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New Composite Leading Indicators for Hungary and Poland

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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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    Cited by:

    1. Shirly Siew-Ling Wong & Toh-Hao Tan & Shazali Abu Mansor & Venus Khim-Sen Liew, 2018. "Rethinking and Moving Beyond GDP: A New Measure of Sarawak Economy Panorama," International Business Research, Canadian Center of Science and Education, vol. 11(12), pages 127-133, December.
    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, 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.
    4. 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.

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    More about this item

    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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