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Learning by doing, spillovers and shakeouts

Author

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  • Jim Jin
  • Juan Perote-Peña
  • Michael Troege

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Abstract

This paper studies industry evolution driven by non strategic learning by doing and spillovers. We characterize a dynamic process of cost and output changes and its effect on welfare and industry profits. The paper gives conditions for shakeouts to occur and analyzes the key factors affecting these conditions. Since shakeouts could lead to a long-run social loss due to higher market concentration, there is a role for a government to play in limiting unnecessary shakeouts. The most effective way to do so is to enhance spillovers. Copyright Springer-Verlag Berlin/Heidelberg 2004

Suggested Citation

  • Jim Jin & Juan Perote-Peña & Michael Troege, 2004. "Learning by doing, spillovers and shakeouts," Journal of Evolutionary Economics, Springer, vol. 14(1), pages 85-98, January.
  • Handle: RePEc:spr:joevec:v:14:y:2004:i:1:p:85-98
    DOI: 10.1007/s00191-003-0177-5
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    Citations

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    Cited by:

    1. André van Stel & Andrew Burke, 2008. "The Entrepreneurial Adjustment Process in Disequilibrium," Scales Research Reports H200809, EIM Business and Policy Research.
    2. Bläsi, Albrecht & Requate, Till, 2005. "Learning-by-Doing with Spillovers in Competitive Industries, Free Entry, and Regulatory Policy," Economics Working Papers 2005-09, Christian-Albrechts-University of Kiel, Department of Economics.
    3. Emanuela Randon & Ahmad Naimzada, 2007. "Dynamics of the non linear learning curve with spillovers in a differentiated oligopoly: effects on industry structure," Journal of Evolutionary Economics, Springer, vol. 17(1), pages 95-106, February.
    4. Amir, Rabah & Halmenschlager, Christine & Jin, Jim, 2011. "R&D-induced industry polarization and shake-outs," International Journal of Industrial Organization, Elsevier, vol. 29(4), pages 386-398, July.
    5. Christopher A. Laincz & Ana Rodrigues, 2006. "The Impact of Cost Reducing R\&D Spillovers on the Ergodic Distribution of Market Structures," Computing in Economics and Finance 2006 307, Society for Computational Economics.

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