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Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model

Author

Listed:
  • Kai Carstensen

    (University of Kiel, Ifo Institute, CESifo)

  • Markus Heinrich

    (University of Kiel)

  • Magnus Reif

    (University of Kiel, Ifo Institute)

  • Maik H. Wolters

    (University of Jena, Kiel Institute for the World Economy, IMFS at Goethe University Frankfurt)

Abstract

We estimate a Markow-switching dynamic factor model with three states based on six leading business cycle indicators for Germany preselected from a broader set using the Elastic Net soft-thresholding rule. The three states represent expansions, normal recessions and severe recessions. We show that a two-state model is not sensitive enough to reliably detect relatively mild recessions when the Great Recession of 2008/2009 is included in the sample. Adding a third state helps to clearly distinguish normal and severe recessions, so that the model identifies reliably all business cycle turning points in our sample. In a real-time exercise the model detects recessions timely. Combining the estimated factor and the recession probabilities with a simple GDP forecasting model yields an accurate nowcast for the steepest decline in GDP in 2009Q1 and a correct prediction of the timing of the Great Recession and its recovery one quarter in advance.

Suggested Citation

  • Kai Carstensen & Markus Heinrich & Magnus Reif & Maik H. Wolters, 2019. "Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model," Jena Economics Research Papers 2019-006, Friedrich-Schiller-University Jena.
    • Handle: RePEc:jrp:jrpwrp:2019-006
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    Cited by:

    1. Longo, Luigi & Riccaboni, Massimo & Rungi, Armando, 2022. "A neural network ensemble approach for GDP forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
    2. Proaño, Christian R. & Tarassow, Artur, 2018. "Evaluating the predicting power of ordered probit models for multiple business cycle phases in the U.S. and Japan," Journal of the Japanese and International Economies, Elsevier, vol. 50(C), pages 60-71.
    3. Bofinger, Peter & Feld, Lars P. & Schmidt, Christoph M. & Schnabel, Isabel & Wieland, Volker, 2018. "Vor wichtigen wirtschaftspolitischen Weichenstellungen. Jahresgutachten 2018/19 [Setting the Right Course for Economic Policy. Annual Report 2018/19]," Annual Economic Reports / Jahresgutachten, German Council of Economic Experts / Sachverständigenrat zur Begutachtung der gesamtwirtschaftlichen Entwicklung, volume 127, number 201819.
    4. Magnus Reif, 2022. "Time‐Varying Dynamics of the German Business Cycle: A Comprehensive Investigation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(1), pages 80-102, February.
    5. Gehrke, Britta & Weber, Enzo, 2018. "Identifying asymmetric effects of labor market reforms," European Economic Review, Elsevier, vol. 110(C), pages 18-40.
    6. Ademmer, Martin & Boysen-Hogrefe, Jens & Fiedler, Salomon & Groll, Dominik & Hauber, Philipp & Jannsen, Nils & Kooths, Stefan & Potjagailo, Galina & Wolters, Maik H., 2018. "Deutsche Konjunktur im Sommer 2018 - Deutsche Wirtschaft: Luftloch im konjunkturellen Höhenflug [German Economy Summer 2018 - German economy: Temporary slowdown, boom not over yet]," Kieler Konjunkturberichte 44, Kiel Institute for the World Economy (IfW Kiel).
    7. Christian Glocker & Philipp Wegmueller, 2020. "Business cycle dating and forecasting with real-time Swiss GDP data," Empirical Economics, Springer, vol. 58(1), pages 73-105, January.
    8. Jannsen, Nils, 2018. "Prognosen des IfW und tatsächliche Entwicklung 2017," Kiel Insight 2018.2, Kiel Institute for the World Economy (IfW Kiel).
    9. Robert Lehmann & Magnus Reif, 2021. "Predicting the German Economy: Headline Survey Indices Under Test," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(2), pages 215-232, November.
    10. Kai Carstensen & Magnus Reif & Maik Wolters, 2019. "Rezessionsrisiko der deutschen Wirtschaft deutlich erhöht," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 72(05), pages 28-31, March.
    11. Robert Lehmann, 2023. "The Forecasting Power of the ifo Business Survey," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 19(1), pages 43-94, March.
    12. Hauber, Philipp & Jannsen, Nils & Wolters, Maik H., 2018. "Schwacher Jahresauftakt 2018: Delle oder Beginn eines Abschwungs?," Kiel Insight 2018.10, Kiel Institute for the World Economy (IfW Kiel).
    13. Grimme, Christian & Lehmann, Robert & Noeller, Marvin, 2021. "Forecasting imports with information from abroad," Economic Modelling, Elsevier, vol. 98(C), pages 109-117.
    14. Ademmer, Martin & Boysen-Hogrefe, Jens & Fiedler, Salomon & Groll, Dominik & Jannsen, Nils & Kooths, Stefan & Potjagailo, Galina & Wolters, Maik H., 2017. "Deutsche Konjunktur im Herbst 2017 - Deutsche Wirtschaft nähert sich der Hochkonjunktur [German Economy Autumn 2017 - German economy approaches boom period]," Kieler Konjunkturberichte 35, Kiel Institute for the World Economy (IfW Kiel).
    15. Ademmer, Martin & Boysen-Hogrefe, Jens & Fiedler, Salomon & Groll, Dominik & Hauber, Philipp & Jannsen, Nils & Kooths, Stefan & Potjagailo, Galina, 2018. "Deutsche Konjunktur im Frühjahr 2018 - Deutsche Wirtschaft näher am Limit [German Economy Spring 2018 - German economy closer to its limit]," Kieler Konjunkturberichte 41, Kiel Institute for the World Economy (IfW Kiel).
    16. Klarl, Torben, 2020. "The response of CO2 emissions to the business cycle: New evidence for the U.S," Energy Economics, Elsevier, vol. 85(C).
    17. Christian Grimme & Robert Lehmann & Marvin Nöller, 2018. "Das ifo Importklima – ein erster Frühindikator für die Prognose der deutschen Importe," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 71(12), pages 27-32, June.
    18. Stefan Sauer & Klaus Wohlrabe, 2020. "ifo Handbuch der Konjunkturumfragen," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 88, July.
    19. Heinrich, Markus, 2020. "Does the Current State of the Business Cycle matter for Real-Time Forecasting? A Mixed-Frequency Threshold VAR approach," EconStor Preprints 219312, ZBW - Leibniz Information Centre for Economics.
    20. Carstensen, Kai & Wolters, Maik H., 2017. "Normaler Abschwung oder schwere Rezession? Ein neues Modell für die Prognose der Konjunkturphasen in Deutschland," Kiel Insight 2017.14, Kiel Institute for the World Economy (IfW Kiel).
    21. Peng Qin & Manying Bai, 2022. "Does oil price uncertainty matter in stock market volatility forecasting?," PLOS ONE, Public Library of Science, vol. 17(12), pages 1-21, December.
    22. 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, July.
    23. Agnieszka Gehringer & Thomas Mayer, 2021. "Measuring the Business Cycle Chronology with a Novel Business Cycle Indicator for Germany," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(1), pages 71-89, April.
    24. Ademmer, Martin & Jannsen, Nils & Kooths, Stefan & Wolters, Maik H., 2019. "Deutsche Wirtschaft in der Rezession?," Kiel Insight 2019.10, Kiel Institute for the World Economy (IfW Kiel).
    25. Eraslan, Sercan & Schröder, Maximilian, 2019. "Nowcasting GDP with a large factor model space," Discussion Papers 41/2019, Deutsche Bundesbank.

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    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • 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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