Tag Archives: Complexity Economics

Does Economics Suffer From Physics Envy?

Time is Money - 003

Every year when the Central Bank of Sweden hands out its “Nobel Memorial Prize in Economic Sciences”, there are always snorts of derision and cries of protest that this is “not a real Nobel Prize” and economics is “not a real science”…

The Oxford Dictionary definition of science is “the systematic study of the structure and behaviour of the physical and natural world through observation and experiment”.

Economics is sort of unique among the “social sciences” in that it attempts to apply mathematical rigor to the study of human behaviour.  This would seem to imply that economics is an exact science, like physics or chemistry; which further implies that economists are in the business of discovering “fundamental truths”…

Critics of “economic science” argue that the use of the paraphernalia of physics, like dense mathematical models, is in reality, purely “for show”; a vain attempt to give economics the elevated aura of physics (without unfortunately the same power of prediction). In fact some people would go so far as to say that “economic science” is really about as scientific as astrology and voodoo.

A bit Harsh Maybe !?…

Linear Dynamics

Physicists like to describe their science as the hardest of “hard science” because physics can claim to be governed by hard and fast scientific “Laws”.  This of course would seem to imply that many of the so-called “soft sciences” are in some way not quite as elevated, not quite as good.

In truth however we could say that physics is an “easy science”, and the soft sciences are “difficult” because the “laws” of physics only really work in the absence of “noise”, and yet the everyday world of the soft sciences is full of noise because most everything is continually battered and buffeted by “constantly changing feedback” which can generate wild “nonlinear dynamics”.

In reality all dynamics have feedback (and resultant nonlinearity), it is just that some dynamics have much less feedback than others.  Physics is, in a sense, the science of “dynamics with negligible feedback”, the science of linear dynamics” — or in other words it is the science of the nonlinear stuff that can be safely “compressed” into neat linear differential equations which express neat linear “cause and effect”.

All the mathematical laws of physics are linear approximations of nonlinear behavior.  In fact the reason that these “Laws of Physics” are actually considered to be “Universal Laws” is precisely because the dynamics behind these laws can be linearized (which then allows us to repeat experiments over and over again, with the same initial conditions, and always get the same predictable result).

Nonlinear Dynamics

Ironically, it is our inability to express the dynamics of a system in a linear form that results in us referring to that system’s behavior as being “nonlinear dynamics”.  In the simplest possible terms, linear dynamics are dynamics where the effect is proportional to the cause, and nonlinear dynamics are where the effect is disproportional to the cause.  In any system of any type, the universal causes of nonlinearity are

  1. The inability to damp down constant adaptation causes the emergence of diversity (i.e. deviations from the uniformity of equilibrium).
  2. The inability to damp down positive feedback causes the emergence of bias or “skew” (i.e. some random things can arbitrarily get reinforced).

Economics is highly nonlinear and subject to both incompressible adaptation and incompressible feedback.  This means that there are no, and never will be any “fundamental laws of economics”.  Even  the slightly move away from linearity is akin to moving away from a “law” to a “strong probability”; and economics has moved a long way away from linearity.

Economics is highly nonlinear because economies and economic activity are riddled with adaptation and feedback, which means that even probabilistic predictions can become difficult; but this is not necessarily a bad thing, because this unpredictable nonlinearity can lead to the emergence of unpredictable complexity”…

The Nature of Emergence

In an economy it is innovation that drives adaptation, and it is investment that drives positive reinforcement.

In any nonlinear system, it is hard to know what adaptations are going to occur and which of them will get reinforced through investment; and the more nonlinear the system is, the less amenable it will be to even probabilistic prediction. However this lack of predictability does not mean that we cannot have a “Qualitative Understanding” of the potential behavior of the system.

Both adaptation and positive reinforcement can independently drive emergent behavior, but it is the interplay between the two that determines “the nature of emergence”.  While diverse innovation without positive reinforcement can lead to the emergence of chaos, and reinforcement without diversity to the emergence of a bubble, the right balance between the two will always drive “the emergence of complexity”.

Matrix of EconoComplexity Dynamics

Aggregated Behaviour

Economies are effectively aggregated behaviour.  Some would argue that, left to its own devices, a society’s aggregate behaviour will self-organise the optimal economic equilibrium; but this is obviously not true, for without laws society’s aggregate behaviour can often disintegrate into chaos.

Okay, you might say, we need laws but we don’t need government nor bureaucratic interference in the economy; but this is not true either.  When it comes to financial matters, in general humans (and banks for that matter) can often behave like complete idiots, displaying a herd-like follow the crowd mentality.

The raison d’être of rational capital markets is that valuable investment funds are allocated to a diverse number of innovative business ideas, thereby generating economic complexity to the benefit of society as a whole.  But with the emergence of herding these funds (and even borrowed funds) are often almost blindly redirected and allocated into one particular area or asset class thereby generating a financial asset bubble to the detriment of society as a whole.

