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Statistical Methods of Predicting Country Debt Crisis

In: The Practice of Lending

Author

Listed:
  • Terence M. Yhip

    (University of the West Indies)

  • Bijan M. D. Alagheband

    (McMaster University and Hydro One Networks Inc.)

Abstract

This chapter discusses discriminant analysis, a statistical method for handling classification problem, and applies the analysis to predict sovereign debt crisis by differentiating two groups, “Default” and “Non-default”, based on certain quantitative and qualitative country characteristics. The model is tested on a new country to determine which of the two groups it belongs, and the model correctly predicts default. With the same characteristics for the discriminant function, the logit function, which measures the odds of default in relation to such characteristics, is also estimated. For classification purposes, discriminant analysis uses normal distribution, whereas the logit model assumes a distribution with fatter tails compared to normal distribution, thus making logit analysis more relevant in the presence of abnormal and extreme values in the population.

Suggested Citation

  • Terence M. Yhip & Bijan M. D. Alagheband, 2020. "Statistical Methods of Predicting Country Debt Crisis," Springer Books, in: The Practice of Lending, chapter 9, pages 383-418, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-32197-0_9
    DOI: 10.1007/978-3-030-32197-0_9
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    Cited by:

    1. Ogawa, Keishi & Garrod, Guy & Yagi, Hironori, 2023. "Sustainability strategies and stakeholder management for upland farming," Land Use Policy, Elsevier, vol. 131(C).
    2. Lenka PÅ™eÄ ková & Iveta PaleÄ ková, 2023. "Financial Stability of the Czech Insurance Companies," Journal of Economics / Ekonomicky casopis, Institute of Economic Research, Slovak Academy of Sciences, vol. 71(1), pages 65-86, January.

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