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Journal of Evolutionary Economics

, Volume 23, Issue 1, pp 1–15 | Cite as

A new formal approach to evolutionary processes in socioeconomic systems

  • Rodrick Wallace
Regular Article

Abstract

Generalized Darwinian evolutionary theory has emerged as central to the description of economic process (e.g., Aldrich et al., J Evol Econ 18:577–596, 2008). Just as Darwinian principles provide necessary, but not sufficient, conditions for understanding the dynamics of social entities, so too the asymptotic limit theorems of information theory instantiate another set of necessary conditions that constrain socioeconomic evolution. These restrictions can be formulated as a statistics-like analytic toolbox for the study of empirical data that is consistent with generalized Darwinism, but escapes the intellectual straightjacket of replicator dynamics. The formalism is a coevolutionary theory in which punctuated convergence to temporary quasi-equilibira is inherently nonequilibrium, involving highly dynamic ‘languages’ rather than system stable points.

Keywords

Cognition Coevolution Competition Information theory Interaction Punctuated equilibrium Selection 

JEL Classification

B52 C61 D02 L10 P50 Z10 

Notes

Acknowledgement

The author thanks a reviewer for remarks useful in revision.

References

  1. Adami C, Cerf N (2000) Physical complexity of symbolic sequences. Physica D 137:62–69CrossRefGoogle Scholar
  2. Adami C, Ofria C, T. Collier T (2000) Evolution of biological complexity. Proc Natl Acad Sci 97:4463–4468CrossRefGoogle Scholar
  3. Aldrich H, Hodgson G, Hull D, Knudsen T, Mokyr J, Vanberg V (2008) In defense of generalized Darwinism. J Evol Econ 18:577–596CrossRefGoogle Scholar
  4. Ash R (1990) Information theory. Dover, New YorkGoogle Scholar
  5. Atlan H, Cohen I (1998) Immune information, self-organization and meaning. Int Immunol 10:711–717CrossRefGoogle Scholar
  6. Beck C, Schlogl F (1993) Thermodynamics of chaotic systems: an introduction. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  7. Beinhocker E (2011) Evolution as computation: integrating self-organization with generalized Darwinism. J Evol Econ 7. doi: 10.1017/S1744137411000257 Google Scholar
  8. Champagnat N, Ferriere R, Meleard S (2006) Unifying evolutionary dynamics: from individual stochastic processes to macroscopic models. Theor Popul Biol 69:297–321CrossRefGoogle Scholar
  9. Cover T, Thomas J (1991) Elements of information theory. Wiley, New YorkCrossRefGoogle Scholar
  10. Dembo A, Zeitouni O (1998) Large deviations and applications, 2nd edn. Springer, New YorkCrossRefGoogle Scholar
  11. Diekmann U, Law R (1996) The dynamical theory of coevolution: a derivation from stochastic ecological processes. J Math Biol 34:579–612CrossRefGoogle Scholar
  12. Eldredge N, Gould S (1972) Punctuated equilibrium: an alternative to phyletic gradualism. In Schopf T (ed) Models in paleobiology. Freeman, Cooper and Co., San Francisco, pp 82–115Google Scholar
  13. Feynman R (2000) Lectures on computation. Westview, New YorkGoogle Scholar
  14. Fodor J, Piatelli-Palmarini M (2010) What Darwin got wrong. Farrar, Straus, and Giroux, New YorkGoogle Scholar
  15. Glazebrook JF, Wallace R (2009) Rate distortion manifolds as models for cognitive information. Informatica 33:309–345Google Scholar
  16. Gould S (2002) The structure of evolutionary theory. Harvard University Press, CambridgeGoogle Scholar
  17. Haldane A, May R (2011) Systemic risk in banking ecosystems. Nature 469:351–355CrossRefGoogle Scholar
  18. Hodgson G, Knudsen T (2006a) Why we need a generalized Darwinism: and why a generalized Darwinism is not enough. J Econ Behav Organ 61:1–19CrossRefGoogle Scholar
  19. Hodgson G, Knudsen T (2006b) Dismantling Lamarckism: why descriptions of socioeconomic evolution as Lamarckian are misleading. J Evol Econ 16:343–366CrossRefGoogle Scholar
  20. Hodgson G, Knudsen T (2010) Darwin’s conjecture: the search for general principles of social and economic evolution. University of Chicago Press, ChicagoGoogle Scholar
  21. Holling C (1992) Cross-scale morphology, geometry and dynamics of ecosystems. Ecol Monogr 62:447–502CrossRefGoogle Scholar
  22. Johnson N (2011) Proposing policy by analogy is risky. Nature 469:302–303CrossRefGoogle Scholar
  23. Khinchin A (1957) Mathematical foundations of information theory. Dover, New YorkGoogle Scholar
  24. Levin S (1989) Ecology in theory and application. In Levin S, Hallam T, Gross L (eds) Applied mathematical ecology. Biomathematics texts, vol 18. Springer, New YorkCrossRefGoogle Scholar
  25. Lewontin R (2010) Not so natural selection. New York Review of Books. http://www.nybooks.com/articles/archives/2010/may/27/not-so-natural-selection/
  26. Ofria C, Adami C, Collier T (2003) Selective pressures on genomes in molecular evolution. J Theor Biol 222:62–69CrossRefGoogle Scholar
  27. Pelikan P (2010) Evolutionary developmental economics: how to generalize Darwinism fruitfully to help comprehend economic change. J Evol Econ 21:341–366. doi: 10.1007/s00191-010-0178-0 CrossRefGoogle Scholar
  28. Pielou E (1977) Mathematical ecology. Wiley, New YorkGoogle Scholar
  29. Stoelhorst J (2005) The naturalist view of universal Darwinism: an application of evolutionary theory to the firm. In Finch J, Orillard M (eds) Complexity and the economy: implications for economic policy. Cheltenham, UK, pp 127–147Google Scholar
  30. Stoelhorst J (2008) The explanatory logic and ontological commitments of generalized Darwinism. J Econ Method 15:343–363CrossRefGoogle Scholar
  31. Wallace R (2005) Consciousness: a mathematical treatment of the global neuronal workspace model. Springer, New YorkGoogle Scholar
  32. Wallace R (2010) Expanding the modern synthesis. C R Biol 333:701–709CrossRefGoogle Scholar
  33. Wallace R, Wallace RG (2008a) On the spectrum of prebiotic chemical systems: an information-theoretic treatment of Eigen’s Paradox. Orig Life Evol Biosph 38:419–455CrossRefGoogle Scholar
  34. Wallace R, Wallace D (2008b) Punctuated equilibrium in statistical models of generalized coevolutionary resilience. Trans Comput Sys Biol IX, LNBI 5121:23–85CrossRefGoogle Scholar
  35. Wallace R, Wallace D (2009) Code, context and epigenetic catalysis in gene expression. Trans Comput Sys Biol XI, LNBI 5750:283–334CrossRefGoogle Scholar
  36. Wallace R, Wallace D, Wallace RG (2009) Farming human pathogens: ecological resilience and evolutionary process. Springer, New YorkGoogle Scholar
  37. Wymer C (1997) Structural nonlinear continuous-time models in econometrics. Macroecon Dyn 1:518–548CrossRefGoogle Scholar
  38. Zhu R, Rebirio A, Salahub D, Kaufmann S (2007) Studying genetic regulatory networks at the molecular level: delayed reaction stochastic models. J Theor Biol 246:725–745CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  1. 1.Division of EpidemiologyThe New York State Psychiatric InstituteNew YorkUSA

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