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A regime-switching approach to the study of speculative attacks: A focus on EMS crises

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  • Maria Soledad Martinez Peria

    () (The World Bank, 1818 H St., N.W., Room MC 3-451, Washington D.C. 20433)

Abstract

This paper implements a regime-switching framework to study speculative attacks against EMS currencies during 1979-1993. To identify speculative episodes, we model exchange rates, reserves, and interest rates as time series subject to discrete regime shifts between two possible states: "tranquil" and "speculative". We allow the probabilities of switching between states to be a function of fundamentals and expectations. The regime-switching framework improves the ability to identify speculative attacks vis-à-vis the indices of speculative pressure used in the literature. The results also indicate that fundamentals (particularly budget deficits) and expectations drive the probability of switching to a speculative state.

Suggested Citation

  • 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.
  • Handle: RePEc:spr:empeco:v:27:y:2002:i:2:p:299-334
    Note: Received: October 2000/Final Version Received: June 2001
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    Cited by:

    1. Frankel, Jeffrey & Saravelos, George, 2012. "Can leading indicators assess country vulnerability? Evidence from the 2008–09 global financial crisis," Journal of International Economics, Elsevier, vol. 87(2), pages 216-231.
    2. Daniel Aromi & Marcos Dal Bianco, 2014. "Un analisis de los desequilibrios del tipo de cambio real argentino bajo cambios de regimen," Working Papers 1431, BBVA Bank, Economic Research Department.
    3. Marcel Fratzscher, 2003. "On currency crises and contagion," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 8(2), pages 109-129.
    4. Alexis Cruz-Rodriguez, 2013. "Choosing and Assessing Exchange Rate Regimes: a Survey of the Literature," Revista de Analisis Economico – Economic Analysis Review, Ilades-Georgetown University, Universidad Alberto Hurtado/School of Economics and Bussines, vol. 28(2), pages 37-61, October.
    5. Brandner, Peter & Grech, Harald & Stix, Helmut, 2006. "The effectiveness of central bank intervention in the EMS: The post 1993 experience," Journal of International Money and Finance, Elsevier, vol. 25(4), pages 580-597, June.
    6. 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.
    7. Terra, Cristina & Valladares, Frederico, 2010. "Real exchange rate misalignments," International Review of Economics & Finance, Elsevier, vol. 19(1), pages 119-144, January.
    8. 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;International Monetary Fund, vol. 60(1), pages 75-113, April.
    9. Jan Bulla, 2010. "Hidden Markov models with t components. Increased persistence and other aspects," Quantitative Finance, Taylor & Francis Journals, vol. 11(3), pages 459-475.
    10. Ronald MacDonald & Jun Nagayasu, 2013. "Currency forecast errors at times of low interest rates: evidence from survey data on the Yen/Dollar exchange rate," Working Papers 1321, University of Strathclyde Business School, Department of Economics.
    11. Daniela Bragoli & Piero Ganugi & Giancarlo Ianulardo, 2013. "Gini’s transvariation analysis: an application on financial crises in developing countries," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 40(1), pages 153-174, February.
    12. Beckmann, Daniela & Menkhoff, Lukas & Sawischlewski, Katja, 2006. "Robust lessons about practical early warning systems," Journal of Policy Modeling, Elsevier, vol. 28(2), pages 163-193, February.
    13. Marie Bessec, 2000. "Mean-Reversion versus PPP Adjustment: The Two Regimes of Exchange Rate Dynamics Under the EMS, 1979-1998," Econometric Society World Congress 2000 Contributed Papers 1305, Econometric Society.
    14. M. Araceli RodrÌguez LÛpez, "undated". "Variables fundamentales o ataques "Self-fulfilling"? Una explicaciÛn a las crisis de credibilidad de la peseta espanola," Studies on the Spanish Economy 90, FEDEA.
    15. Morales Vásquez, Daniel, 2011. "Presiones cambiarias en el Perú: Un enfoque no lineal," Revista Estudios Económicos, Banco Central de Reserva del Perú, issue 20, pages 57-71.
    16. Alberto Humala, 2006. "Depreciation expectations and interest rate differentials: Are there regime switches? The Peruvian case," Working Papers 2006-002, Banco Central de Reserva del Perú.
    17. Humala, Alberto, 2007. "Expectativas de depreciación y diferencial de tasas de interés: ¿Hay regímenes cambiantes? El caso de Perú," Revista Estudios Económicos, Banco Central de Reserva del Perú, issue 14, pages 77-106.
    18. Kaufmann, Daniel & Mehrez, Gil & Schmukler, Sergio L., 2005. "Predicting currency fluctuations and crises: Do resident firms have an informational advantage?," Journal of International Money and Finance, Elsevier, vol. 24(6), pages 1012-1029, October.
    19. Ihle, Rico & von Cramon-Taubadel, Stephan, 2008. "A Comparison of Threshold Cointegration and Markov-Switching Vector Error Correction Models in Price Transmission Analysis," 2008 Conference, April 21-22, 2008, St. Louis, Missouri 37603, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    20. Mandilaras, Alex & Bird, Graham, 2010. "A Markov switching analysis of contagion in the EMS," Journal of International Money and Finance, Elsevier, vol. 29(6), pages 1062-1075, October.
    21. Jeffrey A. Frankel & George Saravelos, 2010. "Are Leading Indicators of Financial Crises Useful for Assessing Country Vulnerability? Evidence from the 2008-09 Global Crisis," NBER Working Papers 16047, National Bureau of Economic Research, Inc.

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