Complexity and the Economy — W. Brian Arthur on Perpetual Formation and Combinatorial Evolution

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Perpetual formation, combinatorial evolution, and complexity economics — W. Brian Arthur on technology and the economy

Formation and the economy

There are two big questions in the study of economics. The first pertains to allocation, and the effects that economic interactions have on prices, quantities, efficiency, welfare, and related measures. The second, by contrast, pertains to formation. It is interested in the emergence, development, and renewal of economies over time.

While allocation problems have been studied at length, and are rooted today in general equilibrium analysis, studies of formation continue to receive less attention. Economist William Brian Arthur suggests, however, in his book Complexity and the Economy, that the field of complexity economics may have a lot to offer on this front.

Perpetual formation and algorithm

But formation and complexity economics demands a different set of intuitions. Where orthodox economics puts output, capital, labor, price, and quantity in the spotlight, a complexity approach focuses on technology. 

Indeed, technologies, in the broadest sense, from our engineering know-how to our political institutions, are the building blocks of society. They determine what we can and cannot do, and the manner in which we organize and interact. 

Arthur wants people to picture an “economy [that] continually creates and recreates itself” — an entity in perpetual formation and renewal, constantly adapting and recombining available technologies and institutions for various ends.

In this light, what we are looking for is not necessarily a closed-form equilibrium description of economic behavior, but an algorithm to talk about economic formation based on the dynamics of technological change.

“Complexity economics thus sees the economy as in motion, perpetually “computing” itself — perpetually constructing itself anew. Where equilibrium economics emphasizes order, determinacy, deduction, and stasis, complexity economics emphasizes contingency, indeterminacy, sense-making, and openness to change.”

W. Brian Arthur. (2014). Complexity and the Economy. 

An example of formation

For starters, new technologies tend to emerge from the adaptation and recombination of existing knowledge. Arthur highlights, for example, the invention of the railway locomotive, which relied on existing steam engines, iron wheels, boilers, and so on.

This “novel element”, if adopted, generates additional and adjacent technological and institutional requirements. Demand for railway locomotives, for instance, led to iron rail fabrication, railway enterprises, and many complementary industries. 

Of course, formation may also replace incumbent technologies and their adjacent components. With the arrival of railways and automobiles, horse-powered transportation and adjacent services were quickly displaced.

In turn, the new technology becomes a building block for future technologies. General purpose technologies, like railways or the internet, are similar to keystone species in ecology. Their addition or removal comes with profound change to the technology web.

Finally, formation leads to allocation (and vice versa). Prices, costs, output, and whatnot adjusts to the structural changes in the economy. The railway effect was felt everywhere, from trade to warfare, shaping the course of the First World War.

This formation process and structural change — from recombination and adaptation, to creation, displacement and allocation — repeats itself over and over again.

Creative gales and combination

Of course, there’s nothing radical about this formation algorithm. Most of us have an intuitive sense of technological change. But it doesn’t hurt to emphasize where Arthur is coming from. That is, we are looking at systems of perpetual novelty, harkening back to Joseph Schumpeter’s “gales” of creative destruction. 

Here, building blocks are central to complexity. They constrain the possible adjacencies and exaptations of the system. Arthur points, for example, to the triode vacuum tube, which led to the amplifier circuit, which led to the oscillator and to the heterodyne mixer; and then to radio transmitters and receivers; culminating eventually in radio broadcasting.1

As Arthur explains:

“Radar could not have been invented without the building blocks of electronic amplification and wave generation — and the needs that brought these simpler functions into existence. … There is a parallel observation in biology. Complex organismal features such as the human eye cannot appear without intermediate structures and “needs” or uses for these intermediate structures”.

W. Brian Arthur. (2014). Complexity and the Economy.

1 I’ve oversimplified the historical transition, of course. Many more components are involved in this story. For the interested, I also recommend W. Brian Arthur’s The Nature of Technology: What it Is and How it Evolves.

Evolution by combination

Much of this may sound like Darwinian evolution to you. Indeed, we can trace the lineage of science, technology, and culture, much like we do with species on the evolutionary tree of life. Arthur argues, however, that the “base mechanism” for technology is not Darwinian-like.

Novel technologies come not only from small cumulative selections over time, but from integrations and recombinations of available subcomponents. The evolutionary processes that led to clocks and bicycles are different to that which led to the animals. For this reason, Arthur finds it helpful to distinguish between Darwinian evolution and combinatorial evolution.

What’s more, evolutionary systems, whether by natural selection or combination, exhibit a tendency to become more complex over time. Arthur suggests three possible reasons for why this might be so: (1) coevolutionary diversity; (2) structural deepening; and (3) capturing software.

