IDEAS home Printed from https://ideas.repec.org/a/wly/jforec/v44y2025i3p978-1008.html
   My bibliography  Save this article

Evaluating Inflation Forecasts in the Euro Area and the Role of the ECB

Author

Listed:
  • Bertrand Candelon
  • Francesco Roccazzella

Abstract

This paper evaluates the informative value of the ECB inflation forecasts vis‐à‐vis other institutional and model‐based forecasts in the euro area using ex post optimal combinations of forecasts and nonnegative weights. From a methodological perspective, we adapt the corresponding forecast encompassing test to the constrained parameter space, showcasing its superior performance over traditional encompassing tests in both size and power properties. Empirically, the combining weights and the forecast encompassing test reveal that the ECB was the most informative forecaster of euro area inflation over the 2009–2021 period. This changed in 2022: The ECB lost its position as the most informative forecaster, and when using rolling windows to estimate the combining weights using a rolling window, we find an important decline in the ECB's weight over time. This time dependency can be associated with the economic environment and, in particular, the level of uncertainty, the monetary policy, and the macro‐financial conditions in which the ECB operates.

Suggested Citation

  • Bertrand Candelon & Francesco Roccazzella, 2025. "Evaluating Inflation Forecasts in the Euro Area and the Role of the ECB," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(3), pages 978-1008, April.
  • Handle: RePEc:wly:jforec:v:44:y:2025:i:3:p:978-1008
    DOI: 10.1002/for.3235
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/for.3235
    Download Restriction: no

