:The aim of this paper is to examine the impact of local government competition and environmental regulation intensity on regional innovation performance and its regional heterogeneity. Based on the theoretical mechanism of the aforementioned variables, this study uses the Chinese provincial panel data from 2001 to 2016. We use the super-efficiency data envelopment analysis (SE-DEA) to evaluate regional innovation performance. To systematically examine the impact of local government competition and environmental regulation intensity on regional innovation performance, we build a panel date model using the feasible generalized least squares (FGLS) method. The results indicate that: the regional innovation performance can be significantly improved through technological spillover; local governments compete for foreign direct investment (FDI) to participate in regional innovative production. Moreover, improvements in environmental regulation intensity enhance regional innovation performance through the innovation compensation effect. Our results show that the local governments tend to choose lower environmental regulation intensity to compete for more FDI, which has an inhibitory effect on regional innovation performance. Furthermore, due to regional differences in factor endowments, economic reforms and economic development levels in Chinese provinces, there exists a significant regional consistency in the impact of local government competition and environmental regulation intensity on regional innovation performance. Therefore, institutional arrangements and incentive constraints must be adopted to enhance regional innovation performance as well as to guide and foster the mechanism of green innovation competition among local governments. At the same time, considering the regional heterogeneity of local government competition and environmental regulation intensity affecting regional innovation performance, policy makers should avoid the "one-size-fits-all" strategy of institutional arrangements.
* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.