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Beyond Replicator Dynamics: Innovation-Selection Dynamics and Optimal Diversity

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  • Karolina Safarzynska

    (Institute for the Environment and Regional Development - Institute for the Environment and Regional Development)

  • Jeroen C.J.M. van den Bergh

Abstract

We propose a new evolutionary approach to model technological change based on an extension of replicator dynamics with recombination and mutation. It gives rise to interactive innovation-selection dynamics. The model allows studying the combined effects of selection and variety generation on evolutionary-economic change. The developed framework describes a population of boundedly rational entrepreneurs who decide each period on the allocation of investments in different production technologies. They tend to invest in below-average cost technologies, just as under replicator dynamics. In addition, they spend a constant fraction of investments, captured by mutation and recombination rates, on alternative technologies and research on recombinant innovation. As opposed to most previous studies, mutation and recombination are here conceptual variables with a concrete behavioral interpretation, namely describing the decision rules (heuristics) of investors. We compare the dynamics of shares of investments in various technologies for three cases: with constant costs of capital, with costs decreasing steadily and exogenously over time, and with costs depending on the level of cumulative investments. For each model version, we examine under which conditions the coexistence of technological options is feasible and optimal in terms of minimising the average cost of investments.

Suggested Citation

  • Karolina Safarzynska & Jeroen C.J.M. van den Bergh, 2011. "Beyond Replicator Dynamics: Innovation-Selection Dynamics and Optimal Diversity," Post-Print hal-00989520, HAL.
  • Handle: RePEc:hal:journl:hal-00989520
    DOI: 10.1016/j.jebo.2011.01.008
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    2. Wood, Aaron D. & Mason, Charles F. & Finnoff, David, 2016. "OPEC, the Seven Sisters, and oil market dominance: An evolutionary game theory and agent-based modeling approach," Journal of Economic Behavior & Organization, Elsevier, vol. 132(PB), pages 66-78.
    3. Sakaki, Shungo, 2022. "An Alternative Approach to Optimal Growth Path by Adaptive Decision-Making based on Budgetary Control Management," SocArXiv 3p9ke, Center for Open Science.
    4. Kenichi Kurita & Shunsuke Managi, 2022. "COVID-19 and Stigma: Evolution of Self-restraint Behavior," Dynamic Games and Applications, Springer, vol. 12(1), pages 168-182, March.
    5. Jacob Rubæk Holm & Esben Sloth Andersen & J. Stanley Metcalfe, 2016. "Confounded, augmented and constrained replicator dynamics," Journal of Evolutionary Economics, Springer, vol. 26(4), pages 803-822, October.
    6. Dan C. Baciu, 2023. "Causal models, creativity, and diversity," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-15, December.
    7. Paolo Zeppini & Koen Frenken & Roland Kupers, 2013. "Threshold models of technological transitions," Working Papers 13-06, Eindhoven Center for Innovation Studies, revised Aug 2013.
    8. Salvador Pueyo, 2014. "Ecological Econophysics for Degrowth," Sustainability, MDPI, vol. 6(6), pages 1-53, May.
    9. Shungo Sakaki, 2023. "The rationality of adaptive decision-making and the feasibility of optimal growth planning," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-12, December.
    10. Safarzyńska, Karolina & Frenken, Koen & van den Bergh, Jeroen C.J.M., 2012. "Evolutionary theorizing and modeling of sustainability transitions," Research Policy, Elsevier, vol. 41(6), pages 1011-1024.
    11. Lee, Won Sang & Han, Eun Jin & Sohn, So Young, 2015. "Predicting the pattern of technology convergence using big-data technology on large-scale triadic patents," Technological Forecasting and Social Change, Elsevier, vol. 100(C), pages 317-329.
    12. Jan-Dirk Schmöcker & Tsuyoshi Hatori & David Watling, 2014. "Dynamic process model of mass effects on travel demand," Transportation, Springer, vol. 41(2), pages 279-304, March.
    13. Lee, Won Sang & Sohn, So Young, 2018. "Effects of standardization on the evolution of information and communications technology," Technological Forecasting and Social Change, Elsevier, vol. 132(C), pages 308-317.

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