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Robust real-time estimates of the German output gap based on a multivariate trend-cycle decomposition

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  • Berger, Tino
  • Ochsner, Christian

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.

Suggested Citation

  • Berger, Tino & Ochsner, Christian, 2022. "Robust real-time estimates of the German output gap based on a multivariate trend-cycle decomposition," Discussion Papers 35/2022, Deutsche Bundesbank.
    • Handle: RePEc:zbw:bubdps:352022
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    References listed on IDEAS

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    1. Athanasios Orphanides & Simon van Norden, 2002. "The Unreliability of Output-Gap Estimates in Real Time," The Review of Economics and Statistics, MIT Press, vol. 84(4), pages 569-583, November.
    2. Günes Kamber & James Morley & Benjamin Wong, 2018. "Intuitive and Reliable Estimates of the Output Gap from a Beveridge-Nelson Filter," The Review of Economics and Statistics, MIT Press, vol. 100(3), pages 550-566, July.
    3. Marek Jarociński & Michele Lenza, 2018. "An Inflation‐Predicting Measure of the Output Gap in the Euro Area," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(6), pages 1189-1224, September.
    4. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    5. Daniel F. Waggoner & Tao Zha, 1999. "Conditional Forecasts In Dynamic Multivariate Models," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 639-651, November.
    6. Berger, Tino & Richter, Julia & Wong, Benjamin, 2022. "A unified approach for jointly estimating the business and financial cycle, and the role of financial factors," Journal of Economic Dynamics and Control, Elsevier, vol. 136(C).
    7. Claudio BorioBy & Piti Disyatat & Mikael Juselius, 2017. "Rethinking potential output: embedding information about the financial cycle," Oxford Economic Papers, Oxford University Press, vol. 69(3), pages 655-677.
    8. Josefine Quast & Maik H. Wolters, 2022. "Reliable Real-Time Output Gap Estimates Based on a Modified Hamilton Filter," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 152-168, January.
    9. Berger, Tino & Richter, Julia & Wong, Benjamin, 2022. "A unified approach for jointly estimating the business and financial cycle, and the role of financial factors," Journal of Economic Dynamics and Control, Elsevier, vol. 136(C).
    10. James D. Hamilton, 2018. "Why You Should Never Use the Hodrick-Prescott Filter," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 831-843, December.
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    Citations

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    Cited by:

    1. Granados, Camilo & Parra-Amado, Daniel, 2024. "Estimating the output gap after COVID: How to address unprecedented macroeconomic variations," Economic Modelling, Elsevier, vol. 135(C).
    2. Christian Ochsner & Christopher Zuber, 2022. "Die Konjunkturbereinigung der Schuldenbremse: ein Plädoyer für methodische Reformen [The Cyclical Adjustment Procedure of the German Debt Brake: a Plea for Methodical Reforms]," Wirtschaftsdienst, Springer;ZBW - Leibniz Information Centre for Economics, vol. 102(11), pages 822-825, November.

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    More about this item

    Keywords

    output gap; Germany; nowcast; mixed frequency; vector-autoregression;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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