Students for Liberty talk: economics and complexity

Lynne Kiesling

UPDATE: I’ve had a report that the link to the slides is not working, but I can’t get it not to work … so if you are having trouble please let me know in the comments and I’ll go bug-stomping. UPDATED UPDATE: mischief managed, I think!

On Saturday I was honored to be the morning keynote speaker at the Students for Liberty Chicago Regional Conference. In only four years SFL has grown into a large and effective organization for bringing together students who share an interest in exploring and promoting individual liberty, classical liberal ideas, and public policy that reflects those principles.

My talk, Beneficial Complexity (pdf of slides), took some basic economic concepts and looked at them through the lens of complexity science. My main objective was to encourage the attendees to see ways to integrate some core classical liberal ideas into their own thinking, their own work, their persuasive discussions with others, and their advocacy activities.

Start with a story: a flower market selling calla lilies grown in Colombia. Lots of buyers and sellers, lots of parties involved in getting the flowers from places like Colombia to your neighborhood flower shop. Mostly impersonal exchange, but not entirely devoid of personal relationships. And without any one person knowing how to do so in its entirety, the flowers get from Colombia to my flower shop for me to buy. If you are familiar with Leonard Reed’s I, Pencil essay about the highly decentralized yet coordinated processes that combine to bring pencils to consumers, you recognize this theme. One of the fundamental economic and epistemological concepts that I, Pencil illustrates is the knowledge problem — no one person knows how to make a pencil, or how to grow and sell calla lilies globally. We associate this idea primarily with the work of F.A. Hayek, as stated in his famous essay “The Use of Knowledge in Society” in 1945 (which also inspires the title of this blog).

Knowledge is dispersed and, importantly, it is also private and often subjective. Your willingness to use some of your resources to buy a cup of coffee, or a pencil or a calla lily bouquet, is known only to you and is context dependent, which means that much of the knowledge that goes into individual decisions is local and hard to centralize. Yet calla lilies show up in Chicago shops, as do pencils, in ways that satisfy the preferences of consumers and profit producers along the supply chain. How does that happen? Markets and prices create networks of dispersed, local, private knowledge that connects and aggregates that knowledge and sends valuable signals to economic actors about the relative benefits and costs of the decisions they take.

When we think about economic activity taking place in networks, and how exchange and prices connect networks and extend and deepen them, we are using the tools of complexity science to understand economic behavior. Think back to the flower market and the pencil. As Eric Beinhocker writes in The Origin of Wealth, “The complexity of all this activity is mind-boggling. … all the jobs that must get done, all the things that need to get coordinated, and the timing and sequence of everything. … there is no one in charge of the global to-do list. … Yet, extraordinarily, these sorts of things happen every day in a bottom-up, self-organized way. … The economy is a marvel of complexity.” (2006, pp. 5-6)

Technically speaking, what is a complex system? It’s a system or arrangement of many component parts, and those parts interact. These interactions generate outcomes that you could not necessarily have predicted in advance. In other words, it’s a non-deterministic system. Scholars in many different fields use this general idea to study a range of systems and phenomena, from molecular and cellular interactions in physics, chemistry, or biology, to the organization of the brain in neuroscience, to species and environment interactions in ecosystems, to cascading network failures in electric power systems, to networks of co-author collaborations in particular fields of research, and many other applications.

These applications share an interest in three features of a complex system: its structure (how are the parts connected, how do they interact?), its rules (physical or human-generated), and its behavior. apply this idea of a complex system to our economic and social interactions. Go back to Beinhocker’s description of the market economy as “a marvel of complexity” in which all sorts of activities get coordinated in a “bottom-up, self-organized way”. Think of the economy as a complex system, in which individuals are the agents, the component parts, with dispersed private knowledge. We are connected in many ways — social relations, economic exchange, organizations, and so on — and our interactions shape individual decisions, individual behavior, and ultimately overall system behavior. The profound insights of writers like Ferguson, Smith, Hayek, and others is that individual agents have their own preferences and private knowledge, but we interact, and in so doing we generate system-level behavior that is generally self-organized — emergent order. In this unplanned order no one person can predict the specific outcome we’ll achieve, but we still experience over and over and over in human history that order generally does emerge.

But order doesn’t necessarily always emerge, and the order that emerges sometimes isn’t pretty. That observation leads to the elephant in the room with respect to emergent order in social system: the rules. All exchange takes place within a framework of rules, an institutional context. Those institutions include formal laws enforcing property ownership, contracts, and punishment for theft and fraud, as well as informal social norms and peer pressure that may, for example, affect how the bargaining and negotiation in the exchange take place. Rules shape how agents interact, and shape their incentives … and as a result they can also affect system behavior. One important implication of studying economies as complex systems is that when we design institutions, we should model and test and strive for rules that enable order to emerge, which means an emphasis on process rather than using rules to achieve some specific outcome. That’s one important intersection of classical liberal principles with complexity science.

