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Robust lessons about practical early warning systems

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  • Beckmann, Daniela
  • Menkhoff, Lukas
  • Sawischlewski, Katja

Abstract

Early warning systems (EWSs) are subject to restrictions that apply to exchange rates in general: fundamentals matter but their influence is small and unstable. Despite this limitation four major lessons emerge: First, EWSs have robust forecasting power and thus help policy-makers to prevent crises. Second, policy-makers must decide about some EWSs elements, such as the sensitivity of the forecasts. Third, EWSs performance is increased by taking a logit model, shorter samples and a regional approach. Fourth, the finding of contagion may motivate policy to shield its economy against inefficient international financial markets.
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Suggested Citation

  • 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.
  • Handle: RePEc:eee:jpolmo:v:28:y:2006:i:2:p:163-193
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    Cited by:

    1. Nakatani, Ryota, 2017. "Real and Financial Shocks, Exchange Rate Regimes and the Probability of a Currency Crisis," MPRA Paper 82186, University Library of Munich, Germany.
    2. Marcin Chlebus, 2016. "One-Day Prediction of State of Turbulence for Portfolio. Models for Binary Dependent Variable," Working Papers 2016-01, Faculty of Economic Sciences, University of Warsaw.
    3. Marcin Chlebus, 2014. "One-day prediction of state of turbulence for financial instrument based on models for binary dependent variable," Ekonomia journal, Faculty of Economic Sciences, University of Warsaw, vol. 37.
    4. Esaka, Taro, 2013. "Evaluating the effect of de facto pegs on currency crises," Journal of Policy Modeling, Elsevier, vol. 35(6), pages 943-963.
    5. Cristian STANCIU, 2010. "A review of early warning system models," Finante - provocarile viitorului (Finance - Challenges of the Future), University of Craiova, Faculty of Economics and Business Administration, vol. 1(11), pages 222-228, May.
    6. Ryota Nakatani, 2014. "The Effects of Financial and Real Shocks, Structural Vulnerability and Monetary Policy on Exchange Rates from the Perspective of Currency Crises Models," UTokyo Price Project Working Paper Series 043, University of Tokyo, Graduate School of Economics.
    7. 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.
    8. 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.
    9. Jo-Hui Chen & Chih-Sean Chen, 2012. "The study of contagious paces of financial crises," Quality & Quantity: International Journal of Methodology, Springer, vol. 46(6), pages 1825-1846, October.
    10. Cevik, Emrah I. & Dibooglu, Sel & Kenc, Turalay, 2016. "Financial stress and economic activity in some emerging Asian economies," Research in International Business and Finance, Elsevier, vol. 36(C), pages 127-139.
    11. Su, Dongwei & He, Xingxing, 2010. "A Hybrid Intelligent Early Warning System for Predicting Economic Crises: The Case of China," MPRA Paper 19962, University Library of Munich, Germany.
    12. Fabio Comelli, 2013. "Comparing Parametric and Non-parametric Early Warning Systems for Currency Crises in Emerging Market Economies," IMF Working Papers 13/134, International Monetary Fund.
    13. Fabio Comelli, 2014. "Comparing the Performance of Logit and Probit Early Warning Systems for Currency Crises in Emerging Market Economies," IMF Working Papers 14/65, International Monetary Fund.
    14. Licchetta, Mirko, 2009. "Common determinants of currency crises: role of external balance sheet variables," Bank of England working papers 366, Bank of England.
    15. repec:eee:riibaf:v:42:y:2017:i:c:p:605-615 is not listed on IDEAS
    16. Seoung Hwan Suh & Kabsung Kim, 2014. "Global financial crisis and early warning system of Korean housing market," Chapters,in: The Global Financial Crisis and Housing, chapter 4, pages 62-81 Edward Elgar Publishing.

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    JEL classification:

    • F33 - International Economics - - International Finance - - - International Monetary Arrangements and Institutions
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications
    • F31 - International Economics - - International Finance - - - Foreign Exchange

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