A Quick Take on Complexity Economics and Eric Beinhocker’s The Origin of Wealth

The Origin of Wealth by Eric Beinhocker presents a thorough explanation of Complexity Economics and how it compares to Traditional Economics. Basically, Complexity Economics takes the view that the economy is a complex adaptive system that does not reach equilibrium states but constantly keeps changing to allocate resources to society. Given that market equilibriums are an integral part of Traditional Economics, the idea that equilibriums are not actually reached in real world economies is a bold and controversial claim.

Although Complexity Economics has some ideas that are more in line with Traditional Economics, it largely offers new ways to think about the drivers of the global economy, including interesting views on other core economic topics like rationality. Here are 4 key takeaways from Beinhocker’s The Origin of Wealth.

Key takeaway #1 — Assuming perfect rationality is problematic

There’s a big problem with one of the central assumptions of Traditional Economics. In Traditional Economics, we assume that people are perfectly rational in our models, but increasingly we know that this isn’t true. After decades of Nobel Prize-winning work in behavioral economics, Daniel Kahneman published Thinking, Fast and Slow which provides countless examples of how humans are affected by their biases, their misunderstandings of probabilities, the availability of information, the sunk cost fallacy, and loss aversion.

• “One assumption that got the scientists particularly exercised was what economists refer to as perfect rationality. Traditional Economics simplifies human behavior by assuming that people know everything possible about the future and crunch all that information through the incredibly complex calculations to make sure basic decisions as whether to buy a pint of milk.” (p. 47)
• “Behavioral economists such as Herbert Simon, Daniel Kahneman and Amos Tversky have shown that while people are intelligent in their decision making, they are intelligent in ways very different from the picture presented by Traditional Economics.” (p. 52)
• “In 1985, a mathematician named Alain Lewis used some sophisticated techniques from the theory of computation to prove that no one, not even the smartest arbitrageur, could actually make the calculations described by perfect rationality.” (p. 123)

Key takeaway #2—We can understand the economy’s inputs but predicting its exact movements or outputs is futile

According to Beinhocker, the economy is too complicated to predict with precision, but we can get a general understanding of how things are going. Although there is value in knowing if the economy is trending up or down, Beinhocker’s focus is more on what is inputed into the economy rather than trying to predict how the economy will perform. The argument goes that if we can understand the central constructs of the economy and what makes it tick, then we can design the inputs* such as our institutions to produce a higher level of economic output.

• “The economy is too complex, too nonlinear, too dynamic, and too sensitive to the twists and turns of chance to be amenable to prediction over anything but the very shortest of terms.” (p. 323)
• “The message of Complexity Economics is that evolution may indeed be cleverer than we are, but rather than outsmart it, we can understand it and harness its power to serve human purposes.” (p. 324)

Key takeaway #3—The economy is more like a biological system rather than a physical system

Free market economies are constantly adapting to optimize resource allocation for society. In short, as old business plans “wear out”, new business plans are tested in the market and the ones that are successful are amplified to create wealth for society. According to Beinhocker, the process of testing and amplifying new business plans never ends as what is economically “fit” one decade may not be a net value creator in the next decade.

• “We will see that variation occurs as people continually experiment with, tinker with, and invent new business strategies and organizational designs. Selection works at multiple levels in the economy, causing some Business Plans to succeed and others to fail. Likewise, replication occurs in economic systems as successful designs are rewarded with more resources and are widely copied.” (p. 238)
• “In each space, evolution is at work, churning through possible designs, finding and amplifying ones that work, discarding those that don’t, and thereby creating the order that we see in our technological, social, and economic worlds.” (p. 239)
• “Thus, the evolutionary process never stops, as modules come and go and businesses rise and fall adapting to the needs of the marketplace.” (p. 293)

Key takeaway #4 — Free markets are still best

Traditional Economics strongly supports markets as the mechanism for scarce resource allocation, because they create equilibriums which optimize wealth for society. We know that Complexity Economics doesn’t really agree with the concept of equilibriums, but it still ardently supports free markets for a different reason. According to Beinhocker, “markets provide incentives for the deductive-tinkering process,” (p. 294) and allow for the economy to figure out society’s needs iteratively rather than through a deterministic, top-down approach.

• “Markets win over command and control, not because of their efficiency at resource allocation in equilibrium, but because of their effectiveness at innovation in disequilibrium.” (p. 294)

Parting words

Complexity Economics is still a fairly young field that has yet to gain mainstream adoption. As someone who studied economics in college (just a few years ago), Beinhocker’s book served as a great lens to evaluate the frameworks that I was taught and consider that there might be theories that better explain the massively complex workings of today’s global economy. After all, Traditional Economics, like other academic fields, will have to evolve at some point. If I had to guess, it will be in the direction of Complexity Economics.

Notes

*The inputs to the economy according to Complexity Economics are:

• Physical technologies
• Social techonolgies
• Business plans
• Management teams