How does public data openness enhance urban total factor productivity? A perspective from government governance and transaction costs

This study evaluates the causal effect of public data openness on urban total factor productivity (TFP) and explores its mechanisms through government governance and transaction costs. Using panel data of Chinese prefecture-level cities from 2000 to 2023, we treat the launch of government data open platforms as a quasi-natural experiment and employ a multi-period difference-in-differences (DID) approach. TFP is measured via the two-step Solow residual method, with robustness verified by instrumental variable estimation, PSM-DID, placebo tests, and green TFP. Baseline regressions show that public data openness significantly enhances urban TFP. Mechanism analysis reveals that improved government governance and reduced transaction costs are the primary drivers. Heterogeneity analysis indicates stronger policy effects in non-Yangtze River Economic Belt regions and areas with lower financial development, exhibiting a ‘timely assistance’ characteristic. This study provides city-level causal evidence, identifies concrete transmission channels, expands research on data factor economic value, and offers empirical support for differentiated data openness policies and inclusive growth.