Krugman wrote a book inspired by his brief stay at SFI, _The Self Organizing Economy_. I have little to say about that book, although it does make some not totally inaccurate points.

Regarding Chicagoites versus Austrians on the question of axiomatization, I would see it as more of an issue that cuts across both schools rather than one that divides the two from each other, although in general the Chicagoans were/are more favorable to using mathematics in their economic theorizing than were/are the Austrians, who tend to have a downright aversion to same.

So, among Chicagoans, older ones such as Milton Friedman (the “positivist”) tended to eschew axiomatization, perhaps whom TGGP is thinking of, calling himself a “Marshallian” rather than a “Walrasian,” although he was hardly averse to at least some math, and did some very mathematical work for its time when he was an econometrician in his professional youth. More recent Chicagoans, such as Robert Lucas, are much more axiomatic and explicitly “Walrasian” in orientation, although Thomas Sargent became much less so after a visit to SFI in the 90s, which led him to write his _Bounded Rationality in Macroeconomics_, which argues that people actually have adaptive expectations, although learning processes tend to move them towards rational expectations asymptotically.

With regard to the Austrians, the debate over “a priorism” is a central issue in the split between the “Misesians” and the “Hayekians,” although as near as I can tell, Robin Hanson seems to view both schools as ‘popular “nonsense”‘. In any case, it can be argued that Hayek was a proto-complexity SFI type, having published a famous essay back in 1967 on complexity in economics that echoes many themes that later would appear at Santa Fe, and which were already prevalent at such outfits as Brussels (the Prigogine group) and Stuttgart (the Haken group), both of which he contacted and interacted with, eventually becoming a close personal friend of Hermann Haken of Stuttgart, the founder of the synergetics approach.

With regards to Chicagoites vs Austrians, it had seemed to me that the latter (of which I thought Kirzner was one, rather than “other”) were the most axiom-focused, with the former advocating “positivism” in economics so that theories would be evaluated by the correspondence of their predictions with reality rather than believing in results because they follow from true premises.

I have seen economists expressing a low opinion of sociologists in other places. I think it is a tribute to the quality of this site that the same thing has not been displayed here. This is not to say that sociology deserves more respect than it gets, just that this is a classy place that doesn’t really go into dirt-slinging.

Blume, Lawrence, 1995, “The statistical mechanics of best-strategy response revision,” Games and Economic Behavior, 11:111-145.

Brock, William A., 1993, “Pathways to randomness in the economy: Emergent nonlinearity and chaos in economics and finance,” Estudios Economicos, 8:3-55.

Brock, William A. and Cars Hommes, 1997, “Rational routes to randomness,” Econometrica, 65:1059-1095.

Brock, William A. and Steven N. Durlauf, 2001, “Discrete choice with social interactions,” Review of Economic Studies, 68:235-260.

Dawid, Herbert, 1996, Adaptive Learning by Genetic Algorithms: Analytical Results and Applications to Economic Models. Springer-Verlag.

Hommes, Cars H., 2006, “heterogeneous agent models in economics and finance,” in K.L. Judd and L. Tesfatsion (eds.) Handbook of Computational Economics, vol. 2, Amsterdam: Elsevier, pp. 1109-1186

LeBaron, Blake, 2006, “Agent-based computational finance,” same book as Hommes paper above, pp. 187-233.

However, do not think any of these specifically model your Chinese factory example, but plenty to chew on in them. For further references, you can go rooting around some of the papers on my website at
http://cob.jmu.edu/rosserjb
.

I think the social sciences (including economics) may already trending in the direction of adaptive models. I see these tools as a compliment rather than a substitute for current economic methods. They may allow for a much better testbed for conventional (and unconventional) economic thinking.

Coincidentally, I am taking a course in Agent Based Modeling (ABM) this semester with Robert Axtell (who recently came to GMU). It looks to be an exciting class and I am impressed with the applications of ABM to many fields of study. You can read more about ABM here.

I was very interested in the complexity theory paradigm when I first encountered it but I was very disappointed by the lack of followup with evidence-based science, as well as my own discovery that one particular idea was very wrong. I would take Kaufmann’s speculations on spin glasses and economic groups far more seriously if there were evidence that intermediate control levels produced faster innovation (plus some other feature suggestive of spin glass dynamics like backtracking frequency) in some developing industry like, say, Chinese garment manufacturers. But, that idea’s been on the table for, what, over ten years, and, AFAIK, there’s no there there.

In this specific case, I think the economists are right. I tried to extend Kaufmann’s model for the # of different cell types being a spontaneous self-organization due to the number of regulatory genes. In his model every gene affects the exact same number of other genes; I modified it to a stochastic model more like real regulatory networks. Spontaneous order collapsed – it required the mathematical peculiarities of his model. Indeed, it turns out that differentiation occurs via a small number of genes in a cascade of decisions, not via a spontaneous organization at all. I can’t think of any other biological models which came out particularly useful either. I haven’t followed Kaufmann recently but I’d be very surprised if he had any successful predictions in economics (he would have mentioned them), and it’s just quackery to say “Yet there can be little doubt that learning to apply these lessons from biology to technology will usher in a remarkable era of innovation and growth.” when the lessons are weak in biology and nonexistent in economics.