Open Government Data, Resource Allocation Efficiency, and Sustainable Development in Manufacturing Firms: A Quasi-Natural Experiment Based on City-Level Government Data Platforms

Open government data is a key institutional arrangement in market-oriented data factor reforms. Using the staggered rollout of city-level government data platforms in China as a quasi-natural experiment and panel data of listed manufacturing firms (2011–2024), we employ a staggered difference-in-differences design to examine the effect of open government data on firms’ resource allocation efficiency. We find that government data platforms significantly reduce resource misallocation, a result robust to propensity score matching, exclusion of concurrent policy shocks, and double machine learning. Channel-level tests do not find statistically significant transmission through government transparency, firm digital innovation, or fiscal subsidy reallocation. Directional identification shows that the effect operates primarily as a corrective force on capital-overallocated firms by curbing inefficient investment, rather than as a relief effect on constrained firms, and is more pronounced in high-digital-intensity industries, smaller cities, and regions with lower digital development. By reducing the wasteful use of capital, labour, and energy and improving the information environment in factor markets, open government data offers a low-cost, institutionalized instrument for reconciling productivity growth with sustainable resource use, with direct relevance to the United Nations (UN) Sustainable Development Goals (SDGs).