Predicting sovereign debt crises using artificial neural networks: A comparative approach
Recent episodes of financial crisis have revived interest in developing models able to signal their occurrence in timely manner. The literature has developed both parametric and non-parametric models, the so-called Early Warning Systems, to predict these crises. Using data related to sovereign debt crises which occurred in developing countries from 1980 to 2004, this paper shows that further progress can be achieved by applying a less developed non-parametric method based on artificial neural networks (ANN). Thanks to the high flexibility of neural networks and their ability to approximate non-linear relationship, an ANN-based early warning system can, under certain conditions, outperform more consolidated methods.
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- Gary Chamberlain, 1980. "Analysis of Covariance with Qualitative Data," Review of Economic Studies, Oxford University Press, vol. 47(1), pages 225-238.
- 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.).
- Frankel, Jeffrey A. & Rose, Andrew K., 1996. "Currency crashes in emerging markets: An empirical treatment," Journal of International Economics, Elsevier, vol. 41(3-4), pages 351-366, November.
- Abdul d Abiad, 2003. "Early Warning Systems; A Survey and a Regime-Switching Approach," IMF Working Papers 03/32, International Monetary Fund.
- Graciela L. Kaminsky, 2003. "Varieties of Currency Crises," NBER Working Papers 10193, National Bureau of Economic Research, Inc.
- Kaminsky, Graciela & Lizondo, Saul & Reinhart, Carmen M., 1997.
"Leading indicators of currency crises,"
Policy Research Working Paper Series
1852, The World Bank.
- Axel Schimmelpfennig & Nouriel Roubini & Paolo Manasse, 2003. "Predicting Sovereign Debt Crises," IMF Working Papers 03/221, International Monetary Fund.
- Ciarlone, Alessio & Trebeschi, Giorgio, 2005. "Designing an early warning system for debt crises," Emerging Markets Review, Elsevier, vol. 6(4), pages 376-395, December.
- AndrÃ© FourÃ§ans & RaphaÃ«l Franck, 2003. "Currency Crises," Books, Edward Elgar Publishing, number 3124.
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