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On Market Economies: How Controllable Constructs Become Complex

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  • Dominique, C-Rene

Abstract

Since Lėon Walras neoclassical economists hold an inalterable belief in a unique and stable equilibrium for the economic system, which remains to this day unobservable. Yet that belief is the corner stone of other theories such as the ‘Efficient Market Hypothesis’ as well as the philosophy of neo-liberalism, whose outcomes are shown by recent events to be flawed. A modern market economy is indeed a nonlinear controllable construct, but this paper uses the affine nonlinear feedback H∞-control to show that the ‘data requirement’ precludes all attempts at the empirical verification of the existence of a stable equilibrium. In a complex nonlinear deterministic systems, equilibria, whether multiple or deterministically chaotic, depends on their parameter values and uncertainties. The best approach suggested is to focus on endurable patterns thrown-off by such systems.

Suggested Citation

  • Dominique, C-Rene, 2014. "On Market Economies: How Controllable Constructs Become Complex," MPRA Paper 56579, University Library of Munich, Germany, revised 10 Jun 2014.
    • Handle: RePEc:pra:mprapa:56579
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    References listed on IDEAS

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    1. Alexandre Scheinkman, Jose, 1976. "On optimal steady states of n-sector growth models when utility is discounted," Journal of Economic Theory, Elsevier, vol. 12(1), pages 11-30, February.
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    4. Dominique, C-Rene, 2008. "Walrasian Solutions Without Utility Functions," MPRA Paper 8906, University Library of Munich, Germany, revised 2008.
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    More about this item

    Keywords

    Equilibrium; nonlinearity; controllability; nonlinear-feedback; H∞-control; data requirement; complexity.;
    All these keywords.

    JEL classification:

    • C0 - Mathematical and Quantitative Methods - - General
    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models

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