So when it comes to managing the economy, a hands off approach is not always the greatest idea….

Managing an Economy

When it comes to managing an economy, the question that needs to be asked is not what are the driving forces unique to economic systems, but “what the universal forces that drive all complex systems?…”

All complex systems are driven by an interplay of diversity and combination, or in other words, “complexity emerges” as a result of the diversification of uniformity and how this emergent diversity best fits together”.

So in reality, it is not really possible to truly understand economics without understanding complexity, and it is not possible to understand complexity unless we understand the interplay between  order and chaos.

Managing an economy, like managing any other complex system, is an art, or more aptly a talent, like cooking, and like cooking it needs a good chef.  A good chef knows how much of each thing he needs and how long to cook it for (to achieve optimal integration).

Too much reinforcement without diversity of innovation and we get inequality and lock-in. Too much innovation and no reinforcement and we get the chaos of many fragmented ideas (that can quickly form, but just as quickly disappear).

What we need is to ensure that “the demand for investment opportunities is, as much as possible, always in sync with the supply of good ideas”; we need to ensure just the right mixture between innovation and reinforcement to achieve the perfect dish of integrated diversity…

Economics vs. Physics

Both physicists and economists need to realise that economics is indeed a science, just not a linear science; which means it cannot rely on linear mathematics, and thus is not amenable to mathematical prediction.

Economics is a nonlinear science, a “complex system science”, and so although not predictable it is still deterministic, governed by the same universal forces that drive all complex systems.

Economics as a disciple should cease attempting to be like Physics, because although natural systems are predictable, economics systems have vast potential for “unpredictable creativity”, and with the right complexity management we harness this potential, to the benefit of all…

Long Term Economic Growth

This Cartoon is from The Economist -0

“Austerity” or “Quantitative Easing” ?

In nature after an evolutionary collapse, mother-nature will begin to rebuild, and in a normal business cycle so too would an economy.  However in a boom and bust cycle things are not quite so easy!

Disposable Income

Economics is often thought of as a study of the allocation of “scarce” resources.  But that’s just another way of saying that economics is the study of “people making rational decisions”; and unfortunately we now all know that this is not true.

The starting point for all of economics is actually the ability to “produce excess”.  In a time before money, being able to produce more than one’s own immediate needs lead to the emergence of barter.  But with the introduction of money – which acts both, as a means of exchange, and a store of wealth – “excess productivity and production” could lead to the accumulation of “disposable income”; and it is this disposable income that drives an economy in 2 separate ways

  1. Consumption: disposable income drives trade, and thus economic activity.
  2. Investment: disposable income drives innovation, and thus self-organized, economic-complexity.

[Note: Complexity can be defined as “integrated diversity” and thus a Complex Adaptive Economy is a highly diverse & integrated  system.]


In a boom, investments are funded not only from accumulated savings, but usually also with overly-available credit (i.e non-accumulated future income).  In a bust, investments funded out of future income (i.e. debt) continue to incur ongoing interest costs despite the fall in value (or in many cases wipe-out) of the investment.  Not only that, but unfortunately for the borrower (and the economy at large), the principle also still needs to be repaid.

Thus an economic boom funded by excessive credit, eats into disposable income long after the boom has completely disappeared.  And since disposable income is what drives both investment and consumption, it depletion affects not only the growth of complexity in the economy but also the level of economic activity/trade and thereby the size of the economy.

In an economy the only time we really have stability is when nothing much is happening – and nothing much will happen when the driving force of the “Invisible Hand” is severely weakened.

In a weak economy, with very little funding only the very best ideas have a chance of being funded; but with no funding at all, and no consumer spending to boot, not only is new business growth stunted, but many existing businesses will likely decay! [In an economic bust, even healthy business go under; because a large amount of pre-existing disposable income is been redirected towards paying off debt.] 

In a dysfunctional economy, the weight of unproductive debt substantially weakens the driving force of growth and innovation in a normal functional economy.  An economy mired in debt will stagnate!  An economy devoid of disposable income is akin to a planet devoid of sunlight; nothing will grow!

Credit and Excess

Capitalism is perceived as the optimal growth engine of economic development and growth!  Financial Markets are supposed to be the invisible hand that optimally allocates the supply of, and demand for, investment funds in a Complex Adaptive Economy (CAE).  Chaos Theory alerts us however, to a possible vulnerability in the system!

The mathematics of chaos shows us that there is in fact an “Optimal Rate of Investment” in this Driven-Damped System – beyond which the system is vulnerable to “Coarse Synchronicity and Chaos”!

