Robust Real-Time Estimates of the German Output Gap Based on a Multivariate Trend-Cycle Decomposition

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 2022 and present a nowcasting scheme that accurately predicts the German 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 compared to the final estimate is very small (0.28 percentage points) after only one month of observed data. Moreover, we show that business and consumer expectations, international trade and labour market aggregates consistently explain large shares of variation in the German output gap. Finally, our procedure is very reliable, as it implies an output gap that is hardly revised ex post. This is particularly important for policymakers.

Keywords: output gap, Germany, nowcast, mixed frequency, vector-autoregression

JEL Classification: E32, E37, C53