Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
We use machine learning techniques to quantify trade tensions between the United States and China. Our measure matches well‐known events in the US‐China trade dispute and is exogenous to the developments on global financial markets. Local projections show that rising trade tensions leave US markets largely unaffected, except for firms that are more exposed to China, while negatively impacting stock market indices and exchange rates in China and emerging markets. We complement these findings with additional evidence suggesting that the US‐China trade tensions have been interpreted as a negative demand shock for the Chinese economy rather than as a global risk shock.