Data on Chinese Innovation
Key Takeaways
- •The researchers examined almost 14 million domestic Chinese patent publications, including critical technologies identified by the U.S. Department of Defense.
- •Chinese patenting appears to track broader innovation progress rather than functioning as a noisy standalone metric.
- •Universities contribute more to the patenting ecosystem than state-owned enterprises or government-owned facilities.
- •Fewer than one in ten Chinese critical technology patents includes an inventor with U.S. experience or training.
- •Text-based quality measures showed no deterioration in Chinese critical technology patent quality relative to U.S. awards.

China’s technological progress in recent decades has been viewed with admiration, alarm, and, in some cases, doubt. To better understand the Chinese innovation ecosystem, researchers compiled a dataset of almost 14 million domestic Chinese patent publications, with a focus on the subset of critical technologies identified by the U.S. Department of Defense.
Several patterns emerge from the data. Chinese patenting is strongly associated with other measures of innovative progress, suggesting that patent counts in this setting are tracking a broader buildout of technical activity rather than standing alone as a noisy metric. Patent activity is not concentrated in corporate giants such as Huawei. Universities have played a major role in innovation, far more than state-owned enterprises or government-owned facilities, which matters because it points to a wider base of contributors across China’s research system. In addition, fewer than one in ten Chinese critical technology patents involves an inventor with U.S. experience or training, indicating that this portion of the innovation pipeline is largely domestically rooted.
The researchers also use four text-based measures of patent quality and find that the rise of Chinese patenting in critical technologies has not been associated with a decline in quality relative to U.S. awards.
The findings are from a recent paper by Josh Lerner, Namrate Narain, Dimitris Papanikolaou, Amit Seru, and Zunda Winston Xu. Via Kevin Lewis.