Complexity Theory and Evolution in Economics

24 April, 2017

This book looks interesting:

• David S. Wilson and Alan Kirman, editors, Complexity and Evolution: Toward a New Synthesis for Economics, MIT Press, Cambridge Mass., 2016.

You can get some chapters for free here. I’ve only looked carefully at this one:

• Joshua M. Epstein and Julia Chelen, Advancing Agent_Zero.

Agent_Zero is a simple toy model of an agent that’s not the idealized rational actor often studied in economics: rather, it has emotional, deliberative, and social modules which interact with each other to make decisions. Epstein and Chelen simulate collections of such agents and see what they do:

Abstract. Agent_Zero is a mathematical and computational individual that can generate important, but insufficiently understood, social dynamics from the bottom up. First published by Epstein (2013), this new theoretical entity possesses emotional, deliberative, and social modules, each grounded in contemporary neuroscience. Agent_Zero’s observable behavior results from the interaction of these internal modules. When multiple Agent_Zeros interact with one another, a wide range of important, even disturbing, collective dynamics emerge. These dynamics are not straightforwardly generated using the canonical rational actor which has dominated mathematical social science since the 1940s. Following a concise exposition of the Agent_Zero model, this chapter offers a range of fertile research directions, including the use of realistic geographies and population levels, the exploration of new internal modules and new interactions among them, the development of formal axioms for modular agents, empirical testing, the replication of historical episodes, and practical applications. These may all serve to advance the Agent_Zero research program.

It sounds like a fun and productive project as long as one keeps ones wits about one. It’s hard to draw conclusions about human behavior from such simplified agents. One can argue about this, and of course economists will. But regardless of this, one can draw conclusions about which kinds of simplified agents will engage in which kinds of collective behavior under which conditions.

Basically, one can start mapping out a small simple corner of the huge ‘phase space’ of possible societies. And that’s bound to lead to interesting new ideas that one wouldn’t get from either 1) empirical research on human and animal societies or 2) pure theoretical pondering without the help of simulations.

Here’s an article whose title, at least, takes a vastly more sanguine attitude toward benefits of such work:

• Kate Douglas, Orthodox economics is broken: how evolution, ecology, and collective behavior can help us avoid catastrophe, Evonomics, 22 July 2016.

I’ll quote just a bit:

For simplicity’s sake, orthodox economics assumes that Homo economicus, when making a fundamental decision such as whether to buy or sell something, has access to all relevant information. And because our made-up economic cousins are so rational and self-interested, when the price of an asset is too high, say, they wouldn’t buy—so the price falls. This leads to the notion that economies self-organise into an equilibrium state, where supply and demand are equal.

Real humans—be they Wall Street traders or customers in Walmart—don’t always have accurate information to hand, nor do they act rationally. And they certainly don’t act in isolation. We learn from each other, and what we value, buy and invest in is strongly influenced by our beliefs and cultural norms, which themselves change over time and space.

“Many preferences are dynamic, especially as individuals move between groups, and completely new preferences may arise through the mixing of peoples as they create new identities,” says anthropologist Adrian Bell at the University of Utah in Salt Lake City. “Economists need to take cultural evolution more seriously,” he says, because it would help them understand who or what drives shifts in behaviour.

Using a mathematical model of price fluctuations, for example, Bell has shown that prestige bias—our tendency to copy successful or prestigious individuals—influences pricing and investor behaviour in a way that creates or exacerbates market bubbles.

We also adapt our decisions according to the situation, which in turn changes the situations faced by others, and so on. The stability or otherwise of financial markets, for instance, depends to a great extent on traders, whose strategies vary according to what they expect to be most profitable at any one time. “The economy should be considered as a complex adaptive system in which the agents constantly react to, influence and are influenced by the other individuals in the economy,” says Kirman.

This is where biologists might help. Some researchers are used to exploring the nature and functions of complex interactions between networks of individuals as part of their attempts to understand swarms of locusts, termite colonies or entire ecosystems. Their work has provided insights into how information spreads within groups and how that influences consensus decision-making, says Iain Couzin from the Max Planck Institute for Ornithology in Konstanz, Germany—insights that could potentially improve our understanding of financial markets.

Take the popular notion of the “wisdom of the crowd”—the belief that large groups of people can make smart decisions even when poorly informed, because individual errors of judgement based on imperfect information tend to cancel out. In orthodox economics, the wisdom of the crowd helps to determine the prices of assets and ensure that markets function efficiently. “This is often misplaced,” says Couzin, who studies collective behaviour in animals from locusts to fish and baboons.

