IDEAS home Printed from https://ideas.repec.org/a/eee/poleco/v34y2014icp157-166.html
   My bibliography  Save this article

The impact of preferences on early warning systems — The case of the European Commission's Scoreboard

Author

Listed:
  • Knedlik, Tobias

Abstract

The European Commission's Scoreboard of Macroeconomic Imbalances is a rare case of a publicly released early warning system. It allows the preferences of the politicians involved to be analysed with regard to the two potential errors of an early warning system — missing a crisis and issuing a false alarm. These preferences might differ with the institutional setting. Such an analysis is done for the first time in this article for early warning systems in general by using a standard signals approach, including a preference-based optimisation approach, to set thresholds. It is shown that, in general, the thresholds of the Commission's Scoreboard are rather tight (resulting in more alarm signals), as compared to a neutral stand. Based on political economy considerations the result could have been expected.

Suggested Citation

  • Knedlik, Tobias, 2014. "The impact of preferences on early warning systems — The case of the European Commission's Scoreboard," European Journal of Political Economy, Elsevier, vol. 34(C), pages 157-166.
  • Handle: RePEc:eee:poleco:v:34:y:2014:i:c:p:157-166
    DOI: 10.1016/j.ejpoleco.2014.01.008
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0176268014000093
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejpoleco.2014.01.008?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Tobias Knedlik & Gregor Von Schweinitz, 2012. "Macroeconomic Imbalances as Indicators for Debt Crises in Europe," Journal of Common Market Studies, Wiley Blackwell, vol. 50(5), pages 726-745, September.
    2. Carmen M. Reinhart & Graciela L. Kaminsky, 1999. "The Twin Crises: The Causes of Banking and Balance-of-Payments Problems," American Economic Review, American Economic Association, vol. 89(3), pages 473-500, June.
    3. Alessi, Lucia & Detken, Carsten, 2011. "Quasi real time early warning indicators for costly asset price boom/bust cycles: A role for global liquidity," European Journal of Political Economy, Elsevier, vol. 27(3), pages 520-533, September.
    4. Hali J. Edison, 2003. "Do indicators of financial crises work? An evaluation of an early warning system," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 8(1), pages 11-53.
    5. Laffont, Jean-Jacques, 2001. "Incentives and Political Economy," OUP Catalogue, Oxford University Press, number 9780199248681, Decembrie.
    6. Bussiere, Matthieu & Fratzscher, Marcel, 2008. "Low probability, high impact: Policy making and extreme events," Journal of Policy Modeling, Elsevier, vol. 30(1), pages 111-121.
    7. Demirguc, Asli & Detragiache, Enrica, 2000. "Monitoring Banking Sector Fragility: A Multivariate Logit Approach," The World Bank Economic Review, World Bank, vol. 14(2), pages 287-307, May.
    8. El-Shagi, M. & Knedlik, T. & von Schweinitz, G., 2013. "Predicting financial crises: The (statistical) significance of the signals approach," Journal of International Money and Finance, Elsevier, vol. 35(C), pages 76-103.
    9. Bussiere, Matthieu & Fratzscher, Marcel, 2006. "Towards a new early warning system of financial crises," Journal of International Money and Finance, Elsevier, vol. 25(6), pages 953-973, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dany-Knedlik, Geraldine & Kämpfe, Martina & Knedlik, Tobias, 2021. "The appropriateness of the macroeconomic imbalance procedure for Central and Eastern European Countries," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 48(1), pages 123-139.
    2. Pirschel, Inske, 2016. "Forecasting euro area recessions in real-time," Kiel Working Papers 2020, Kiel Institute for the World Economy (IfW Kiel).
    3. Maria Siranova & Marek Radvanský, 2018. "Performance of the Macroeconomic Imbalance Procedure in light of historical experience in the CEE region," Journal of Economic Policy Reform, Taylor & Francis Journals, vol. 21(4), pages 335-352, October.
    4. Gould, David M. & Melecky, Martin & Panterov, Georgi, 2016. "Finance, growth and shared prosperity: Beyond credit deepening," Journal of Policy Modeling, Elsevier, vol. 38(4), pages 737-758.
    5. Claudia M. Buch & Oliver Holtemöller, 2014. "Do we need new modelling approaches in macroeconomics?," Chapters, in: Ewald Nowotny & Doris Ritzberger-Grünwald & Peter Backé (ed.), Financial Cycles and the Real Economy, chapter 3, pages 36-58, Edward Elgar Publishing.
    6. Sondermann, David & Zorell, Nico, 2019. "A macroeconomic vulnerability model for the euro area," Working Paper Series 2306, European Central Bank.
    7. Ostrihoň, Filip, 2022. "Exploring macroeconomic imbalances through EU Alert Mechanism Reports," European Journal of Political Economy, Elsevier, vol. 75(C).
    8. Boysen-Hogrefe, Jens & Jannsen, Nils & Plödt, Martin & Schwarzmüller, Tim, 2015. "An empirical evaluation of macroeconomic surveillance in the European Union," Kiel Working Papers 2014, Kiel Institute for the World Economy (IfW Kiel).
    9. Krzysztof Biegun & Jacek Karwowski & Piotr Luty, 2021. "How Effective is Macroeconomic Imbalance Procedure (MIP) in Predicting Negative Macroeconomic Phenomena?," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 3), pages 822-837.
    10. Erhart, Szilard, 2019. "Exposition, climax, denouement: Life-cycle evaluation of the recent financial crisis in the EU by linking the ESRB financial crisis database to the European Commission's Macroeconomic Imbalance Proced," ESRB Working Paper Series 102, European Systemic Risk Board.

