When Santa Fe Institute scientists first started working on economics more than thirty years ago, many of their insights, approaches, and tools were considered beyond heterodox. These once-disparaged approaches included network economics, agents of limited rationality, and institutional evolution—all topics that are now increasingly considered mainstream. SFI continues to expand the boundary of our economic understanding by pioneering fields as diverse as collective intelligence and organizational scaling. This volume, edited by W. Brian Arthur, Eric D. Beinhocker, and Allison Stanger, includes panel and talk transcripts from SFI’s 2019 Applied Complexity Network Symposium, with newly written introductions and reflections. Representing both scholarly and practitioner perspectives, this book explores the history and frontiers of complexity economics in a broad-ranging, accessible manner.
William Brian Arthur is an economist credited with developing the modern approach to increasing returns. He has lived and worked in Northern California for many years. He is an authority on economics in relation to complexity theory, technology and financial markets.
I have been a lay student of complexity for some years and I have read Eric Beinhocker's 'The Origin of Wealth' (originally published in 2005) three times. As a graduate in economics, it served to reorient my understand considerably and this new book is a great reminder of complexity's scope and the great work done at the Santa Fe Institute by those like W Brian Arthur, a founder, and many others.
The symposium record is a useful means to catch up on some of the ideas, the progress and questions being asked by complexity researchers. I was particularly interested in the scope for analysing pandemics (covid19 to the fore) as well as economics.
Smart series of lectures/discussions focusing on (well, as the title suggests,) complexity economics - a heterodox branch most definitively known for departing from gen eq. They’re definitely onto something and very likely more right than the nns/mainstream though that is not a very high standard. The economy, after all, is a complex dynamic system, and the higher predictive quality of their models (eci with per cap gdp and INET’s uk covid peak unemployment forecast) has likely bolstered perceived legitimacy.
Main drawback from the book is that it’s compiled of spoken rather than written language, which definitely takes time to adjust to. I would have probably been better off reading beinhocker origin of wealth. Oh well. Really makes me reconsider what I what do study/pursue as a career.
The opening page starts with a proposition that economics is an “imaginary process”. In fact, this book is an imaginary process without the essential facts. Another view, the correct one is that economics is an evolutionary biological process based on the Laws of Physics and Chemistry: specifically Thermodynamics. Here I refer the editors to “What is Life?” By Erwin Schrödinger and secondly, I refer the editors to any of the references on human ethology or human instinctive behaviour.
- most of the talks feel like intellectual candy; quick dopamine hits but don't really dive into enough specifics and feel like they lack substance as a result - the format is tough: it didn't feel like panels translate well to a book, but made me want to go to the SFI - difficult intro to complexity economics if someone didn't come in with some base-level knowledge (not a judgement on the book, just a comment re: who i'd recommend it to)
The panel discussions are fantastic, the physicists are helpful, the programmers are insightful, the finance folks are most valuable, and traditional economics, of course, is worthless
I feel lucky to have come across this book, incredibly influencial in the way that most of us have been taught to look at the world.
Here you have more than 10 points of view on Economics coming from multiple fields of science giving you a full range of view on economics as we know it.
Mixed with amazing irony and humor during the dialogues I will say that this allings with my thought of: "In order to understand something study all the outliers"