We know that, too much investment can overdrive the system causing the emergence of the so-called “business cycle”; excessive investment however has the effect of converting a functional cycle driven (even if slightly out of sync) by “The Wisdom of Crowds”, finely balancing “Supply and Demand” (of investment funds); into a dysfunctional cycle driven by “The Madness of Mobs” coarsely balancing “Fear and Greed” (of a financial market gamble).  What tips the system from one to the other (i.e. from functional to excessive) is when over-investment becomes “supercharged” by credit-fuelled investment!  Fundamentally, there are 5 levels of Driving Force in a Complex Adaptive Economy

  1. Minimum: Stops the natural decay of a naturally damping system.
  2. Small Excess: Under-Drives the Economy – a lot of good ideas are left unfunded.
  3. Critical Excess: Critically-Drives the Economy – optimally funds all the best ideas.
  4. Large Excess: Over-Drives the Economy into a “Business Cycle” – many poor ideas also get funded.
  5. Excessive Excess: Supercharges the Economy into a “Boom and Bust and Stagnation-Dead-End” – basically any idea will do!

Clearly credit is the lifeblood of business and trade in the economy.  Credit however has no place in the funding of asset price speculation.  Excessive credit fuelled speculation is simply a build-up of instability in markets; an accident waiting to happen!


Implicit to the idea of the “Wisdom of Crowds” is that no one player in the market might know all the available information, but the market as a whole does.  This apparent “rational wisdom” however, relies heavily on the “Law of Large Numbers” (LLN)!

The LLN is a statistical concept that deals with the idea that statistical accuracy is related to the size of the sample.  Most people would recognize the central thesis: if you toss a coin four times, you won’t necessarily get a 50/50 split of heads and tails: indeed, you could get 4 tails, suggesting (wrongly) that the coin will always land on tails. But if you toss a coin a trillion times, you will get something close to a 50/50 split between heads and tails.

The tendency in financial markets towards “herding behavior” weakens the apparent wisdom of the crowd by reducing the large number of independent players in the market into smaller collective groups, and in so doing, effectively engineers a Reverse of the Law of Large Numbers (RLLN)…

Macro-Economic Behaviour -1

Debt and Inequality

The RLLN is the reason why financial markets don’t always do what they are supposed to do.  Financial markets are a Complex Adaptive System and thus inherent vulnerability to the emergence of herding and the RLLN.  If we want these markets to operate in the most efficient fashion, we need to guard against any amplification of the RLLN; we need better control over the amount of credit in the system; both before and after a market bubble.

Vulnerability to the RLLN leads to the sub-optimal allocation of resources.  The misallocation of savings and credit has 4 main effects:

  1. In the short term, it burns though savings wasting a valuable economic resource.
  2. In the long run, it starves good ideas of investment.
  3. It creates inequality, because bad investments always suck the poor in last, allowing the rich to get out…
  4. It creates suffocating debt, and with that debt, it sucks the driving force out of the economic system…

Complexity Theory shows us that the “optimal” Complex Adaptive Economy (CAE) self-organizes from the bottom up.  Chaos shows us that there is an optimal rate of investment in a CAE – beyond which financial markets are vulnerable to “coarse synchronicity and chaos”.

Moreover the mathematics of chaos tells us that

In the short term artificially pumped up asset markets, can have a trickle-down effect, but ultimately in the long term, the primary effect is to increase inequality!

The Economic Engine

There has been a long running argument in economics as to whether an economy should be left alone or needs supervision.  In a way both sides are right!

The economy is like a car, it has a battery, but we never use the battery when the car is running – the battery’s sole purpose is to kick-start the car into ignition.  Using excessive credit in a booming economy is always going to flood the engine; lack of credit when the economy is stalled however is like trying to start the car without the ignition.

The takeaway message is that in any Driven-Damped Complex Adaptive System, positive feedback is always required in order for the system to be able to work its way away from the gravitational pull of natural decay.  In the push and pull of a Complex Adaptive Economy, a collapse in positive feedback can collapse the complex equilibrium which can mean that the “Business Cycle” itself effectively disappears.

Excessive Consumer Credit can overdrives an economy, but Excessive Consumer Debt can kill the drive altogether!

We should treat the economy as we would a car – we should leave well alone when the engine is running and the battery is charging; but if the engine is not running, then we have no option but to use the ignition…


But if there is but one single take-home message about understanding the behavior of the Driven-Damped Complex Adaptive Economy for the current economic climate, it is that: a CAE naturally self-organizes “from the bottom up”, driven by “disposable income”, and consequently

“Austerity” severely weakens the driving force of economic growth, and, in such a weaken environment, “Quantitative Easing” will simply widen the inequality gap!

So in answer to the implied headline question, “what will really drive long-term economic growth; austerity or quantitative easing?” – Neither of the above!

[This post is adapted from Incompressible Chaos in Financial Markets.]