Journals / Journal of Business Economics and Finance / 2026 / Volume: 8 Issue: 3

MODELLING AN EARLY WARNING SYSTEM FOR CURRENCY CRISES: A DYNAMIC PANEL PROBIT MODEL

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Publication Date
2019-09-30
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⚡ TL;DR(Too Long; Didn't Read)

Purpose- The probability of currency crisis is attempted to be predicted by analysing the lagged binary crisis variable and some macroeconomic indicators.

📌 3 Key Takeaways

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Objective & Hypothesis:Purpose- The probability of currency crisis is attempted to be predicted by analysing the lagged binary crisis variable and some macroeconomic indicators.
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Key Findings & Data:Purpose- The probability of currency crisis is attempted to be predicted by analysing the lagged binary crisis variable and some macroeconomic indicators.
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Conclusion & Impact:Purpose- The probability of currency crisis is attempted to be predicted by analysing the lagged binary crisis variable and some macroeconomic indicators.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Currency crises · dynamic panel probit models · early warning systems (EWS)

Abstract

Purpose- The probability of currency crisis is attempted to be predicted by analysing the lagged binary crisis variable and some macroeconomic indicators.

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Cite This Article

Poyraz, G. (2019). MODELLING AN EARLY WARNING SYSTEM FOR CURRENCY CRISES: A DYNAMIC PANEL PROBIT MODEL. Journal of Business Economics and Finance, Volume: 8 Issue: 3. https://doi.org/10.17261/Pressacademia.2019.1125

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References (18)

  1. Berg, A., & Borensztein, E., & Milesi-Ferretti G. M., & Pattillo, C. (1999). Anticipating balance of payment crises-the role early warning systems. IMF Occasional Papers, 186, 1-32.
  2. Berg, A., & Pattillo, C. (1999). Predicting currency crises: The indicators approach and an alternative. Journal of International Money and Finance, 8, 561-586.
  3. Bussiere, M., & Fratzscher, M. (2006). Towards a new early warning system of financial crises. Journal of International Money and Finance, 25(6), 953-973.
  4. Bussiere M. (2007). Balance of payment crises in emerging markets how early were the “early” warning signals?. ECB Working Paper, 713, 1-41.
  5. Candelon, B., & Dumitrescu, E. I., & Hurlin, C. (2014). Currency crises early warning systems: Why they should be dynamic. International Journal of Forecasting, 30(4), 1016-1029.
  6. Dumitrescu, E. I. (2012). Econometric models for financial crises, Maastricht University, Dissertation, ISBN: 978 94 6159 152 4.
  7. Eichengreen, B., & Rose, A. K., & Wyplosz, C. (1996). Contagious currency crises. NBER Working Paper Series, 1-48.
  8. Falcetti, E., & Tudela, M. (2006). Modelling currency crises in emerging markets: A dynamic probit model with unobserved heterogeneity and autocorrelated errors. Oxford Bulletin of Economics and Statistics, 68(4), 445-471.
  9. Frankel, J.A., & Rose, A. K. (1996). Currency crashes in emerging markets: an empirical treatment. International Finance Discussion Papers, 534, 1- 26.
  10. Grotti, R., & Cutuli, G. (2018). Estimating dynamic random effects probit model with unobserved heterogeneity using stata. Retrieved from https://www.researchgate.net/publication/323524968_Estimating_dynamic_random_effects_probit_model_with_unobserved_heterogenei ty_ using_Stata
  11. Heckman, J. J. (1981). Heterogeity and state dependence. National Bureau of Economic Research, 91-140.
  12. Kaminsky, G., & Lizondo, S., & Reinhart, C. M. (1998). Leading indicators of currency crises. IMF Staff Papers, 45(1), 1-48.
  13. Kaminsky, G. L., & Reinhart, C. M. (1999). The twin crises: The causes of banking and balance-of-payments problems. The American Economic Review, 89(3), 473-500.
  14. Kumar, M., & Moorthy, U., & Perraudin, W. (2003). Predicting emerging market currency crashes. Journal of Empirical Finance, 427- 454.
  15. Moreno, R., & Trehan, B. (2000). Common shocks and currency crises, Federal Reserve Bank of San Francisco, 1-41.
  16. Rabe-Hesketh, S., & Skrondal, A. (2013). Avoiding biased versions of wooldridge’s simple solution to the initial conditions problem. Economics Letters, 120(2), 346-349.
  17. Von Hagen, J., & Ho, T. (2003). Twin crises: A reexamination of empirical links. Center for European Integration Studies, Retrieved from https://www.gtap.agecon.purdue.edu/resources/download/1386.pdf.
  18. Wooldridge, J. M. (2005). Simple solutions to the initial conditions problem in dynamic, nonlinear panel data model s with unobserved heterogeneity. Journal of Applied Econometrics, 20, 39-54.