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In Search of Leading Indicators of Economic Activity in Germany

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  • Harm Bandholz

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  • 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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Bibliographic Info

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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Related research

Keywords: Business Cycles; Leading Indicators; Turning Points; Markov Switching; Germany;

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References

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  1. Lawrence J. Christiano & Terry J. Fitzgerald, 1999. "The Band Pass Filter," NBER Working Papers 7257, National Bureau of Economic Research, Inc.
    • Lawrence J. Christiano & Terry J. Fitzgerald, 2003. "The Band Pass Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(2), pages 435-465, 05.
  2. Trueman, Brett, 1994. "Analyst Forecasts and Herding Behavior," Review of Financial Studies, Society for Financial Studies, vol. 7(1), pages 97-124.
  3. Kim, C-J., 1991. "Dynamic Linear Models with Markov-Switching," Papers 91-8, York (Canada) - Department of Economics.
  4. Diebold & Rudebusch, . "Measuring Business Cycle: A Modern Perspective," Home Pages _061, University of Pennsylvania.
  5. Timothy Cogley & James M. Nason, 1993. "Effects of the Hodrick-Prescott filter on trend and difference stationary time series: implications for business cycle research," Working Papers in Applied Economic Theory 93-01, Federal Reserve Bank of San Francisco.
  6. Neftici, Salih N., 1982. "Optimal prediction of cyclical downturns," Journal of Economic Dynamics and Control, Elsevier, vol. 4(1), pages 225-241, November.
  7. Hamilton, James D & Perez-Quiros, Gabriel, 1996. "What Do the Leading Indicators Lead?," The Journal of Business, University of Chicago Press, vol. 69(1), pages 27-49, January.
  8. Robert F. Engle & Sharon Kozicki, 1990. "Testing For Common Features," NBER Technical Working Papers 0091, National Bureau of Economic Research, Inc.
  9. King, R.G. & Rebelo, S.T., 1989. "Low Frequency Filtering And Real Business Cycles," RCER Working Papers 205, University of Rochester - Center for Economic Research (RCER).
  10. 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.
  11. 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.
  12. Ulrich Fritsche & Sabine Stephan, 2000. "Leading Indicators of German Business Cycles: An Assessment of Properties," Macroeconomics 0004005, EconWPA.
  13. Jaeger, Albert, 1994. "Mechanical Detrending by Hodrick-Prescott Filtering: A Note," Empirical Economics, Springer, vol. 19(3), pages 493-500.
  14. Godfrey, L. G. & Pesaran, M. H., 1983. "Tests of non-nested regression models: Small sample adjustments and Monte Carlo evidence," Journal of Econometrics, Elsevier, vol. 21(1), pages 133-154, January.
  15. Robert J. Hodrick & Edward Prescott, 1981. "Post-War U.S. Business Cycles: An Empirical Investigation," Discussion Papers 451, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
  16. Marianne Baxter & Robert G. King, 1995. "Measuring Business Cycles Approximate Band-Pass Filters for Economic Time Series," NBER Working Papers 5022, National Bureau of Economic Research, Inc.
  17. Orphanides, Athanasios, 2003. "Monetary policy evaluation with noisy information," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 605-631, April.
  18. Chang-Jin Kim & Charles R. Nelson, 1998. "Business Cycle Turning Points, A New Coincident Index, And Tests Of Duration Dependence Based On A Dynamic Factor Model With Regime Switching," The Review of Economics and Statistics, MIT Press, vol. 80(2), pages 188-201, May.
  19. Harvey, A C & Jaeger, A, 1993. "Detrending, Stylized Facts and the Business Cycle," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(3), pages 231-47, July-Sept.
  20. James H. Stock & Mark W. Watson, 1992. "A Procedure for Predicting Recessions With Leading Indicators: Econometric Issues and Recent Experience," NBER Working Papers 4014, National Bureau of Economic Research, Inc.
  21. Jurgen A. Doornik & Henrik Hansen, 2008. "An Omnibus Test for Univariate and Multivariate Normality," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(s1), pages 927-939, December.
  22. Pesaran, M H, 1974. "On the General Problem of Model Selection," Review of Economic Studies, Wiley Blackwell, vol. 41(2), pages 153-71, April.
  23. repec:att:wimass:9520 is not listed on IDEAS
  24. Pedersen, Torben Mark, 2001. "The Hodrick-Prescott filter, the Slutzky effect, and the distortionary effect of filters," Journal of Economic Dynamics and Control, Elsevier, vol. 25(8), pages 1081-1101, August.
  25. Chang-Jin Kim & Charles R. Nelson, 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262112388, December.
  26. Stock, James H. & Watson, Mark W., 1999. "Business cycle fluctuations in us macroeconomic time series," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 1, pages 3-64 Elsevier.
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Citations

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Cited by:
  1. Michael Graff, 2006. "Internationale Konjunkturverbunde," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), Justus-Liebig University Giessen, Department of Statistics and Economics, vol. 226(4), pages 385-417, July.
  2. Jonas Dovern & Christina Ziegler, 2008. "Predicting Growth Rates and Recessions. Assessing U.S. Leading Indicators Under Real-Time Conditions," Kiel Working Papers 1397, Kiel Institute for the World Economy.
  3. 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.
  4. 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.
  5. 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.
  6. Harm Bandholz, 2005. "New Composite Leading Indicators for Hungary and Poland," Ifo Working Paper Series Ifo Working Paper No. 3, Ifo Institute for Economic Research at the University of Munich.
  7. 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.
  8. Burcu Gurcihan Yunculer & Gonul Sengul & Arzu Yavuz, 2014. "A Quest for Leading Indicators of the Turkish Unemployment Rate," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 14(1), pages 23-45.

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