• Medientyp: Bericht; E-Book
  • Titel: Predicting ordinary and severe recessions with a three-state Markov-switching dynamic factor model
  • Beteiligte: Carstensen, Kai [Verfasser:in]; Heinrich, Markus [Verfasser:in]; Reif, Magnus [Verfasser:in]; Wolters, Maik H. [Verfasser:in]
  • Erschienen: Jena: Friedrich Schiller University Jena, 2019
  • Sprache: Englisch
  • Schlagwörter: Markov-Switching Dynamic Factor Model ; Great Recession ; GDP Forecasting ; GDP Nowcasting ; E32 ; Turning Points ; E37 ; C53
  • Entstehung:
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  • Beschreibung: We estimate a Markow-switching dynamic factor model with three states based on six leading business cycle indicators for Germany preselected from a broader set using the Elastic Net soft-thresholding rule. The three states represent expansions, normal recessions and severe recessions. We show that a two-state model is not sensitive enough to reliably detect relatively mild recessions when the Great Recession of 2008/2009 is included in the sample. Adding a third state helps to clearly distinguish normal and severe recessions, so that the model identifies reliably all business cycle turning points in our sample. In a real-time exercise the model detects recessions timely. Combining the estimated factor and the recession probabilities with a simple GDP forecasting model yields an accurate nowcast for the steepest decline in GDP in 2009Q1 and a correct prediction of the timing of the Great Recession and its recovery one quarter in advance.
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