| Title |
Revisiting the determinants of sovereign debt ratings in Europe through artificial intelligence techniques |
| Authors |
Galnares, Carlos , MARTÍNEZ ESTUDILLO, ALFONSO CARLOS, CARBONERO RUZ, MARIANO, CAMPOY MUÑOZ, MARÍA DEL PILAR |
| External publication |
No |
| Means |
APPLIED ECONOMICS LETTERS |
| Scope |
Article |
| Nature |
Científica |
| JCR Quartile |
3 |
| SJR Quartile |
2 |
| JCR Impact |
1.6 |
| SJR Impact |
0.45 |
| Web |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133500641&doi=10.1080%2f13504851.2022.2097171&partnerID=40&md5=e40036e6a17f27079be8f6e408f69006 |
| Publication date |
06/07/2022 |
| ISI |
000825249200001 |
| Scopus Id |
2-s2.0-85133500641 |
| DOI |
10.1080/13504851.2022.2097171 |
| Abstract |
In papers using artificial intelligence (AI) techniques, little attention has been paid to the determinants of sovereign debt ratings. We propose a reduced set of variables regarding the economic performance of a country that are consistent with the idea of debt sustainability. The robustness of this set is supported by the results obtained with different well-known AI techniques using data from EU-15 countries during the 2002-2017 period as the experimental setting. The variables are publicly available, allowing a quick and reliable assessment of the creditworthiness of a sovereign and providing useful information for decision-makers and investors. |
| Keywords |
Sovereign credit ratings; credit rating agencies; EU-15; artificial intelligence |
| Universidad Loyola members |
|
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