IDEAS home Printed from https://ideas.repec.org/h/spr/dymchp/978-3-030-70982-2_17.html
   My bibliography  Save this book chapter

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
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Levy, Daniel & Chen, Haiwei, 1994. "Estimates of the Aggregate Quarterly Capital Stock for the Post-War U.S. Economy," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 40(3), pages 317-349.
    2. Otto Eckstein & Allen Sinai, 1986. "The Mechanisms of the Business Cycle in the Postwar Era," NBER Chapters, in: The American Business Cycle: Continuity and Change, pages 39-122, National Bureau of Economic Research, Inc.
    3. Addo, Peter Martey & Billio, Monica & Guégan, Dominique, 2013. "Nonlinear dynamics and recurrence plots for detecting financial crisis," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 416-435.
    4. Levy, Daniel & Chen, Haiwei, 1994. "Estimates of the Aggregate Quarterly Capital Stock for the Post-war U.S. Economy," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 40(3), pages 317-349, September.
    5. D. Colander & H. Follmer & A. Haas & M. Goldberg & K. Juselius & A. Kirman & T. Lux & B. Sloth, 2010. "The Financial Crisis and the Systemic Failure of Academic Economics," Voprosy Ekonomiki, NP Voprosy Ekonomiki, issue 6.
    6. Karagianni Stella & Kyrtsou Catherine, 2011. "Analysing the Dynamics between U.S. Inflation and Dow Jones Index Using Non-Linear Methods," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(2), pages 1-25, March.
    7. Dezhbakhsh, Hashem & Levy, Daniel, 1994. "Periodic properties of interpolated time series," Economics Letters, Elsevier, vol. 44(3), pages 221-228.
    8. A. N. Gorban & E. V. Smirnova & T. A. Tyukina, 2009. "Correlations, Risk and Crisis: From Physiology to Finance," Papers 0905.0129, arXiv.org, revised Aug 2010.
    9. Lucas, Robert E, Jr, 1980. "Methods and Problems in Business Cycle Theory," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 12(4), pages 696-715, November.
    10. Kydland, Finn E & Prescott, Edward C, 1982. "Time to Build and Aggregate Fluctuations," Econometrica, Econometric Society, vol. 50(6), pages 1345-1370, November.
    11. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1, March.
    12. Dezhbakhsh, Hashem & Levy, Daniel, 1994. "Periodic properties of interpolated time series (Economics Letters 44, no. 3, 1994, pp. 221-228)," Economics Letters, Elsevier, vol. 46(2), pages 183-183, October.
    13. Gorban, Alexander N. & Smirnova, Elena V. & Tyukina, Tatiana A., 2010. "Correlations, risk and crisis: From physiology to finance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(16), pages 3193-3217.
    14. Bernanke, Ben S, 1995. "The Macroeconomics of the Great Depression: A Comparative Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 27(1), pages 1-28, February.
    15. Lucas, Robert Jr., 1972. "Expectations and the neutrality of money," Journal of Economic Theory, Elsevier, vol. 4(2), pages 103-124, April.
    16. Crowley, Patrick & Aaron, Schultz, 2010. "A New Approach to Analyzing Convergence and Synchronicity in Growth and Business Cycles: Cross Recurrence Plots and Quantification Analysis," MPRA Paper 23728, University Library of Munich, Germany.
    17. Bastos, João A. & Caiado, Jorge, 2011. "Recurrence quantification analysis of global stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(7), pages 1315-1325.
    18. repec:zbw:bofrdp:2010_016 is not listed on IDEAS
    19. Strozzi, Fernanda & Zaldívar, José-Manuel & Zbilut, Joseph P., 2007. "Recurrence quantification analysis and state space divergence reconstruction for financial time series analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 376(C), pages 487-499.
    20. Gerhard Bry & Charlotte Boschan, 1971. "Standard Business Cycle Analysis of Economic Time Series," NBER Chapters, in: Cyclical Analysis of Time Series: Selected Procedures and Computer Programs, pages 64-150, National Bureau of Economic Research, Inc.
    21. Guhathakurta, Kousik & Bhattacharya, Basabi & Chowdhury, A. Roy, 2010. "Using recurrence plot analysis to distinguish between endogenous and exogenous stock market crashes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(9), pages 1874-1882.
    22. Orlando, Giuseppe, 2016. "A discrete mathematical model for chaotic dynamics in economics: Kaldor’s model on business cycle," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 125(C), pages 83-98.
    23. Chen, Wei-Shing, 2011. "Use of recurrence plot and recurrence quantification analysis in Taiwan unemployment rate time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(7), pages 1332-1342.
    24. A. Fabretti & M. Ausloos, 2005. "Recurrence Plot And Recurrence Quantification Analysis Techniques For Detecting A Critical Regime. Examples From Financial Market Inidices," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 16(05), pages 671-706.
    25. Mario Sportelli & Giuseppe Celi, 2011. "A Mathematical Approach To Harrod'S Open Economy Dynamics," Metroeconomica, Wiley Blackwell, vol. 62(3), pages 459-493, July.
