear.  As the strength and/or multiplicity of interactions and feedbacks increases in such systems, behaviour tends to move from very simple, perhaps steady or oscillatory, through increasingly complicated and ultimately into the regime of deterministic chaos, in which the detailed behaviour is non-repeating and fundamentally unpredictable.

Short of chaos is a regime of behaviour known as complexity, in which order and disorder wax and wane.  Systems in this regime are known as complex self-organising systems, or complex systems for short.  Living systems seem to be in this regime.  Complex systems typically have many possible quasi-stable states, but often undergo transitions between such states.  When they do they are hypersensitive to small disturbances, which renders their long-term behaviour also unpredictable in detail.

Although complex systems are unpredictable in detail, they typically have a recognisable style or character of behaviour.  Think of the difference between dog behaviour and cat behaviour.  Neoclassical theory portrays the economy as a gentle old cart horse that will convey a little old lady safely to church and home, never straying far from the righteous path.

If the economy is a complex system then it has astronomically-many possible states.  It is not practically possible to decide which of those states might be the most efficient (in whatever sense you wish to define).  If the system is time-dependent, then it is not even sensible to ask which state is the most efficient, because it may soon not be.  Thus there is no way of deciding which might be the globally optimal way to organise an economy.

The central neoclassical conclusion is thus lost.  There is no global equilibrium state, which is also the optimal state in the neoclassical theory.  Thus there is no reason in theory to expect free markets to deliver an optimal state, or even a desirable state.

On the other hand markets are clearly powerful.  They stimulate innovation and, as Hayek has observed[3], they enable a vast amount of information processing, though not necessarily of a very rational kind.  Unfettered markets currently are generating profound dysfunctions.  For example, instabilities in financial markets nearly threw the global system into depression, and may yet.  As the system generates super-wealth, it also generates poverty.  The system is consuming the biosphere, upon which we are totally and intimately dependent for our food, water and our very breath.  Its health is our health and we are destroying it, our life support system.

If free markets are delivering dystopia, the implication is not necessarily to get rid of markets and all become socialists.  Rather, it is to learn to manage markets.  Rather than a gentle old cart horse, we should regard our market economy as a team of wild horses – powerful, but needing to be harnessed and guided.

Guiding a complex, unpredictable, near-chaotic system may seem like a tall order, but we already do it in many ways, though not with any coherence.  The bluntest form of guidance is regulation, but the more elegant way is through incentives and disincentives.  These are the economic version of feedbacks, and feedbacks govern the behaviour of the system.  By intervening judiciously, and cautiously, to tweak the feedbacks, we can aspire to learn to manage the system.  If we approach the job without the crippling mental baggage of the neoclassical tradition we ought quickly to learn to manage it much better than have been doing.

Our guiding metaphor here might be of the bonsai master.  He does not try to force or stifle the impulses of his tree to grow, but rather closely observes them and intervenes minimally.  He aspires to work with the tree, as much as possible, rather than against it.  The complex dance between the master and the tree can satisfy both the tree’s urge to grow and the master’s aesthetic desires.

Three other fundamental conclusions emerge from this analysis.  First, if economies have multiple possible states, many of which are not obviously inferior to others, then we can tailor our economy to support the kind of society we choose to live in.  In other words we can restore economies to their proper role, of supporting our way of life rather than dictating it.

Second, each society and culture might choose differently, and tailor its economy accordingly.  Thus the present rush to a global monoculture might be reversed, and cultural diversity might flourish once again.

Third, if economies and living systems are both forms of complex systems, then there is no reason in principle why an economy cannot be made compatible with living systems.  At present our economies are highly incompatible, and are killing people and other living things as a consequence.  Thus we can aspire to create economies that allow the natural world to thrive around them.  Indeed we must, or we have no future.

The recognition of complexity in economies has been growing for some time.  There are many studies of particular parts of economies, using a variety of approaches including the use of interacting adaptive agents. There are many instructive results and promising insights.  An excellent review is given by Eric Beinhocker inThe Origin of Wealth[4].  He covers many detailed studies, of management, behaviour and related fields as well as economic phenomena.

