A Complex, Economic Mess? Take Out Your Checkerboard.

How strongly is one set of outcomes connected to another?  

First, consider T. Rowe Price.  

You may be familiar with them from their TV commercials.  Yes, commercials are meant to sell, and persuasiveness outsells accuracy. Still, the firm claims wisdom that borders on omniscience, including understanding the relationships among:

  • Luminous protein in jellyfish, life expectancy in the US, real estate in Hong Kong, and the optics industry in Germany.  
  • Rice production in India, wheat output in the U.S., the shipping industry in Norway, and the rubber industry in South America. 
  • The oil industry in the North Sea, fishing markets in Japan, marine legislation in the U.S., and food consumption in Italy.

Let me be completely accurate and state that their commercials ask, "How can luminous protein in jellyfish  ...", "How can rice production in India  ...", "How can the oil industry in the North Sea" affect the laundry list of seemingly unrelated concerns mentioned in their commercials.  But they sure leave the viewer thinking that they fully understand these connections (and others don't) by answering their own questions:  "We understand the connections of a complex, global economy."  

(Also: jellyfish researchers won a Nobel prize in 2008 and human cells, injected with jellyfish proteins, lighting up like weak lasers and may, some day, provide new medical treatments.)

Next, consider Rick Perry.

Perry, the governor and presidential candidate, seems not to believe in connections at all.  He claims that the growth in jobs in Texas was his doing, and his alone, without any benefit from connection to the federal government, or from regulation.  ("I'll work every day to make Washington, D.C., as inconsequential in your life as I can.")  

Yet, much of Texas' growth has been due to federal stimulus money, growth in the military, NASA, jobs in local government, additional police, and other public sector hiring.  Oh, Texas also had surprisingly tight regulations in the housing industry, preventing both predatory mortgage practices and excessive home equity loans.  Texas thus took a much less of a "hit" than most other states whose less-regulated citizens are more likely to have lost their homes or be on the verge of foreclosure.

So ... is everything connected in ways we can comprehend?  Is nothing?  Or how do we find a reasonable position in between?

The field of complex systems takes a practical position on these questions.  It suggests that we build models, with relatively simple, comprehensible rules, and then see what results they produce.  One of the earliest, and still highly influential models of this sort is Thomas Schelling's model of segregation    (The magazine The Atlantic gives an easy to follow account.)     

Think of Schelling's work this way:  You have a very large checkerboard on which there are some some empty spaces and some coins -- both pennies and silver dollars.  Pennies are "happy" if at least half of their neighbors directly above, below, and to both sides are also pennies.  Silver dollars want to be "happy," too, by having at least half their neighbors be other silver dollars. Unhappy coins can move to squares on the checkerboard that are unoccupied.  

You'd think that pennies or silver dollars that are happy living with 50% of their neighbors of the same denomination as themselves would end up with diverse, integrated neighborhoods.  Yet, the neighborhoods that results are extremely segregated -- pennies living near each other, and the same with silver dollars.  

In fact, even when each type of coin is happy when only a third of its neighbors are of its own kind, the same rules about happiness and moving to new squares again produce highly segregated neighborhoods.  (For the curious, you can try this out. Using this website, adjust the %-similar-wanted (i.e. "happy" percentage), click "setup," click "go," and watch the results unfold).

Effects like these are often called "emergent":  even though individuals follow rules of one sort (in this case, accepting diversity), their interactions produce an effect that "emerges" in aggregate and is quite different (here, segregation).

The same type of emergent phenomena occur in economics.  Another well known set of experiments by Epstein and Axtell shows that income inequality is very hard to avoid.  In these models, coins are replaced by "agents" who have certain traits that make them more or less likely to get wealthy.  Even when every effort is made to make these agents identical, some get extremely wealth, but most become poor.  

The income inequality comes not from agents being: less capable, less hard working, less shrewd, or anything else that might be offered as a rich-poor explanation.  Instead, advantages that arise by chance compound; so do disadvantages.  Together, these effects create highly skewed income distributions, Lorenz curves, and Gini coefficients that are found in every economy in the world today.

We are in the midst of the Occupy movement.  What lessons can be gleaned from the kinds of models I've been sketching:

  1. Markets and trade are beneficial for promoting overall economic progress; yet as they do so, they also increase the inequality between "haves" and "have nots."  
  2. Different local markets can have different prices for the same goods, with the poor often paying the most.
  3. The easier it is for everyone to interact with each other economically on even terms, the better for reducing poverty.  
  4. Volatile investments (and investments are an opportunity almost exclusively for the wealthy) actually worsen the rich-poor divide.
  5. Small, "bottom up" changes in economic policy and activity might produce surprising (and positive) results. 

Need convincing?  Get out your checkerboard.

About this Entry

This page contains a single entry by Michael Gordon published on November 6, 2011 11:55 AM.

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