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New Composite Leading Indicators for Hungary and Poland

Author

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  • Harm Bandholz

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 recessionary state agree well with a priori determined cycle chronologies.

Suggested Citation

  • Harm Bandholz, 2005. "New Composite Leading Indicators for Hungary and Poland," ifo Working Paper Series 3, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
  • Handle: RePEc:ces:ifowps:_3
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    File URL: http://www.cesifo-group.de/DocDL/IfoWorkingPaper-3.pdf
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    References listed on IDEAS

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    1. 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.
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    Citations

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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. Kholodilin Konstantin A., 2005. "Forecasting the German Cyclical Turning Points: Dynamic Bi-Factor Model with Markov Switching," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 225(6), pages 653-674, December.
    3. 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.

    More about this item

    Keywords

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

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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