Title: How do geopolitical tensions affect firms’ direction of technological change?

Speaker: Hongxun Ruan, Associate Professor, Peking University

Host: Xiangwei Wan, Associate Professor, Antai College of Economics and Management, Shanghai Jiao Tong University

Time: 13:30-15:00, Wednesday, March 25, 2026

Venue: Room 306, Antai Haoran Building, Xuhui Campus, Shanghai Jiao Tong University

Brief introduction of the content: 

This paper reveals a large and overlooked source of distortion in predictive regressions: higher-order bias. While existing corrections only address first-order bias, we show that higher- order terms in both direct regression (DR) and implication (IM) based estimators can seriously mislead both statistical and economic conclusions, especially with persistent predictors and long horizons. We then develop iBoot, a unified framework that integrates indirect inference with bootstrap methods. iBoot (i) jointly corrects first- and higher-order biases in both estimation and inference for DR and IM estimators, and (ii) applies seamlessly to both short- and long-horizon regressions. Simulations demonstrate that iBoot achieves minimal bias, accurate confidence intervals, correct test size, and high power. When applied to classic return predictors, iBoot materially changes the economic significance of return predictability. This paper thus establishes a new foundation for credible and robust estimation and inference in predictive regressions.

Technology export controls shrink the effective market for embargoed U.S.-centric technological trajectories and redirect innovative effort toward sanction–resilient alternatives. We develop a text–based Technology Redirection Score (TRS) that uses patent similarities to measure a patent’s proximity to an incumbent U.S.-led technology base relative to alternative

technology bases. We apply the measure to U.S. export controls imposed through additions of Chinese firms to the BIS Entity List. Using patent text for both U.S. and Chinese assignees, we find a pronounced decline in TRS for exposed U.S. suppliers and Chinese firms, indicating systematic redirection away from U.S.-centric stacks toward alternative trajectories. Among U.S. suppliers, patents that shift more toward alternative trajectories are valued about $3.07 million higher than otherwise comparable patents that remain on the incumbent path after sanctions. Consistent with this redirection, U.S. suppliers to sanctioned Chinese customers experience cumulative abnormal returns (CARs) of -2.93% around Entity List announcements, whereas Chinese upstream suppliers earn positive CARs of 3.48%. We also find that exposed U.S. firms experience declines in innovation output and profitability following the shock. Sanctioned Chinese entities and their domestic suppliers exhibit significant increases in both the quantity and quality of innovation. By linking stock returns, patent text, and firm-level innovation outcomes, the paper provides new micro-evidence on how technology sanctions act as a directed technical change shock, reallocating innovative activity across technological trajectories.

Speaker's profile:

Hongxun Ruan, Associate Professor of Finance at Guanghua School of Management, Peking University. He received his PhD in Finance from Wharton School, University of Pennsylvania. His research focuses on institutional investors, empirical asset pricing, and structural estimation. Professor Ruan’s research has been published in leading academic journals worldwide, including The Journal of Finance, The Review of Financial Studies, and Journal of Financial Research. He also serves as a reviewer for top academic journals home and abroad, including JF, JFE, and RFS..

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