IDEAS home Printed from https://ideas.repec.org/a/wly/jforec/v45y2026i3p1129-1144.html

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

Author

Listed:
  • Tino Berger
  • Christian Ochsner

Abstract

The German economy is an important economic driver in the Euro area in terms of gross domestic product, labor 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 3 months prior to a gross domestic product data release. To this end, we elicit a mixed‐frequency Bayesian vector‐autoregressive model (MF‐BVAR) using monthly information to form an expectations about the current‐quarter output gap. The mean absolute error of the MF‐BVAR nowcast compared to the final estimate is very small (0.28 percentage points) after only 1 month of observed data. Moreover, we show that business and consumer expectations, international trade, and labor market aggregates consistently explain large shares of variation in the German output gap. Finally, the MF‐BVAR procedure is very reliable, as it implies an output gap that is hardly revised ex post. This is particularly important for policymakers.

Suggested Citation

  • Tino Berger & Christian Ochsner, 2026. "Robust Real‐Time Estimates of the German Output Gap Based on a Multivariate Trend‐Cycle Decomposition," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 45(3), pages 1129-1144, April.
    • Handle: RePEc:wly:jforec:v:45:y:2026:i:3:p:1129-1144
    DOI: 10.1002/for.70079
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/for.70079
    Download Restriction: no
    File URL: https://libkey.io/10.1002/for.70079?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. James Morley & Benjamin Wong, 2020. "Estimating and accounting for the output gap with large Bayesian vector autoregressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 1-18, January.
    2. Karel Havik & Kieran Mc Morrow & Fabrice Orlandi & Christophe Planas & Rafal Raciborski & Werner Roeger & Alessandro Rossi & Anna Thum-Thysen & Valerie Vandermeulen, 2014. "The Production Function Methodology for Calculating Potential Growth Rates & Output Gaps," European Economy - Economic Papers 2008 - 2015 535, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    3. 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.
    4. Berger, Tino & Morley, James & Wong, Benjamin, 2023. "Nowcasting the output gap," Journal of Econometrics, Elsevier, vol. 232(1), pages 18-34.
      • Tino Berger & James Morley & Benjamin Wong, 2020. "Nowcasting the Output Gap," CAMA Working Papers 2020-78, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. Eickmeier, Sandra, 2007. "Business cycle transmission from the US to Germany--A structural factor approach," European Economic Review, Elsevier, vol. 51(3), pages 521-551, April.
    10. 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).
    11. 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.
    12. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Tino Berger & Christian Ochsner, 2022. "Tracking the German Business Cycle," MAGKS Papers on Economics 202212, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    3. Tore Dubbert & Adrian Schroeder, 2025. "Conditioning business and financial cycles on multivariate information," CQE Working Papers 11225, Center for Quantitative Economics (CQE), University of Muenster.
    4. Morley, James & Rodríguez-Palenzuela, Diego & Sun, Yiqiao & Wong, Benjamin, 2023. "Estimating the euro area output gap using multivariate information and addressing the COVID-19 pandemic," European Economic Review, Elsevier, vol. 153(C).
    5. Christian Glocker & Serguei Kaniovski & Philipp Wegmüller, 2026. "Estimating a weighted output gap for Switzerland: methodology and application," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 162(1), pages 1-25, December.
    6. Chalmovianský, Jakub & Němec, Daniel, 2022. "Assessing uncertainty of output gap estimates: Evidence from Visegrad countries," Economic Modelling, Elsevier, vol. 116(C).
    7. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Papers 2202.04146, arXiv.org, revised Oct 2024.
    8. Nataliia Ostapenko, 2022. "Do output gap estimates improve inflation forecasts in Slovakia?," Working and Discussion Papers WP 4/2022, Research Department, National Bank of Slovakia.
    9. Francesco Furlanetto & Kåre Hagelund & Frank Hansen & Ørjan Robstad, 2020. "Norges Bank Output Gap Estimates: Forecasting Properties, Reliability and Cyclical Sensitivity," Working Paper 2020/7, Norges Bank.
    10. Andrew B. Martinez & Alexander D. Schibuola & David Beckworth, 2026. "The Reliability of the Nominal GDP Expectations Gap," International Journal of Central Banking, International Journal of Central Banking, vol. 22(2), pages 525-557, April.
    11. Bassi, Federico, 2024. "Excess capacity and hysteresis in EU Countries. A structural approach," Structural Change and Economic Dynamics, Elsevier, vol. 71(C), pages 116-134.
    12. Alessandro Barbarino & Travis J. Berge & Han Chen & Andrea Stella, 2020. "Which Output Gap Estimates Are Stable in Real Time and Why?," Finance and Economics Discussion Series 2020-102, Board of Governors of the Federal Reserve System (U.S.).
    13. Berger, Tino & Morley, James & Wong, Benjamin, 2023. "Nowcasting the output gap," Journal of Econometrics, Elsevier, vol. 232(1), pages 18-34.
      • Tino Berger & James Morley & Benjamin Wong, 2020. "Nowcasting the Output Gap," CAMA Working Papers 2020-78, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    14. Josefine Quast & Maik H. Wolters, 2023. "The Federal Reserve's output gap: The unreliability of real‐time reliability tests," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(7), pages 1101-1111, November.
    15. Francesco Furlanetto & Kåre Hagelund & Frank Hansen & Ørjan Robstad, 2023. "Norges Bank Output Gap Estimates: Forecasting Properties, Reliability, Cyclical Sensitivity and Hysteresis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(1), pages 238-267, February.
    16. Alessandro Barbarino & Travis J. Berge & Andrea Stella, 2024. "The stability and economic relevance of output gap estimates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(6), pages 1065-1081, September.
    17. Biolsi, Christopher, 2023. "Do the Hamilton and Beveridge–Nelson filters provide the same information about output gaps? An empirical comparison for practitioners," Journal of Macroeconomics, Elsevier, vol. 75(C).
    18. Kamber, Güneş & Morley, James & Wong, Benjamin, 2025. "Trend-cycle decomposition in the presence of large shocks," Journal of Economic Dynamics and Control, Elsevier, vol. 173(C).
    19. Kumar, Labesh, 2026. "The Output Gap: Method Choice, Data Revisions, and Policy Implications," MPRA Paper 127829, University Library of Munich, Germany.
    20. 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).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:jforec:v:45:y:2026:i:3:p:1129-1144. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www3.interscience.wiley.com/cgi-bin/jhome/2966 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.