    26. Jaeger, Albert, 1990. "Shock persistence and the measurement of prewar output series," Economics Letters, Elsevier, vol. 34(4), pages 333-337, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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).
    2. 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.
    3. Ashe, Sinéad & Egan, Paul, 2023. "Examining financial and business cycle interaction using cross recurrence plot analysis," Finance Research Letters, Elsevier, vol. 51(C).
    4. 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.
    5. 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.
    6. 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).
    7. Giuseppe Orlando & Fabio Della Rossa, 2019. "An Empirical Test on Harrod’s Open Economy Dynamics," Mathematics, MDPI, vol. 7(6), pages 1-13, June.
    8. 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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Giuseppe Orlando & Fabio Della Rossa, 2019. "An Empirical Test on Harrod’s Open Economy Dynamics," Mathematics, MDPI, vol. 7(6), pages 1-13, June.
    2. 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.
    3. Bordo, Michael D. & Haubrich, Joseph G., 2010. "Credit crises, money and contractions: An historical view," Journal of Monetary Economics, Elsevier, vol. 57(1), pages 1-18, January.
    4. Levy, Daniel, 2000. "Investment-Saving Comovement and Capital Mobility: Evidence from Century Long U.S. Time Series," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 3(1), pages 100-136.
    5. Teresa Aparicio & Dulce Saura, 2013. "Do Exchange Rate Series Present General Dependence? Some Results using Recurrence Quantification Analysis," Journal of Economics and Behavioral Studies, AMH International, vol. 5(10), pages 678-686.
    6. Andrew G. Haldane & Arthur E. Turrell, 2019. "Drawing on different disciplines: macroeconomic agent-based models," Journal of Evolutionary Economics, Springer, vol. 29(1), pages 39-66, March.
    7. Ashe, Sinéad & Egan, Paul, 2023. "Examining financial and business cycle interaction using cross recurrence plot analysis," Finance Research Letters, Elsevier, vol. 51(C).
    8. Stijn Claessens & M Ayhan Kose, 2018. "Frontiers of macrofinancial linkages," BIS Papers, Bank for International Settlements, number 95.
    9. Xu, Mengjia & Shang, Pengjian & Lin, Aijing, 2017. "Multiscale recurrence quantification analysis of order recurrence plots," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 381-389.
    10. Jun, Bogang & Kim, Tai-Yoo, 2015. "A neo-Schumpeterian perspective on the analytical macroeconomic framework: The expanded reproduction system," Hohenheim Discussion Papers in Business, Economics and Social Sciences 11-2015, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    11. Luca Pensieroso, 2011. "Real business cycle models of the Great Depression," Cliometrica, Journal of Historical Economics and Econometric History, Association Française de Cliométrie (AFC), vol. 5(2), pages 101-119, June.
    12. Olivier Darné & Amélie Charles, 2012. "A note on the uncertain trend in US real GNP: Evidence from robust unit root tests," Economics Bulletin, AccessEcon, vol. 32(3), pages 2399-2406.
    13. Lilian Carol Bohórquez Olarte & Jesús María Godoy Bejarano & Diego Fernando Téllez Falla, 2009. "Los ciclos del empleo regional en Colombia: dependencia interregional 2001-2006," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 27(58), pages 16-55, August.
    14. Giorgio Canarella & Luis A. Gil-Alana & Rangan Gupta & Stephen M. Miller, 2016. "Modeling U.S. Historical Time-Series Prices and Inflation Using Various Linear and Nonlinear Long-Memory Approaches," Working Papers 201683, University of Pretoria, Department of Economics.
    15. Romuald Fernand AWOUTCHA TCHIEUZING & NEBA Cletus YAH, 2021. "Financial, Absorption and Business Cycles in Selected African Countries," International Journal of Social and Administrative Sciences, Asian Economic and Social Society, vol. 6(1), pages 14-25, June.
    16. Galbács Peter, 2021. "What did it take for Lucas to set up ‘useful’ analogue systems in monetary business cycle theory?," Economics and Business Review, Sciendo, vol. 7(3), pages 61-82, September.
    17. Olkhov, Victor, 2018. "Economic Transactions Govern Business Cycles," MPRA Paper 87207, University Library of Munich, Germany.
    18. Sergio Rebelo, 2005. "Real Business Cycle Models: Past, Present, and Future," NBER Working Papers 11401, National Bureau of Economic Research, Inc.
    19. Leijonhufvud, Axel, 1983. "What would Keynes have thought of rational expectations?," Discussion Papers, Series I 177, University of Konstanz, Department of Economics.
    20. Francis X. Diebold, 1998. "The Past, Present, and Future of Macroeconomic Forecasting," Journal of Economic Perspectives, American Economic Association, vol. 12(2), pages 175-192, Spring.

    More about this item

    Keywords

    Nonlinear dynamics; Determinism; Chaos; RQA; Business cycles;
    All these keywords.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:dymchp:978-3-030-70982-2_17. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.