Green Mergers and Acquisitions, and Corporate Green Innovation: Innovation Types, Timing, and the Moderating Role of Carbon Information Disclosure

Green mergers and acquisitions (M&A) may enable firms to acquire external environmental technologies, assets, and organizational capabilities. However, whether green M&A is associated with subsequent green innovation, how this association evolves across innovation types and time horizons, and whether prior carbon information disclosure conditions this process remain unclear. Using 40,923 firm year observations of Chinese A-share-listed firms from 2012 to 2024, this study combines licensed green M&A data from Zhixing Data Analytics, green patent data from CNRDS, and carbon disclosure, financial, and corporate governance data from CSMAR. The baseline treatment identifies firm years in which at least one green M&A transaction first announced during the year was subsequently recorded as completed. The analysis employs firm and year fixed-effects models, common-sample distributed-lag specifications, formal cross-type coefficient comparisons, forward-outcome tests, propensity score matching, entropy balancing, and alternative measures and specifications. Green M&A is positively associated with total green patenting. The baseline coefficient of 0.045 implies an approximately 4.65% increase in one plus the number of total green patent applications. The contemporaneous association is stronger for green utility model patenting than for green invention patenting, whereas the association with invention patenting becomes more evident in subsequent periods. Prior carbon information disclosure positively moderates the association between green M&A and one-year-ahead invention patenting (β = 0.220, p = 0.018), while the corresponding moderation estimates for total and utility model patenting are not statistically significant. The findings are supported by observable selection adjustments and several alternative measurements and specifications, although fixed-effects PPML estimates using the original patent counts are not statistically significant. This study provides an integrated framework for understanding how innovation timing and prior information governance shape the green M&A dilemma. The results suggest that regulators and investors should assess green acquisitions using credible pre-acquisition carbon disclosure and post-acquisition innovation trajectories rather than relying on environmental transaction labels alone.