    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. Knedlik, Tobias, 2012. "The European Commission’s Scoreboard of Macroeconomic Imbalances – The Impact of Preferences on an Early Warning System," IWH Discussion Papers 10/2012, Halle Institute for Economic Research (IWH).
    2. Sarlin, Peter & von Schweinitz, Gregor, 2021. "Optimizing Policymakers’ Loss Functions In Crisis Prediction: Before, Within Or After?," Macroeconomic Dynamics, Cambridge University Press, vol. 25(1), pages 100-123, January.
    3. von Schweinitz, Gregor & Sarlin, Peter, 2015. "Signaling Crises: How to Get Good Out-of-Sample Performance Out of the Early Warning System," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112964, Verein für Socialpolitik / German Economic Association.
    4. Lo Duca, Marco & Koban, Anne & Basten, Marisa & Bengtsson, Elias & Klaus, Benjamin & Kusmierczyk, Piotr & Lang, Jan Hannes & Detken, Carsten & Peltonen, Tuomas, 2017. "A new database for financial crises in European countries," ESRB Occasional Paper Series 13, European Systemic Risk Board.
    5. El-Shagi, M. & Knedlik, T. & von Schweinitz, G., 2013. "Predicting financial crises: The (statistical) significance of the signals approach," Journal of International Money and Finance, Elsevier, vol. 35(C), pages 76-103.
    6. Tobias Knedlik & Gregor Von Schweinitz, 2012. "Macroeconomic Imbalances as Indicators for Debt Crises in Europe," Journal of Common Market Studies, Wiley Blackwell, vol. 50(5), pages 726-745, September.
    7. Geraldine Dany-Knedlik & Martina Kämpfe & Tobias Knedlik, 2021. "The appropriateness of the macroeconomic imbalance procedure for Central and Eastern European Countries," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 48(1), pages 123-139, February.
    8. Betz, Frank & Oprică, Silviu & Peltonen, Tuomas A. & Sarlin, Peter, 2014. "Predicting distress in European banks," Journal of Banking & Finance, Elsevier, vol. 45(C), pages 225-241.
    9. Oet, Mikhail V. & Gramlich, Dieter & Sarlin, Peter, 2016. "Evaluating measures of adverse financial conditions," Journal of Financial Stability, Elsevier, vol. 27(C), pages 234-249.
    10. Makram El-Shagi & Gregor von Schweinitz, 2016. "Qual VAR revisited: Good forecast, bad story," Journal of Applied Economics, Universidad del CEMA, vol. 19, pages 293-322, November.
    11. Markus Holopainen & Peter Sarlin, 2015. "Toward robust early-warning models: A horse race, ensembles and model uncertainty," Papers 1501.04682, arXiv.org, revised Apr 2016.
    12. Beutel, Johannes & List, Sophia & von Schweinitz, Gregor, 2019. "Does machine learning help us predict banking crises?," Journal of Financial Stability, Elsevier, vol. 45(C).
    13. Tristan Nguyen & Nguyen Ngoc Duy, 2017. "Developing an Early Warning System for Financial Crises in Vietnam," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 7(4), pages 413-430, April.
    14. El-Shagi, Makram & Kelly, Logan, 2019. "What can we learn from country-level liquidity in the EMU?," Journal of Financial Stability, Elsevier, vol. 42(C), pages 75-83.
    15. Panayotis Michaelides & Mike Tsionas & Panos Xidonas, 2020. "A Bayesian Signals Approach for the Detection of Crises," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(3), pages 551-585, September.
    16. Mikkel Hermansen & Oliver Röhn, 2017. "Economic resilience: The usefulness of early warning indicators in OECD countries," OECD Journal: Economic Studies, OECD Publishing, vol. 2016(1), pages 9-35.
    17. Beutel, Johannes & List, Sophia & von Schweinitz, Gregor, 2018. "An evaluation of early warning models for systemic banking crises: Does machine learning improve predictions?," Discussion Papers 48/2018, Deutsche Bundesbank.
    18. Tölö, Eero, 2020. "Predicting systemic financial crises with recurrent neural networks," Journal of Financial Stability, Elsevier, vol. 49(C).
    19. K. Batu Tunay, 2010. "Banking Crises and Early Warning Systems: A Model Suggestion for Turkish Banking Sector," Journal of BRSA Banking and Financial Markets, Banking Regulation and Supervision Agency, vol. 4(1), pages 9-46.
    20. Alessi, Lucia & Detken, Carsten, 2018. "Identifying excessive credit growth and leverage," Journal of Financial Stability, Elsevier, vol. 35(C), pages 215-225.

    More about this item

    Keywords

    Early warning system; Scoreboard; Preferences; Incentives; Political economy;
    All these keywords.

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • F47 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Forecasting and Simulation: Models and Applications
    • F53 - International Economics - - International Relations, National Security, and International Political Economy - - - International Agreements and Observance; International Organizations

    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:eee:poleco:v:34:y:2014:i:c:p:157-166. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/505544 .

    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.