By creating a computer model based on how these animals make consensus decisions, Couzin and his colleagues showed last year that the wisdom of the crowd works only under certain conditions—and that contrary to popular belief, small groups with access to many sources of information tend to make the best decisions.

That’s because the individual decisions that make up the consensus are based on two types of environmental cue: those to which the entire group are exposed—known as high-correlation cues—and those that only some individuals see, or low-correlation cues. Couzin found that in larger groups, the information known by all members drowns out that which only a few individuals noticed. So if the widely known information is unreliable, larger groups make poor decisions. Smaller groups, on the other hand, still make good decisions because they rely on a greater diversity of information.

So when it comes to organising large businesses or financial institutions, “we need to think about leaders, hierarchies and who has what information”, says Couzin. Decision-making structures based on groups of between eight and 12 individuals, rather than larger boards of directors, might prevent over-reliance on highly correlated information, which can compromise collective intelligence. Operating in a series of smaller groups may help prevent decision-makers from indulging their natural tendency to follow the pack, says Kirman.

Taking into account such effects requires economists to abandon one-size-fits-all mathematical formulae in favour of “agent-based” modelling—computer programs that give virtual economic agents differing characteristics that in turn determine interactions. That’s easier said than done: just like economists, biologists usually model relatively simple agents with simple rules of interaction. How do you model a human?

It’s a nut we’re beginning to crack. One attendee at the forum was Joshua Epstein, director of the Center for Advanced Modelling at Johns Hopkins University in Baltimore, Maryland. He and his colleagues have come up with Agent_Zero, an open-source software template for a more human-like actor influenced by emotion, reason and social pressures. Collections of Agent_Zeros think, feel and deliberate. They have more human-like relationships with other agents and groups, and their interactions lead to social conflict, violence and financial panic. Agent_Zero offers economists a way to explore a range of scenarios and see which best matches what is going on in the real world. This kind of sophistication means they could potentially create scenarios approaching the complexity of real life.

Orthodox economics likes to portray economies as stately ships proceeding forwards on an even keel, occasionally buffeted by unforeseen storms. Kirman prefers a different metaphor, one borrowed from biology: economies are like slime moulds, collections of single-celled organisms that move as a single body, constantly reorganising themselves to slide in directions that are neither understood nor necessarily desired by their component parts.

For Kirman, viewing economies as complex adaptive systems might help us understand how they evolve over time—and perhaps even suggest ways to make them more robust and adaptable. He’s not alone. Drawing analogies between financial and biological networks, the Bank of England’s research chief Andrew Haldane and University of Oxford ecologist Robert May have together argued that we should be less concerned with the robustness of individual banks than the contagious effects of one bank’s problems on others to which it is connected. Approaches like this might help markets to avoid failures that come from within the system itself, Kirman says.

To put this view of macroeconomics into practice, however, might mean making it more like weather forecasting, which has improved its accuracy by feeding enormous amounts of real-time data into computer simulation models that are tested against each other. That’s not going to be easy.

 


Information Aversion

22 August, 2014

 

Why do ostriches stick their heads under the sand when they’re scared?

They don’t. So why do people say they do? A Roman named Pliny the Elder might be partially to blame. He wrote that ostriches “imagine, when they have thrust their head and neck into a bush, that the whole of their body is concealed.”

That would be silly—birds aren’t that dumb. But people will actually pay to avoid learning unpleasant facts. It seems irrational to avoid information that could be useful. But people do it. It’s called information aversion.

Here’s a new experiment on information aversion:

In order to gauge how information aversion affects health care, one group of researchers decided to look at how college students react to being tested for a sexually transmitted disease.

That’s a subject a lot of students worry about, according to Josh Tasoff, an economist at Claremont Graduate University who led the study along with Ananda Ganguly, an associate professor of accounting at Claremont McKenna College.

The students were told they could get tested for the herpes simplex virus. It’s a common disease that spreads via contact. And it has two forms: HSV1 and HSV2.

The type 1 herpes virus produces cold sores. It’s unpleasant, but not as unpleasant as type 2, which targets the genitals. Ganguly says the college students were given information — graphic information — that made it clear which kind of HSV was worse.

“There were pictures of male and female genitalia with HSV2, guaranteed to kind of make them really not want to have the disease,” Ganguly says.

Once the students understood what herpes does, they were told a blood test could find out if they had either form of the virus.

Now, in previous studies on information aversion it wasn’t always clear why people declined information. So Tasoff and Ganguly designed the experiment to eliminate every extraneous reason someone might decline to get information.

First, they wanted to make sure that students weren’t declining the test because they didn’t want to have their blood drawn. Ganguly came up with a way to fix that: All of the students would have to get their blood drawn. If a student chose not to get tested, “we would draw 10 cc of their blood and in front of them have them pour it down the sink,” Ganguly says.

