IMF Working Papers

Debt Is Not Free

By Marialuz Moreno Badia, Paulo A Medas, Pranav Gupta, Yuan Xiang

January 3, 2020

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Marialuz Moreno Badia, Paulo A Medas, Pranav Gupta, and Yuan Xiang. Debt Is Not Free, (USA: International Monetary Fund, 2020) accessed November 21, 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

With public debt soaring across the world, a growing concern is whether current debt levels are a harbinger of fiscal crises, thereby restricting the policy space in a downturn. The empirical evidence to date is however inconclusive, and the true cost of debt may be overstated if interest rates remain low. To shed light into this debate, this paper re-examines the importance of public debt as a leading indicator of fiscal crises using machine learning techniques to account for complex interactions previously ignored in the literature. We find that public debt is the most important predictor of crises, showing strong non-linearities. Moreover, beyond certain debt levels, the likelihood of crises increases sharply regardless of the interest-growth differential. Our analysis also reveals that the interactions of public debt with inflation and external imbalances can be as important as debt levels. These results, while not necessarily implying causality, show governments should be wary of high public debt even when borrowing costs seem low.

Subject: External debt, Financial crises, Machine learning, Personal income, Public debt

Keywords: Crisis observation, Crisis threshold, Fiscal crisis, Interest-growth differential, Probability of a crisis, WP

Publication Details

  • Pages:

    68

  • Volume:

    ---

  • DOI:

    ---

  • Issue:

    ---

  • Series:

    Working Paper No. 2020/001

  • Stock No:

    WPIEA2020001

  • ISBN:

    9781513523767

  • ISSN:

    1018-5941

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