The Impact of Data Element Governance on Cross-regional Capital Flow: Quasi-Natural Experimental Evidence from Mergers and Acquisitions of Chinese Listed Companies

In the era of the digital economy, data elements are increasingly emerging as a key driver of economic growth and the optimization of resource allocation. As the data volume expands rapidly, effective governance is essential to enhance its authenticity, usability, and shareability. In this context, the paper delves into the impact of data element governance on cross-regional capital flow, with a particular focus on the mechanisms that affect the geographical distance of corporate cross-regional mergers and acquisitions (M&As). Using a sample of 8,251 cross-city M&A cases initiated by Chinese A-share listed companies between 2007 and 2021, and considering the big data bureau setting in prefecture-level cities as a quasi-natural experiment, this paper applies a multi-period difference-in-differences (DID) model to assess the impact of data element governance on the geographic distance of corporate M&As. The findings indicate that the big data bureau setting significantly expands the geographical scope of M&A transactions. This is primarily achieved by optimizing the regional information environment and strengthening regional resource endowments, thereby reducing information asymmetry and transaction costs, increasing expected investment returns, and facilitating the cross-regional capital flow. Further heterogeneity analysis reveals that state-owned enterprises, firms with low growth rate, firms with large boards of directors, and firms located in cities with high per capita GDP benefit more substantially from these effects. This paper contributes to the theoretical understanding of the mechanisms through which data element governance affects capital flow and provides policy insights for governments to enhance data governance capacity and guide the optimal allocation of capital.