I’d like to raise a point that I didn’t in my remarks on Saturday, but builds on a discussion in a later session at the conference. One challenge that we often face as classical liberals is putting “the human face” on our ideas, countering the perception that a libertarian society would be cold, calculating, and lacking in compassion or personal relationships. Nothing is further from the truth, and the language of complexity science gives us a way to communicate that reality, because it frames economic/social interactions as relationships and connections. It emphasizes the mutuality of exchange and the multiple dimensions of our relationships with others in our voluntary associations.

Resiliency comes from more risk of bank failure, not less

Lynne Kiesling

In the always-smart-and-interesting City AM paper from London, Anthony Evans makes an important argument that has been overlooked in financial regulation debates: risk of failure is what creates system resilience, and regulation creates brittle monocultures. He writes in the context of last week’s Independent Commission on Banking (ICB) recommendations for creating regulatory divisions between retail banking and investment banking and implementing other structural changes, with the objective of a more resilient financial system. Evans critiques the over-simplified concept of risk that the report employs:

We can’t say that one thing is more risky than another – only that different activities expose people to different types of risk. Bodies like the ICB needs to shift from trying to – impossibly – reduce risk to placing responsibility on those who are choosing between different risks.

For example, ordinary depositors should not be protected from risk – they need to confront it. It can seem counterintuitive, but the genuine threat of bank runs is probably the best disciplinary device to prevent them from happening.

Evans’ argument stems from an assertion that he makes later in his column, that risk cannot be reduced but can only be transferred from one party to another. While I think that assertion is debatable, the important insight from this part of his argument is that resiliency in complex market systems arises from agents having responsibility for losses associated with taking additional risks, in addition to their receiving profits associated with taking additional risks. Breaking that connection among risk, profit, and loss is one of the core causes of the brittleness of the financial system over the past two decades, and the transmission and magnification of those losses.

Evans makes a second important observation: when regulation imposes a higher degree of uniformity in a complex system, it reduces resilience of the overall system by creating separated monocultures:

By making arbitrary decisions about what must stay within fences and what doesn’t, or about the level of equity capital that banks will be required to keep, regulators make banking more homogenous. Banks are already free to set up their own ring fences, and a competitive system would be one where they can experiment with different ones. …

All regulations create clusters of errors – by their nature they harmonise behaviour and therefore increase systemic dangers. Policy efforts need to focus on reducing barriers to exit, making it easier for banks to fail, making the costs of failure more visible and ensuring they fall on those who make bad decisions – bankers, regulators, or even the public.

We see this paradox of control in all forms of economic regulation; in this case in financial regulation, but also in the electricity regulation that is the focus of my attention. Regulators believe that by increasing control, by limiting the range of actions that agents can take in complex systems, they are reducing the risk of bad outcomes. But what they do not realize (or choose to ignore) is, as Evans points out here, that by imposing more top-down centralized control on their actions and interactions, they reduce the incentives of the agents to develop their own forms of individual control based on their local knowledge and their own experimentation. Thus regulation makes this complex system more rigid, more brittle, less resilient, and therefore regulation does not achieve its stated goals.

Note here that I am using the tools and language of complexity science and complexity economics, but you can see in this discussion where moral hazard shows up, where you could talk about the failures of corporate governance (as does Charlie Calomiris), etc. Framing the objective as a resilient system broadens the focus beyond top-down regulation to include the individual, decentralized institutions that can keep dangers from becoming systemic. Thinking about regulation in terms of the locus of control and the consequences of the imposition of control in a complex system is more likely to enable us to incorporate the costs of imposing control into the analysis, and to harness decentralized institutions to enable a more resilient system.

Worried about too much demand elasticity in electric power markets

Michael Giberson

Will electric power consumers facing smart-grid enabled real time prices have the potential to accidentally destabilize the power grid and cause a blackout?  A paper presented at a recent IEEE conference says it is a possibility. The surprising culprit? Too much price elasticity in the market demand function.

It is a surprising culprit because consumer demand for electricity is currently notoriously inelastic (that is to say, not responsive to changing prices) in the short run, in part due to the way standard regulatory rate structures end up with consumers being presented with relatively unchanging prices reflecting a longer-term average cost of production. Prices don’t change much, so consumers don’t watch prices much. But this price inelasticity of demand doesn’t mean the quantity of electricity consumers want to consume is unchanging – consumers want more or less electricity throughout the day in response to ordinary household schedules and in response to outside temperatures and building heating and cooling demands. Consumer demand for power responds to a lot of things, but rarely to changes in the price of power itself.

Because of the way the current grid is designed, the quantity of energy supplied and demanded must be balanced continuously. Therefore, the grid is typically operated to take the quantity of power demanded as a given and make whatever adjustments in the quantity supplied to maintain system balance. (In brief, because prices can’t do much work coordinating supply and demand in the short-run, all of the coordination must be done by adjusting quantities. Grid operators can typically control suppliers but not consumers, so quantity-based supply side adjustment does most of the work of keeping the market balanced.)

