D. Murali

Humanity's most complex creation is the economy, according to Eric D. Beinhocker, author of The Origin of Wealth, who takes us along as he retraces the journey `from a state of nature to the stunning self-organised complexity of the modern global economy'. D. MURALI recommends the book as a fit read to accelerate your evolutionary process.

A fat book on economics may be the last thing you'd like to lug around during a weekend, but this one is different: The Origin of Wealth, by Eric D. Beinhocker, from Harvard Business School Press (www.HBSPress.org). Because it talks about `the complexity economics revolution' which has clues to `the deepest mysteries in economics'.

Chapter 1 begins with the question, `How is wealth created?' and seeks answers `not just from the work of economists, but also from biologists, physicists, evolutionary theorists, computer scientists, anthropologists, psychologists and cognitive scientists.'

Humanity's most complex creation, according to the author, is the economy. Though there are CEOs, governments and organisations managing their own specific domains, `no one is really in charge' of the $36.5-trillion global economy, points out Beinhocker.

To know how we have travelled `from a state of nature to the stunning self-organised complexity of the modern global economy,' the author studies `2.5 million years of economic history', beginning with the Homo habilis, who use a `relatively large brain' to make crude stone tools.

It was about 35,000 years ago that trading between groups should have happened, postulates the book, citing archaeological evidence such as "burial-site tools made from non-local materials, seashell jewellery found with non-coastal tribes, and patterns suggesting trading routes."

With trade came specialisation and `a dramatic increase in the variety of tools and artefacts'. Cooperative trading between non-relatives is a uniquely human activity, says the author, quoting the work of Paul Seabright of the University of Toulouse.

Bending to update theories

Travel through a chapter on traditional economics, that is, `the set of ideas that have dominated economic theory for the past century'. Names that find ample mention here are Adam Smith, Leon Walras, Vilfredo Pareto, Alfred Marshall, Paul Samuelson, Kenneth Arrow, Gerard Debreu, Joseph Schumpeter, Robert Solow and Paul Romer. Great economists of the twentieth century were the master-builders of a gothic cathedral called general equilibrium theory, reads an analogy of Werner Hildenbrand that the author mentions. Only, `the cathedral was built on very shaky ground,' he declares.

In the `critique' that follows, Beinhocker narrates how at a cross-disciplinary workshop on economics, physical scientists were shocked that `economics was a throwback to another era'.

For the physicists, much of what they saw in economics had a `vintage' felling to it!

"It looked to them as if economics had been locked in its own intellectual embargo, out of touch with several decades of scientific progress, but meanwhile ingeniously bending, stretching, and updating its theories to keep them running." Economists' maths was `a blast from the past' and their models used `simplifying assumptions'.

The `new eyes'

Part II, titled `complexity economics', begins with this quote of Marcel Proust: "The real voyage of discovery consists, not in seeking new landscapes, but in having new eyes."

The `new eyes' that the book brings in is `complexity economics', which the author describes more as a research program than a single, synthesised theory, with many grey areas.

However, what distinguishes it from the traditional economics are five `big ideas', viz. dynamics, agents, networks, emergence, and evolution.

The dynamics are open, non-linear and far from equilibrium, rather than `closed, static, linear systems in equilibrium' that traditional economics hinges on.

Agents are modelled not collectively, but individually; and they use inductive rules of thumb to make decisions, and not deductive calculations. Importantly, agents aren't assumed to be making no errors and having no biases; and they `learn and adapt over time'.

Be prepared to see graphs that resemble baby-scrawls in a section that discusses `the science of nonpachydermology'.

Non-linear systems are very common in nature, explains the author. "They show up in phenomena ranging from turbulence over an aircraft wing, to weather, lasers, and the firing of synapses in your brain."

It was Henri Poincare, a French mathematician, who studied chaos. However, "The study of non-linear systems languished for seventy years until the 1960s and 1970s... non-linear systems are now a bread-and-butter topic for physicists."

The economy is complex but not chaotic, says Beinhocker, because "truly chaotic systems tend to have relatively few variables and few degrees of freedom."

The economy has "a massive number of stocks and flows dynamically connected in an elaborate web of positive and negative feedback relationships".

The author delves into `mind games' when talking about agents. He argues that the Homo economicus (the economic man) of traditional economics is "a bad map that both ignores important details about how real human beings behave and at the same time adds critical features that real humans do not have."

Mindgames

You aren't Spock (the Vulcan in the Star Trek series) who could "remember the pi to 50 decimal places and perform incredibly complex calculations, all while under enemy phaser-fire and without the slightest trace of emotion," reminds Beinhocker.

Traditional economics would demand that you do intricate number-crunching before buying tomatoes, beginning with knowing exactly what your budget is for the vegetable.

"To calculate this budget, you must have fully formed expectations of your future earnings over your entire lifetime and have optimised your current budget on the basis of that knowledge... You might hold back on those tomatoes because you know that the money spent on them could be better spent in your retirement."

Thankfully, we don't behave that way; instead, we use inductive rationality, points out the author. "It goes like this: `Hmmm... tomatoes. They look nice and fresh. I kinda feel like salad tonight. Price looks okay.' And into the shopping basket they go... "

An important insight in the chapter on networks is that, as an organisation grows, "its degrees of possibility increase exponentially while its degrees of freedom collapse exponentially."

Which explains why big corporates may find it difficult to adapt to a changing market. Similarly, in software, any enhancement or bug fix in a complex program can introduce five new bugs! In architecture too you can see the tension between interdependence and adaptability; moving a wall just one foot can have `knock-on effects that send the project's cost sky-high.'

Puzzle of patterns

The chapter on the fourth `big idea', emergence, is on the puzzle of patterns. An enduring puzzle is of stock market volatility. To disentangle this, the author takes the help of `power laws', which explain a distribution by an equation with an exponent, or power.

"Power laws have been discovered in a wide variety of phenomena, including the size of biological extinction events, the intensity of solar flares, the ranking of cities by size, traffic jams, cotton prices, the number of fatalities in warfare, and even the distribution of sex partners in social networks."

It's a jungle out there, cautions the `evolution' chapter. Economy is a design without a designer, notes Beinhocker. To him, pioneers down this road are Richard Nelson and Sidney Winter who wrote Evolutionary Theory of Economic Change. Other names that find mention are: John Holland's Adaptation in Natural and Artificial Systems; Richard Dawkin's Selfish Gene; John Maynard Smith's Evolution and the Theory of Games; and Stuart Kauffman's Origins of Order. Important work continues today, one learns.

Part III, on how evolution creates wealth, has a chapter titled `a new definition of wealth'. In it, the author draws inputs from Georgescu-Roegen, and proposes that a pattern of matter, energy, and or information has economic value if three conditions are jointly met, viz. irreversibility, entropy, and fitness.

Both economic and biological wealth are "systems of low entropy, patterns of order that evolved over time under the constraint of fitness functions," explains Beinhocker.

"Evolution is a knowledge-creation machine, a learning algorithm." For, wealth is `fit order', and since order is the same thing as information in physics, we can call wealth `fit information' or `knowledge', he proposes.

Fit read for the Saturday afternoon, to accelerate your evolutionary process!

(http://BookPeek.blogspot.com)

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