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Recurrence Quantification Analysis of Business Cycles

In: Nonlinearities in Economics

Author

Listed:
  • Giuseppe Orlando

    (University of Bari, Department of Economics and Finance
    University of Camerino, School of Sciences and Technology)

  • Giovanna Zimatore

    (eCampus University, Department of Theoretical and Applied Sciences)

Abstract

This chapter is dedicated to describe RQA applications in detecting spatio-temporal recurrent patterns of dynamical regimes of economic time series. Here we investigate the nature of economic dynamics and specifically of business cycles Orlando and Zimatore (Chaos, Solitons Fractals 110:82–94, 2018). Thus, after having devised a suitable model for business cycles such as that discussed in Chap. 16 and in References (Orlando, Math Comput Simul 125:83–98, 2016; 2018, https://doi.org/10.1007/978-3-319-71243-7_6 ), we look for an indicator that could show structural changes in a time series and that might be chaotic (Orlando and Zimatore, Indian Academy of Sciences Conference Series—Proceedings of the Conference on Perspectives in Nonlinear Dynamics—2016, vol. 1, pp. 35–41, Springer, Berlin, 2017, https://doi.org/10.29195/iascs.01.01.0009). More specifically we apply RQA and statistical techniques to real time series to: (1) find common properties if and where they do exist, (2) discover some hidden features of economic dynamics and (3) highlight potential indicators of structural changes in the signal (i.e. precursors of a crash).

Suggested Citation

  • Giuseppe Orlando & Giovanna Zimatore, 2021. "Recurrence Quantification Analysis of Business Cycles," Dynamic Modeling and Econometrics in Economics and Finance, in: Giuseppe Orlando & Alexander N. Pisarchik & Ruedi Stoop (ed.), Nonlinearities in Economics, chapter 0, pages 269-282, Springer.
    • Handle: RePEc:spr:dymchp:978-3-030-70982-2_17
    DOI: 10.1007/978-3-030-70982-2_17
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    Cited by:

    1. is not listed on IDEAS
    2. Zhou, Ling & You, Zhenzhen & Tang, Yun, 2021. "A new chaotic system with nested coexisting multiple attractors and riddled basins," Chaos, Solitons & Fractals, Elsevier, vol. 148(C).
    3. Dezhbakhsh, Hashem & Levy, Daniel, 2022. "Interpolation and shock persistence of prewar U.S. macroeconomic time series: A reconsideration," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 213.
    4. Ata Ozkaya & Omer Altun, 2024. "Domestic and Global Causes for Exchange Rate Volatility: Evidence From Turkey," SAGE Open, , vol. 14(2), pages 21582440241, April.
    5. Ashe, Sinéad & Egan, Paul, 2023. "Examining financial and business cycle interaction using cross recurrence plot analysis," Finance Research Letters, Elsevier, vol. 51(C).
    6. 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.
    7. Mostafa Shabani & Martin Magris & George Tzagkarakis & Juho Kanniainen & Alexandros Iosifidis, 2022. "Predicting the State of Synchronization of Financial Time Series using Cross Recurrence Plots," Papers 2210.14605, arXiv.org, revised Nov 2022.
    8. He, Qian & Yu, Fusheng, 2023. "Trend recurrence analysis and time series classification via trend fuzzy granular recurrence plot method," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    9. Giuseppe Orlando & Fabio Della Rossa, 2019. "An Empirical Test on Harrod’s Open Economy Dynamics," Mathematics, MDPI, vol. 7(6), pages 1-13, June.
    10. Orlando, Giuseppe & Bufalo, Michele, 2022. "Modelling bursts and chaos regularization in credit risk with a deterministic nonlinear model," Finance Research Letters, Elsevier, vol. 47(PA).

    More about this item

    Keywords

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    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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