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Disentangling the enigma of multi-structured economic cycles - A new appearance of the golden ratio

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  • de Groot, E.A.
  • Segers, R.
  • Prins, D.

Abstract

We study whether there is an interrelationship between the lengths of economic cycles. Such an interrelationship would be helpful to signal future economic downturns, thus to alleviate economic and societal distress. To detect the lengths of economic cycles, we introduce an improved method, where Fourier analysis is coupled with GARCH regression, mixed distribution estimation, and harmonic regression. We apply our methodology to detect cycles in percentage GDP growth in 25 OECD countries, and in Europe. The results indicate that in each economy, between two and five cycles are present. Cycles with a length between 5–6 years and between 9–10 years appear most frequently. A meta-analysis on the detected cycle lengths reveals that the ratio between the lengths of consecutive cycles often closely matches the golden ratio, ϕ. Interestingly, this finding opposes several existing theories about multi-cycle structures, which imply that the lengths of shorter cycles should be integer fractions of the lengths of longer cycles. Our paper thus provides a new direction for theory development regarding economic cycles and dynamic stability.

Suggested Citation

  • de Groot, E.A. & Segers, R. & Prins, D., 2021. "Disentangling the enigma of multi-structured economic cycles - A new appearance of the golden ratio," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
  • Handle: RePEc:eee:tefoso:v:169:y:2021:i:c:s0040162521002250
    DOI: 10.1016/j.techfore.2021.120793
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    1. Alfred Kleinknecht, 1987. "Basic Innovations, Radically New Products, Major Innovations: An Assessment of Recent Research," Palgrave Macmillan Books, in: Innovation Patterns in Crisis and Prosperity, chapter 3, pages 57-75, Palgrave Macmillan.
    2. Grinin, Leonid E. & Grinin, Anton L. & Korotayev, Andrey, 2017. "Forthcoming Kondratieff wave, Cybernetic Revolution, and global ageing," Technological Forecasting and Social Change, Elsevier, vol. 115(C), pages 52-68.
    3. Michael Artis & Jos� G. Clavel & Mathias Hoffmann & Dilip Nachane, 2007. "Harmonic Regression Models: A Comparative Review with Applications," IEW - Working Papers 333, Institute for Empirical Research in Economics - University of Zurich.
    4. Gerald Silverberg & Bart Verspagen, 2003. "Breaking the waves: a Poisson regression approach to Schumpeterian clustering of basic innovations," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 27(5), pages 671-693, September.
    5. Thompson, William R., 1990. "Long waves, technological innovation, and relative decline," International Organization, Cambridge University Press, vol. 44(2), pages 201-233, April.
    6. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    7. Beveridge, Stephen & Nelson, Charles R., 1981. "A new approach to decomposition of economic time series into permanent and transitory components with particular attention to measurement of the `business cycle'," Journal of Monetary Economics, Elsevier, vol. 7(2), pages 151-174.
    8. Modis, Theodore, 2007. "The normal, the natural, and the harmonic," OSF Preprints 84tgs, Center for Open Science.
    9. Francois-Éric Racicot, 2011. "Low-frequency components and the Weekend effect revisited: Evidence from Spectral Analysis," RePAd Working Paper Series UQO-DSA-wp052011, Département des sciences administratives, UQO.
    10. Coccia, Mario, 2018. "A Theory of the General Causes of Long Waves: War, General Purpose Technologies, and Economic Change," Technological Forecasting and Social Change, Elsevier, vol. 128(C), pages 287-295.
    11. Watson, Mark W., 1986. "Univariate detrending methods with stochastic trends," Journal of Monetary Economics, Elsevier, vol. 18(1), pages 49-75, July.
    12. Andrew Tylecote, 1994. "Long Waves, Long Cycles, and Long Swings," Journal of Economic Issues, Taylor & Francis Journals, vol. 28(2), pages 477-488, June.
    13. Modis, Theodore, 2017. "A hard-science approach to Kondratieff's economic cycle," Technological Forecasting and Social Change, Elsevier, vol. 122(C), pages 63-70.
    14. Jan Reijnders, 1990. "Long Waves in Economic Development," Books, Edward Elgar Publishing, number 366.
    15. Andrew C. Harvey & Thomas M. Trimbur, 2003. "General Model-Based Filters for Extracting Cycles and Trends in Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 85(2), pages 244-255, May.
    16. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
    17. Rainer Metz, 2011. "Do Kondratieff waves exist? How time series techniques can help to solve the problem," Cliometrica, Journal of Historical Economics and Econometric History, Association Française de Cliométrie (AFC), vol. 5(3), pages 205-238, October.
    18. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    19. Masaaki Hirooka, 2005. "Nonlinear dynamism of innovation and business cycles," Springer Books, in: Uwe Cantner & Elias Dinopoulos & Robert F. Lanzillotti (ed.), Entrepreneurships, the New Economy and Public Policy, pages 289-316, Springer.
    20. Solomou, Solomos & Shimazaki, Masao, 2007. "Japanese episodic long swings in economic growth," Explorations in Economic History, Elsevier, vol. 44(2), pages 224-241, April.
    21. Muriel Dal-Pont Legrand & Hagemann Harald, 2007. "Business cycles in Juglar and Schumpeter," Post-Print halshs-00454505, HAL.
    22. Focacci, Antonio, 2017. "Controversial curves of the economy: An up-to-date investigation of long waves," Technological Forecasting and Social Change, Elsevier, vol. 116(C), pages 271-285.
    23. David N. DeJong & Chetan Dave, 2011. "Structural Macroeconometrics Second Edition," Economics Books, Princeton University Press, edition 1, number 9622.
    24. Drew Creal & Siem Jan Koopman & Eric Zivot, 2010. "Extracting a robust US business cycle using a time-varying multivariate model-based bandpass filter," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 695-719.
    25. Modis, Theodore, 2013. "Long-term GDP forecasts and the prospects for growth," Technological Forecasting and Social Change, Elsevier, vol. 80(8), pages 1557-1562.
    26. Valle e Azevedo, Joao & Koopman, Siem Jan & Rua, Antonio, 2006. "Tracking the Business Cycle of the Euro Area: A Multivariate Model-Based Bandpass Filter," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 278-290, July.
    27. de Groot, Bert & Franses, Philip Hans, 2012. "Common socio-economic cycle periods," Technological Forecasting and Social Change, Elsevier, vol. 79(1), pages 59-68.
    28. Modis, Theodore, 2013. "Long-Term GDP Forecasts and the Prospects for Growth," OSF Preprints aqcht, Center for Open Science.
    29. Grinin, Leonid & Grinin, Anton & Korotayev, Andrey, 2020. "A quantitative analysis of worldwide long-term technology growth: From 40,000 BCE to the early 22nd century," Technological Forecasting and Social Change, Elsevier, vol. 155(C).
    30. Sanidas, Elias, 2014. "Four harmonic cycles explain and predict commodity currencies' wide long term fluctuations," Technological Forecasting and Social Change, Elsevier, vol. 87(C), pages 135-151.
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    Cited by:

    1. de Groot, E.A. & Segers, R. & Prins, D., 2022. "Non-resonating cycles in a dynamic model for investment behavior," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
    2. Kajikawa, Yuya & Mejia, Cristian & Wu, Mengjia & Zhang, Yi, 2022. "Academic landscape of Technological Forecasting and Social Change through citation network and topic analyses," Technological Forecasting and Social Change, Elsevier, vol. 182(C).

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