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Simulating heterogeneous corporate dynamics via the Rulkov map

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  • Orlando, Giuseppe

Abstract

This work deals with corporate dynamics as they emerge from mutual interaction between firms competing on the market. As it is commonly observed, corporate dynamics may oscillate between periods of fierce competition and calmer periods when companies settle in their niche. This is much like mutual synchronization and chaos regularization of bursts in a group of chaotically bursting cells modelled by the Rulkov map. We find that our framework can accommodate dynamic changes between multiple equilibria, model skewness, and idiosyncrasy even in the case of homogeneous firms. These features allow the link with empirical findings in labour and industrial economics. This paper supports the idea that nature is governed by simple laws from physics to engineering, from biology to economics, etc. For this reason, a low-dimensional deterministic model like the Rulkov map may be applied to economics and game theory for describing corporate dynamics.

Suggested Citation

  • Orlando, Giuseppe, 2022. "Simulating heterogeneous corporate dynamics via the Rulkov map," Structural Change and Economic Dynamics, Elsevier, vol. 61(C), pages 32-42.
    • Handle: RePEc:eee:streco:v:61:y:2022:i:c:p:32-42
    DOI: 10.1016/j.strueco.2022.02.003
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    Cited by:

    1. Willi Semmler & Fabio Della Rossa & Giuseppe Orlando & Gabriel R. Padro Rosario & Levent Kockesen, 2023. "Endogenous Economic Resilience, Loss of Resilience, Persistent Cycles, Multiple Attractors, and Disruptive Contractions," Working Papers 2309, New School for Social Research, Department of Economics.

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    More about this item

    Keywords

    Rulkov map; Corporate dynamics; Duopoly; Chaos; Nash equilibrium;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling

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