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On policymakers' loss function and the evaluation of early warning systems

  • Sarlin, Peter

This paper introduces a new loss function and Usefulness measure for evaluating early warning systems (EWSs) that incorporate policymakers' preferences between issuing false alarms and missing crises, as well as individual observations. The novelty derives from three enhancements: i) accounting for unconditional probabilities of the classes, ii) computing the proportion of available Usefulness that the model captures, and iii) weighting observations by their importance for the policymaker. The proposed measures are model free such that they can be used to assess signals issued by any type of EWS, such as logit and probit analysis and the signaling approach, and flexible for any type of crisis EWSs, such as banking, debt and currency crises. Applications to two renowned EWSs, and comparisons to two commonly used evaluation measures, illustrate three key implications of the new measures: i) further highlights the importance of an objective criterion for choosing a final specification and threshold value, and for models to be useful ii) the need to be more concerned about the rare class and iii) the importance of correctly classifying observations of the most relevant entities. Beyond financial stability surveillance, this paper also opens the door for cost-sensitive evaluations of predictive models in other tasks. JEL Classification: E44, E58, F01, F37, G01

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Paper provided by European Central Bank in its series Working Paper Series with number 1509.

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Date of creation: Feb 2013
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Handle: RePEc:ecb:ecbwps:20131509
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  1. Sarlin, Peter & Peltonen, Tuomas A., 2011. "Mapping the state of financial stability," BOFIT Discussion Papers 18/2011, Bank of Finland, Institute for Economies in Transition.
  2. Graciela Laura Kaminsky, 1997. "Leading Indicators of Currency Crises," IMF Working Papers 97/79, International Monetary Fund.
  3. Berg, Andrew & Pattillo, Catherine, 1999. "Predicting currency crises:: The indicators approach and an alternative," Journal of International Money and Finance, Elsevier, vol. 18(4), pages 561-586, August.
  4. El-Shagi, Makram & Knedlik, Tobias & von Schweinitz, Gregor, 2012. "Predicting Financial Crises: The (Statistical) Significance of the Signals Approach," IWH Discussion Papers 3/2012, Halle Institute for Economic Research (IWH).
  5. Fuertes, Ana-Maria & Kalotychou, Elena, 2006. "Early warning systems for sovereign debt crises: The role of heterogeneity," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1420-1441, November.
  6. Enrica Detragiache & Asli Demirgüç-Kunt, 1999. "Monitoring Banking Sector Fragility; A Multivariate Logit Approach," IMF Working Papers 99/147, International Monetary Fund.
  7. Jeffrey A. Frankel & Andrew K. Rose, 1996. "Currency crashes in emerging markets: an empirical treatment," International Finance Discussion Papers 534, Board of Governors of the Federal Reserve System (U.S.).
  8. Òscar Jordà & Moritz Schularick & Alan M Taylor, 2011. "Financial Crises, Credit Booms, and External Imbalances: 140 Years of Lessons," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 59(2), pages 340-378, June.
  9. 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.
  10. Abhyankar, Abhay & Sarno, Lucio & Valente, Giorgio, 2004. "Exchange Rates and Fundamentals: Evidence on the Economic Value of Predictability," CEPR Discussion Papers 4365, C.E.P.R. Discussion Papers.
  11. Òscar Jordà & Alan M. Taylor, 2011. "Performance Evaluation of Zero Net-Investment Strategies," NBER Working Papers 17150, National Bureau of Economic Research, Inc.
  12. Kasper Lund-Jensen, 2012. "Monitoring Systemic Risk Basedon Dynamic Thresholds," IMF Working Papers 12/159, International Monetary Fund.
  13. Sarlin, Peter & Peltonen, Tuomas A., 2011. "Mapping the state of financial stability," Working Paper Series 1382, European Central Bank.
  14. 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.
  15. Mathias Drehmann & Claudio Borio & Kostas Tsatsaronis, 2011. "Anchoring Countercyclical Capital Buffers: The role of Credit Aggregates," International Journal of Central Banking, International Journal of Central Banking, vol. 7(4), pages 189-240, December.
  16. A. Berg & C. Pattillo, 1999. "What Caused the Asian Crises: An Early Warning System Approach," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 28(3), pages 285-334, November.
  17. Axel Schimmelpfennig & Nouriel Roubini & Paolo Manasse, 2003. "Predicting Sovereign Debt Crises," IMF Working Papers 03/221, International Monetary Fund.
  18. Bertrand Candelon & Elena Ivona Dumitrescu & Christophe Hurlin, 2012. "How to Evaluate an Early Warning System? Towards a Unified Statistical Framework for Assessing Financial Crises Forecasting Methods," Post-Print hal-01385900, HAL.
  19. repec:zbw:iwhdps:3-12 is not listed on IDEAS
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