Existing literature predominantly relies on patent metrics to measure innovation in the medical industry; however, patents merely reflect early-stage technological "ideas" and fail to capture the product development phase. This study utilizes clinical trial data as a novel innovation indicator to examine the causal effect of venture capital (VC) on medical enterprises' ability to cross the "valley of death" and achieve innovation commercialization, along with the boundaries of this impact. Based on panel data of 2,823 medical enterprises in China's Yangtze River Delta from 2010–2019, clinical trial application data were obtained from the China Drug Clinical Trial Registration Platform. High-dimensional fixed-effects regression models were employed, with endogeneity and sample selection biases addressed through Propensity Score Matching (PSM), Instrumental Variable Two-Stage Least Squares (IV-2SLS), and the Heckman two-stage selection model. VC investment significantly promoted clinical trial activities, with Average Treatment Effects (ATE) indicating increases of 9.7%, 19.5%, and 27.4% in trial applications one, two, and three years post-investment, respectively . However, Heckman model results revealed that this effect primarily operated by facilitating firms' entry decision into clinical development rather than linearly expanding trial scale among existing participants. The 2015 clinical trial policy reform significantly amplified VC's innovation-driving effect. Heterogeneity analyses demonstrated that local investment, syndicated investment , and government venture capital all positively affected trial activities, with no evidence of crowding-out effects from government VC. This study overcomes the limitations of patent-based measurement, confirming VC's threshold-crossing role in the critical phase of medical innovation transformation and the moderating role of institutional environments. The findings indicate that government VC effectively functions as "patient capital" within the Chinese context, providing empirical evidence for designing financing policies and regional innovation cluster strategies in emerging economies.
Kaihuang Zhang (Mon,) studied this question.