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The Santa Fe Institute and Econophysics: A Possible Genealogy?

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Abstract

For the last three decades, physicists have been moving beyond the boundaries of their discipline, using their methods to study various problems usually instigated by economists. This trend labeled ‘econophysics’ can be seen as a hybrid area of knowledge that exists between economics and physics. Econophysics did not spring from nowhere—the existing literature agrees that econophysics emerged in the 1990s and historical studies on the field mainly deal with what happened during that decade. This article aims at investigating what happened before the 1990s by clarifying the epistemic background that might have paved the way to the emergence of econophysics. This historical exploration led me to highlight the active role played by the Santa Fe Institute by promoting interdisciplinary research on complexity in 1980s. Precisely, by defining three research themes on economic complexity, the SFI defined a research agenda and a way of extending physics\biology to economics. This article offers a possible archeology of econophysics to clarify what could have contributed to the development of a particular episteme in the 1980s easing the advent of econophysics in the 1990s.

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Notes

  1. The twentieth century distant origin of econophysics are often associated with Bachelier (1900) or Majorana (1942)—see Tusset (2018), Dash (2019) or Sharma et al. (2011) on this possible distant origins of econophysics.

  2. Pareto (1897) was one of the first authors to study this relationship when he investigated the repartition of wealth in the population (he noticed that many people seem to have a low wealth whereas few ones have a huge wealth).

  3. Kerr served as assistant director of the FBI (from 1997 to 2001), as director of research for the CIA (from 2001 to 2005) and as Principal Deputy Director of U.S. National Intelligence from October 2007 to January 2009. He is currently a member of the board of Iridium Communications.

  4. The initial name of the SFI was the Rio Grande Institute because the label “Santa Fe Institute” belonged to an existing organization that helped alcoholics and drugs addicted people. When this institution became defunct a few months later, the final name of the research institute was “Santa Fe Institute”.

  5. In the chapter of his memoires, Cowan commented on how he contacted people he met at WHSC.

  6. The study on complexity probably started with May (1972) and his analysis of stability of complex systems.

  7. See Chopard and Droz (2005) or Schiff (2011) for further details about the early history of cellular automata.

  8. See Moore (1962), Myhill (1963) or Hedlund (1969).

  9. This idea that the physical universe is a computer is called “pancomputationalism”, see Müller (2010) or Milokowski (2007) for a presentation of debates related to this view.

  10. Wolfram (1984, p. 186) wrote “Through computers, many complex systems are for the first time becoming amenable to scientific investigation. The revolution associated with the introduction in science may well be a fundamental as, say, the revolution in biology with the introduction of the telescope”. Wolfram (2002) wrote a book in which he discussed the possibility to have a “new kind of science” [the title of his book] “which refers to the idea that the universe, and everything in it, can be explained by simple [computerized] programs” (Mitchell 2009, p. 157). Wolfram attended the first meeting where the Institute was founded and he has always been an active member of this community.

  11. Without a priori segregationist structure (such as ghettos, for example), agents generate a global segregation by behaving in line with their local preferences relating their neighbourhood—See Schelling (1969, 1971, 1978).

  12. According to Walrop (1992), Arthur mainly found his inspiration in his non-academic experience (as demographer for the Population Council in Bangladesh) in order to develop his concept of adaptive system, whereas Holland derived his idea of adaptive system from the studies on what computer scientists called “perceptron” in the 1950s (a perceptron was an algorithm that was able to classify or recognize specific output).

  13. Although Estoup (1916) was the first scientist to discuss this linearity in relation to words.

  14. Interestingly, Zipf observed this linearity in different languages.

  15. Although modern probability theory was properly created in the 1930s, in particular through the works of Kolmogorov, it was not until the 1950s that Kolmogorov’s axioms became the dominant paradigm in this discipline thanks to the popularizing works of Doob (1953) and Feller (1957). These two writers had a major influence on the construction of modern probability theory, particularly through their two main books published in the early 1950s, which proved, on the basis of the framework laid down by Kolmogorov, all results obtained prior to the 1950s, thereby enabling them to be accepted and integrated into the discipline’s theoretical corpus (Shafer and Vovk 2001, p. 60).

  16. See Stanley (1971) for a review of theoretical literature related to the scaling laws in the 1960s.

  17. See Walrop (1992) for further information on the role played by the computer at the SFI.

  18. See Schinckus (2018) for more details on the link between the SFI, econophyscis and biology.

  19. These first publications also aimed to clarify the difference between chaos theory and complexity era (see Mitchell 2009).

  20. Let us mention that Citicorp is still a funding body of the Santa Fe Institute.

  21. The first one was organized few months (September 1987) after the financial support provided by Citicorp. It is worth mentioning that on the 21 contributors, 6 were working in a department of Economics, 12 in a department of physics, 1 in a Food Research Institute, 1 in a department of computer sciences and 1 in a school of Medicine (See Anderson et al. 1988).

  22. Rosser (1999) identified three predecessors of complexity: Cybernetics, Catastrophe theory and Chaos theory, which all proposed a specific framework for dealing with non-linear dynamics. Within the complexity framework, this non-linear dynamics is combined with emergent properties. See Rosser (1999) for further details about these issues and their links with complexity.

  23. It is worth mentioning here that power laws can be used for describing other things than a complex system and that a complex system can also be described through other lenses than a power law—this section simply highlights that the high number of works in statistical econophysics tend to characterize complex system through a power law in line with Bak’s methodological suggestions.

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    Christophe Schinckus

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Schinckus, C. The Santa Fe Institute and Econophysics: A Possible Genealogy?. Found Sci 26, 925–945 (2021). https://doi.org/10.1007/s10699-020-09714-9

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