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Complexity and emperical economics

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  • Durlauf,S.N.

    (University of Wisconsin-Madison, Social Systems Research Institute)

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.

(This abstract was borrowed from another version of this item.)

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Bibliographic Info

Paper provided by Wisconsin Madison - Social Systems in its series Working papers with number 2.

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Date of creation: 2003
Date of revision:
Handle: RePEc:att:wimass:20032

Contact details of provider:
Postal: UNIVERSITY OF WISCONSIN MADISON, SOCIAL SYSTEMS RESEARCH INSTITUTE(S.S.R.I.), MADISON WISCONSIN 53706 U.S.A.

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Keywords: empirical economics; complex systems;

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References

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Citations

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Cited by:
  1. 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.
  2. Vallino.Elena, 2013. "Why droughts started to turn into famines in the Late Victorian periods? A complex system approach," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201317, University of Turin.
  3. Consoli, Davide & Patrucco, Pier Paolo, 2013. "Complexity and the Coordination of Technological Knowledge: The Case of Innovation Platforms," 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 201317, University of Turin.
  4. Xavier Gabaix, 2008. "Power Laws in Economics and Finance," NBER Working Papers 14299, National Bureau of Economic Research, Inc.
  5. Thomas Lux, 2008. "Stochastic Behavioral Asset Pricing Models and the Stylized Facts," Kiel Working Papers 1426, Kiel Institute for the World Economy.
  6. Antonelli Cristiano & Scellato Giuseppe, 2011. "Complexity and Technological Change: Knowledge 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 201102, University of Turin.
  7. 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.
  8. 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.
  9. Robert E. Marks, 2013. "Validation and Functional Complexity," Discussion Papers 2013-30, School of Economics, The University of New South Wales.
  10. 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.
  11. 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.
  12. 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.
  13. Gräbner, Claudius, 2014. "Agent-Based Computational Models - A Formal Heuristic for Institutionalist Pattern Modelling?," MPRA Paper 56415, University Library of Munich, Germany.
  14. 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.
  15. 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.

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