Measuring and predicting turning points using a dynamic bi-factor model
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- 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.
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Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(5), pages 557-580, December.
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- 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.
- 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.
- Konstantin A. Kholodilin, 2007. "Using the Dynamic Bi-Factor Model with Markov Switching to Predict the Cyclical Turns in the Large European Economies," Money Macro and Finance (MMF) Research Group Conference 2006 13, Money Macro and Finance Research Group.
- Zhang, Wei & He, Jie & Ge, Chanyuan & Xue, Rui, 2022. "Real-time macroeconomic monitoring using mixed frequency data: Evidence from China," Economic Modelling, Elsevier, vol. 117(C).
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"Model averaging in Markov-switching models: Predicting national recessions with regional data,"
Economics Letters, Elsevier, vol. 157(C), pages 45-49.
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Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot, Berlin, vol. 54(4), pages 293-318.
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