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Cross-Border spillover of imported sovereign risk to China: Key factors identification based on XGBoost-SHAP explainable machine learning algorithm

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  • Shi, Guifen
  • Chen, Zhizhen
  • Luo, Weichen
  • Wei, Zijun

Abstract

This paper examines the imported sovereign risk from G20 countries to China and the transmission channels. To explore how sovereign risk transmit in different conditions, the study constructs QVAR model to measure China's imported sovereign risk and use XGBoost-SHAP machine learning algorithm to explain the key channels. The research reveals key findings. First, external sovereign risk importing to China in upper and lower conditions are asymmetric. Second, developing countries have more significant risk spillovers to China comparing to advanced countries in normal condition. Third, there are significant differences in risk transmission channels under different quantile conditions.

Suggested Citation

  • Shi, Guifen & Chen, Zhizhen & Luo, Weichen & Wei, Zijun, 2024. "Cross-Border spillover of imported sovereign risk to China: Key factors identification based on XGBoost-SHAP explainable machine learning algorithm," Finance Research Letters, Elsevier, vol. 70(C).
    • Handle: RePEc:eee:finlet:v:70:y:2024:i:c:s1544612324013369
    DOI: 10.1016/j.frl.2024.106307
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