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How much is too much? Assessing the non-linear relationship between debt and sovereign creditworthiness

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  • Zwart, Sanne

Abstract

Public debt is a very weak predictor of a country's credit rating if a country's other features are not taken into account. However, everything else equal, more public debt is associated with worse ratings. This paper explores the relationship between debt and sovereign creditworthiness by explicitly modelling the debt thresholds associated with rating changes. It finds that the impact of an increase in public debt is highly non-linear and crucially depends on a country's economic situation. In particular, low levels of GDP per capita are associated with a smaller range of possible ratings than higher levels. Hence, for countries with a higher GDP per capita, a change in debt levels is thus more likely to result in a rating change. Overall, the non-linear relationship between debt and creditworthiness is substantial, and accounting for it improves the performance of sovereign credit rating models significantly.

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  • Zwart, Sanne, 2022. "How much is too much? Assessing the non-linear relationship between debt and sovereign creditworthiness," EIB Working Papers 2022/05, European Investment Bank (EIB).
    • Handle: RePEc:zbw:eibwps:202205
    DOI: 10.2867/961968
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    References listed on IDEAS

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    1. Dilek Teker & Aynur Pala & Oya Kent, 2013. "Determination of Sovereign Rating: Factor Based Ordered Probit Models for Panel Data Analysis Modelling Framework," International Journal of Economics and Financial Issues, Econjournals, vol. 3(1), pages 122-132.
    2. Antonio Afonso & Pedro Gomes & Philipp Rother, 2009. "Ordered response models for sovereign debt ratings," Applied Economics Letters, Taylor & Francis Journals, vol. 16(8), pages 769-773.
    3. Metodij Hadzi-Vaskov & Mr. Luca A Ricci, 2019. "The Nonlinear Relationship Between Public Debt and Sovereign Credit Ratings," IMF Working Papers 2019/162, International Monetary Fund.
    4. Reusens, Peter & Croux, Christophe, 2017. "Sovereign credit rating determinants: A comparison before and after the European debt crisis," Journal of Banking & Finance, Elsevier, vol. 77(C), pages 108-121.
    5. Tran, Yen & Vu, Huong & Klusak, Patrycja & Kraemer, Moritz & Hoang, Tri, 2021. "Sovereign credit ratings during the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 78(C).
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