Coevolutionary diversity

The first is coevolutionary diversity. When entities or components “coexist together in an interacting population”, they may open up new niches and possibilities. An ecology, for example, is teeming with parasites and mutualists on many scales. From biomes in the gut to animals in the savannah, organisms are creating niches upon niches upon niches.

Arthur provides a similar example with the coevolutionary explosion in computing. Growth in computing demand and the advent of the microprocessor birthed numerous niches — motherboards, hard-drives, software packages, graphic monitors and laser printers, just to name a few.

In Only the Paranoid Survive, former Intel CEO Andy Grove similarly recalls how the computing industry moved on from vertical giants, like IBM and DEC that did everything (i.e., from chipmaking through to sales), to horizontal specialists, like Intel in chips, Hewlett Packard in computers and Microsoft in operating systems.

The evolution of social media provides a similar example. True, the number of keystone platforms, like Facebook and Twitter, have consolidated over time due to network effects. But they have led also to new niches, from celebrity-like influencers to digital marketers to big-data media analytics.  

“Complexity in the form of greater diversity and a more intricate web of interactions tends to bootstrap itself upward over time… In coevolutionary systems it may grow by increases in “species” diversity: under certain circumstances new species may provide further niches that call forth further new species in a steady upward spiral”.

W. Brian Arthur. (2014). Complexity and the Economy.

Structural deepening

The second complexity-generating mechanism is structural deepening. Competition, as you know, tends to push systems towards their performance limits. But systems may “break out” of existing moulds by introducing new components for improved fitness in their environment.

Larger animal species, for example, tend to evolve complex organs to cope with scaling challenges that size imposes on big bodies. Examples include lungs for breathing, or intestines for digestion. Smaller organisms, by contrast, tend to lack such “structural depth”. 

Structural deepening is common to human institutions and technologies as well. Take aviation, for example. Just look at its transformation over the last century as commercial and military pressures push relentlessly for better designs, materials and components (Figure 1). 

Figure 1. Wright Military Flier (1908) & Lockheed SR-71 Blackbird (1999)
Source: Wikimedia Commons (2008) and NASA (2021)

Capturing software

The third mechanism is capturing software. In Arthur’s words, this is when an “outside system” uses simple components and rules “in complicated combinations for its own multipurpose ends”. 

This may sound abstract. But it is akin to how children learn to talk or program code. They pick up simple elements and rules and learn to combine them in useful ways. Over time, their language or programming chops grow in ability and sophistication.

For a simple illustration, Arthur points to the engineering of electronics. In the humble days of Michael Faraday and Ben Franklin, electricity was much more of a novelty. Over time, however, entrepreneurs and scientists discovered the rules behind electromagnetism and harnessed it to useful ends.

An economic expression

Putting all of this together, Arthur says we can think of the economy as “an expression of [its] technologies”.2 It is a “self-producing or autopoietic” process. Technology begets technology — “[calling] forth yet further arrangements — further technologies — and further changes.”

That’s not to say, however, that technological change and growth in complexity is uniform. Coevolutionary diversity, structural deepening, and capturing software may interact in ways to produce “intermittent and epochal” behavior. The rate of innovation may not conform to a neat runaway geometric process.

“The economy is an expression of its technologies… It is like seeing the mind not as a container for its concepts… but as something that emerges from these. Or seeing an ecology not as containing a collection of biological species, but as forming from its collection of species.”

W. Brian Arthur. (2014). Complexity and the Economy.

2 Remember, we mean technologies in the broadest sense. This includes institutions, like our financial, legal, and political systems; as well as organizational arrangements, like our models for business and community.

Perpetual challenge and response

It is reasonable then to ask if economic evolution by combination will continue into perpetuity. Arthur believes the answer is probably yes — putting aside, of course, existential threats like climate change, nuclear war and resource depletion.

For one, satisfying every human need and exhausting every conceivable innovation seems unlikely. Want and envy, I suspect, will continue to motivate individual, commercial, and national interests into the foreseeable future.

What’s more, progress tends to create new challenges that demand new solutions. The Great Acceleration, for example, brought a lot of new knowledge and wealth to the world. But it has also left in its wake a sustainability crisis for us to manage.

The Agricultural Revolution, likewise, freed hunter-gatherers from the immediate issue of subsistence. But the densely populated empires that arose from food production created another deadly foe in highly infectious diseases.

This process of formation and reformation, Arthur highlights, is a “sequence of problem and solution”, and “of challenge and response”. Until some negative feedback loop stops us or ends us, humanity will continue on this invisible hamster wheel in search of something forevermore.

“The economy therefore exists always in a perpetual openness of change — in perpetual novelty. It exists perpetually in a process of self-creation. It is always unsatisfied.”

W. Brian Arthur. (2014). Complexity and the Economy.

Sources and further reading