Public Data Openness and Corporate Debt Financing Cost: Quasi-Experimental Evidence from Chinese Listed Firms

초록

Purpose – This paper asks whether opening government-held public data lowers the price that firms pay for debt. Because bank borrowing dominates corporate external finance in China, the informational content of credit pricing is a first-order question for both financial policy and corporate financial management. Design/Methodology/Approach – We treat the staggered launch of municipal public data open platforms in 194 of 250 Chinese prefecture-level cities as a quasi-natural experiment and estimate multi-period difference-in-differences models on a firm-year panel of A-share listed companies covering 2011-2023 (39,673 observations). The preferred specification includes firm and year fixed effects together with 17 firm-level and city-level controls, and standard errors are clustered by firm. Three transmission channels and three moderators are examined, and identification is assessed with dynamic-effect, PSM-DID, placebo, instrumental-variable and Heckman tests. Findings – Public data openness reduces the cost of debt by about 0.25 percentage points, some 4.7% of the sample mean. The effect works through lower information asymmetry, smaller analyst forecast dispersion and a longer debt maturity structure. It is stronger for firms with more advanced digital transformation and wider analyst coverage, and weaker for state-owned enterprises. The estimates survive alternative measures, samples, estimators and endogeneity corrections. Research Implications – Data openness is a low-cost instrument of financial policy: by enriching the public information environment it improves credit pricing, not only credit quantity. Governments should widen data supply and standardise data quality, while firms should build the absorptive capacity needed to convert open data into cheaper external finance.

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