Public Data Platforms, Information Friction, and the Quality of Corporate Innovation

Whether open government data improves how efficiently firms convert R&D resources into innovation outcomes remains underexplored, as existing studies focus on the scale of innovation activity rather than the quality of output per unit of input. Drawing on A-share listed firms in China from 2007 to 2024, this paper exploits the staggered rollout of public data platforms across 283 prefecture-level cities as a quasi-natural experiment. Platform launch raises the intensity of invention patent output per unit of R&D investment, and this effect proves robust to alternative specifications including patent quality measures, stochastic frontier efficiency scores, and constructions that accommodate the multi-year examination cycle of invention patents, as well as to corrections for endogeneity. Platform launch is followed by a systematic narrowing of corporate bond issuance spreads within cities, a result that holds after controlling for local government financing vehicle issuance volumes, suggesting that government disclosure of administrative records lowers the cost for external capital providers to verify firm credit conditions and compresses financing risk premiums. Firm-level financing constraint indices and commercial credit utilization patterns yield concordant evidence on the channel. The positive effect is more pronounced among private enterprises, R&D-intensive industries, and cities with stronger digital infrastructure, indicating that gains from open data depend on firms' information needs aligning with the absorptive capacity of their local digital environment. These findings carry implications for open data governance reform across developing economies in the Asia-Pacific region.