Complexity and the Economy Read online

  Thus the railway locomotive was constructed from the already existing

  steam engine, boiler, cranks, and iron wheels. It entered the collective around 1829 (step 1); replaced existing horse-drawn trains (step 2); set up needs for the fabrication of iron rails and the organization of railways (step 3); caused the canal and horse-drayage industries to wither (step 4); became a key component in the transportation of goods (step 5); and in time caused prices and

  comPlexi t y economics [ 19 ]

  incentives across the economy to change (step 6). Such events may operate in parallel: new opportunities for example appear almost as soon as a new

  technology appears.

  If you play the algorithm out in your mind you see something interesting.

  It can set in motion a sequence of happenings that never end, because each

  of the events may trigger a cascade of further events. A novel technology may

  cause further technologies to be added, by steps 3 and 5; further replacements of old technologies, by step 4; and further readjustments, by step 6. And these new technologies in turn can cause yet further opportunities, further technologies, and further replacements. The algorithm may be simple, but once set in motion it engenders rich, patterned, endlessly novel behavior.

  So far this depicts the basic mechanism of formation of the economy. But

  there is a second layer of mechanism that adds further structure. New technologies often enter in groups (Perez, 2002; Arthur, 2009): over decades, families of technologies, the steam-driven ones, electrical ones, chemical ones, digital ones, enter. These are based on a given key technology, the steam engine say,

  or on families of related phenomena—chemical, electrical, genetic—that are

  harnessed and become available. And they build haltingly from one or two early central technologies then fill in the needed sub-technologies. These bodies of technology are not adopted within the economy, rather they are encountered by industries, combining with business processes that already exist and causing new activities, new incentives, new available processes, and little irruptions in the shape of little firms, a few of which go on to become large firms.

  The economy—the set of arrangements and activities that satisfy our needs—

  builds out as a result of all this. Indeed the economy is the result of all this.

  I have given only the bare bones of the processes by which the economy

  re-forms itself, and each mechanism has sub-mechanisms omitted here (see

  Arthur, 2009). But notice the overall theme: A few simple properties of tech-

  nology yield a system of changing elements (technologies), each new element

  created from previous elements, each causing replacements, and all bringing

  on an ever-changing set of demands for further elements, the whole chan-

  neled and structured by the properties and possibilities of the dominant fami-

  lies of phenomena recently captured.

  This overall process is a self-creating one. Novel technologies form from

  existing technologies, so the collective of technology is self-producing or autopoietic. So too is the economy. It forms from its technologies and mediates the creation of further technologies and thereby its own further formation. Here

  again we are very much in complexity territory.

  We can now see how the economy changes structurally. As novel physical

  technologies enter, novel forms of organization and novel institutions are called for and come into place, and these in turn call forth further new technologies—

  further methods, organizations, and institutions. Structure emerges. On a lon-

  ger time scale, the large bodies of technology define a thematic way by which

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  operations in the economy are carried out. So we have the steam era, the railroad era, the digital era. They also pose characteristic or thematic challenges that call forth novel solutions; the economy changes structurally. The steam engine and

  early textile machinery made possible the Victorian mill-based economy, and

  its excesses called forth new arrangements: laws covering child safety, regu-

  lations ameliorating working conditions, and labor unions in modern form.27

  As the economy changes then, its organizations and institutions change, and

  these call forth yet further arrangements—further technologies—and further

  changes. The economy transforms structurally. We can isolate the mechanisms

  by which the economy renews itself, but we can’t predict the exact ways these

  play out. The overall process (or computation, if you will) is far from determinate. And it is par excellence one of nonequilibrium.

  Notice that the theory I have outlined is algorithmic: it is expressed as a

  set of processes triggered by other processes, not as a set of equations. The

  reader may again ask how this can be theory? Consider a parallel with biology.

  Even now, 150 years after Darwin’s Origin, no one has succeeded in reducing to an equation-based system the process by which novel species are created,

  form ecologies, and bring into being whole eras dominated by characteristic

  species. The reason is that the evolutionary process is based on mechanisms

  that work in steps and trigger each other, and it continually defines new cat-

  egories—new species. Equations do well with changes in number or quanti-

  ties within given categories, but poorly with the appearance of new categories themselves. Yet we must admit that evolution’s central mechanisms are deeply

  understood and form a coherent group of general propositions that match

  real world observations, so these understandings indeed constitute theory.28

  Biology then is theoretical but not mathematical; it is process-based, not

  quantity-based. In a word it is procedural. By this token, a detailed economic theory of formation and change would also be procedural.29 It would seek to

  27. Political economist William Tabb (1999), expresses structural change this

  way: “Technological revolutions and political upheavals condition economic possibilities, which then become the givens for sustained periods of seeming stability in which regulatory regimes designed for the conditions of the social structure of accumulation of the era lend a semblance of orderly progress. These institutional forms, appropriate to one stage of development, become a drag on the development of new forces and emergent relations of production. The vitality of market forces create in their wake social problems which, when they become severe enough need to be addressed through spirited struggle out of which new rules, regulations, and institutions form.”

