An analysis of the impact of open government data on innovation in Chinese cities: based on the PSM-DID method

Purpose With the advent of the big data era, open government data (OGD) has become an important driver of social innovation and economic development. This study aims to explore the impact of the current hot issue of OGD on innovation, and further investigates the heterogeneous effects of OGD in cities with different levels of factor agglomeration and education. Design/methodology/approach Based on the specific year when each prefecture-level city in China opens the public data platform one after another as a quasi-natural experiment, this study constructs panel data of Chinese cities from 2007 to 2021 and adopts the method of propensity score matching – difference in differences (PSM-DID) to carry out empirical research. Findings The results proved that the implementation of OGD has a significant positive impact on innovation capacity. In addition, heterogeneity analysis reveals that the promotion effect of OGD on urban innovation is more significant in cities with higher degrees of factor aggregation and education levels. Originality/value First, although a few existing studies have examined the impact of OGD on innovation, they have not adequately addressed sample selection bias and the resulting endogeneity issues. This study employs a PSM-DID approach to accurately identify the causal effect of OGD on innovation. Second, it reveals the moderating mechanisms of factor agglomeration and education level, enriching the theoretical framework and understanding of how OGD influences innovation. The findings provide empirical evidence and policy implications for governments seeking to better leverage the economic value of OGD.