On the Estimation of True State Dependence in the Persistence of Innovation*
用动态非线性面板数据模型估计企业创新的真实状态依赖，发现真实状态依赖仅解释约一半的持续性，而随机效应方法高估了这一比例。
Abstract This paper explores the persistence often found in firms’ innovation and advances current research by investigating its actual nature. Previous studies have aimed at disentangling true state dependence from spurious state dependence by using a random effects (RE) dynamic panel probit approach, thereby imposing strong conditions on the underlying structure of the unobserved heterogeneity. Building on recent advances in the econometric literature, which allows for true fixed effects estimation of dynamic nonlinear panel data models, we demonstrate that relaxing the assumptions on the unobserved heterogeneity can have a considerable effect on the estimates of true state dependence. While we confirm the existence of a strong persistence of innovation in firms, we however find that true state dependence only explains about half of the persistent behaviour displayed by firms; this is in contrast to the popular RE methodology that attributes 70% to 100% of persistence to true state dependence. Our results suggest that policy programs aimed at encouraging initial innovations alone are useful but may not possess a long‐term stimulating effect on innovation activity.