  28. Similar observations can be made about the theories of embryological development, of biochemical pathways, of molecular genetics, and of cell biology. The process of mitosis (cell division) has no mathematics, but does have a series of well-understood, if complicated, phases or steps.

  29. The reader might be tempted to translate this back into familiar terms such as capital, labor, growth, etc. That might be possible, but I prefer to see this as a different way to “image” or understand change in the economy, much as MRI scanning images organs differently than conventional x-ray scanning.

  comPlexi t y economics [ 21 ]

  understand deeply the mechanisms that drive formation in the economy and not necessarily seek to reduce these to equations. The procedural theory I have outlined doesn’t negate the standard one, but it does give an alternative that puts the emphasis squarely on the driver of change itself—on technology.

  How can we study all this more deeply? The base processes are algorith-

  mic, so certainly we can construct computer-based models of their key mecha-

  nisms.30 Studies here are still at their beginning. The overall view we end up with is one of creative formation: of new
elements forming from existing elements, new structure forming from existing structure, formation itself pro-

  ceeding from earlier formation. This is very much a complexity view.

  DISCUSSION

  It should be clear by now that we have a different framework for thinking

  about the economy, one that emphasizes not the physics of goods and ser-

  vices, but processes of change and creation. Yet, as the reader may have sur-

  mised, this new view is not entirely new within economic thought. It links

  with earlier thinking in a way I want to comment on now.

  There are two great problems in economics. One is allocation within the economy: how quantities of goods and services and their prices are determined within and across markets. This is represented by the great theories

  of general equilibrium, international trade, and game-theoretic analysis. The

  other is formation within the economy: how an economy emerges in the first place, and grows and changes structurally over time. This is represented by

  ideas about innovation, economic development, structural change, and the

  role of history, institutions, and governance in the economy. The allocation

  problem is well understood and highly mathematized, the formation one less

  well understood and barely mathematized.31

  How did this come about? Until about 1870 both problems were of equal

  importance to the great theorists in economics. Smith, Mill, and Marx all

  contributed to making a rational science out of allocation, yet they equally

  contributed to questions of formation, governance, and history. Then in

  Victorian times came the great marginalist and general-equilibrium revolu-

  tion that rendered the problem of allocation into algebra and calculus (given

  strict assumptions of rationality and equilibrium). But the problem of forma-

  tion could not be so rendered. By its nature it couldn’t be restricted to either 30. In 2006 Wolfgang Polak and I modeled a creation process successfully on the computer by which increasingly complicated technologies (digital logic circuits) emerged from initially simple ones via random combination of earlier combinations (circuits).

  31. See Tabb (1999) for an excellent discussion of these two branches of economics.

  Also Bronk (2009).

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  stasis or rationality, and so the mathematization of economics—what came in the twentieth century to be taken as “theory”—passed it by. Formation

  was still studied by Marshall, Veblen, Schumpeter, Hayek, and Shackle, and by

  the many institutionalists and historians that followed. But the thinking was

  largely history-specific, particular, case-based, and intuitive—in a word, literary—and therefore held to be beyond the reach of generalizable reasoning, so

  in time what had come to be called political economy became pushed to the

  side, acknowledged as practical and useful but not always respected.

  It is now clear to economists that the mathematical analysis of allocation

  far from covers all of economics and operates poorly with questions of forma-

  tion, exploration, adaptation, and qualitative change (Tabb, 1999). Complexity economics by contrast is very much about these questions of creation and the

  formation of structure, and it studies the mechanisms by which these operate.

  So here complexity meets up with and revives the grand tradition of political

  economy, and the two—much to my delight—have a lot to say to each other.

  Complexity economics allows us to explore the world of formation theoreti-

  cally and systematically; political economy allows us to explore it intuitively and empirically. The new approach will help provide a theoretical backbone

  for political economy. It will not and should not displace case-based historical analysis, but will deepen and develop this venerable branch of thinking. And

  political economy will deepen and develop complexity economics.

