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Regionality Revisited: An Examination of the Direction of Spread of Currency Crisis


  • Amil Dasgupta
  • Roberto Leon-Gonzalez
  • Anja Shortland


What determines the direction of spread of currency crises? We examine data on waves of currency crises in 1992, 1994, 1997, and 1998 to evaluate several hypotheses on the determinants of contagion. We simultaneously consider trade competition, financial links, and institutional similarity to the "ground-zero" country as potential drivers of contagion. To overcome data limitations and account for model uncertainty, we utilize Bayesian methodologies hitherto unused in the empirical literature on contagion. In particular, we use the Bayesian averaging of binary models which allows us to take into account the uncertainty regarding the appropriate set of regressors. We find that institutional similarity to the ground-zero country plays an important role in determining the direction of contagion in all the emerging market currency crises in our dataset. We thus provide persuasive evidence in favour of the "wake up call" hypothesis for financial contagion. Trade and financial links may also play a role in determining the direction of contagion, but their importance varies amongst the crisis periods.

Suggested Citation

  • Amil Dasgupta & Roberto Leon-Gonzalez & Anja Shortland, 2010. "Regionality Revisited: An Examination of the Direction of Spread of Currency Crisis," Discussion Papers of DIW Berlin 1023, DIW Berlin, German Institute for Economic Research.
  • Handle: RePEc:diw:diwwpp:dp1023

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    References listed on IDEAS

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    Cited by:

    1. Geert Bekaert & Michael Ehrmann & Marcel Fratzscher & Arnaud Mehl, 2014. "The Global Crisis and Equity Market Contagion," Journal of Finance, American Finance Association, vol. 69(6), pages 2597-2649, December.
    2. Ahnert, Toni & Bertsch, Christoph, 2013. "A wake-up call: information contagion and strategic uncertainty," Working Paper Series 282, Sveriges Riksbank (Central Bank of Sweden), revised 01 Mar 2014.
    3. Debarsy, Nicolas & Dossougoin, Cyrille & Ertur, Cem & Gnabo, Jean-Yves, 2018. "Measuring sovereign risk spillovers and assessing the role of transmission channels: A spatial econometrics approach," Journal of Economic Dynamics and Control, Elsevier, vol. 87(C), pages 21-45.
    4. Lee, Seohyun, 2017. "Three essays on uncertainty: real and financial effects of uncertainty shocks," MPRA Paper 83617, University Library of Munich, Germany.
    5. Steel, Mark F. J., 2017. "Model Averaging and its Use in Economics," MPRA Paper 81568, University Library of Munich, Germany.
    6. Manz, Michael, 2010. "Information-based contagion and the implications for financial fragility," European Economic Review, Elsevier, vol. 54(7), pages 900-910, October.
    7. Kocsis, Zalan & Monostori, Zoltan, 2016. "The role of country-specific fundamentals in sovereign CDS spreads: Eastern European experiences," Emerging Markets Review, Elsevier, vol. 27(C), pages 140-168.
    8. Heng Chen & Wing Suen, 2016. "Falling Dominoes: A Theory of Rare Events and Crisis Contagion," American Economic Journal: Microeconomics, American Economic Association, vol. 8(1), pages 228-255, February.
    9. Leila Ali & Marie Lebreton, 2013. "The Fall of Bretton Woods: Which Geography Matters?," Economics Bulletin, AccessEcon, vol. 33(2), pages 1396-1419.

    More about this item


    Financial contagion; exchange rate; institutions; Bayesian model averaging;

    JEL classification:

    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • F32 - International Economics - - International Finance - - - Current Account Adjustment; Short-term Capital Movements
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General

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