The researchers also assured the students that if they elected to get the blood tested for HSV1 and HSV2, they would receive the results confidentially.

And to make triply sure that volunteers who said they didn’t want the test were declining it to avoid the information, the researchers added one final catch. Those who didn’t want to know if they had a sexually transmitted disease had to pay $10 to not have their blood tested.

So what did the students choose? Quite a few declined a test.

And while only 5 percent avoided the HSV1 test, three times as many avoided testing for the nastier form of herpes.

For those who didn’t want to know, the most common explanation was that they felt the results might cause them unnecessary stress or anxiety.

Let’s try extrapolating from this. Global warming is pretty scary. What would people do to avoid learning more about it? You can’t exactly pay scientists to not tell you about it. But you can do lots of other things: not listen to them, pay people to contradict what they’re saying, and so on. And guess what? People do all these things.

So, don’t expect that scaring people about global warming will make them take action. If a problem seems scary and hard to solve, many people will just avoid thinking about it.

Maybe a better approach is to tell people things they can do about global warming. Even if these things aren’t big enough to solve the problem, they can keep people engaged.

There’s a tricky issue here. I don’t want people to think turning off the lights when they leave the room is enough to stop global warming. That’s a dangerous form of complacency. But it’s even worse if they decide global warming is such a big problem that there’s no point in doing anything about it.

There are also lots of subtleties worth exploring in further studies. What, exactly, are the situations where people seek to avoid unpleasant information? What are the situations where they will accept it? This is something we need to know.

The quote is from here:

• Shankar Vedantham, Why we think ignorance Is bliss, even when It hurts our health, Morning Edition, National Public Radio, 28 July 2014.

Here’s the actual study:

• Ananda Ganguly and Joshua Tasoff, Fantasy and dread: the demand for information and the consumption utility of the future.

Abstract. Understanding the properties of intrinsic information preference is important for predicting behavior in many domains including finance and health. We present evidence that intrinsic demand for information about the future is increasing in expected future consumption utility. In the first experiment subjects may resolve a lottery now or later. The information is useless for decision making but the larger the reward, the more likely subjects are to pay to resolve the lottery early. In the second experiment subjects may pay to avoid being tested for HSV-1 and the more highly feared HSV-2. Subjects are three times more likely to avoid testing for HSV-2, suggesting that more aversive outcomes lead to more information avoidance. We also find that intrinsic information demand is negatively correlated with positive affect and ambiguity aversion.

Here’s an attempt by economists to explain information aversion:

• Marianne Andries and Valentin Haddad, Information aversion, 27 February 2014.

Abstract. We propose a theory of inattention solely based on preferences, absent any cognitive limitations and external costs of acquiring information. Under disappointment aversion, information decisions and risk attitude are intertwined, and agents are intrinsically information averse. We illustrate this link between attitude towards risk and information in a standard portfolio problem, in which agents balance the costs, endogenous in our framework, and benefits of information. We show agents never choose to receive information continuously in a diffusive environment: they optimally acquire information at infrequent intervals only. We highlight a novel channel through which the optimal frequency of information acquisition decreases when risk increases, consistent with empirical evidence. Our framework accommodates a broad range of applications, suggesting our approach can explain many observed features of decision under uncertainty.

The photo, probably fake, is from here.


To Really Judge Good Music, Turn Off the Sound

21 August, 2013

In a study published in the Proceedings of the National Academy of Sciences, Chia-Jung Tsay showed musicians clips from classical music competitions. She asked them to guess the winners. Different musicians were given different kinds of clips: audio recordings… videos with sound… and videos with no sound!

They did best when they saw videos with no sound.

It’s not that the winners were good-looking. It’s that they moved in expressive ways.

This reminds me of how people are willing to pay more for wines whose names are hard to pronounce… or how you can predict who will win an election by watching videos of the candidates—with the sound off.

I think there’s something important about these results. They’re a bit depressing: if our cognitive apparatus is so deeply flawed, maybe we’re doomed. But maybe it’s not so bad. Maybe we just tend to define the point of various activities too narrowly!

We go to a concert, not just to listen to music, but to watch the performer. We drink a wine, not just to taste it in our mouth, but to bask in the sense of being sophisticated. We judge a candidate, not just by what they say, but by how they say it.

You can see the paper here:

• Chia-Jung Tsay, Sight over sound in the judgment of music performance, Proceedings of the National Academy of Sciences, 19 August 2013.

You can hear (or see) a nice summary and discussion here:

• Shankar Vedantam, How to win that music competition? Send a video, National Public Radio, 20 August 2013.