IDEAS home Printed from https://ideas.repec.org/p/diw/diwwpp/dp314.html
   My bibliography  Save this paper

Do Leading Indicators Help to Predict Business Cycle Turning Points in Germany?

Author

Listed:
  • Ulrich Fritsche
  • Vladimir Kuzin

Abstract

Using a binary reference series based on the dating procedure of Artis, Kontolemis and Osborn (1997) different procedures for predicting turning points of the German business cycles were tested. Specifically, a probit model as proposed by Estrella and Mishkin (1997) as well as Markov-switching models were taken into consideration. The overall results indicate that the interest rate spread, the longterm interest rate as well as some monetary indicators and some survey indicators can help predicting turning points of the business cycle.

Suggested Citation

  • Ulrich Fritsche & Vladimir Kuzin, 2002. "Do Leading Indicators Help to Predict Business Cycle Turning Points in Germany?," Discussion Papers of DIW Berlin 314, DIW Berlin, German Institute for Economic Research.
    • Handle: RePEc:diw:diwwpp:dp314
    as

    Download full text from publisher

    File URL: https://www.diw.de/documents/publikationen/73/diw_01.c.38604.de/dp314.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bernard, Henri & Gerlach, Stefan, 1998. "Does the Term Structure Predict Recessions? The International Evidence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 3(3), pages 195-215, July.
    2. Canova, Fabio, 1998. "Detrending and business cycle facts: A user's guide," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 533-540, May.
    3. Canova, Fabio, 1998. "Detrending and business cycle facts," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 475-512, May.
    4. Estrella, Arturo & Mishkin, Frederic S., 1997. "The predictive power of the term structure of interest rates in Europe and the United States: Implications for the European Central Bank," European Economic Review, Elsevier, vol. 41(7), pages 1375-1401, July.
    5. Ulrich Fritsche & Sabine Stephan, 2000. "Leading Indicators of German Business Cycles: An Assessment of Properties," Macroeconomics 0004005, University Library of Munich, Germany.
    6. Michael J. Dueker, 1997. "Strengthening the case for the yield curve as a predictor of U.S. recessions," Review, Federal Reserve Bank of St. Louis, issue Mar, pages 41-51.
    7. Döpke, Jörg, 1999. "Predicting Germany's recessions with leading indicators: Evidence from probit models," Kiel Working Papers 944, Kiel Institute for the World Economy (IfW Kiel).
    8. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1, March.
    9. James H. Stock & Mark W. Watson, 1989. "New Indexes of Coincident and Leading Economic Indicators," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409, National Bureau of Economic Research, Inc.
    10. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    11. Estrella, Arturo, 1998. "A New Measure of Fit for Equations with Dichotomous Dependent Variables," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 198-205, April.
    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. Brand, Claus & Reimers, Hans-Eggert & Seitz, Franz, 2003. "Forecasting real GDP: what role for narrow money?," Working Paper Series 254, European Central Bank.
    2. Deimante Teresiene & Greta Keliuotyte-Staniuleniene & Yiyi Liao & Rasa Kanapickiene & Ruihui Pu & Siyan Hu & Xiao-Guang Yue, 2021. "The Impact of the COVID-19 Pandemic on Consumer and Business Confidence Indicators," JRFM, MDPI, vol. 14(4), pages 1-23, April.
    3. Michael J. Lamla & Sarah M. Lein & Jan-Egbert Sturm, 2020. "Media reporting and business cycles: empirical evidence based on news data," Empirical Economics, Springer, vol. 59(3), pages 1085-1105, September.
    4. 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.
    5. Claus Brand & Hans-Eggert Reimers & Franz Seitz, 2003. "Narrow Money and the Business Cycle: Theoretical aspects and euro area evdence," Macroeconomics 0303012, University Library of Munich, Germany.
    6. Cruz-Rodríguez, Alexis, 2015. "Sostenibilidad fiscal y crisis cambiarias: Un análisis empírico [Fiscal sustainability and currency crises: An empirical analysis]," MPRA Paper 67741, University Library of Munich, Germany.
    7. Cruz-Rodriguez, Alexis, 2014. "¿Puede un índice de sostenibilidad fiscal predecir la ocurrencia de crisis cambiarias? Evidencias para algunos países seleccionados [Can a fiscal sustainability indicator predict the occurrence of ," MPRA Paper 54103, University Library of Munich, Germany.

