When uncertainty rises: can innovation safeguard cross-border M&A?
Hukam Mongia & M. Thenmozhi
What the paper says
Purpose This study examines how national innovation capacity influences cross-border mergers and acquisitions, particularly under economic policy uncertainty and climate risk conditions. It investigates how innovation functions not only as a growth enabler but also as a strategic buffer against uncertainty. Design/methodology/approach We employ a panel fixed-effects regression to analyze cross-border M&A activity across 19 countries from 2004 to 2020. To ensure the robustness of our results, we supplement the analysis with Tobit, negative binomial and quantile regression. Additionally, we apply a two-step system GMM estimator and a Difference-in-Differences analysis to address potential endogeneity concerns. Findings Our analysis reveals that innovation significantly attracts inbound M&A and mitigates the adverse effects of EPU and carbon emissions on inbound acquisitions. This moderating effect is especially strong in emerging economies and during the post-European debt crisis period. In contrast, innovation has a limited influence on outbound M&A. Innovation serves as a mechanism to alleviate the negative impact of uncertainty, whether stemming from EPU or climate change, on inbound acquisitions. Originality/value This study offers a novel contribution by exploring how national innovation capacity can strengthen a country's ability to sustain cross-border M&A activity amid rising economic and environmental uncertainty. Unlike prior studies that have typically focused on narrow regional or firm-level contexts, this study adopts a broader cross-country perspective and examines both inbound and outbound M&A activity.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.