How Do Geopolitical Shocks Shape Analyst Forecast Bias? Evidence from the US–China Trade War

Zheyuan Ji et al.

Economics & Politics2026https://doi.org/10.1111/ecpo.70044article
AJG 2ABDC A
Weight
0.50

Abstract

Geopolitical risk (GPR) has emerged as a major source of global economic uncertainty, yet its impact on key information intermediaries remains underexplored. This paper examines how GPR shapes analyst forecast bias. We exploit the 2018 US–China trade war as a quasi‐natural experiment and construct a firm‐level GPR exposure measure based on pre‐shock profit sensitivities. We find that analysts significantly reduced their optimistic bias for firms with high GPR exposure in the post‐trade war period. This correction, however, is consistent with a behavioral, non‐rational learning path. Analysts showed initial over‐pessimism during the conflict, and this was followed by significant over‐compensation after the conflict de‐escalated. Mechanism tests show analysts also use coverage termination as an “implicit sell” signal, rather than expressing pessimism directly through revised forecasts. Heterogeneity analyses show the effects are concentrated in non‐SOEs and firms with deep, rather than broad, international exposure. Our study contributes to the literature on GPR and information intermediaries, offering key insights for regulators and investors navigating geopolitical uncertainty.

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https://doi.org/https://doi.org/10.1111/ecpo.70044

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@article{zheyuan2026,
  title        = {{How Do Geopolitical Shocks Shape Analyst Forecast Bias? Evidence from the US–China Trade War}},
  author       = {Zheyuan Ji et al.},
  journal      = {Economics & Politics},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1111/ecpo.70044},
}

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How Do Geopolitical Shocks Shape Analyst Forecast Bias? Evidence from the US–China Trade War

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.