Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model. An Application to the German Business Cycle

Markus Heinrich, Kai Carstensen, Magnus Reif and Maik Wolters

VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking from Verein für Socialpolitik / German Economic Association

Abstract: We use a Markow-switching dynamic factor model with three states for Germany with indicators selected by the Elastic Net. The states represent expansions, normal - and severe recessions. Adding a third state helps to identify all business cycle turning points in-sample and in real-time. Combining the factor and the recession probabilities with a GDP forecasting model yields accurate nowcasts and a correct prediction of the timing of the Great Recession and its recovery one quarter in advance.

JEL-codes: C53 E32 E37 (search for similar items in EconPapers)
Date: 2017
New Economics Papers: this item is included in nep-eec, nep-for, nep-mac and nep-ore
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Citations: View citations in EconPapers (23)

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Related works:
Journal Article: Predicting ordinary and severe recessions with a three-state Markov-switching dynamic factor model (2020)
Working Paper: Predicting ordinary and severe recessions with a three-state Markov-switching dynamic factor model An application to the German business cycle (2020)
Working Paper: Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model (2019)
Working Paper: Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model. An Application to the German Business Cycle (2017)
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