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Currency crisis early warning systems: Why they should be dynamic

Author

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  • Candelon, Bertrand
  • Dumitrescu, Elena-Ivona
  • Hurlin, Christophe

Abstract

Traditionally, financial crisis Early Warning Systems (EWSs) have relied on macroeconomic leading indicators when forecasting the occurrence of such events. This paper extends such discrete-choice EWSs by taking the persistence of the crisis phenomenon into account. The dynamic logit EWS is estimated using an exact maximum likelihood estimation method in both a country-by-country and a panel framework. The forecasting abilities of this model are then scrutinized using an evaluation methodology which was designed recently, specifically for EWSs. When used for predicting currency crises for 16 countries, this new EWS turns out to exhibit significantly better predictive abilities than the existing static one, both in- and out-of-sample, thus supporting the use of dynamic specifications for EWSs for financial crises.

Suggested Citation

  • Candelon, Bertrand & Dumitrescu, Elena-Ivona & Hurlin, Christophe, 2014. "Currency crisis early warning systems: Why they should be dynamic," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1016-1029.
  • Handle: RePEc:eee:intfor:v:30:y:2014:i:4:p:1016-1029
    DOI: 10.1016/j.ijforecast.2014.03.015
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    Citations

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    Cited by:

    1. Freitag L., 2014. "Default probabilities, CDS premiums and downgrades : A probit-MIDAS analysis," Research Memorandum 038, Maastricht University, Graduate School of Business and Economics (GSBE).
    2. Dawood, Mary & Horsewood, Nicholas & Strobel, Frank, 2017. "Predicting sovereign debt crises: An Early Warning System approach," Journal of Financial Stability, Elsevier, vol. 28(C), pages 16-28.
    3. Li, Haixi, 2012. "An Optimal Design of Early Warning Systems: A Bayesian Quickest Change Detection Approach," MPRA Paper 37302, University Library of Munich, Germany.
    4. Maixé-Altés, J. Carles & Iglesias, Emma M., 2015. "Banking, Currency, Stock Market and Debt Crises: Revisiting Reinhart & Rogoff Debt Analysis in Spain, 1850-1995," MPRA Paper 68199, University Library of Munich, Germany.
    5. Elena-Ivona Dumitrescu & Bertrand Candelon & Christophe Hurlin & Franz C. Palm, 2012. "Multivariate Dynamic Probit Models: An Application to Financial Crises Mutation," Working Papers halshs-00630036, HAL.
    6. Antunes, António & Bonfim, Diana & Monteiro, Nuno & Rodrigues, Paulo M.M., 2018. "Forecasting banking crises with dynamic panel probit models," International Journal of Forecasting, Elsevier, vol. 34(2), pages 249-275.
    7. repec:lrk:eeaart:36_2_12 is not listed on IDEAS
    8. Freitag L., 2014. "Procyclicality and path dependence of sovereign credit ratings: The example of Europe," Research Memorandum 020, Maastricht University, Graduate School of Business and Economics (GSBE).
    9. Dogus Emin & Aysegul Aytac, 2016. "The challenge of predicting currency crises: how do definition and probability threshold choice make a difference?," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 6(2), pages 195-213, August.
    10. Adrian Pagan, 2013. "Patterns and Their Uses," NCER Working Paper Series 96, National Centre for Econometric Research.
    11. repec:eee:joecas:v:13:y:2016:i:c:p:100-113 is not listed on IDEAS
    12. Anna Pestova, 2015. "Leading Indicators of the Business Cycle: Dynamic Logit Models for OECD Countries and Russia," HSE Working papers WP BRP 94/EC/2015, National Research University Higher School of Economics.
    13. Bertrand Candelon & Elena-Ivona DUMITRESCU & Christophe HURLIN & Franz C. PALM, 2011. "Modelling Financial Crises Mutation," LEO Working Papers / DR LEO 1238, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    14. Christian von Haldenwang & Maksym Ivanyna, 2017. "Does the political resource curse affect public finance? The vulnerability of tax revenue in resource-rich countries," WIDER Working Paper Series 007, World Institute for Development Economic Research (UNU-WIDER).

    More about this item

    Keywords

    Dynamic models; Currency crisis; Early warning system;

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications

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