Geopolitical and geoeconomic shocks reprice sovereign credit risk through different transmission channels. Using a daily panel of 42 advanced and emerging economies over 2018--2025, we show that geopolitical shocks raise sovereign CDS spreads primarily through direct sovereign repricing, while the Global Financial Cycle (GFC) channel moves in the opposite direction and partly offsets that increase -- a ``scissors pattern.'' Geoeconomic shocks, by contrast, transmit mainly through financial conditions, policy uncertainty, and domestic amplification, with only a limited direct repricing component. A semistructural framework provides sign benchmarks for four transmission channels, and a Shapley--Taylor decomposition of nonlinear machine-learning predictions partitions each observation's spread into Direct, GFC, Uncertainty, and Local components. Narrative local projections around four dated crisis events recover the scissors pattern for Russia--Ukraine and support the broader channel taxonomy in the remaining episodes. Additional scorecard, placebo, and sign-restricted SVAR evidence corroborates the taxonomy beyond the baseline ML decomposition. Geopolitical direct effects decay with distance from the conflict zone in a gravity-style pattern (R2 = 0.35 for Russia--Ukraine), while policy-uncertainty shocks activate the Uncertainty channel more globally. The taxonomy implies that liquidity provision can mitigate GFC-driven spread widening, but not direct geopolitical sovereign repricing.

翻译：地缘政治与地缘经济冲击通过不同的传导渠道重新定价主权信用风险。利用2018—2025年间42个发达与新兴经济体的日度面板数据，我们表明地缘政治冲击主要通过直接主权重新定价推高主权CDS利差，而全球金融周期（GFC）渠道则向相反方向运动并部分抵消这一上升——形成"剪刀差模式"。相比之下，地缘经济冲击主要通过金融条件、政策不确定性和国内放大效应传导，直接重新定价成分有限。一个半结构化框架为四种传导渠道提供了符号基准，而基于非线性机器学习预测的Shapley—Taylor分解将每个观测值的利差分解为直接效应、GFC效应、不确定性效应和本地效应。围绕四个有明确日期的危机事件进行叙事性局部投影，恢复了俄乌冲突的剪刀差模式，并在其余事件中支持了更广泛的渠道分类。额外的评分卡、安慰剂和符号约束SVAR证据证实了该分类体系超越了基准机器学习分解。地缘政治直接效应随与冲突区域距离的增加呈重力模式衰减（俄乌冲突R²=0.35），而政策不确定性冲击在全球范围内激活了不确定性渠道。该分类体系意味着流动性提供可缓解GFC驱动的利差扩大，但无法缓解直接地缘政治主权重新定价。