IDEAS home Printed from https://ideas.repec.org/p/imf/imfwpa/2019-296.html
   My bibliography  Save this paper

Autonomous Factor Forecast Quality: The Case of the Eurosystem

Author

Listed:
  • Mr. Romain M Veyrune
  • Shaoyu Guo

Abstract

The publication of liquidity forecasts can be understood as part of central banks’ push toward greater transparency regarding monetary policy implementation. However, the advantages of transparency can only be realized if the information provided is accurate and reliable. This paper (1) provides an overview of the international practice of publishing the forecasts; (2) proposes and implements a framework to evaluate the accuracy and reliability of forecasts using the long history of Eurosystem forecasts as a case study; and (3) analyzes the Eurosystem forecast errors to determine the factors influencing forecast quality. A supporting factor for a high-quality forecast is the contemporaneousness of the information used, whereas money market segmentation can weigh on forecast quality.

Suggested Citation

  • Mr. Romain M Veyrune & Shaoyu Guo, 2019. "Autonomous Factor Forecast Quality: The Case of the Eurosystem," IMF Working Papers 2019/296, International Monetary Fund.
  • Handle: RePEc:imf:imfwpa:2019/296
    as

    Download full text from publisher

    File URL: http://www.imf.org/external/pubs/cat/longres.aspx?sk=48861
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Froot, Kenneth A, 1989. " New Hope for the Expectations Hypothesis of the Term Structure of Interest Rates," Journal of Finance, American Finance Association, vol. 44(2), pages 283-305, June.
    2. N. Nergiz Dincer & Barry Eichengreen, 2014. "Central Bank Transparency and Independence: Updates and New Measures," International Journal of Central Banking, International Journal of Central Banking, vol. 10(1), pages 189-259, March.
    3. Frankel, Jeffrey A & Froot, Kenneth A, 1987. "Using Survey Data to Test Standard Propositions Regarding Exchange Rate Expectations," American Economic Review, American Economic Association, vol. 77(1), pages 133-153, March.
    4. Ms. Inci Ötker, 2007. "Moving to Greater Exchange Rate Flexibility: Operational Aspects Based on Lessons from Detailed Country Experiences," IMF Occasional Papers 2007/005, International Monetary Fund.
    5. Andrew Patton & Allan Timmermann, 2012. "Forecast Rationality Tests Based on Multi-Horizon Bounds," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 1-17.
    6. 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.
    7. Kraenzlin, Sébastien & Schlegel, Martin, 2012. "Bidding behavior in the SNB’s repo auctions," Journal of International Money and Finance, Elsevier, vol. 31(2), pages 170-188.
    8. Bindseil, Ulrich, 2001. "Central bank forecasts of liquidity factors: Quality, publication and the control of the overnight rate," Working Paper Series 70, European Central Bank.
    9. Vogel, Edgar, 2016. "Forward looking behavior in ECB liquidity auctions: Evidence from the pre-crisis period," Journal of International Money and Finance, Elsevier, vol. 61(C), pages 120-142.
    10. Beirne, John, 2012. "The EONIA spread before and during the crisis of 2007–2009: The role of liquidity and credit risk," Journal of International Money and Finance, Elsevier, vol. 31(3), pages 534-551.
    11. Alberto Cabrero & Gonzalo Camba-Mendez & Astrid Hirsch & Fernando Nieto, 2009. "Modelling the daily banknotes in circulation in the context of the liquidity management of the European Central Bank," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(3), pages 194-217.
    12. Alvarez, Inmaculada & Casavecchia, Fabio & Luca, Marino De & Duering, Alexander & Eser, Fabian & Helmus, Caspar & Hemous, Christophe & Herrala, Niko & Jakovicka, Julija & Russo, Michelina Lo & Pasqual, 2017. "The use of the Eurosystem’s monetary policy instruments and operational framework since 2012," Occasional Paper Series 188, European Central Bank.
    13. Mr. Bernard J Laurens & Mr. Kelly Eckhold & Mr. Darryl King & Mr. Nils O Maehle & Abdul Naseer & Alain Durré, 2015. "The Journey to Inflation Targeting: Easier Said than Done The Case for Transitional Arrangements along the Road," IMF Working Papers 2015/136, International Monetary Fund.
