Registration System Reform and Analyst Forecast Accuracy: Evidence from China

Abstract

The registration system reform (RSR) in China’s capital market has gradually become the focus of academic discussion and attention. However, the existing literature has not yet offered systematic theoretical insights into how RSR influences analyst forecasts. To explore the impact of RSR on analyst forecasts, drawing on information spillover effect theory and limited attention theory, using the data from Chinese A-share companies that are listed under the approval system in 2015-2021 and a staggered difference-in-differences model, the spillover effect of the RSR on analyst forecast accuracy from the analysts’ perspective was examined. The results show that the RSR has a positive spillover effect on analyst forecast accuracy. After the RSR, the analyst forecast accuracy for peer companies under the approval system has significantly improved. This spillover effect intensifies with the improvement of industry information that has been provided by companies under the registration system. The RSR induces a “catfish effect” on the disclosure quality of peers under the approval system, which compels them to elevate their information disclosure and enhances analyst forecast accuracy. The impact of the RSR on improving analyst forecast accuracy becomes pronounced when the same analyst follows companies under the registration system and peers under the approval system and when these peers are located in regions with superior institutional environments and with high internal control quality. The conclusions provide empirical evidence that supports the government’s active promotion of the RSR and the optimization of the information environment in the capital market.