Abstract
To study the multi-factor linkage effect of carbon trading on green technology innovation, this paper employs the dynamic QCA analysis method and uses panel data from China's carbon trading pilot areas. The aim is to explore the causal path considering the time effect. Additionally, the Kruskal-Wallis rank sum test is applied to investigate the provincial coverage difference of the configuration and reveal the variation in configuration preferences between regions from a spatial dimension. The results indicate that a single factor alone does not constitute the necessary conditions for the "quantity" and "quality" of high-green technology innovation. However, the necessity of carbon trading price exhibits a declining trend over the years, demonstrating the presence of a time effect. Regarding the sufficiency analysis of conditional configuration, it mainly includes a "price-market scale" dual effect model and a single market scale effect model, with three configuration paths for each model. Among them, the "price-market scale" dual effect model can drive the increase in the quantity of green technology innovation through carbon trading price, market scale, government intervention degree, and other factors. The single market scale effect model can promote the high-quality development of green technology innovation, but the impact of carbon trading price on the quality of green technology innovation is relatively insignificant. In terms of the time dimension, the three configurations still maintain good applicability to green technology innovation under normal conditions. However, when considering the spatial dimension, the coverage distribution of the three configurations exhibits evident regional differences. This study introduces the dynamic panel QCA method into the research field for the first time. It addresses the limitations of the traditional QCA method, which is constrained by cross-section data and lacks the ability to explore the linkage effect between factors over time. Additionally, the study analyzes the effects of carbon trading price and market size on the "quantity" and "quality" of green technology innovation, considering both time and space dimensions, from a configuration perspective.