    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. Markiewicz, Agnieszka & Pick, Andreas, 2014. "Adaptive learning and survey data," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PB), pages 685-707.
    2. Miah, Fazlul & Khalifa, Ahmed Ali & Hammoudeh, Shawkat, 2016. "Further evidence on the rationality of interest rate expectations: A comprehensive study of developed and emerging economies," Economic Modelling, Elsevier, vol. 54(C), pages 574-590.
    3. Cathy Yi-Hsuan Chen & Thomas C. Chiang, 2017. "Surprises, sentiments, and the expectations hypothesis of the term structure of interest rates," Review of Quantitative Finance and Accounting, Springer, vol. 49(1), pages 1-28, July.
    4. Christopher J. Neely & Lucio Sarno, 2002. "How well do monetary fundamentals forecast exchange rates?," Review, Federal Reserve Bank of St. Louis, vol. 84(Sep), pages 51-74.
    5. 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.
    6. Baumeister, Christiane, 2021. "Measuring Market Expectations," CEPR Discussion Papers 16520, C.E.P.R. Discussion Papers.
    7. Hung, Kuo-Che & Ma, Tai, 2017. "The effects of expectations-based monetary policy on international stock markets: An application of heterogeneous agent model," International Review of Economics & Finance, Elsevier, vol. 47(C), pages 70-87.
    8. Faruk Balli & Elsayed Mousa Elsamadisy, 2012. "Modelling the currency in circulation for the State of Qatar," International Journal of Islamic and Middle Eastern Finance and Management, Emerald Group Publishing Limited, vol. 5(4), pages 321-339, November.
    9. Schmeling, Maik & Schrimpf, Andreas & Steffensen, Sigurd A.M., 2022. "Monetary policy expectation errors," Journal of Financial Economics, Elsevier, vol. 146(3), pages 841-858.
    10. Ellen, Saskia ter & Zwinkels, Remco C.J., 2010. "Oil price dynamics: A behavioral finance approach with heterogeneous agents," Energy Economics, Elsevier, vol. 32(6), pages 1427-1434, November.
    11. Bragoli, Daniela & Modugno, Michele, 2017. "A now-casting model for Canada: Do U.S. variables matter?," International Journal of Forecasting, Elsevier, vol. 33(4), pages 786-800.
    12. Alberto Cabrero & Gonzalo Camba-Mendez & Astrid Hirsch & Fernando Nieto, 2009. "Modelling the daily banknotes in circulation in the context of the liquidity management of the European Central Bank," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(3), pages 194-217.
    13. Bacchetta, Philippe & Mertens, Elmar & van Wincoop, Eric, 2009. "Predictability in financial markets: What do survey expectations tell us?," Journal of International Money and Finance, Elsevier, vol. 28(3), pages 406-426, April.
    14. Arai, Natsuki, 2014. "Using forecast evaluation to improve the accuracy of the Greenbook forecast," International Journal of Forecasting, Elsevier, vol. 30(1), pages 12-19.
    15. Della Corte, Pasquale & Sarno, Lucio & Thornton, Daniel L., 2008. "The expectation hypothesis of the term structure of very short-term rates: Statistical tests and economic value," Journal of Financial Economics, Elsevier, vol. 89(1), pages 158-174, July.
    16. Faust, Jon & Wright, Jonathan H., 2013. "Forecasting Inflation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 2-56, Elsevier.
    17. Pierre L. Siklos, 2016. "Forecast Disagreement and the Inflation Outlook: New International Evidence," IMES Discussion Paper Series 16-E-03, Institute for Monetary and Economic Studies, Bank of Japan.
    18. Dick, Christian D. & Schmeling, Maik & Schrimpf, Andreas, 2013. "Macro-expectations, aggregate uncertainty, and expected term premia," European Economic Review, Elsevier, vol. 58(C), pages 58-80.
    19. El-Shagi, Makram & Tochkov, Kiril, 2022. "Divisia monetary aggregates for Russia: Money demand, GDP nowcasting and the price puzzle," Economic Systems, Elsevier, vol. 46(4).
    20. Baghestani, Hamid & Toledo, Hugo, 2017. "Do analysts' forecasts of term spread differential help predict directional change in exchange rates?," International Review of Economics & Finance, Elsevier, vol. 47(C), pages 62-69.

    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:imf:imfwpa:2019/296. 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: Akshay Modi (email available below). General contact details of provider: https://edirc.repec.org/data/imfffus.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.