The value of digital government transformation: Evidence from R&D subsidy efficiency in China

Abstract

Exploiting a quasi-natural experiment in China in which the Big Data Administration was established in various cities across different times (i.e., pilot cities), we explore the role that digital government transformation plays in curbing firms' R&D manipulation activities. We rely on a staggered difference-in-differences research design and find that firms located in pilot cities significantly reduce the magnitude of their R&D manipulation from the pre- to the post- digital government transformation period, compared to firms located in nonpilot cities during the same time frame. Our analysis shows that digital government transformation mitigates R&D manipulation by strengthening government regulatory powers and normalizing corporate R&D practices. Additionally, we find that this impact is more pronounced in non-state-owned enterprises, manufacturing companies, smaller businesses, and those with less rigorous external oversight. Moreover, we identify a regulatory effect similar to “poverty alleviation” in China, where digital governance has a more substantial impact on R&D manipulation in economically developed areas. Our results also demonstrate that digital government transformation significantly improves the efficiency of governmental R&D subsidies and the quality of firms' innovation outputs. Collectively, these findings indicate that digital transformation can amplify the effectiveness of industrial policies. Our study, therefore, contributes to the literature by offering theoretical perspectives and vital microeconomic evidence on how to optimize subsidy efficiency through the rapid development of big data and other cutting-edge digital technologies.