The green value of data: evidence on how open government data promote sustainable economic growth from a multi-period DID approach

Introduction The symbiotic relationship between GDP growth and carbon reduction has been a global challenge, particularly for China, where green growth has become an urgent issue. This study explores the role of government data openness as an innovative policy tool to address the structural contradiction between economic growth and emission reduction. Methods We treat “government data openness” as a quasi-natural experiment and use panel data from 240 Chinese cities between 2007 and 2022. The empirical analysis employs a difference-in-differences (DID) approach to test the impact of government data openness on carbon intensity. We address endogeneity concerns using two-stage least squares (2SLS) and machine learning methods. Results Our findings show that government data openness significantly reduces carbon intensity. The results remain robust after sensitivity tests and the use of alternative methods. Further analysis reveals that the reduction in carbon intensity is primarily driven by green technological innovation and reduced energy consumption intensity. Discussion The study highlights that the effect of data openness in reducing carbon intensity is more pronounced in cities located northwest of the Hu Line, cities with better economic development, and those with higher vegetation coverage. Additionally, there is a notable spatial spillover effect in the causal relationship between government data openness and reduced carbon intensity. This research offers important policy insights for promoting green growth in China’s economy.