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Do probit models help in forecasting turning points of German business cycles?

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  • Ulrich Fritsche

    (German Institute for Economic Research)

Abstract

In this paper we used a data set constructed for a companion paper (Fritsche/Stephan, 2000) where we explored the leading indicator properties of different time series for the German business cycle. Now we test for the ability of different indicator series to forecast recessions by using a probit approach as proposed by Estrella/Mishkin (1997). The dating procedure refers to the study by Artis et. al. (1997). We took into consideration the criticism made by Dueker (1997) who stated that in the probit model the fact that the economy is already in a state of recession must be controlled for. The results of our estimate are unsatisfactory on the whole. Only the ifo institute's business expectation of producers of intermediate inputs, the interest rate spread, the long-term interest rate, and money supply M2 show satisfactory leading properties.

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File URL: http://128.118.178.162/eps/mac/papers/0012/0012022.pdf
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Bibliographic Info

Paper provided by EconWPA in its series Macroeconomics with number 0012022.

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Length: 15 pages
Date of creation: 28 Feb 2001
Date of revision:
Handle: RePEc:wpa:wuwpma:0012022

Note: Type of Document - PDF; prepared on IBM PC; pages: 15 ; figures: included
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Web page: http://128.118.178.162

Related research

Keywords: business cycle; probit model; modified McFadden's R2; recession; Germany;

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References

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  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. Michael 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.
  3. 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.
  4. Canova, Fabio, 1993. "Detrending and Business Cycle Facts," CEPR Discussion Papers 782, C.E.P.R. Discussion Papers.
  5. Stock, J.H. & Watson, M.W., 1989. "New Indexes Of Coincident And Leading Economic Indicators," Papers 178d, Harvard - J.F. Kennedy School of Government.
  6. Jörg Döpke, 1999. "Predicting Germany's Recessions with Leading Indicators � Evidence from Probit Models," Kiel Working Papers 944, Kiel Institute for the World Economy.
  7. Artis, Michael J & Kontolemis, Zenon G & Osborn, Denise R, 1997. "Business Cycles for G7 and European Countries," The Journal of Business, University of Chicago Press, vol. 70(2), pages 249-79, April.
  8. Ulrich Fritsche & Sabine Stephan, 2002. "Leading Indicators of German Business Cycles - An Assessment of Properties," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), Justus-Liebig University Giessen, Department of Statistics and Economics, vol. 222(3), pages 289-315.
  9. Canova, Fabio, 1998. "Detrending and business cycle facts: A user's guide," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 533-540, May.
  10. 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.
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Citations

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Cited by:
  1. Klaus Abberger & Sascha Becker & Barbara Hofmann & Klaus Wohlrabe, 2007. "Mikrodaten im ifo Institut für Wirtschaftsforschung – Bestand, Verwendung und Zugang," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer, vol. 1(1), pages 27-42, June.
  2. 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.
  3. Benner, Joachim & Meier, Carsten-Patrick, 2005. "Was leisten Stimmungsindikatoren für die Prognose des realen Bruttoinlandsprodukts in Deutschland? : Eine Echtzeit-Analyse," Open Access Publications from Kiel Institute for the World Economy 3725, Kiel Institute for the World Economy (IfW).
  4. Sascha O. Becker & Klaus Wohlrabe, 2007. "Micro Data at the Ifo Institute for Economic Research – The “Ifo Business Survey”, Usage and Access," Ifo Working Paper Series Ifo Working Paper No. 47, Ifo Institute for Economic Research at the University of Munich.
  5. Joachim Benner & Carsten-Patrick Meier, 2004. "Prognosegüte alternativer Frühindikatoren für die Konjunktur in Deutschland," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), Justus-Liebig University Giessen, Department of Statistics and Economics, vol. 224(6), pages 639-652, November.
  6. Klaus Abberger & Sascha O. Becker & Barbara Hofmann & Klaus Wohlrabe, 2007. "Mikrodaten im ifo Institut für Wirtschaftsforschung: Bestand, Verwendung, Zugang," Ifo Working Paper Series Ifo Working Paper No. 44, Ifo Institute for Economic Research at the University of Munich.
  7. Joachim Benner & Carsten-Patrick Meier, 2003. "Prognosegüte alternativer Frühindikatoren für die Konjunktur in Deutschland," Kiel Working Papers 1139, Kiel Institute for the World Economy.

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