  One of the main strengths of political economy is its sense of history, of historical time—time that makes a real, irreversible difference, and that continually creates new structures. By contrast neoclassical economics handles time

  poorly (Smolin, 2009, 2013). At equilibrium an outcome simply persists and

  so time largely disappears; or in dynamic models it becomes a parameter that

  can be slid back and forth reversibly to denote the current outcome (Harris,

  2003). This has made many economic thinkers uncomfortable (Robinson,

  1980). In 1973 Joan Robinson said famously, “Once we admit that an econ-

  omy exists in time, that history goes one way, from the irrevocable past into

  the unknown future, the conception of equilibrium . . . becomes untenable. The whole of traditional economics needs to be thought out afresh.”

  Certainly, in rethinking this issue of time, complexity economics accords

  with political economy. In the “computation” that is the economy, large and

  small probabilistic events at particular non-repeatable moments determine

  the attractors fallen into, the temporal structures that form and die away, the technologies that are brought to life, the economic structures and institutions that result from these, the technologies and structures that in turn build

  upon these; indeed the future shape of the economy—the future path taken.

  The economy at all levels and at all times is path dependent. History again

  becomes important. And time reappears.

  A natural question is whether this new approach has policy implications.

  Certainly, complexity teaches us that markets left to themselves possess

  comPlexi t y economics [ 23 ]

  a tendency to bubbles and crashes, induce a multiplicity of local attractor states, propagate events through financial networks, and generate a sequence

  of technological solutions and challenges, and this opens a role for policies of regulating excess, nudging towards favored outcomes, and judiciously foster-ing conditions for innovation. Colander and Kupers (2014) express this suc-

  cinctly as getting meta conditions right.

  This is certainly valid. But I believe we can make a stronger statement. The

  failures of economics in the practical world are largely due to seeing the economy in equilibrium. If we look at the economic crises of the last 25 years—the debacle that followed the freeing of markets in Russia in 1990, the extensive

  gaming of California’s energy market after the lifting of regulations in 2000, the collapse of Iceland’s banks in 2008, the ongoing Euro crisis, the Wall Street meltdown of 2008—all these were caused in no small part by the exploitation

  of the system by a few well-positioned players, or by markets that careened

  out of control (Arthur, 2010a). Equilibrium thinking cannot “see” such exploi-

  tation in advance for a subtle reason: by definition, equilibrium is a condition where no agent has any incentive to diverge from its present behavior, therefore exploitive behavior cannot happen. And it cannot see extreme market

  behavior easily either: divergences are quickly corrected by countervailing

  forces. By its base assumptions, equilibrium economics is not primed to look

  for exploitation of parts of the economy or for system breakdowns.

  Complexity economics, by contrast, teaches us that the economy is perma-

  nently open to response and that every part of it is open to new behavior—to

  being exploited for gain, or to abrupt changes in structure. A complexity out-

  look would recommend putting carefully thought out controls in place, much

  as authorities put sensible building codes in place in seismic regions. But just as important, it would bring a shift in at
titude in the direction of realism.

  The economy does not consist of a set of behaviors that have no motivation

  to change and collectively cause optimality; the economy is a web of incen-

  tives that always induce further behavior, invite further strategies, provide

  collectively “reasonable” outcomes along the way, and ever cause the system

  to change.

  CONCLUSION

  Complexity economics is neither an add-on to standard economics (see

  Fontana, 2010), nor does it consist of adding agent-based behavior to stan-

  dard models. It is a different way of thinking about the economy. It sees the

  economy not as a system in equilibrium but as one in motion, perpetually

  “computing” itself—perpetually constructing itself anew. Where equilib-

  rium economics emphasizes order, determinacy, deduction, and stasis, this

  new framework emphasizes contingency, indeterminacy, sense-making, and

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  openness to change. There is another way to say this. Until now, economics has been a noun-based rather than verb-based science. It has pictured changes

  over time in the economy function as changes in levels of fixed noun-entities—

  employment, production, consumption, prices. Now it is shifting toward see-

  ing these changes as a series of verb-actions—forecast, respond, innovate,

  replace—that cause further actions.

  This shift reveals an important middle layer in the economy, the meso-layer.

  And it redefines what constitutes a solution in economics. A solution is no

  longer necessarily a set of mathematical conditions but a pattern, a set of

  emergent phenomena, a set of changes that may induce further changes, a

  set of existing entities creating novel entities. Theory in turn becomes not the discovery of theorems of undying generality, but the deep understanding of

  mechanisms that create these patterns and propagations of change.

  This shift in economics is very much part of a larger shift in science itself.

  All the sciences are becoming more procedural, more algorithmic, more

  Turingesque; and less equation-based, less continuous, less Newtonian, than