    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. Ulrich FRITSCHE & Vladimir KOUZINE, 2010. "Prediction of Business Cycle Turning Points in Germany," EcoMod2004 330600054, EcoMod.
    2. Ulrich Fritsche, 2001. "Do probit models help in forecasting turning points of German business cycles?," Macroeconomics 0012022, University Library of Munich, Germany.
    3. Fritsche Ulrich & Kuzin Vladimir, 2005. "Prediction of Business Cycle Turning Points in Germany / Prognose konjunktureller Wendepunkte in Deutschland," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 225(1), pages 22-43, February.
    4. Franck Sédillot, 2001. "La pente des taux contient-elle de l'information sur l'activité économique future ?," Economie & Prévision, La Documentation Française, vol. 147(1), pages 141-157.
    5. Michael J. Dueker & Katrin Wesche, 2001. "European business cycles: new indices and analysis of their synchronicity," Working Papers 1999-019, Federal Reserve Bank of St. Louis.
    6. Ang, Andrew & Piazzesi, Monika & Wei, Min, 2006. "What does the yield curve tell us about GDP growth?," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 359-403.
    7. Marcus Scheiblecker, 2007. "Datierung von Konjunkturwendepunkten in Österreich," WIFO Monatsberichte (monthly reports), WIFO, vol. 80(9), pages 715-730, September.
    8. Nissilä, Wilma, 2020. "Probit based time series models in recession forecasting – A survey with an empirical illustration for Finland," BoF Economics Review 7/2020, Bank of Finland.
    9. Ahrens, R., 2002. "Predicting recessions with interest rate spreads: a multicountry regime-switching analysis," Journal of International Money and Finance, Elsevier, vol. 21(4), pages 519-537, August.
    10. Ivanova, Detelina & Lahiri, Kajal & Seitz, Franz, 2000. "Interest rate spreads as predictors of German inflation and business cycles," International Journal of Forecasting, Elsevier, vol. 16(1), pages 39-58.
    11. Gomez-Biscarri, Javier, 2008. "Changes in the informational content of term spreads: Is monetary policy becoming less effective?," Journal of Economics and Business, Elsevier, vol. 60(5), pages 415-435.
    12. Carriero, Andrea & Marcellino, Massimiliano, 2007. "A comparison of methods for the construction of composite coincident and leading indexes for the UK," International Journal of Forecasting, Elsevier, vol. 23(2), pages 219-236.
    13. Carriero, Andrea & Marcellino, Massimiliano, 2007. "A comparison of methods for the construction of composite coincident and leading indexes for the UK," International Journal of Forecasting, Elsevier, vol. 23(2), pages 219-236.
    14. Ulrich Fritsche & Felix Marklein, 2001. "Leading Indicators of Euroland Business Cycles," Discussion Papers of DIW Berlin 238, DIW Berlin, German Institute for Economic Research.
    15. Drew Creal & Siem Jan Koopman & Eric Zivot, 2008. "The Effect of the Great Moderation on the U.S. Business Cycle in a Time-varying Multivariate Trend-cycle Model," Tinbergen Institute Discussion Papers 08-069/4, Tinbergen Institute.
    16. Arturo Estrella & Anthony P. Rodrigues & Sebastian Schich, 2003. "How Stable is the Predictive Power of the Yield Curve? Evidence from Germany and the United States," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 629-644, August.
    17. L.A. Gil-Alana, 2005. "Fractional Cyclical Structures & Business Cycles in the Specification of the US Real Output," European Research Studies Journal, European Research Studies Journal, vol. 0(1-2), pages 99-126.
    18. Guglielmo Caporale & Luis Gil-Alana, 2006. "Long memory at the long run and at the cyclical frequencies: modelling real wages in England, 1260–1994," Empirical Economics, Springer, vol. 31(1), pages 83-93, March.
    19. Fabio Moneta, 2005. "Does the Yield Spread Predict Recessions in the Euro Area?," International Finance, Wiley Blackwell, vol. 8(2), pages 263-301, August.
    20. Usama Ehsan KHAN & Syed Monis JAWED, 2019. "Dynamics of business cycle and long-term economic growth of Pakistan," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(2(619), S), pages 173-184, Summer.

    More about this item

    Keywords

    Business cycle; leading indicators; probit model; McFadden's R2; Markov switching models;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:diw:diwwpp:dp314. 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: Bibliothek (email available below). General contact details of provider: https://edirc.repec.org/data/diwbede.html .

    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.