IMF Working Papers

The Nonlinear Relationship Between Public Debt and Sovereign Credit Ratings

By Metodij Hadzi-Vaskov, Luca A Ricci

July 26, 2019

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Metodij Hadzi-Vaskov, and Luca A Ricci. The Nonlinear Relationship Between Public Debt and Sovereign Credit Ratings, (USA: International Monetary Fund, 2019) accessed November 23, 2024

Disclaimer: IMF Working Papers describe research in progress by the author(s) and are published to elicit comments and to encourage debate. The views expressed in IMF Working Papers are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management.

Summary

This study investigates the nonlinear relationship between public debt and sovereign credit ratings, using a wide sample of over one hundred advanced, emerging, and developing economies. It finds that: i) higher public debt lowers the probability of being placed in a higher rating category; ii) the negative debt-ratings relationship is nonlinear and depends on the rating grade itself; and iii) the identified nonlinearity explains the differential impact of debt on ratings in advanced economies versus in emerging markets and developing economies. These results hold for both gross debt and net debt, and are robust to alternative dependent variable definitions, analytical techniques, and empirical specifications. These findings underscore the potential for fiscal consolidation in helping countries achieve a better credit rating.

Subject: Credit ratings, Inflation, Money, Prices, Public debt

Keywords: Advanced economies, Asia and Pacific, Credit rating agencies, Credit rating grade, Credit ratings, Debt-ratings relationship, Emerging markets, Europe, Financial markets, GDP growth, Global, High-Investment Grade, Inflation, LIG rating, NIG rating, Non-linearities, North Africa, Panel regression, Public debt, Rating category, Rating grade, Sub-Saharan Africa, WP

Publication Details

  • Pages:

    37

  • Volume:

    ---

  • DOI:

    ---

  • Issue:

    ---

  • Series:

    Working Paper No. 2019/162

  • Stock No:

    WPIEA2019162

  • ISBN:

    9781498325059

  • ISSN:

    1018-5941

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