Lynne Kiesling
Mark Thoma draws our attention to a recent Martin Wolf column in the FT, discussing complexity and evolution as a methodological framework for economic modeling and analysis.
[M]ost [economists] must also know that the economy is not characterised by perfect foresight and equilibrium, but by trial and error and evolution. That was the intuition of the Austrian economists, Joseph Schumpeter and Friedrich Hayek. But this vision has had next to no influence in the discipline itself.
This observation is a lead-in to discussing Eric Beinhocker’s The Origin of Wealth: Evolution, Complexity, and the Radical Remaking of Economics. Mark’s post has useful excerpts from Fox’s column.
I have not yet read Beinhocker’s book, but I think his point about economic methodology is important. Models premised on perfect foresight and completely knowable information sets, and focused on outcomes instead of processes, are going to do a bad job of helping us to understand economic behavior and phenomena that are complicated, like growth, innovation, and entrepreneurship. I also contend that they do a bad job of helping us to design regulatory institutions that can adapt to changing and unknown conditions. That’s why I pay attention to complexity science, because I think it can help us build more useful models of institutional change.