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Complexity and Empirical Economics

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  • Steven N. Durlauf

Abstract

This article explores the state of interplay between recent efforts to introduce complex systems methods into economics and the understanding of empirical phenomena. The empirical side of economic complexity may be divided into three general branches: historical studies, the identification of power and scaling laws, and analyses of social interactions. I argue that, while providing useful 'stylised facts', none of these empirical approaches has produced compelling evidence that economic contexts exhibit the substantive microstructure or properties of complex systems. This failure reflects inadequate attention to identification problems. Identification analysis should therefore be at the centre of future work on the empirics of complexity. Copyright 2005 Royal Economic Society.

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Bibliographic Info

Article provided by Royal Economic Society in its journal The Economic Journal.

Volume (Year): 115 (2005)
Issue (Month): 504 (06)
Pages: F225-F243

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Handle: RePEc:ecj:econjl:v:115:y:2005:i:504:p:f225-f243

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References

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Citations

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Cited by:
  1. Thomas Lux, 2008. "Stochastic Behavioral Asset Pricing Models and the Stylized Facts," Kiel Working Papers 1426, Kiel Institute for the World Economy.
  2. Cristiano, Antonelli & Scellato, Giuseppe, 2007. "Complexity and Innovation: Social Interactions and Firm Level Total Factor Productivity," Department of Economics and Statistics Cognetti de Martiis LEI & BRICK - Laboratory of Economics of Innovation "Franco Momigliano", Bureau of Research in Innovation, Complexity and Knowledge, Collegio 200709, University of Turin.
  3. Xavier Gabaix, 2009. "Power Laws in Economics and Finance," Annual Review of Economics, Annual Reviews, vol. 1(1), pages 255-294, 05.
  4. Aidt, Toke S. & Leong, Bernard & Saslaw, William C. & Sgroi, Daniel, 2006. "A power-law distribution for tenure lengths of sports managers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 370(2), pages 697-703.
  5. Cristiano Antonelli & Giuseppe Scellato, 2013. "Complexity and technological change: knowledge interactions and firm level total factor productivity," Journal of Evolutionary Economics, Springer, vol. 23(1), pages 77-96, January.
  6. Patrucco, Pier Paolo, 2008. "Complexity and Organizational Change in the Coordination of Technological Knowledge: Evidence from the Automobile Cluster in Turin," Department of Economics and Statistics Cognetti de Martiis LEI & BRICK - Laboratory of Economics of Innovation "Franco Momigliano", Bureau of Research in Innovation, Complexity and Knowledge, Collegio 200808, University of Turin.
  7. Cristiano, Antonelli & Ferraris, Gianluigi, 2009. "Innovation as an Emerging System Property: an Agent Based Model," Department of Economics and Statistics Cognetti de Martiis LEI & BRICK - Laboratory of Economics of Innovation "Franco Momigliano", Bureau of Research in Innovation, Complexity and Knowledge, Collegio 200911, University of Turin.
  8. Robert Marks, 2007. "Validating Simulation Models: A General Framework and Four Applied Examples," Computational Economics, Society for Computational Economics, vol. 30(3), pages 265-290, October.
  9. Robert E. Marks, 2013. "Validation and Functional Complexity," Discussion Papers 2013-30, School of Economics, The University of New South Wales.
  10. Antonelli, Cristiano & Patrucco, Pier Paolo & Rossi, Federica, 2008. "The economics of knowledge interaction and the changing role of universities," Department of Economics and Statistics Cognetti de Martiis LEI & BRICK - Laboratory of Economics of Innovation "Franco Momigliano", Bureau of Research in Innovation, Complexity and Knowledge, Collegio 200802, University of Turin.
  11. Katarzyna Ostasiewicz & Michal H. Tyc & Piotr Goliczewski & Piotr Magnuszewski & Andrzej Radosz & Jan Sendzimir, 2006. "Integrating economic and psychological insights in binary choice models with social interactions," Papers physics/0609170, arXiv.org.
  12. Kieran Donaghy, 2011. "Models of travel demand with endogenous preference change and heterogeneous agents," Journal of Geographical Systems, Springer, vol. 13(1), pages 17-30, March.

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