The long-run performance of cross-border mergers and acquisitions: Evidence to support the internalization theory
Bibliographic record
Abstract
Our study contributes to improving the understanding of cross-border M&As in two domains: evaluation of the long-term financial performance of acquiring firms in cross-border M&As and detection of the determinants of their long-term success. Our results show no sustained gains or losses during the post-acquistion period for Canadian acquirers. In contrast to their performance in domestic M&As, Canadian firms carrying out crossborder M&As do generate enough value to keep up with stockmarket requirements, relative to their risk level as determined by the Fama & French three-factor model and the level of returns generated by peer firms in their main industrial sector. Our findings agree with the internalization theory and suggest that acquiring firms engaged in cross-border M&As can indeed realize efficiency gains and create long -term value for their shareholders, but only under certain conditions: namely, when they possess high levels of R&D and a strong combination of R&D and intangibles
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".