    File URL: https://libkey.io/10.1002/for.3235?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. Gambetti, Paolo & Gauthier, Geneviève & Vrins, Frédéric, 2019. "Recovery rates: Uncertainty certainly matters," Journal of Banking & Finance, Elsevier, vol. 106(C), pages 371-383.
    2. J. Paul Elhorst & Marco Gross & Eugen Tereanu, 2021. "Cross‐Sectional Dependence And Spillovers In Space And Time: Where Spatial Econometrics And Global Var Models Meet," Journal of Economic Surveys, Wiley Blackwell, vol. 35(1), pages 192-226, February.
    3. Svensson, Lars E. O., 1997. "Inflation forecast targeting: Implementing and monitoring inflation targets," European Economic Review, Elsevier, vol. 41(6), pages 1111-1146, June.
    4. Jianqing Fan & Yuan Liao & Martina Mincheva, 2013. "Large covariance estimation by thresholding principal orthogonal complements," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 75(4), pages 603-680, September.
    5. Ravi Jagannathan & Tongshu Ma, 2003. "Risk Reduction in Large Portfolios: Why Imposing the Wrong Constraints Helps," Journal of Finance, American Finance Association, vol. 58(4), pages 1651-1683, August.
    6. Jonas Dovern & Ulrich Fritsche & Jiri Slacalek, 2012. "Disagreement Among Forecasters in G7 Countries," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1081-1096, November.
    7. Capistrán, Carlos, 2008. "Bias in Federal Reserve inflation forecasts: Is the Federal Reserve irrational or just cautious?," Journal of Monetary Economics, Elsevier, vol. 55(8), pages 1415-1427, November.
    8. Candelon, Bertrand & Luisi, Angelo & Roccazzella, Francesco, 2022. "Fragmentation in the European Monetary Union: Is it really over?," Journal of International Money and Finance, Elsevier, vol. 122(C).
    9. Saikkonen, Pentti & Lutkepohl, Helmut, 2000. "Testing for the Cointegrating Rank of a VAR Process with Structural Shifts," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(4), pages 451-464, October.
    10. Lars E O Svensson, 2005. "Monetary Policy with Judgment: Forecast Targeting," International Journal of Central Banking, International Journal of Central Banking, vol. 1(1), May.
    11. Jing Cynthia Wu & Fan Dora Xia, 2020. "Negative interest rate policy and the yield curve," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(6), pages 653-672, September.
    12. Cornand, Camille & Hubert, Paul, 2020. "On the external validity of experimental inflation forecasts: A comparison with five categories of field expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 110(C).
    13. Busetti, Fabio & Marcucci, Juri, 2013. "Comparing forecast accuracy: A Monte Carlo investigation," International Journal of Forecasting, Elsevier, vol. 29(1), pages 13-27.
    14. Ang, Andrew & Bekaert, Geert & Wei, Min, 2007. "Do macro variables, asset markets, or surveys forecast inflation better?," Journal of Monetary Economics, Elsevier, vol. 54(4), pages 1163-1212, May.
    15. De Grauwe, Paul & Ji, Yuemei, 2022. "The fragility of the Eurozone: Has it disappeared?," Journal of International Money and Finance, Elsevier, vol. 120(C).
    16. Roccazzella, Francesco & Gambetti, Paolo & Vrins, Frédéric, 2022. "Correction to: Optimal and robust combination of forecasts via constrained optimization and shrinkage," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1050-1050.
    17. Sebastiano Manzan, 2011. "Differential Interpretation in the Survey of Professional Forecasters," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43(5), pages 993-1017, August.
    18. Jianqing Fan & Jingjin Zhang & Ke Yu, 2012. "Vast Portfolio Selection With Gross-Exposure Constraints," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(498), pages 592-606, June.
    19. Saikkonen, Pentti & Lütkepohl, Helmut, 2000. "Testing For The Cointegrating Rank Of A Var Process With An Intercept," Econometric Theory, Cambridge University Press, vol. 16(3), pages 373-406, June.
    20. Roberto A. De Santis, 2019. "Redenomination Risk," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 51(8), pages 2173-2206, December.
    21. Clements,Michael & Hendry,David, 1998. "Forecasting Economic Time Series," Cambridge Books, Cambridge University Press, number 9780521634809, July.
    22. Roccazzella, Francesco & Gambetti, Paolo & Vrins, Frédéric, 2022. "Optimal and robust combination of forecasts via constrained optimization and shrinkage," International Journal of Forecasting, Elsevier, vol. 38(1), pages 97-116.
    23. Ledoit, Olivier & Wolf, Michael, 2003. "Improved estimation of the covariance matrix of stock returns with an application to portfolio selection," Journal of Empirical Finance, Elsevier, vol. 10(5), pages 603-621, December.
    24. repec:bla:jfinan:v:58:y:2003:i:4:p:1651-1684 is not listed on IDEAS
    25. Ben S. Bernanke & Frederic S. Mishkin, 1997. "Inflation Targeting: A New Framework for Monetary Policy?," Journal of Economic Perspectives, American Economic Association, vol. 11(2), pages 97-116, Spring.
    26. Patton, Andrew J. & Timmermann, Allan, 2010. "Why do forecasters disagree? Lessons from the term structure of cross-sectional dispersion," Journal of Monetary Economics, Elsevier, vol. 57(7), pages 803-820, October.
    27. Lutkepohl, Helmut & Saikkonen, Pentti, 2000. "Testing for the cointegrating rank of a VAR process with a time trend," Journal of Econometrics, Elsevier, vol. 95(1), pages 177-198, March.
    28. Kenneth Rogoff, 1985. "The Optimal Degree of Commitment to an Intermediate Monetary Target," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 100(4), pages 1169-1189.
    29. repec:spo:wpmain:info:hdl:2441/7t8isspkbs8hk8kol9kk9sjdl6 is not listed on IDEAS
    30. Andrade, Philippe & Le Bihan, Hervé, 2013. "Inattentive professional forecasters," Journal of Monetary Economics, Elsevier, vol. 60(8), pages 967-982.
    31. Alesina, Alberto & Gatti, Roberta, 1995. "Independent Central Banks: Low Inflation at No Cost?," American Economic Review, American Economic Association, vol. 85(2), pages 196-200, May.
    32. Silvia Ferrari & Francisco Cribari-Neto, 2004. "Beta Regression for Modelling Rates and Proportions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 31(7), pages 799-815.
