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From Transition Crises to Macroeconomic Stability? Lessons from a Crises Early Warning System for Eastern European and CIS Countries

Author

Listed:
  • Kristina Kittelmann

    (Sovereign Risk Unit, Moody's Deutschland, An der Welle 5, D-60322 Frankfurt/Main, Germany.)

  • Marcel Tirpak

    (Faculty of National Economy, Banking and International Finance Department, University of Economics, Bratislava, Slovakia.)

  • Rainer Schweickert

    (Kiel Institute for World Economics, Duesternbrooker Weg 120, D-24105 Kiel, Germany.)

  • Lúcio Vinhas De Souza

    (Kiel Institute for World Economics and Head, Russia/Belarus Desk, DG-ECFIN, European Commission, Avenue de Beaulieu, 1, B-1160 Brussel, Belgium.)

Abstract

This paper uses a Markov regime-switching model to assess the vulnerability of a series of Central and Eastern European countries (ie Czech Republic, Hungary, Slovak Republic) and two CIS countries (ie, Russia and Ukraine) during the period 1993–2004. For the new EU member states in Central and Eastern Europe, the results of our model show that the majority of crises in those countries can be explained by inconsistencies in the domestic policy mix and by the deterioration of macroeconomic fundamentals, as emphasised by first-generation crises models, while for the CIS countries analysed, financial vulnerability type indicators were the most relevant, that is, indicators connected with the second- and third-generation of crisis model better explain the vulnerability of these countries. Additionally, the set of indicators chosen by our model is rather heterogeneous, supporting the superiority of a country-by-country approach. Comparative Economic Studies (2006) 48, 410–434. doi:10.1057/palgrave.ces.8100162

Suggested Citation

  • Kristina Kittelmann & Marcel Tirpak & Rainer Schweickert & Lúcio Vinhas De Souza, 2006. "From Transition Crises to Macroeconomic Stability? Lessons from a Crises Early Warning System for Eastern European and CIS Countries," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 48(3), pages 410-434, September.
    • Handle: RePEc:pal:compes:v:48:y:2006:i:3:p:410-434
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    Cited by:

    1. Jesús Crespo Cuaresma & Tomáš Slacík, 2007. "Predicting Currency Crises Using the Term Structure of Relative Interest Rates: Case Studies of the Czech Republic and Russia," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue 1, pages 135-149.
    2. 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.
    3. Krkoska, Libor & Teksoz, Utku, 2007. "Accuracy of GDP growth forecasts for transition countries: Ten years of forecasting assessed," International Journal of Forecasting, Elsevier, vol. 23(1), pages 29-45.
    4. Eichler, Stefan & Karmann, Alexander & Maltritz, Dominik, 2009. "The ADR shadow exchange rate as an early warning indicator for currency crises," Journal of Banking & Finance, Elsevier, vol. 33(11), pages 1983-1995, November.
    5. David G. Mayes & Vesa Korhonen, 2006. "The CIS: Does the Regional Hegemony Facilitate Monetary Integration?," Economie Internationale, CEPII research center, issue 107, pages 173-196.
    6. Sorin BURNETE, 2009. "Emerging Economies Faced With The Downside Of Financial Globalization: Hedges And Way Outs," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 3, pages 41-55, May.
    7. Cevik, Emrah Ismail & Dibooglu, Sel & Kutan, Ali M., 2013. "Measuring financial stress in transition economies," Journal of Financial Stability, Elsevier, vol. 9(4), pages 597-611.
    8. Knedlik, Tobias & Scheufele, Rolf, 2007. "Three methods of forecasting currency crises: Which made the run in signaling the South African currency crisis of June 2006?," IWH Discussion Papers 17/2007, Halle Institute for Economic Research (IWH).
    9. 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.

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    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • F47 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Forecasting and Simulation: Models and Applications
    • P20 - Political Economy and Comparative Economic Systems - - Socialist and Transition Economies - - - General

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