IDEAS home Printed from https://ideas.repec.org/a/kap/openec/v30y2019i4d10.1007_s11079-019-09530-0.html
   My bibliography  Save this article

Early Warning Systems for Currency Crises with Real-Time Data

Author

Listed:
  • Tjeerd M. Boonman

    () (Banco de México)

  • Jan P. A. M. Jacobs

    () (University of Groningen
    University of Tasmania
    CAMA
    CIRANO)

  • Gerard H. Kuper

    () (University of Groningen)

  • Alberto Romero

    () (Banco de México)

Abstract

This paper investigates the performance of early warning systems for currency crises in real-time, using forecasts of indicators that are available at the moment predictions are to be made. We investigate two types of commonly used early warning systems for currency crises: the signal approach and the logit model. We apply each EWS to a panel of fifteen emerging economies, distinguishing an estimation period 1991Q1–2010Q4 and a prediction period 2011Q1–2017Q4. We find that using indicator forecasts in the predictions worsens the ability of early warning systems to signal crises compared to the most recently available information.

Suggested Citation

  • Tjeerd M. Boonman & Jan P. A. M. Jacobs & Gerard H. Kuper & Alberto Romero, 2019. "Early Warning Systems for Currency Crises with Real-Time Data," Open Economies Review, Springer, vol. 30(4), pages 813-835, September.
    • Handle: RePEc:kap:openec:v:30:y:2019:i:4:d:10.1007_s11079-019-09530-0
    DOI: 10.1007/s11079-019-09530-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11079-019-09530-0
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Graciela Kaminsky & Saul Lizondo & Carmen M. Reinhart, 1998. "Leading Indicators of Currency Crises," IMF Staff Papers, Palgrave Macmillan, vol. 45(1), pages 1-48, March.
    2. Guillermo A. Calvo & Carmen M. Reinhart, 2002. "Fear of Floating," The Quarterly Journal of Economics, Oxford University Press, vol. 117(2), pages 379-408.
    3. 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.
    4. Berkmen, S. Pelin & Gelos, Gaston & Rennhack, Robert & Walsh, James P., 2012. "The global financial crisis: Explaining cross-country differences in the output impact," Journal of International Money and Finance, Elsevier, vol. 31(1), pages 42-59.
    5. 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.
    6. Johan Rewilak, 2018. "The Impact of Financial Crises on the Poor," Journal of International Development, John Wiley & Sons, Ltd., vol. 30(1), pages 3-19, January.
    7. Klaassen, Franc & Jager, Henk, 2011. "Definition-consistent measurement of exchange market pressure," Journal of International Money and Finance, Elsevier, vol. 30(1), pages 74-95, February.
    8. Frankel, Jeffrey A. & Rose, Andrew K., 1996. "Currency Crashes in Emerging Markets: Empirical Indicators," Center for International and Development Economics Research (CIDER) Working Papers 233424, University of California-Berkeley, Department of Economics.
    9. Jonas Dovern & Ulrich Fritsche & Jiri Slacalek, 2012. "Disagreement Among Forecasters in G7 Countries," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1081-1096, November.
    10. Marc Klau & John Hawkins, 2000. "Measuring potential vulnerabilities in emerging market economies," BIS Working Papers 91, Bank for International Settlements.
    11. Yanping Zhao & Jakob Haan & Bert Scholtens & Haizhen Yang, 2014. "Leading Indicators of Currency Crises: Are They the Same in Different Exchange Rate Regimes?," Open Economies Review, Springer, vol. 25(5), pages 937-957, November.
    12. Alessi, Lucia & Detken, Carsten, 2011. "Quasi real time early warning indicators for costly asset price boom/bust cycles: A role for global liquidity," European Journal of Political Economy, Elsevier, vol. 27(3), pages 520-533, September.
    13. Diebold, Francis X & Rudebusch, Glenn D, 1989. "Scoring the Leading Indicators," The Journal of Business, University of Chicago Press, vol. 62(3), pages 369-391, July.
    14. Derrick Reagle & Dominick Salvatore, 2000. "Forecasting Financial Crises in Emerging Market Economies," Open Economies Review, Springer, vol. 11(3), pages 247-259, July.
    15. Kaminsky, Graciela L., 2006. "Currency crises: Are they all the same?," Journal of International Money and Finance, Elsevier, vol. 25(3), pages 503-527, April.
    16. Gunther, Jeffery W. & Moore, Robert R., 2003. "Early warning models in real time," Journal of Banking & Finance, Elsevier, vol. 27(10), pages 1979-2001, October.
    17. Sarlin, Peter & Holopainen, Markus, 2016. "Toward robust early-warning models: a horse race, ensembles and model uncertainty," Working Paper Series 1900, European Central Bank.
    18. Boonman, Tjeerd Menno, 2019. "Dating currency crises in emerging market economies," The North American Journal of Economics and Finance, Elsevier, vol. 49(C), pages 273-286.
    19. Derrick Reagle & Dominick Salvatore, 2005. "Robustness of Forecasting Financial Crises in Emerging Market Economies with Data Revisions—A Note," Open Economies Review, Springer, vol. 16(2), pages 209-216, April.
    20. 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.
    21. Cumperayot, Phornchanok & Kouwenberg, Roy, 2013. "Early warning systems for currency crises: A multivariate extreme value approach," Journal of International Money and Finance, Elsevier, vol. 36(C), pages 151-171.
    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. Markus Holopainen & Peter Sarlin, 2015. "Toward robust early-warning models: A horse race, ensembles and model uncertainty," Papers 1501.04682, arXiv.org, revised Apr 2016.
