Bidder-Specific Synergies and the Evolution of Acquirer Returns
Bibliographic record
Abstract
Largely constant average acquirer returns over the past four decades mask fundamental changes in the takeover market. Controlling for bidder composition, the common component of acquirer returns has increased by five percentage points relative to the 1980s. Offsetting this increase, the average bidder-specific component has declined. We propose a theory of bidder-specific synergies to help interpret these opposing trends. In our theory and in the data, acquirer returns increase with the extent to which synergies are unique to that bidder. The composition effect reflects bidder uniqueness. Overall, the evidence is consistent with rising merger synergies that have become less bidder specific. This paper was accepted by Victoria Ivashina, finance. Funding: A. Golubov acknowledges financial support from the Bank of Canada [Governor’s Award]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.02208 .
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".