Multivariate quantile regression shows how climate policy uncertainty affects sovereign credit default swaps, indicating varying impacts across developed and emerging economies.
This study investigates the nonlinear and regime-dependent relationship between climate policy uncertainty (CPU) and sovereign credit default swap (CDS) spreads across a panel of developed and emerging economies from February 2010 to March 2025. Utilizing the Quantile-on-Quantile Regression (QQR) and Multivariate QQR (MQQR) frameworks, we capture the heterogeneous effects of CPU under varying market states and assess the marginal role of global risk factors, including geopolitical risk (GPR), economic policy uncertainty (EPU), and market volatility (VIX). The findings indicate that in developed markets, CPU exerts a nonlinear impact that intensifies during periods of heightened sovereign risk, while in low-risk regimes, its effect is often muted or reversed. In contrast, emerging economies exhibit more volatile and state-contingent responses, with CPU exerting stronger effects in calm conditions but diminishing in explanatory power once global risks are taken into account. These dynamics highlight the importance of institutional credibility and financial integration in moderating CPU-driven credit risk.
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Nader Naifar (2025) studied this question.
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