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A further note on the three phases of the US business cycle

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  • Allan Layton
  • Daniel Smith

Abstract

Using a number of alternative approaches, Sichel (1994) demonstrated evidence supporting the notion that the US business cycle is best characterized as having three distinct phases, viz. contraction, followed by rapid expansion during the early stages of the recovery phase, followed by a period of more normal expansionary growth, with the cycle then repeating itself. This contrasts with the more usual expansion/contraction, two phase characterization but is more in keeping with the original notion of the business cycle as conceived by Burns and Mitchell (1946). Here an alternative approach is employed for shedding light on this issue. Following the original suggestion of Hamilton (1989, 1990, 1991), a simple nonlinear, three phase, regime switching Markov model is compared against its simpler two phase version to determine which version is statistically more consistent with the business cycle historical evidence. The evidence seems to clearly support the three phase characterization and that this characterization yields interesting information on business cycle dynamics which is necessarily missed by the two phase model formulation.

Suggested Citation

  • Allan Layton & Daniel Smith, 2000. "A further note on the three phases of the US business cycle," Applied Economics, Taylor & Francis Journals, vol. 32(9), pages 1133-1143.
    • Handle: RePEc:taf:applec:v:32:y:2000:i:9:p:1133-1143
    DOI: 10.1080/000368400404272
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    References listed on IDEAS

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    Cited by:

    1. Carstensen, Kai & Heinrich, Markus & Reif, Magnus & Wolters, Maik H., 2020. "Predicting ordinary and severe recessions with a three-state Markov-switching dynamic factor model," International Journal of Forecasting, Elsevier, vol. 36(3), pages 829-850.
    2. Shyh-Wei Chen, 2008. "Identifying US turning points revisited: the panel model with the regime switching approach," Applied Economics Letters, Taylor & Francis Journals, vol. 15(11), pages 893-897.
    3. Altug, Sumru & Bildirici, Melike, 2010. "Business Cycles around the Globe: A Regime-switching Approach," CEPR Discussion Papers 7968, C.E.P.R. Discussion Papers.
    4. Layton, Allan P. & Smith, Daniel R., 2007. "Business cycle dynamics with duration dependence and leading indicators," Journal of Macroeconomics, Elsevier, vol. 29(4), pages 855-875, December.
    5. Chen, Shyh-Wei, 2006. "Simultaneously modeling the volatility of the growth rate of real GDP and determining business cycle turning points: Evidence from the U.S., Canada and the UK," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 71(2), pages 87-102.
    6. Ferrara, Laurent, 2003. "A three-regime real-time indicator for the US economy," Economics Letters, Elsevier, vol. 81(3), pages 373-378, December.
    7. Benoit Bellone, 2004. "Une lecture probabiliste du cycle d’affaires américain," Econometrics 0407002, University Library of Munich, Germany, revised 28 Mar 2005.
    8. Allan Layton & Daniel R. Smith, 2005. "Testing the Power of Leading Indicators to Predict Business Cycle Phase Changes," School of Economics and Finance Discussion Papers and Working Papers Series 200, School of Economics and Finance, Queensland University of Technology.
    9. Ferrara, Laurent, 2006. "A real-time recession indicator for the Euro area," MPRA Paper 4042, University Library of Munich, Germany.
    10. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
    11. Huang, Jia-Ping & Sumita, Ushio, 2015. "Development of computational algorithms for pricing European bond options under the influence of macro-economic conditions," Applied Mathematics and Computation, Elsevier, vol. 251(C), pages 453-468.
    12. Monica Billio & Jacques Anas & Laurent Ferrara & Marco Lo Duca, 2007. "A turning point chronology for the Euro-zone," Working Papers 2007_33, Department of Economics, University of Venice "Ca' Foscari".
    13. Martha Misas & Maria Teresa Ramirez, 2007. "Depressions in the Colombian economic growth during the twentieth century: a Markov switching regime model," Applied Economics Letters, Taylor & Francis Journals, vol. 14(11), pages 803-808.
    14. Chen, Shyh-Wei & Shen, Chung-Hua, 2006. "Can the identification puzzle of Taiwan's turning points after 1990 be solved?," Economic Modelling, Elsevier, vol. 23(1), pages 174-195, January.
    15. Heinrich, Markus & Carstensen, Kai & Reif, Magnus & Wolters, Maik, 2017. "Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model. An Application to the German Business Cycle," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168206, Verein für Socialpolitik / German Economic Association.
    16. Benoît Bellone, 2006. "Une lecture probabiliste du cycle d’affaires américain," Économie et Prévision, Programme National Persée, vol. 172(1), pages 63-81.
    17. Shyh-Wei Chen & Chung-Hua Shen, 2006. "Is there a duration dependence in Taiwan's business cycles?," International Economic Journal, Taylor & Francis Journals, vol. 20(1), pages 109-128.
    18. Jesper Gregers Linaa, "undated". "Idiosyncrasy of Business Cycles Across EU Countries," EPRU Working Paper Series 02-08, Economic Policy Research Unit (EPRU), University of Copenhagen. Department of Economics.
    19. Kim, Woo Chang & Kim, Jang Ho & Mulvey, John M. & Fabozzi, Frank J., 2015. "Focusing on the worst state for robust investing," International Review of Financial Analysis, Elsevier, vol. 39(C), pages 19-31.

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