Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/204610 
Erscheinungsjahr: 
2019
Schriftenreihe/Nr.: 
Jena Economic Research Papers No. 2019-006
Verlag: 
Friedrich Schiller University Jena, Jena
Zusammenfassung: 
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.
Schlagwörter: 
Markov-Switching Dynamic Factor Model
Great Recession
Turning Points
GDP Nowcasting
GDP Forecasting
JEL: 
C53
E32
E37
Dokumentart: 
Working Paper

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