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New Composite Leading Indicators for Hungary and Poland

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  • Harm Bandholz
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    Abstract

    This paper presents new composite leading indicators for the two largest of the EU accession countries, Poland and Hungary. Using linear and non-linear dynamic factor models we find for both countries that a parsimonious specification, which combines national business cycle indicators,series reflecting trade volumes and supranational business expectations makes for the most reliable business cycle leaders. The composite leading indicators significantly Granger-cause GDP growth rates, while the estimated Markov-switching probabilities of being in a recessionarystate agree well with a priori determined cycle chronologies.

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    File URL: http://www.cesifo-group.de/portal/page/portal/DocBase_Content/WP/WP-Ifo_Working_Papers/wp-ifo-2005-2010/IfoWorkingPaper-3.pdf
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    Bibliographic Info

    Paper provided by Ifo Institute for Economic Research at the University of Munich in its series Ifo Working Paper Series with number Ifo Working Paper No. 3.

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    Date of creation: 2005
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    Handle: RePEc:ces:ifowps:_3

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    Keywords: Business Cycles; Composite Leading Indicators; EU Enlargement; Markovswitching; Turning Points;

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    References

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    1. 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.
    2. Artis, Michael J & Marcellino, Massimiliano & Proietti, Tommaso, 2004. "Characterizing the Business Cycle for Accession Countries," CEPR Discussion Papers 4457, C.E.P.R. Discussion Papers.
    3. Goldfeld, Stephen M. & Quandt, Richard E., 1973. "A Markov model for switching regressions," Journal of Econometrics, Elsevier, vol. 1(1), pages 3-15, March.
    4. Jurgen A Doornik & Henrik Hansen, . "An omnibus test for univariate and multivariate normalit," Economics Papers W4&91., Economics Group, Nuffield College, University of Oxford.
    5. Michael Funke & Harm Bandholz, 2003. "In search of leading indicators of economic activity in Germany," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(4), pages 277-297.
    6. 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.
    7. Anindya Banerjee & Massimiliano Marcellino & Igor Masten, 2004. "Forecasting Macroeconomic Variables for the Acceding Countries," Working Papers 260, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    8. Kim, Chang-Jin, 1994. "Dynamic linear models with Markov-switching," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 1-22.
    9. Victor Zarnowitz, 1963. "Cloos on Reference Dates and Leading Indicators: A Comment," The Journal of Business, University of Chicago Press, vol. 36, pages 461.
    10. Diebold & Rudebusch, . "Measuring Business Cycle: A Modern Perspective," Home Pages _061, University of Pennsylvania.
    11. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-44, January.
    12. 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.
    13. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70.
    14. 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.
    15. Zsolt Darvas & György Szapáry, 2006. "Business Cycle Synchronization in the Enlarged EU," Working Papers 0604, Department of Mathematical Economics and Economic Analysis, Corvinus University of Budapest.
    16. Gerhard Bry & Charlotte Boschan, 1971. "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs," NBER Books, National Bureau of Economic Research, Inc, number bry_71-1, octubre-d.
    17. Bandholz, Harm & Funke, Michael, 2003. "Die Konstruktion und Schätzung eines Konjunkturfrühindikators für Hamburg," Wirtschaftsdienst – Zeitschrift für Wirtschaftspolitik (1998 - 2007), ZBW – German National Library of Economics / Leibniz Information Centre for Economics, vol. 83(8), pages 540-548.
    18. 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.
    19. Boldin, Michael D, 1994. "Dating Turning Points in the Business Cycle," The Journal of Business, University of Chicago Press, vol. 67(1), pages 97-131, January.
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    Cited by:
    1. Konstantin A. Kholodilin, 2006. "Using the Dynamic Bi-Factor Model with Markov Switching to Predict the Cyclical Turns in the Large European Economies," Discussion Papers of DIW Berlin 554, DIW Berlin, German Institute for Economic Research.
    2. Konstantin A. Kholodilin, 2005. "Forecasting the Turns of German Business Cycle: Dynamic Bi-factor Model with Markov Switching," Discussion Papers of DIW Berlin 494, DIW Berlin, German Institute for Economic Research.
    3. Konstantin A. Kholodilin, 2005. "Forecasting the German Cyclical Turning Points: Dynamic Bi-Factor Model with Markov Switching," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), Justus-Liebig University Giessen, Department of Statistics and Economics, vol. 225(6), pages 653-674, November.

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