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In Search of Leading Indicators of Economic Activity in Germany

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  • Harm Bandholz

    ()

  • Michael Funke

    ()

Abstract

In this Paper we present two new composite leading indicators of economic activity in Germany estimated using a dynamic factor model with and without regime switching. The obtained optimal inferences of business cycle turning points indicate that the two-state regime switching procedure leads to a successful representation of the sample data and provides an appropriate tool for forecasting business conditions.

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File URL: http://gulliver.econ.uni-hamburg.de/IWWT/homepage/qmwps/qm703.pdf
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Paper provided by Hamburg University, Department of Economics in its series Quantitative Macroeconomics Working Papers with number 20307.

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Date of creation: Jul 2003
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Handle: RePEc:ham:qmwops:20307
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Keywords: Business Cycles; Leading Indicators; Turning Points; Markov Switching; Germany;

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  6. James H. Stock & Mark W. Watson, 1993. "A Procedure for Predicting Recessions with Leading Indicators: Econometric Issues and Recent Experience," NBER Chapters, in: Business Cycles, Indicators and Forecasting, pages 95-156 National Bureau of Economic Research, Inc.
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  21. Engle, Robert F & Kozicki, Sharon, 1993. "Testing for Common Features: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(4), pages 393-95, October.
  22. Chauvet, Marcelle, 1998. "An Econometric Characterization of Business Cycle Dynamics with Factor Structure and Regime Switching," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 969-96, November.
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  25. Jaeger, Albert, 1994. "Mechanical Detrending by Hodrick-Prescott Filtering: A Note," Empirical Economics, Springer, vol. 19(3), pages 493-500.
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Cited by:

  1. H. Burcu Gurcihan & Gonul Sengul & Arzu Yavuz, 2013. "A Quest for Leading Indicators of the Turkish Unemployment Rate," Working Papers 1341, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
  2. Jonas Dovern & Christina Ziegler, 2008. "Predicting Growth Rates and Recessions. Assessing U.S. Leading Indicators under Real-Time Condition," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot, Berlin, vol. 54(4), pages 293-318.
  3. David Iselin & Boriss Siliverstovs, 2013. "Using Newspapers for Tracking the Business Cycle: A comparative study for Germany and Switzerland," KOF Working papers 13-337, KOF Swiss Economic Institute, ETH Zurich.
  4. Stefan Gerlach & Matthew S. Yiu, 2004. "A Dynamic Factor Model for Current-Quarter Estimates of Economic Activity in Hong Kong," Working Papers 162004, Hong Kong Institute for Monetary Research.
  5. Harm Bandholz, 2005. "New Composite Leading Indicators for Hungary and Poland," Ifo Working Paper Series Ifo Working Paper No. 3, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
  6. Michael Graff, 2005. "Internationale Konjunkturverbunde," KOF Working papers 05-108, KOF Swiss Economic Institute, ETH Zurich.
  7. Sascha O. Becker & Klaus Wohlrabe, 2008. "European Data Watch: Micro Data at the Ifo Institute for Economic Research – The “Ifo Business Survey”, Usage and Access," Schmollers Jahrbuch : Journal of Applied Social Science Studies / Zeitschrift für Wirtschafts- und Sozialwissenschaften, Duncker & Humblot, Berlin, vol. 128(2), pages 307-319.
  8. Mapa, Dennis S. & Simbulan, Maria Christina, 2014. "Analyzing and Forecasting Movements of the Philippine Economy using the Dynamic Factor Models (DFM)," MPRA Paper 54478, University Library of Munich, Germany.

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