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Economic Growth Model with Constant Pace and Dynamic Memory

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  • Valentina V. Tarasova
  • Vasily E. Tarasov

Abstract

The article discusses a generalization of model of economic growth with constant pace, which takes into account the effects of dynamic memory. Memory means that endogenous or exogenous variable at a given time depends not only on their value at that time, but also on their values at previous times. To describe the dynamic memory we use derivatives of non-integer orders. We obtain the solutions of fractional differential equations with derivatives of non-integral order, which describe the dynamics of the output caused by the changes of the net investments and effects of power-law fading memory.

Suggested Citation

  • Valentina V. Tarasova & Vasily E. Tarasov, 2017. "Economic Growth Model with Constant Pace and Dynamic Memory," Papers 1701.06299, arXiv.org, revised Apr 2019.
    • Handle: RePEc:arx:papers:1701.06299
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    File URL: http://arxiv.org/pdf/1701.06299
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    References listed on IDEAS

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    1. Valentina V. Tarasova & Vasily E. Tarasov, 2017. "Logistic map with memory from economic model," Papers 1712.09092, arXiv.org.
    2. Tarasova, Valentina V. & Tarasov, Vasily E., 2017. "Logistic map with memory from economic model," Chaos, Solitons & Fractals, Elsevier, vol. 95(C), pages 84-91.
    3. Vasily E. Tarasov & Valentina V. Tarasova, 2016. "Long and Short Memory in Economics: Fractional-Order Difference and Differentiation," Papers 1612.07903, arXiv.org, revised Aug 2017.
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    Citations

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    Cited by:

    1. Tarasov, Vasily E. & Tarasova, Valentina V., 2018. "Macroeconomic models with long dynamic memory: Fractional calculus approach," Applied Mathematics and Computation, Elsevier, vol. 338(C), pages 466-486.
    2. José A. Tenreiro Machado & Maria Eugénia Mata & António M. Lopes, 2020. "Fractional Dynamics and Pseudo-Phase Space of Country Economic Processes," Mathematics, MDPI, vol. 8(1), pages 1-17, January.
    3. Vasily E. Tarasov, 2019. "Rules for Fractional-Dynamic Generalizations: Difficulties of Constructing Fractional Dynamic Models," Mathematics, MDPI, vol. 7(6), pages 1-50, June.
    4. Vasily E. Tarasov & Svetlana S. Tarasova, 2020. "Fractional Derivatives and Integrals: What Are They Needed For?," Mathematics, MDPI, vol. 8(2), pages 1-22, January.
    5. Hao Ming & JinRong Wang & Michal Fečkan, 2019. "The Application of Fractional Calculus in Chinese Economic Growth Models," Mathematics, MDPI, vol. 7(8), pages 1-6, July.
    6. Ivo Petráš & Ján Terpák, 2019. "Fractional Calculus as a Simple Tool for Modeling and Analysis of Long Memory Process in Industry," Mathematics, MDPI, vol. 7(6), pages 1-9, June.
    7. Tomas Skovranek, 2019. "The Mittag-Leffler Fitting of the Phillips Curve," Mathematics, MDPI, vol. 7(7), pages 1-11, July.
    8. Xu Wang & JinRong Wang & Michal Fečkan, 2020. "BP Neural Network Calculus in Economic Growth Modelling of the Group of Seven," Mathematics, MDPI, vol. 8(1), pages 1-11, January.
    9. Vasily E. Tarasov, 2019. "On History of Mathematical Economics: Application of Fractional Calculus," Mathematics, MDPI, vol. 7(6), pages 1-28, June.
    10. Vasily E. Tarasov, 2020. "Non-Linear Macroeconomic Models of Growth with Memory," Mathematics, MDPI, vol. 8(11), pages 1-22, November.
    11. Andrea Giusti & Francesco Mainardi, 2020. "Advanced Mathematical Methods: Theory and Applications," Mathematics, MDPI, vol. 8(1), pages 1-2, January.

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