Whereas Beinhocker’s book reviews detailed studies, an overview that puts the complex system view in a broad context and draws the overarching conclusions can be found in my own Economia[5].  It is this overarching view that I have briefly summarised here.

I conclude with two observations.  First, there is a great deal of work to be done to understand key parts of the economic system, to transfer those practices and ideas that are useful into the new framework of what Beinhocker calls complexity economics, and to weed out false or unhelpful habits of thought and practice that hang over from neoclassicism.

Second, the process of taking these ideas into the policy realm need not await the development of sophisticated and detailed mathematical models.  Economists, even many heterodox economists, seem to feel an economic idea is not ready for application until someone has made a detailed quantitative model displaying it.  The whole neoclassical enterprise ought to be fair warning that making a mathematical model does not ensure the model, and its underlying idea, have any relevance to real economies.

Indeed neoclassicism seems to have totally missed the distinction between mathematics and science.  Mathematics is about developing logical structures (a noble and powerful activity in itself).  Science is about comparing ideas and their implications (theories, models, deductions) with what we can observe.  The test of a good scientific theory is that it is a useful guide to how the world works.  Even very simple, back-of-the-envelope estimates can, in situations where there is great uncertainty or ignorance, be very useful guides and therefore valid science.  This is more obvious in my own field of geophysics than it might be in laboratory physics where great precision may be justified.  Trying to figure out the state of the Earth during and “soon” after its formation does not require, or justify, great precision, but rather the art of finding ways to test ideas against the quite limited observational constraints available.  A rough estimate may show the idea is incompatible with what little we know.  If it seems to be compatible then it is worth exploring more carefully.

A similar spirit of exploration is required as we come to grips with a new way of looking at economies.  There are major phenomena still to understand, and great uncertainties in some areas, so rough estimates or very simplified models can play a very constructive role, so long as any interim success is not taken to mean further exploration is unnecessary.

In the meantime, a primary implication of the argument summarised above is that there is no justification in theory for believing that unfettered markets will deliver a desirable result.  Given abundant evidence of dysfunction, we can say there is also little justification in practice for unfettered markets.  Therefore we should throw off the neoclassical straightjacket and set about pragmatically and unapologetically managing markets to deliver the results we desire.

The ideas I have outlined here ought certainly to be debated, I don’t mean to pre-empt that.  The point I have just been making is that if this view is accepted, then some broad policy implications follow immediately, and need not await elaborate modelling.  Whether this view becomes accepted remains to be seen.

A reassuring feature of the complexity view is that it returns us closer to common sense, and we could do worse, in the short term, than bring the basic thinking of a shop keeper to our economic management.  For example we would, if we did so, immediately abandon the GDP as a guide to the well being of our societies, because it is like putting all our transactions in the credit column of the ledger and adding them up.

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[1] See, for example: Review of David A. Westbrook’s Out of Crisis: Rethinking Our Financial Markets; Reportfrom the 98th Dahlem Conference by Colander et al.;  Article by Paul Krugman, NYT Magazine, 2 Sept 2009; Blame the Economists, Michael Hirsh in Newsweek, 13 April 2010;  Call to link heterodoxies, Editor RWER Blog, 30 June 2010;  Lament by Radford, What do we tell the students? RWER March 2010;  Sources of crisis, Harcourt, RWER June 2010.

[2] Rothschild, M., Bionomics:  Economy as Ecosystem. 1990, New York: Henry Holt. 423 pp.

[3] McKnight, D., Beyond Right and Left. 2005, Sydney: Allen & Unwin. 298 pp.

[4] Beinhocker, E.D., The Origin of Wealth. 2006, Boston: Harvard Business School Press.

[5] Davies, G.F., Economia: New Economic Systems to Empower People and Support the Living World. 2004, Sydney: ABC Books.  Out of print:  pdf available at http://betternature.wordpress.com/economia/ .