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Currency Crisis Early Warning Systems: Why They should be Dynamic

  • Bertrand Candelon
  • Christophe Hurlin
  • Elena Dumitnescu

Traditionally, nancial crisis Early Warning Systems (EWSs) rely on macroeconomic leading indicators to forecast the occurrence of such events. This paper extends such discrete-choice EWSs by taking into account the persistence of the crisis phenomenon. The dynamic logit EWS is estimated using an exact maximum likelihood estimation method both in a time series and panel form. This model's forecasting abilities are then scrutinized by using an evaluation methodology recently designed speci cally for EWSs. When applied for predict- ing currency crises for 16 countries, this new EWS turns out to exhibit signi cantly better predictive abilities than the existing static one, both in- and out-of -sample, thus supporting the use of dynamic speci cations for EWSs for nancial crises.

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Paper provided by Department of Research, Ipag Business School in its series Working Papers with number 2014-161.

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Length: 41 pages
Date of creation: 25 Feb 2014
Date of revision:
Handle: RePEc:ipg:wpaper:2014-161
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  1. M M Tudela, 2001. "Explaining Currency Crises: A Duration Model Approach," CEP Discussion Papers dp0487, Centre for Economic Performance, LSE.
  2. Bussière, Matthieu & Fratzscher, Marcel, 2002. "Towards a new early warning system of financial crises," Working Paper Series 0145, European Central Bank.
  3. Carro, Jesus M., 2007. "Estimating dynamic panel data discrete choice models with fixed effects," Journal of Econometrics, Elsevier, vol. 140(2), pages 503-528, October.
  4. George Kapetanios, 2003. "Determining the Poolability of Individual Series in Panel Datasets," Working Papers 499, Queen Mary University of London, School of Economics and Finance.
  5. Maddala, G S & Wu, Shaowen, 1999. " A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(0), pages 631-52, Special I.
  6. Rose, Andrew K & Spiegel, Mark, 2010. "Cross-Country Causes and Consequences of the Crisis: An Update," CEPR Discussion Papers 7901, C.E.P.R. Discussion Papers.
  7. Marcel Fratzscher, 2003. "On currency crises and contagion," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 8(2), pages 109-129.
  8. van den Berg, Jeroen & Candelon, Bertrand & Urbain, Jean-Pierre, 2008. "A cautious note on the use of panel models to predict financial crises," Economics Letters, Elsevier, vol. 101(1), pages 80-83, October.
  9. Marek Dabrowski & Malgorzata Jakubiak, 2003. "The Sources of Economic Growth in Ukraine after 1998 Currency Crisis and the Country's Prospects," CASE Network Reports 0055, CASE-Center for Social and Economic Research.
  10. Kaminsky, Graciela & Lizondo, Saul & Reinhart, Carmen M., 1997. "Leading indicators of currency crises," Policy Research Working Paper Series 1852, The World Bank.
  11. Kenneth D. West & Todd Clark, 2006. "Approximately Normal Tests for Equal Predictive Accuracy in Nested Models," NBER Technical Working Papers 0326, National Bureau of Economic Research, Inc.
  12. Andrew Berg & Rebecca N. Coke, 2004. "Autocorrelation-Corrected Standard Errors in Panel Probits; An Application to Currency Crisis Prediction," IMF Working Papers 04/39, International Monetary Fund.
  13. Kumar, Mohan & Moorthy, Uma & Perraudin, William, 2003. "Predicting emerging market currency crashes," Journal of Empirical Finance, Elsevier, vol. 10(4), pages 427-454, September.
  14. Zhiwei Zhang, 2001. "Speculative Attacks in the Asian Crisis," IMF Working Papers 01/189, International Monetary Fund.
  15. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-44, January.
  16. Swati R. Ghosh & Atish R. Ghosh, 2003. "Structural Vulnerabilities and Currency Crises," IMF Staff Papers, Palgrave Macmillan, vol. 50(3), pages 7.
  17. Bertrand Candelon & Elena-Ivona Dumitrescu & Christophe Hurlin, 2012. "How to Evaluate an Early-Warning System: Toward a Unified Statistical Framework for Assessing Financial Crises Forecasting Methods," IMF Economic Review, Palgrave Macmillan, vol. 60(1), pages 75-113, April.
  18. Pesaran, M.H., 2003. "A Simple Panel Unit Root Test in the Presence of Cross Section Dependence," Cambridge Working Papers in Economics 0346, Faculty of Economics, University of Cambridge.
  19. Frankel, Jeffrey & Saravelos, George, 2011. "Can Leading Indicators Assess Country Vulnerability? Evidence from the 2008-09 Global Financial Crisis," Working Paper Series rwp11-024, Harvard University, John F. Kennedy School of Government.
  20. Bertrand Candelon & Elena-Ivona Dumitrescu & Christophe Hurlin, 2012. "How to evaluate an Early Warning System ?," Working Papers halshs-00450050, HAL.
  21. Elisabetta Falcetti & Merxe Tudela, 2006. "Modelling Currency Crises in Emerging Markets: A Dynamic Probit Model with Unobserved Heterogeneity and Autocorrelated Errors," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(4), pages 445-471, 08.
  22. 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.
  23. Maria Soledad Martinez Peria, 2002. "A regime-switching approach to the study of speculative attacks: A focus on EMS crises," Empirical Economics, Springer, vol. 27(2), pages 299-334.
  24. Lestano & Jacobs, Jan P.A.M., 2004. "A comparison of currency crisis dating methods: East Asia 1970-2002," CCSO Working Papers 200412, University of Groningen, CCSO Centre for Economic Research.
  25. Fuertes, Ana-Maria & Kalotychou, Elena, 2007. "Optimal design of early warning systems for sovereign debt crises," International Journal of Forecasting, Elsevier, vol. 23(1), pages 85-100.
  26. Heikki Kauppi & Pentti Saikkonen, 2008. "Predicting U.S. Recessions with Dynamic Binary Response Models," The Review of Economics and Statistics, MIT Press, vol. 90(4), pages 777-791, November.
  27. Don Harding & Adrian Pagan, 2011. "An Econometric Analysis of Some Models for Constructed Binary Time Series," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(1), pages 86-95, January.
  28. Im, Kyung So & Pesaran, M. Hashem & Shin, Yongcheol, 2003. "Testing for unit roots in heterogeneous panels," Journal of Econometrics, Elsevier, vol. 115(1), pages 53-74, July.
  29. Jushan Bai & Serena Ng, 2001. "A New Look at Panel Testing of Stationarity and the PPP Hypothesis," Boston College Working Papers in Economics 518, Boston College Department of Economics.
  30. Abdul Abiad, 2003. "Early Warning Systems; A Survey and a Regime-Switching Approach," IMF Working Papers 03/32, International Monetary Fund.
  31. Fabian Valencia & Luc Laeven, 2012. "Systemic Banking Crises Database: An Update," IMF Working Papers 12/163, International Monetary Fund.
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