The authors, three engineers at MIT, worry that if too many consumers facing real time prices pick similar high price points at which to cycle off appliances (or low prices as which to charge electric vehicles), that the market demand function will acquire highly price elastic segments in which quantity demanded will suddenly drop off (or spike up) at rates faster than the supply side can safely accommodate. Therefore, a blackout risk. To counter this possible risk, the authors suggest diversifying price signals sent to consumers, or employing hourly instead of 5-minute price signals, or using rolling-average prices to consumers rather than location-specific current marginal price. They admit their safeguards would hamper the efficiency of market results, the efficiency loss essentially the price paid to mitigate the possibility of a price-responsive demand shock to the system.

In my view, the idea of having so many real-time price-aware consumers responding in the market remains so far-fetched that I’m not willing to worry about that so many of them will coordinate their home energy management systems on the same price points and unwittingly bring down the system.

And well before this possibility of too-much consumer responsiveness comes about, I suspect most RTOs will be paying suppliers for ramping capability and charging consumers for using it in ways that will enable sufficient short-run system responsiveness. So I’m not ready to worry now about this problem, and don’t think that I’ll need to worry about it later, either.

(See MIT media relations summary here, HT to Scientific American via Economist’s View.) Unplanned order

Lynne Kiesling

I’ve been enjoying the new videos available at LearnLiberty, all of which give clear, insightful discussions of fundamental concepts of classical liberalism (including economics). My highlight of the day is Tom Bell’s “Can order be unplanned?”

The answer is yes. Here Tom explores the rich intellectual history of the concept of spontaneous order, and how individuals pursuing their own ends can coordinate their decentralized actions in ways that lead to the emergence of unplanned order. His brief discussion explains the concepts, refers to its articulation by Adam Smith and F.A. Hayek, and shows how the answer to “who’s in charge here?” can be “no one” without society descending into chaos.

Paul Cézanne’s birthday

Lynne Kiesling

Today’s Google banner celebrates the 172nd birthday of Paul Cézanne, my favorite artist. I love how he unpacks the underlying layers of geometry in landscapes. When I first saw the painting above, Le lac d’Annecy, in the Courtauld Gallery in London when I was a college student, it literally took my breath away.

Last year when I read Jonah Lehrer’s Proust Was A Neuroscientist, I was riveted by his chapter “Paul Cézanne: The Process of Sight”, because he articulated so clearly (where I cannot!) why I respond so strongly to Cézanne’s art:

His paintings were about the subjectivity of sight, the illusion of surfaces. … But Cézanne believed that light was only the beginning of seeing. “The eye is not enough,” he declared. “One needs to think as well.” Cézanne’s epiphany was that our impressions require interpretation; to look is to create what you see.

We now know that Cézanne was right. Our vision begins with photons, but this is only the beginning. Whenever we open our eyes, the brain engages in an act of astonishing imagination, as it transforms the residues of light into a world of form and space that we can understand.” …

… Cézanne’s art exposes the process of seeing.

None of this, or its appeal to someone like me, should surprise any of you familiar with Hayek’s The Sensory Order. On a related note, see this post from Steve Horwitz on The Sensory Order and optical illusion.

NHL’s experiments in hockey

Michael Giberson

Stephen Dubner at Freakonomics points to a Macleans story on some wild experimentation going on in the National Hockey League: shallower nets, moving the second referee off the ice, moving the face-off circles, three-on-three and two-on-two shootouts, and more. The article said:

The unusual nature of some items tested at the camp reminded Simon Fraser University business professor Lindsay Meredith of the freewheeling “skunk works” divisions that tech companies create to investigate advanced projects. “Any major corporation should have some kind of skunk works—a bank, a university, whatever,” he says. “An enterprise of that size and sophistication would be foolish not to.”

FIFA, you listening?

(Related: an April 2009 story in the Financial Times about an “experiments in business” course taught by Freakonomics co-author Steve Leavitt and John List at the University of Chicago.)

David Warsh on complexity and economics

Lynne Kiesling

David Warsh’s Economic Principals column this week is about complexity, and the study of complexity in economics. It is as informative and insightful as Warsh’s columns usually are, despite its selective coverage. He highlights some ideas that I think are important for the future direction of economics — the isolation of the twin methodological peaks of what David Colander calls the “summit of Mt. Walras” and Warsh calls “Game Theory Massif”, a brief history of complexity economics since the 1980s, and the extent to which complexity necessitates a change in research methodology to incorporate work like agent-based modeling and variables that are less “formalizable” on Mt. Walras, such as institutions and knowledge.

This was not Warsh’s purpose in his column, but I’d expand beyond his column to incorporate the intersection of his ideas with Hayek’s “Theory of Complex Phenomena” (1967) and the general relevance of the knowledge problem to why and how phenomena are complex. In social systems, diffuse private knowledge is a big reason why complex social systems evolve, and why we discover and design rules that exploit that complexity to get better outcomes. Markets and prices are just the most obvious and pervasive example, but there are multitudes of others.

I recommend Warsh’s column, both today and as a worthwhile weekly read, for some good thought provocation and for some discussion of the ideas that animate the work here at Knowledge Problem and related ideas.