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We are back again! What can artificial intelligence and machine learning models tell us about why countries knock at the door of the IMF?

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  • Agbloyor, Elikplimi Komla
  • Pan, Lei
  • Dwumfour, Richard Adjei
  • Gyeke-Dako, Agyapomaa

Abstract

This paper examines the factors that predict an IMF bailout. In doing so, we use a large dataset from 1993 to 2021 with 6550 observations and 138 features and adopt recent advances in machine learning and artificial intelligence models such as tree-based, boosting and artificial neural network techniques. We find that apart from traditional indicators such as debt and macroeconomic factors; agricultural, energy, health and social factors are strong predictors of an IMF bailout. These factors have hitherto not received much attention in the literature.

Suggested Citation

  • Agbloyor, Elikplimi Komla & Pan, Lei & Dwumfour, Richard Adjei & Gyeke-Dako, Agyapomaa, 2023. "We are back again! What can artificial intelligence and machine learning models tell us about why countries knock at the door of the IMF?," Finance Research Letters, Elsevier, vol. 57(C).
    • Handle: RePEc:eee:finlet:v:57:y:2023:i:c:s1544612323006165
    DOI: 10.1016/j.frl.2023.104244
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    References listed on IDEAS

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    More about this item

    Keywords

    Artificial intelligence; Machine learning; IMF bailout;
    All these keywords.

    JEL classification:

    • F3 - International Economics - - International Finance
    • F4 - International Economics - - Macroeconomic Aspects of International Trade and Finance

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