The basis of David Colander and Roland Kupers’s book Complexity and the Art of Public Policy: Solving Society’s Problems from the Bottom Up is that the economy is a complex system and it should be examined through a complexity frame. A complex system comprises many parts that interact in a nonlinear manner. You can’t simply add the parts. While you might expect this would lead to chaos, emergent behaviour in complex systems can lead to what appears to be an order state.

Links this week: Lectures on Human Capital by Gary Becker. (HT: Eric Crampton) We learn more from success than failure. A bit semantic, and where is this government agency with a learn-from-failure culture? But worth the read. The 2014 Nanny State awards. Robert Sapolsky on the Christmas truce of 1914. People like gifts that they want. Greater contact between racial groups increases bias?

Links this week: “I worry that most smart people have not learned that a list of dozens of studies, several meta-analyses, hundreds of experts, and expert surveys showing almost all academics support your thesis – can still be bullshit.” Awesome. I have only just realised that Gary Klein blogs at Psychology Today. A relatively recent post - The Insight Test. Bad statistics - same sex marriage edition.

Another clip from David Colander and Roland Kupers’s Complexity and the Art of Public Policy: Solving Society’s Problems from the Bottom Up - a nice description of how two often confused terms, complexity and chaos, differ and interrelate: Chaos theory is a field of applied mathematics whose roots date back to the nineteenth century, to French mathematician Henri Poincaré. Poincaré was a prolific scientist and philosopher who contributed to an extraordinary range of disciplines; among his many accomplishments is Poincaré’s conjecture that deals with a famous problem in physics first formulated by Newton in the eighteenth century: the three body problem.

Following my post last week on the need for more complicated models in economics, a new paper in PLOS Biology argues for the importance of mathematical models in showing ‘proof of concept’ (HT: Santa Fe Institute News). The authors write: Proof-of-concept models, used in many fields, test the validity of verbal chains of logic by laying out the specific assumptions mathematically. The results that follow from these assumptions emerge through the principles of mathematics, which reduces the possibility of logical errors at this step of the process.

Links this week: Why progress has ground to a halt. Development professionals are biased like their subjects. Are schools failing? Cato Unbound - a libertarian perspective on extraterrestrial life.

In the day job, for most of this year I was seconded onto the Australian Government’s Financial System Inquiry. The Inquiry was established to provide a broad review of the Australian financial system, looking at system stability, competition, consumer protection, technological change and whether the system was serving the needs of users. The Inquiry’s final report is now out and available here. It has received a lot of press here - I think my favourite article so far is this one (if you hit the paywall, google “David Murray has gone rogue” and try that link).

I am half way through David Colander and Roland Kupers’s book Complexity and the Art of Public Policy: Solving Society’s Problems from the Bottom Up. Overall, it’s a good book, although the authors are somewhat slow to get to the point and there are plenty of lines that perplex or annoy (Arnold Kling seemed to have a similar reaction). I’ll review later, but one interesting line in the book is that under a complexity approach, you may need more complicated mathematical models than used in neoclassical economics.

Links this week: The case against early cancer detection. The charts on mammogram and PSA testing effectiveness are just as Gerd Gigerenzer would have us present the statistics. The case for business experimentation. Airline inequality. While arguments continue about the predictive power of genetic testing, entrepreneurs are already using it. HT: Steve Hsu However, there are still plenty of average ‘gene for’ studies being produced.

Biologists are usually among the first to tell me that economists rely on unrealistic assumptions about human decision making. They laugh at the idea that people are rational optimisers who care only about maximising consumption. Some of the points are undoubtedly correct. Humans do not care primarily about consumption. They seek mates or other objectives related to their fitness. And of course, humans do not solve complex optimisation problems with constraints in their heads.