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SSRN Electronic Journal
Article . 2022 . Peer-reviewed
Data sources: Crossref
EconStor
Research . 2022
Data sources: EconStor
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Tracking the German Business Cycle

Authors: Berger, Tino; Ochsner, Christian;

Tracking the German Business Cycle

Abstract

The German economy is an important economic driver in the Euro-area in terms of gross domestic product, labour force and international integration. We provide a state of the art estimate of the German output gap between 1995 and 2021 and present a nowcasting scheme that accurately predicts the Germany output gap up to three months prior to a gross domestic product data release. To this end, we elicit a mixed-frequency vector-autoregressive model in the spirit of Berger, Morley, and Wong (forthcoming) who propose to use monthly information to form an expectation about the current-quarter output gap. The mean absolute error of our nowcast is very small (0.25 percentage points) after only one month of observed data. Moreover, we show that international trade and labour market aggregates consistently explain large shares of variation in the German output gap.

Country
Germany
Keywords

mixed frequency, 330, ddc:330, E37, Economics, vector-autoregression, nowcast, Wirtschaft, Germany, output gap, C53, E32

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green