| Issue |
SHS Web Conf.
Volume 225, 2025
2025 3rd International Conference on Financial Management and the Digital Economy (ICFMDE 2025)
|
|
|---|---|---|
| Article Number | 04001 | |
| Number of page(s) | 8 | |
| Section | Macro Policy & Digital Economy Resilience | |
| DOI | https://doi.org/10.1051/shsconf/202522504001 | |
| Published online | 13 November 2025 | |
The Effect of Trade Policy Uncertainty on Chinese Export-Oriented Listed Companies’ Financial Performance
College of Business and Public Management, Wenzhou-Kean University, Wenzhou, China
* Corresponding author: 1308319@wku.edu.cn
This study examines the impact of trade policy uncertainty on the performance of export-oriented listed firms (A-shares) on China’s Shanghai and Shenzhen exchanges from 2016 to 2024. Using firm-level data and the trade policy uncertainty sub-index from the Economic Policy Uncertainty Index, an OLS regression model is employed to analyze the relationship between and corporate financial performance, with robustness tests conducted by substituting the dependent variable with return on equity. The results show a significant negative correlation between and firm profitability: a 1% increase in TPU decreases return on assets () by 0.013 units, a relationship that remains robust after controlling for firm size, financial leverage, and other factors. Robustness tests reveal that also has a significantly negative impact on(coefficient = -0.026, p<0.01), indicating that policy uncertainty not only reduces asset operational efficiency but also impairs shareholder returns. Additionally, firm size is positively correlated with , while financial leverage has a significant negative effect on both and , suggesting that highly leveraged firms are more vulnerable to external shocks. This study concludes that trade policy uncertainty substantially negatively affects the performance of export-oriented firms by increasing operational risks and capital costs.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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