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Bifurcations in economic growth model with distributed time delay transformed to ODE


  • Luca Guerrini
  • Adam Krawiec
  • Marek Szydlowski


We consider the model of economic growth with time delayed investment function. Assuming the investment is time distributed we can use the linear chain trick technique to transform delay differential equation system to equivalent system of ordinary differential system (ODE). The time delay parameter is a mean time delay of gamma distribution. We reduce the system with distribution delay to both three and four-dimensional ODEs. We study the Hopf bifurcation in these systems with respect to two parameters: the time delay parameter and the rate of growth parameter. We derive the results from the analytical as well as numerical investigations. From the former we obtain the sufficient criteria on the existence and stability of a limit cycle solution through the Hopf bifurcation. In numerical studies with the Dana and Malgrange investment function we found two Hopf bifurcations with respect to the rate growth parameter and detect the existence of stable long-period cycles in the economy. We find that depending on the time delay and adjustment speed parameters the range of admissible values of the rate of growth parameter breaks down into three intervals. First we have stable focus, then the limit cycle and again the stable solution with two Hopf bifurcations. Such behaviour appears for some middle interval of admissible range of values of the rate of growth parameter.

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  • Luca Guerrini & Adam Krawiec & Marek Szydlowski, 2020. "Bifurcations in economic growth model with distributed time delay transformed to ODE," Papers 2002.05016,
  • Handle: RePEc:arx:papers:2002.05016

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    References listed on IDEAS

    1. Krawiec, Adam & Szydłowski, Marek, 2017. "Economic growth cycles driven by investment delay," Economic Modelling, Elsevier, vol. 67(C), pages 175-183.
    2. Mavi, Can Askan, 2019. "What can catastrophic events tell us about sustainability?," Journal of Mathematical Economics, Elsevier, vol. 83(C), pages 70-83.
    3. Can Askan Mavi, 2019. "What can catastrophic events tell us about sustainability?," Post-Print halshs-02142121, HAL.
    4. A. Krawiec & M. Szydlowski, 1999. "The Kaldor‐Kalecki business cycle model," Annals of Operations Research, Springer, vol. 89(0), pages 89-100, January.
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