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Sovereign Risk and Economic Complexity: Machine Learning Insights on Causality and Prediction

Serie

  • IREA Working Papers

Resumen

  • We investigate how a country’s economic complexity influences its
    sovereign yield spread with respect to the US. We analyze various maturities
    across 28 countries, consisting of 16 emerging and 12 advanced economies.
    Notably, a one-unit increase in the economic complexity index is associated
    to a reduction of about 87 basis points in the 10-year yield spread (p<0.01).
    However, this effect is largely non-significant for maturities under 3 years
    and, when significant (p<0.1), the reduction is around 54 bps. This suggests
    that economic complexity affects not only the level of the sovereign yield
    spreads but also the curve slope. Our first set of models utilizes advanced
    causal machine learning tools, allowing us to control for a large set of
    potential confounders. This is crucial given our relatively small dataset of
    countries and roughly 15 years of data, as well as the low frequency of
    annual variables. In the second part of our analysis, we shift our focus to
    economic complexity’s predictive power. Our findings reveal that economic
    complexity is a robust predictor of sovereign spreads at 5-year and 10-year
    maturities, ranking among the top three predictors, alongside inflation and
    institutional factors like the rule of law. We also discuss the potential
    mechanisms through which economic complexity reduces sovereign risk and
    emphasize its role as a long-run determinant of productivity, output and
    income stability, and the likelihood of fiscal crises.

fecha de publicación

  • 2023

Líneas de investigación

  • Convenience Yields
  • Double-Machine-Learning
  • Government Debt
  • Sovereign Credit Risk
  • XGBoost
  • Yield Curve

Issue

  • 202315