Understanding and Predicting Systemic Corporate Distress : A Machine-Learning Approach /
In this paper, we study systemic non-financial corporate sector distress using firm-level probabilities of default (PD), covering 55 economies, and spanning the last three decades. Systemic corporate distress is identified by elevated PDs across a large portion of the firms in an economy. A machine-...
| Main Author: | Hacibedel, Burcu |
|---|---|
| Other Authors: | Qu, Ritong |
| Format: | Journal |
| Language: | English |
| Published: |
Washington, D.C. :
International Monetary Fund,
2022.
|
| Series: | IMF Working Papers; Working Paper ;
No. 2022/153 |
| Subjects: | |
| Online Access: | Full text available on IMF |
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