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Subjectivity in sovereign credit ratings

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  • De Moor, Lieven
  • Luitel, Prabesh
  • Sercu, Piet
  • Vanpée, Rosanne

Abstract

A sovereign creditrating is a function of hard and soft information that should reflect the creditworthiness and the probability of default of a country. We propose an alternative characterisation for the subjective component of a sovereign credit rating – the parts related to the ratee’s lobbying effort or its familiarity from a United States point of view – and apply it to S&P, Moody’s and Fitch ratings, using both traditional ordered-logit panel models and machine learning techniques. This subjective component turns out to be large, especially for the low-rated countries. Countries that are rated as investment grade tend to be positively influenced by it, and vice versa. Subjective judgment in credit ratings does have predictive value: it helps in identifying chances of sovereign defaults in the short-term. Still, the impact of subjectivity in sovereign ratings on borrowing costs is very limited on average.

Suggested Citation

  • De Moor, Lieven & Luitel, Prabesh & Sercu, Piet & Vanpée, Rosanne, 2018. "Subjectivity in sovereign credit ratings," Journal of Banking & Finance, Elsevier, vol. 88(C), pages 366-392.
  • Handle: RePEc:eee:jbfina:v:88:y:2018:i:c:p:366-392
    DOI: 10.1016/j.jbankfin.2017.12.014
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    2. Bart H. L. Overes & Michel van der Wel, 2021. "Modelling Sovereign Credit Ratings: Evaluating the Accuracy and Driving Factors using Machine Learning Techniques," Papers 2101.12684, arXiv.org, revised Jul 2021.
    3. Cuadros-Solas, Pedro Jesús & Salvador Muñoz, Carlos, 2022. "Disentangling the sources of sovereign rating adjustments: An examination of changes in rating policies following the GFC," Research in International Business and Finance, Elsevier, vol. 59(C).
    4. Lukasz Dopierala & Daria Ilczuk & Liwiusz Wojciechowski, 2020. "Sovereign credit ratings and CDS spreads in Emerging Europe," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 15(3), pages 419-438, September.
    5. Ahmed, Shamima & Alshater, Muneer M. & Ammari, Anis El & Hammami, Helmi, 2022. "Artificial intelligence and machine learning in finance: A bibliometric review," Research in International Business and Finance, Elsevier, vol. 61(C).
    6. Ambrocio, Gene & Hasan, Iftekhar, 2019. "Friends for the benefits: The effects of political ties on sovereign borrowing conditions," Bank of Finland Research Discussion Papers 13/2019, Bank of Finland.
    7. Slapnik, Ursula & Lončarski, Igor, 2021. "On the information content of sovereign credit rating reports: Improving the predictability of rating transitions☆," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).
    8. Boumparis, Periklis & Milas, Costas & Panagiotidis, Theodore, 2019. "Non-performing loans and sovereign credit ratings," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 301-314.
    9. Patrycja Klusak & Matthew Agarwala & Matt Burke & Moritz Kraemer & Kamiar Mohaddes, 2021. "Rising Temperatures, Falling Ratings: The Effect of Climate Change on Sovereign Creditworthiness," Working Papers EPRG2110, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    10. Ambrocio, Gene & Hasan, Iftekhar, 2021. "Quid pro quo? Political ties and sovereign borrowing," Journal of International Economics, Elsevier, vol. 133(C).
    11. Ambrocio, Gene & Hasan, Iftekhar, 2019. "Friends for the benefits: The effects of political ties on sovereign borrowing conditions," Research Discussion Papers 13/2019, Bank of Finland.
    12. Cuadros-Solas, Pedro J. & Salvador, Carlos & Suárez, Nuria, 2021. "Am I riskier if I rescue my banks? Beyond the effects of bailouts," Journal of Financial Stability, Elsevier, vol. 56(C).
    13. Šergo Zdravko & Gržinić Jasmina, 2018. "Does the International Tourism Industry Relax Sovereign Credit Ratings: The Case of Countries Most Reliant on Tourism," South East European Journal of Economics and Business, Sciendo, vol. 13(2), pages 100-111, December.
    14. Anastasios Petropoulos & Vasilis Siakoulis & Evangelos Stavroulakis, 2022. "Towards an early warning system for sovereign defaults leveraging on machine learning methodologies," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 29(2), pages 118-129, April.
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    More about this item

    Keywords

    Credit ratings; Rating agencies; Artificial intelligence;
    All these keywords.

    JEL classification:

    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • O16 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Financial Markets; Saving and Capital Investment; Corporate Finance and Governance

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