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The Twin Peaks in National Income. Parametric and Nonparametric Estimates

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Listed:
  • Uwe Cantner
  • Bernd Ebersberger
  • Horst Hanusch
  • Jens J. Krüger
  • Andreas Pyka

Abstract

The twin-peaked (bimodal) shape of the distribution of per capita income is an intensively discussed topic in economic growth research. The data show that the world income distribution starts with an unimodal structure in 1960 and evolves subsequently towards a bimodal or twin-peaked structure. This empirical result can be replicated by a theoretically based synergetic model using the master equation approach. The present paper extends this discussion by trying to find direct empirical evidence for the mechanism of the theoretical model. We empirically determine the transition rates used in the synergetic approach by applying alternatively nls to a priori specified functional forms and genetic programming in order to determine the parameters simultaneously with the functional forms. Plugging the so determined transition rates into the synergetic model leads in both cases to the emergence of the bimodal distribution which, however, appears to be only a transitory phenomenon.

Suggested Citation

  • Uwe Cantner & Bernd Ebersberger & Horst Hanusch & Jens J. Krüger & Andreas Pyka, 2004. "The Twin Peaks in National Income. Parametric and Nonparametric Estimates," Revue économique, Presses de Sciences-Po, vol. 55(6), pages 1127-1144.
  • Handle: RePEc:cai:recosp:reco_556_1127
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    References listed on IDEAS

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    Cited by:

    1. Petra Ahrweiler & Mark Keane, 2013. "Innovation networks," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 12(1), pages 73-90, June.
    2. Pier Saviotti & Andreas Pyka, 2011. "Generalized barriers to entry and economic development," Journal of Evolutionary Economics, Springer, vol. 21(1), pages 29-52, February.
    3. Jens K. Perret, 2010. "A Core-Periphery Pattern in Russia – Twin Peaks or a Rat’s Tail," EIIW Discussion paper disbei178, Universitätsbibliothek Wuppertal, University Library.
    4. Petra Ahrweiler, 2017. "Agent-based simulation for science, technology, and innovation policy," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(1), pages 391-415, January.

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