Green innovation and carbon emission reduction: Empirical insights from spatial durbin and dynamic threshold models

Abstract

Addressing global climate challenges requires innovative solutions to reduce greenhouse gas emissions; however, research exploring how regional differences and spatial interactions impact the effectiveness of environmental innovation remains limited. Past research has examined green innovation and emission reduction separately, overlooking their complex geographic interdependency. This study used transaction cost theory to examine the impact of green innovation on carbon emission reduction across Chinese provinces. The findings indicate significant regional patterns in innovation effectiveness by applying spatial Durbin and dynamic threshold models based on data from China's A-share listed companies from 2015 to 2022. The findings show that green innovation significantly reduced carbon emissions while positively affecting neighboring regions. This impact varied notably across areas, with eastern provinces exhibiting the most significant effects, followed by the western and central areas. This relationship was nonlinear, influenced by government intervention, economic development, and foreign direct investment. These findings inform environmental policy by illustrating how regional factors shape innovation outcomes while proposing targeted strategies to enhance emission reductions across varying economic contexts.