    24. Sevim, Cuneyt & Oztekin, Asil & Bali, Ozkan & Gumus, Serkan & Guresen, Erkam, 2014. "Developing an early warning system to predict currency crises," European Journal of Operational Research, Elsevier, vol. 237(3), pages 1095-1104.
    25. 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.
    26. Chun Wei Choo, 2009. "Information use and early warning effectiveness: Perspectives and prospects," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(5), pages 1071-1082, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tjeerd Boonman & Jan P.A.M. Jacobs & Gerard H. Kuper & Alberto Romero, 2017. "Early Warning Systems with Real-Time Data," Working Papers 2017-16, Banco de México.
    2. John Adams & Ali Metwally, 2019. "Identifying currency crises indicators: the case of Egypt," African Journal of Economic and Management Studies, Emerald Group Publishing, vol. 10(2), pages 241-259, June.
    3. Christofides, Charis & Eicher, Theo S. & Papageorgiou, Chris, 2016. "Did established Early Warning Signals predict the 2008 crises?," European Economic Review, Elsevier, vol. 81(C), pages 103-114.
    4. Markus Behn & Carsten Detken & Tuomas Peltonen & Willem Schudel, 2017. "Predicting Vulnerabilities in the EU Banking Sector: The Role of Global and Domestic Factors," International Journal of Central Banking, International Journal of Central Banking, vol. 13(4), pages 147-189, December.
    5. Kauko, Karlo, 2014. "How to foresee banking crises? A survey of the empirical literature," Economic Systems, Elsevier, vol. 38(3), pages 289-308.
    6. Medina Moral, Eva & Salvador Perucha, David, 2018. "Medición de la vulnerabilidad monetaria en el área latinoamericana bajo un enfoque de señales ?móviles?/Measurement of Monetary Vulnerability in the Latin American Area using a," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 36, pages 603-634, Mayo.
    7. Balaga Mohana Rao & Puja Padhi, 2020. "Common Determinants of the Likelihood of Currency Crises in BRICS," Global Business Review, International Management Institute, vol. 21(3), pages 698-712, June.
    8. Yanping Zhao & Jakob Haan & Bert Scholtens & Haizhen Yang, 2014. "Leading Indicators of Currency Crises: Are They the Same in Different Exchange Rate Regimes?," Open Economies Review, Springer, vol. 25(5), pages 937-957, November.
    9. Dieckelmann, Daniel, 2020. "Cross-border lending and the international transmission of banking crises," Discussion Papers 2020/13, Free University Berlin, School of Business & Economics.
    10. El-Shagi, M. & Knedlik, T. & von Schweinitz, G., 2013. "Predicting financial crises: The (statistical) significance of the signals approach," Journal of International Money and Finance, Elsevier, vol. 35(C), pages 76-103.
    11. Ryota Nakatani, 2017. "The Effects of Productivity Shocks, Financial Shocks, and Monetary Policy on Exchange Rates: An Application of the Currency Crisis Model and Implications for Emerging Market Crises," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 53(11), pages 2545-2561, November.
    12. Ali Ari & Raif Cergibozan, 2016. "A Comparison of Currency Crisis Dating Methods: Turkey 1990-2014," Montenegrin Journal of Economics, Economic Laboratory for Transition Research (ELIT), vol. 12(3), pages 19-37.
    13. Sondermann, David & Zorell, Nico, 2019. "A macroeconomic vulnerability model for the euro area," Working Paper Series 2306, European Central Bank.
    14. Babecký, Jan & Havránek, Tomáš & Matějů, Jakub & Rusnák, Marek & Šmídková, Kateřina & Vašíček, Bořek, 2014. "Banking, debt, and currency crises in developed countries: Stylized facts and early warning indicators," Journal of Financial Stability, Elsevier, vol. 15(C), pages 1-17.
    15. Panayotis Michaelides & Mike Tsionas & Panos Xidonas, 2020. "A Bayesian Signals Approach for the Detection of Crises," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(3), pages 551-585, September.
    16. Hyeongwoo Kim & Wen Shi & Hyun Hak Kim, 2020. "Forecasting financial stress indices in Korea: a factor model approach," Empirical Economics, Springer, vol. 59(6), pages 2859-2898, December.
    17. Stijn Claessens & M. Ayhan Kose, 2013. "Financial Crises: Explanations, Types and Implications," CAMA Working Papers 2013-06, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    18. Bruce N. Lehmann & David M. Modest, 1985. "The Empirical Foundations of the Arbitrage Pricing Theory I: The Empirical Tests," NBER Working Papers 1725, National Bureau of Economic Research, Inc.
    19. Mustapha Djennas & Mohamed Benbouziane & Meriem Djennas, 2011. "An Approach of Combining Empirical Mode Decomposition and Neural Network Learning for Currency Crisis Forecasting," Working Papers 627, Economic Research Forum, revised 09 Jan 2011.
    20. Joon-Ho Hahm & Hyun Song Shin & Kwanho Shin, 2013. "Noncore Bank Liabilities and Financial Vulnerability," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 45, pages 3-36, August.

    More about this item

    Keywords

    Real time data; Early warning system; Currency crises; Signal approach; Logit model; Emerging economies;
    All these keywords.

    JEL classification:

    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications
    • G01 - Financial Economics - - General - - - Financial Crises
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:openec:v:30:y:2019:i:4:d:10.1007_s11079-019-09530-0. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla) or (Springer Nature Abstracting and Indexing). General contact details of provider: http://www.springer.com .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.