    33. Ball, Laurence, 1992. "Why does high inflation raise inflation uncertainty?," Journal of Monetary Economics, Elsevier, vol. 29(3), pages 371-388, June.
    34. Favero, Carlo A., 2013. "Modelling and forecasting government bond spreads in the euro area: A GVAR model," Journal of Econometrics, Elsevier, vol. 177(2), pages 343-356.
    35. Camille Cornand & Paul Hubert, 2020. "On the external validity of experimental inflation forecasts: A comparison with five categories of field expectations," Post-Print halshs-02285233, HAL.
    36. David Harvey & Paul Newbold, 2000. "Tests for multiple forecast encompassing," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 471-482.
    37. Diebold, Francis X. & Shin, Minchul, 2019. "Machine learning for regularized survey forecast combination: Partially-egalitarian LASSO and its derivatives," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1679-1691.
    38. repec:hal:spmain:info:hdl:2441/7t8isspkbs8hk8kol9kk9sjdl6 is not listed on IDEAS
    39. Tilman Ehrbeck & Robert Waldmann, 1996. "Why Are Professional Forecasters Biased? Agency versus Behavioral Explanations," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 111(1), pages 21-40.
    40. Gross, Jonas & Zahner, Johannes, 2021. "What is on the ECB’s mind? Monetary policy before and after the global financial crisis," Journal of Macroeconomics, Elsevier, vol. 68(C).
    41. G. Kontogeorgos & K. Lambrias, 2022. "Evaluating the Eurosystem/ECB staff macroeconomic projections: The first 20 years," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 213-229, March.
    42. Sebastiano Manzan, 2011. "Differential Interpretation in the Survey of Professional Forecasters," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43(5), pages 993-1017, August.
    43. Andrew Atkeson & Lee E. Ohanian, 2001. "Are Phillips curves useful for forecasting inflation?," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 25(Win), pages 2-11.
    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. Roccazzella, Francesco & Candelon, Bertrand, 2022. "Should we care about ECB inflation expectations?," LIDAM Discussion Papers LFIN 2022004, Université catholique de Louvain, Louvain Finance (LFIN).
    2. Chini, Emilio Zanetti, 2023. "Can we estimate macroforecasters’ mis-behavior?," Journal of Economic Dynamics and Control, Elsevier, vol. 149(C).
    3. Benchimol, Jonathan & El-Shagi, Makram & Saadon, Yossi, 2022. "Do expert experience and characteristics affect inflation forecasts?," Journal of Economic Behavior & Organization, Elsevier, vol. 201(C), pages 205-226.
    4. Zhentao Shi & Liangjun Su & Tian Xie, 2020. "L2-Relaxation: With Applications to Forecast Combination and Portfolio Analysis," Papers 2010.09477, arXiv.org, revised Aug 2022.
    5. Li, You & Tay, Anthony, 2021. "The role of macroeconomic and policy uncertainty in density forecast dispersion," Journal of Macroeconomics, Elsevier, vol. 67(C).
    6. Jonas Dovern & Ulrich Fritsche & Jiri Slacalek, 2012. "Disagreement Among Forecasters in G7 Countries," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1081-1096, November.
    7. Olivier Coibion & Yuriy Gorodnichenko, 2015. "Information Rigidity and the Expectations Formation Process: A Simple Framework and New Facts," American Economic Review, American Economic Association, vol. 105(8), pages 2644-2678, August.
    8. Conrad, Christian & Lahiri, Kajal, 2023. "Heterogeneous expectations among professional forecasters," ZEW Discussion Papers 23-062, ZEW - Leibniz Centre for European Economic Research.
    9. Manzan, Sebastiano, 2021. "Are professional forecasters Bayesian?," Journal of Economic Dynamics and Control, Elsevier, vol. 123(C).
    10. Wasim Shahid Malik & Ather Maqsood Ahmed, 2010. "Taylor Rule and the Macroeconomic Performance in Pakistan," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 49(1), pages 37-56.
    11. Distaso, Walter & Roccazzella, Francesco & Vrins, Frédéric, 2023. "Business cycle and realized losses in the consumer credit industry," LIDAM Discussion Papers LFIN 2023007, Université catholique de Louvain, Louvain Finance (LFIN).
    12. Karlyn Mitchell & Douglas K. Pearce, 2017. "Direct Evidence on Sticky Information from the Revision Behavior of Professional Forecasters," Southern Economic Journal, John Wiley & Sons, vol. 84(2), pages 637-653, October.
    13. Qiu, Yajie & Deschamps, Bruno & Liu, Xiaoquan, 2024. "Uncertainty and macroeconomic forecasts: Evidence from survey data," Journal of Economic Behavior & Organization, Elsevier, vol. 224(C), pages 463-480.
    14. Cornand, Camille & Hubert, Paul, 2022. "Information frictions across various types of inflation expectations," European Economic Review, Elsevier, vol. 146(C).
    15. Capistrán, Carlos, 2008. "Bias in Federal Reserve inflation forecasts: Is the Federal Reserve irrational or just cautious?," Journal of Monetary Economics, Elsevier, vol. 55(8), pages 1415-1427, November.
    16. Sven Husmann & Antoniya Shivarova & Rick Steinert, 2020. "Company classification using machine learning," Papers 2004.01496, arXiv.org, revised May 2020.
    17. Donato Masciandaro, 2023. "How Elastic and Predictable Money Should Be: Flexible Monetary Policy Rules from the Great Moderation to the New Normal Times (1993-2023)," BAFFI CAREFIN Working Papers 23196, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    18. Raffaella Giacomini & Vasiliki Skreta & Javier Turen, 2015. "Models, Inattention and Expectation Updates," Discussion Papers 1602, Centre for Macroeconomics (CFM).
    19. Sven Husmann & Antoniya Shivarova & Rick Steinert, 2021. "Cross-validated covariance estimators for high-dimensional minimum-variance portfolios," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 35(3), pages 309-352, September.
    20. Camille Cornand & Paul Hubert, 2021. "Information frictions in inflation expectations among five types of economic agents," Working Papers halshs-03351632, HAL.

    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:44:y:2025:i:3:p:978-1008. 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.