IDEAS home Printed from https://ideas.repec.org/p/ptu/wpaper/w202317.html
   My bibliography  Save this paper

Navigating with a compass: Charting the course of underlying inflation

Author

Listed:
  • António Rua
  • Nuno Lourenço
  • João Quelhas

Abstract

We propose a novel tool to gauge price pressures resorting to circular statistics, the so-called inflation compass. We show that it provides a reliable indication on inflationary pressures in the euro area by focusing on key episodes of high and low inflation since the monetary union inception. Unlike most alternative measures of underlying inflation, the inflation compass does not exclude any subitems of inflation, ensuring that all disaggregated information is taken on board. Moreover, it is not subject to revisions, providing policymakers with real-time signals about the course of underlying inflation, while being easily understood and visually appealing. We also provide evidence of the usefulness of the inflation compass to forecast overall inflation up to 36 months ahead, even during periods of increased turbulence, such as those marked by the COVID-19 pandemic or the recent inflation surge. Our findings indicate that the inflation compass surpasses other widely used measures of underlying inflation for the euro area, leading to statistically significant improvements in forecast accuracy. Lastly, we show that our approach can handle large-dimensional data by leveraging on finer product-level and country-level data. In such environment, the inflation compass still exhibits higher accuracy, underscoring its robustness and reliability.

Suggested Citation

  • António Rua & Nuno Lourenço & João Quelhas, 2023. "Navigating with a compass: Charting the course of underlying inflation," Working Papers w202317, Banco de Portugal, Economics and Research Department.
  • Handle: RePEc:ptu:wpaper:w202317
    as

    Download full text from publisher

    File URL: https://www.bportugal.pt/sites/default/files/anexos/papers/wp202317.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Cogley, Timothy, 2002. "A Simple Adaptive Measure of Core Inflation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 34(1), pages 94-113, February.
    2. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    3. Nuno Lourenço & António Rua, 2023. "Correction to: Business cycle clocks: Time to get circular," Empirical Economics, Springer, vol. 65(5), pages 2499-2499, November.
    4. Nuno Lourenço & António Rua, 2023. "Business cycle clocks: Time to get circular," Empirical Economics, Springer, vol. 65(4), pages 1513-1541, October.
    5. Chahad, Mohammed & Hofmann-Drahonsky, Anna-Camilla & Page, Adrian & Tirpák, Marcel & Meunier, Baptiste, 2022. "What explains recent errors in the inflation projections of Eurosystem and ECB staff?," Economic Bulletin Boxes, European Central Bank, vol. 3.
    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. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    2. Pincheira-Brown, Pablo & Selaive, Jorge & Nolazco, Jose Luis, 2019. "Forecasting inflation in Latin America with core measures," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1060-1071.
    3. Pincheira, Pablo & Selaive, Jorge & Nolazco, Jose Luis, 2016. "The Evasive Predictive Ability of Core Inflation," MPRA Paper 68704, University Library of Munich, Germany.
    4. Carstensen, Kai & Heinrich, Markus & Reif, Magnus & Wolters, Maik H., 2020. "Predicting ordinary and severe recessions with a three-state Markov-switching dynamic factor model," International Journal of Forecasting, Elsevier, vol. 36(3), pages 829-850.
    5. Eric Ghysels & Leonardo Iania & Jonas Striaukas, 2018. "Quantile-based Inflation Risk Models," Working Paper Research 349, National Bank of Belgium.
    6. Boysen-Hogrefe, Jens & Dovern, Jonas & Gern, Klaus-Jürgen & Jannsen, Nils & Van Roye, Björn & Scheide, Joachim & Boss, Alfred & Groll, Dominik & Meier, Carsten-Patrick, 2010. "Weltkonjunktur und deutsche Konjunktur im Winter 2009," Kiel Discussion Papers 470/471, Kiel Institute for the World Economy (IfW Kiel).
    7. Craig S. Hakkio, 2008. "PCE and CPI inflation differentials: converting inflation forecasts," Economic Review, Federal Reserve Bank of Kansas City, vol. 93(Q I), pages 51-68.
    8. Liu, Shan & Li, Ziwei, 2023. "Macroeconomic attention and oil futures volatility prediction," Finance Research Letters, Elsevier, vol. 57(C).
    9. Faria, Gonçalo & Verona, Fabio, 2023. "Forecast combination in the frequency domain," Bank of Finland Research Discussion Papers 1/2023, Bank of Finland.
    10. Papapostolou, Nikos C. & Pouliasis, Panos K. & Nomikos, Nikos K. & Kyriakou, Ioannis, 2016. "Shipping investor sentiment and international stock return predictability," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 96(C), pages 81-94.
    11. Galvão, Ana Beatriz, 2013. "Changes in predictive ability with mixed frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 395-410.
    12. Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2023. "Large Time‐Varying Volatility Models for Hourly Electricity Prices," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 545-573, June.
    13. Wang, Yubao & Huang, Xiaozhou & Huang, Zhendong, 2024. "Energy-related uncertainty and Chinese stock market returns," Finance Research Letters, Elsevier, vol. 62(PB).
    14. Su, Yuandong & Lu, Xinjie & Zeng, Qing & Huang, Dengshi, 2022. "Good air quality and stock market returns," Research in International Business and Finance, Elsevier, vol. 62(C).
    15. Mehmet Balcilar & Elie Bouri & Rangan Gupta & Christian Pierdzioch, 2021. "El Niño, La Niña, and the Forecastability of the Realized Variance of Heating Oil Price Movements," Sustainability, MDPI, vol. 13(14), pages 1-23, July.
    16. Dauwe, Alexander & Moura, Marcelo L., 2011. "Forecasting the term structure of the Euro Market using Principal Component Analysis," Insper Working Papers wpe_233, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    17. Chen, Jian & Jiang, Fuwei & Liu, Yangshu & Tu, Jun, 2017. "International volatility risk and Chinese stock return predictability," Journal of International Money and Finance, Elsevier, vol. 70(C), pages 183-203.
    18. Salisu, Afees A. & Adekunle, Wasiu & Alimi, Wasiu A. & Emmanuel, Zachariah, 2019. "Predicting exchange rate with commodity prices: New evidence from Westerlund and Narayan (2015) estimator with structural breaks and asymmetries," Resources Policy, Elsevier, vol. 62(C), pages 33-56.
    19. Barbara Rossi, 2013. "Exchange Rate Predictability," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1063-1119, December.
    20. Chang, Andrew C. & Hanson, Tyler J., 2016. "The accuracy of forecasts prepared for the Federal Open Market Committee," Journal of Economics and Business, Elsevier, vol. 83(C), pages 23-43.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ptu:wpaper:w202317. 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: DEE-NTD (email available below). General contact details of provider: https://edirc.repec.org/data/bdpgvpt.html .

    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.