Data Trading Platforms and Urban Joint Pollution–Carbon Burden: Quasi-Experimental Evidence from China

Cities face growing pressure to reduce air pollution and carbon emissions simultaneously, yet the data systems supporting energy and environmental decision-making remain fragmented. This study examines whether city-level data trading platforms, as institutions for organizing data circulation, are associated with changes in urban joint pollution–carbon outcomes. Using a balanced panel of 164 Chinese cities from 2009 to 2023, we construct an outcome-oriented joint pollution–carbon burden indicator from an entropy-weighted pollution index and multisource carbon-emission estimates; lower values indicate better joint performance. The empirical results show that platform establishment is associated with a statistically significant decline in the joint burden. This finding remains consistent across alternative indicator constructions, an unbalanced panel of complete observations, controls for regional trends, treatment assignments verified against original sources, and placebo tests based on random assignment. Further analysis indicates that platform establishment is associated with improvements in energy productivity and industrial upgrading, providing evidence consistent with the proposed production mechanisms. These findings suggest that data marketization may contribute to improved environmental outcomes by facilitating the integration of data circulation into energy management and production decisions.